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Avelino-Silva VI, Bruhn R, Zurita KG, Deng X, Yu EA, Grebe E, Stone M, Lanteri MC, Spencer BR, Busch MP, Custer B. SARS-CoV-2 antibody levels and long COVID occurrence in blood donors. Transfusion 2024. [PMID: 38984497 DOI: 10.1111/trf.17952] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2024] [Revised: 06/21/2024] [Accepted: 06/23/2024] [Indexed: 07/11/2024]
Abstract
BACKGROUND Long COVID is a common condition lacking consensus definition; determinants remain incompletely understood. Characterizing immune profiles associated with long COVID could support the development of preventive and therapeutic strategies. METHODS We used a survey to investigate blood donors' infection/vaccination history and acute/persistent symptoms following COVID-19. The prevalence of long COVID was evaluated using self-report and an adapted definition from the RECOVER study. We evaluated factors associated with long COVID, focusing on anti-spike and anti-nucleocapsid SARS-CoV-2 antibodies. Lastly, we investigated long COVID clinical subphenotypes using hierarchical clustering. RESULTS Of 33,610 participants, 16,003 (48%) reported having had COVID-19; 1853 (12%) had self-reported long COVID, 685 (4%) met an adapted RECOVER definition, and 2050 (13%) met at least one definition. Higher anti-nucleocapsid levels measured 12-24 weeks post-infection were associated with higher risk of self-reported and RECOVER long COVID. Higher anti-spike IgG levels measured 12-24 weeks post-infection were associated with lower risk of self-reported long COVID. Higher total anti-spike measured 24-48 weeks post-infection was associated with lower risk of RECOVER long COVID. Cluster analysis identified four clinical subphenotypes; patterns included neurological and psychiatric for cluster 1; neurological and respiratory for cluster 2; multi-systemic for cluster 3; and neurological for cluster 4. DISCUSSION Long COVID prevalence in blood donors varies depending on the adopted definition. Anti-SARS-CoV-2 antibodies were time-dependently associated with long COVID; higher anti-nucleocapsid levels were associated with higher risk; and higher anti-spike levels were associated with lower risk of long COVID. Different underlying pathophysiologic mechanisms may be associated with distinct clinical subphenotypes.
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Affiliation(s)
- Vivian I Avelino-Silva
- Vitalant Research Institute, California, San Francisco, USA
- Department of Epidemiology and Biostatistics, University of California San Francisco, California, San Francisco, USA
| | - Roberta Bruhn
- Vitalant Research Institute, California, San Francisco, USA
- Department of Laboratory Medicine, University of California San Francisco, California, San Francisco, USA
| | - Karla G Zurita
- Vitalant Research Institute, California, San Francisco, USA
- Department of Laboratory Medicine, University of California San Francisco, California, San Francisco, USA
| | - Xutao Deng
- Vitalant Research Institute, California, San Francisco, USA
- Department of Laboratory Medicine, University of California San Francisco, California, San Francisco, USA
| | - Elaine A Yu
- Vitalant Research Institute, California, San Francisco, USA
- Department of Laboratory Medicine, University of California San Francisco, California, San Francisco, USA
| | - Eduard Grebe
- Vitalant Research Institute, California, San Francisco, USA
- Department of Laboratory Medicine, University of California San Francisco, California, San Francisco, USA
- South African Centre for Epidemiological Modeling and Analysis (SACEMA), Stellenbosch University, Stellenbosch, South Africa
| | - Mars Stone
- Vitalant Research Institute, California, San Francisco, USA
- Department of Laboratory Medicine, University of California San Francisco, California, San Francisco, USA
| | - Marion C Lanteri
- Department of Laboratory Medicine, University of California San Francisco, California, San Francisco, USA
- Creative Testing Solutions, Tempe, Arizona, USA
| | - Bryan R Spencer
- Scientific Affairs, American Red Cross, Rockville, Maryland, USA
| | - Michael P Busch
- Vitalant Research Institute, California, San Francisco, USA
- Department of Laboratory Medicine, University of California San Francisco, California, San Francisco, USA
| | - Brian Custer
- Vitalant Research Institute, California, San Francisco, USA
- Department of Laboratory Medicine, University of California San Francisco, California, San Francisco, USA
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Kao SYZ, Nycz E, Benoit TJ, Clarke KEN, Jones JM. Comparison of SARS-CoV-2 seroprevalence estimates between commercial lab serum specimens and blood donor specimens, United States, September-December 2021. Microbiol Spectr 2024:e0012324. [PMID: 38869287 DOI: 10.1128/spectrum.00123-24] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Accepted: 03/21/2024] [Indexed: 06/14/2024] Open
Abstract
We estimated monthly cross-sectional seroprevalence rates of anti-nucleocapsid (anti-N) and anti-spike (anti-S) antibodies to severe acute respiratory syndrome coronavirus 2 in two U.S. nationwide studies. The nationwide blood donor seroprevalence (NBDS) study included specimens from blood donors, while the nationwide commercial laboratory seroprevalence (NCLS) study included residual serum specimens tested in commercial laboratories for reasons unrelated to the assessment of coronavirus disease 2019 infection. In September-December 2021, specimens collected from both nationwide studies were tested for anti-N antibodies. In September-October 2021, specimens from both studies within a five-state area were tested for anti-S antibodies. We used raking methods to adjust all seroprevalence estimates by the population distribution of key demographics in included states. Seroprevalence estimates of each antibody type were compared across the two studies for specimens drawn in the same U.S. states during the same time period. Our analysis revealed that over a 4-month period, national NCLS monthly anti-N estimates were 0.5-1.9 percentage points higher than NBDS estimates. In contrast, across five states during a 2-month period, NBDS anti-S estimates were 7.6 and 8.2 percentage points higher than NCLS estimates. The observed differences in seroprevalence estimates between the NBDS and NCLS studies may be attributed to variations in the characteristics of the study sample populations, particularly with respect to health status, health behaviors, and vaccination status. These differences should be considered in the interpretation of seroprevalence study results based on blood donors or commercial lab residual specimens. IMPORTANCE This study was the first systematic comparison between two nationwide severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) studies which estimated seroprevalence, or the proportion of the population with antibodies to the virus, using differing convenience sample populations. One study tested blood donor specimens; the other study tested specimens left over from clinical blood tests. The seroprevalence of anti-nucleocapsid and anti-spike antibodies was compared in the same states during the same months with statistical adjustments based on state demographics. Similar anti-nucleocapsid antibody seroprevalence estimates produced by two independent studies using differing convenience samples build confidence in the generalizability of their anti-nucleocapsid findings. Due to high blood donor vaccine rates, blood donor SARS-CoV-2 anti-spike antibody estimates might overestimate general population seroprevalence, an important consideration for interpreting national seroprevalence study results. Furthermore, because laboratory residuals and blood donations are two common sources of specimens for seroprevalence studies, study findings may be informative for other respiratory virus seroepidemiology studies.
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Affiliation(s)
- Szu-Yu Zoe Kao
- CDC COVID-19 Response, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Elise Nycz
- CDC COVID-19 Response, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Tina J Benoit
- CDC COVID-19 Response, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Kristie E N Clarke
- CDC COVID-19 Response, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Jefferson M Jones
- CDC COVID-19 Response, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
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Ayoub HH, Tomy M, Chemaitelly H, Altarawneh HN, Coyle P, Tang P, Hasan MR, Al Kanaani Z, Al Kuwari E, Butt AA, Jeremijenko A, Kaleeckal AH, Latif AN, Shaik RM, Nasrallah GK, Benslimane FM, Al Khatib HA, Yassine HM, Al Kuwari MG, Al Romaihi HE, Abdul-Rahim HF, Al-Thani MH, Al Khal A, Bertollini R, Abu-Raddad LJ. Estimating protection afforded by prior infection in preventing reinfection: applying the test-negative study design. Am J Epidemiol 2024; 193:883-897. [PMID: 38061757 PMCID: PMC11145912 DOI: 10.1093/aje/kwad239] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2022] [Revised: 11/20/2023] [Accepted: 12/04/2023] [Indexed: 06/04/2024] Open
Abstract
The COVID-19 pandemic has highlighted the need to use infection testing databases to rapidly estimate effectiveness of prior infection in preventing reinfection ($P{E}_S$) by novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants. Mathematical modeling was used to demonstrate a theoretical foundation for applicability of the test-negative, case-control study design to derive $P{E}_S$. Apart from the very early phase of an epidemic, the difference between the test-negative estimate for $P{E}_S$ and true value of $P{E}_S$ was minimal and became negligible as the epidemic progressed. The test-negative design provided robust estimation of $P{E}_S$ and its waning. Assuming that only 25% of prior infections are documented, misclassification of prior infection status underestimated $P{E}_S$, but the underestimate was considerable only when > 50% of the population was ever infected. Misclassification of latent infection, misclassification of current active infection, and scale-up of vaccination all resulted in negligible bias in estimated $P{E}_S$. The test-negative design was applied to national-level testing data in Qatar to estimate $P{E}_S$ for SARS-CoV-2. $P{E}_S$ against SARS-CoV-2 Alpha and Beta variants was estimated at 97.0% (95% CI, 93.6-98.6) and 85.5% (95% CI, 82.4-88.1), respectively. These estimates were validated using a cohort study design. The test-negative design offers a feasible, robust method to estimate protection from prior infection in preventing reinfection.
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Affiliation(s)
- Houssein H Ayoub
- Mathematics Program, Department of Mathematics and Statistics, College of Arts and Sciences, Qatar University, Doha, Qatar
| | - Milan Tomy
- Mathematics Program, Department of Mathematics and Statistics, College of Arts and Sciences, Qatar University, Doha, Qatar
- Infectious Disease Epidemiology Group, Weill Cornell Medicine–Qatar, Cornell University, Doha, Qatar
- World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine–Qatar, Cornell University, Qatar Foundation–Education City, Doha, Qatar
| | - Hiam Chemaitelly
- Infectious Disease Epidemiology Group, Weill Cornell Medicine–Qatar, Cornell University, Doha, Qatar
- World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine–Qatar, Cornell University, Qatar Foundation–Education City, Doha, Qatar
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY 10065, United States
| | - Heba N Altarawneh
- Infectious Disease Epidemiology Group, Weill Cornell Medicine–Qatar, Cornell University, Doha, Qatar
- World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine–Qatar, Cornell University, Qatar Foundation–Education City, Doha, Qatar
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY 10065, United States
| | - Peter Coyle
- Hamad Medical Corporation, Doha, Qatar
- Biomedical Research Center, Member of QU Health, Qatar University, Doha, Qatar
- Wellcome-Wolfson Institute for Experimental Medicine, Queens University, Belfast BT9 7BL, United Kingdom
| | - Patrick Tang
- Department of Pathology, Sidra Medicine, Doha, Qatar
| | | | | | | | - Adeel A Butt
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY 10065, United States
- Hamad Medical Corporation, Doha, Qatar
| | | | | | | | | | - Gheyath K Nasrallah
- Biomedical Research Center, Member of QU Health, Qatar University, Doha, Qatar
- Department of Biomedical Science, College of Health Sciences, Member of QU Health, Qatar University, Doha, Qatar
| | - Fatiha M Benslimane
- Biomedical Research Center, Member of QU Health, Qatar University, Doha, Qatar
- Department of Biomedical Science, College of Health Sciences, Member of QU Health, Qatar University, Doha, Qatar
| | - Hebah A Al Khatib
- Department of Biomedical Science, College of Health Sciences, Member of QU Health, Qatar University, Doha, Qatar
| | - Hadi M Yassine
- Biomedical Research Center, Member of QU Health, Qatar University, Doha, Qatar
- Department of Biomedical Science, College of Health Sciences, Member of QU Health, Qatar University, Doha, Qatar
| | | | | | - Hanan F Abdul-Rahim
- Department of Public Health, College of Health Sciences, Member of QU Health, Qatar University, Doha, Qatar
| | | | | | | | - Laith J Abu-Raddad
- Infectious Disease Epidemiology Group, Weill Cornell Medicine–Qatar, Cornell University, Doha, Qatar
- World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine–Qatar, Cornell University, Qatar Foundation–Education City, Doha, Qatar
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY 10065, United States
- Department of Public Health, College of Health Sciences, Member of QU Health, Qatar University, Doha, Qatar
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O'Brien SF, Goldman M, Ehsani-Moghaddam B, Fan W, Osmond L, Pambrun C, Drews SJ. SARS-CoV-2 vaccination in Canadian blood donors: Insight into donor representativeness of the general population. Vaccine X 2024; 18:100498. [PMID: 38800670 PMCID: PMC11127215 DOI: 10.1016/j.jvacx.2024.100498] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 05/10/2024] [Accepted: 05/11/2024] [Indexed: 05/29/2024] Open
Abstract
Introduction Blood donors world-wide were indispensable for monitoring anti-SARS-CoV-2 antibodies generated by infection and vaccination during the pandemic. Prior to the pandemic, donor vaccination behaviours were under-studied. We aimed to compare the percentage of Canadian blood donors with SARS-CoV-2 vaccination antibodies with the percentage of the general population who received at least one dose of vaccine each month during initial vaccine deployment. We also report donor attitudes towards SARS-CoV-2 vaccination. Methods Canadian blood donors were randomly selected for SARS-CoV-2 antibody testing over 2021 (N = 165,240). The percentage of donor samples with vaccination antibodies were compared with the percentage of general population who received at least one dose of vaccine in each month of 2021 except February. A random sample of Canadian blood donors were surveyed about vaccination intent and attitudes (N = 4,558 participated, 30.4 % response rate). Results The percentages of the general population vaccinated and donors with vaccination antibodies increased from 1 % to over 90 %. General population vaccination was greater early in vaccine deployment than donors (p < 0.05), greater in donors than the general population by mid-2021 (p < 0.05) but they were similar by the end of 2021. While 52.6 % of surveyed donors had received vaccine in May 2021, a further 41.1 % intended to when eligible. Most donors thought COVID-19 infection could be serious (83.5 %) and that it was important to be vaccinated even if previously infected (77.8 %). Conclusion Early pandemic vaccine prioritization to at-risk individuals and healthcare workers gave rise to higher general population vaccination percentages, while donors had higher vaccine antibody percentages as vaccine was deployed to progressively younger age groups. Since blood donors may be more willing to receive vaccination, under pandemic conditions they may be valuable for monitoring vaccination-induced seroprevalence.
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Affiliation(s)
- Sheila F. O'Brien
- Epidemiology & Surveillance, Canadian Blood Services, 1800 Alta Vista Drive, Ottawa, Ontario K1G 4J5, Canada
- School of Epidemiology & Public Health, University of Ottawa, 600 Peter Morand Crescent, Ottawa, Ontario K1G 5Z3, Canada
| | - Mindy Goldman
- Donation and Policy Studies, Canadian Blood Services, 1800 Alta Vista Drive, Ottawa, Ontario K1G 4J5, Canada
- Department of Pathology & Laboratory Medicine, Faculty of Medicine, University of Ottawa, 600 Peter Morand Crescent, Ottawa, Ontario K1G 5Z3, Canada
| | - Behrouz Ehsani-Moghaddam
- Epidemiology & Surveillance, Canadian Blood Services, 1800 Alta Vista Drive, Ottawa, Ontario K1G 4J5, Canada
- Centre for Studies in Primary Care, Department of Family Medicine, Queens University, 220 Bagot Street, Kingston, Ontario K7L 3G2, Canada
| | - Wenli Fan
- Epidemiology & Surveillance, Canadian Blood Services, 1800 Alta Vista Drive, Ottawa, Ontario K1G 4J5, Canada
| | - Lori Osmond
- Epidemiology & Surveillance, Canadian Blood Services, 1800 Alta Vista Drive, Ottawa, Ontario K1G 4J5, Canada
| | - Chantale Pambrun
- Innovation & Portfolio Management, Medical Affairs & Innovation, Canadian Blood Services, 1800 Alta Vista Drive, Ottawa, Ontario K1G 4J5, Canada
| | - Steven J. Drews
- Microbiology, Canadian Blood Services, 8249-114 Street, Edmonton, Alberta T6G 2R8, Canada
- Department of Laboratory Medicine & Pathology, Faculty of Medicine & Dentistry, University of Alberta, 118 Street & 86 Avenue, Edmonton, Alberta T6G 2R3, Canada
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Binder RA, Matta AM, Forconi CS, Oduor CI, Bedekar P, Patrone PN, Kearsley AJ, Odwar B, Batista J, Forrester SN, Leftwich HK, Cavacini LA, Moormann AM. Minding the margins: Evaluating the impact of COVID-19 among Latinx and Black communities with optimal qualitative serological assessment tools. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.05.23.24307817. [PMID: 38826359 PMCID: PMC11142299 DOI: 10.1101/2024.05.23.24307817] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
COVID-19 disproportionately affected minorities, while research barriers to engage underserved communities persist. Serological studies reveal infection and vaccination histories within these communities, however lack of consensus on downstream evaluation methods impede meta-analyses and dampen the broader public health impact. To reveal the impact of COVID-19 and vaccine uptake among diverse communities and to develop rigorous serological downstream evaluation methods, we engaged racial and ethnic minorities in Massachusetts in a cross-sectional study (April - July 2022), screened blood and saliva for SARS-CoV-2 and human endemic coronavirus (hCoV) antibodies by bead-based multiplex assay and point-of-care (POC) test and developed across-plate normalization and classification boundary methods for optimal qualitative serological assessments. Among 290 participants, 91.4 % reported receiving at least one dose of a COVID-19 vaccine, while 41.7 % reported past SARS-CoV-2 infections, which was confirmed by POC- and multiplex-based saliva and blood IgG seroprevalences. We found significant differences in antigen-specific IgA and IgG antibody outcomes and indication of cross-reactivity with hCoV OC43. Finally, 26.5 % of participants reported lingering COVID-19 symptoms, mostly middle-aged Latinas. Hence, prolonged COVID-19 symptoms were common among our underserved population and require public health attention, despite high COVID-19 vaccine uptake. Saliva served as a less-invasive sample-type for IgG-based serosurveys and hCoV cross-reactivity needed to be evaluated for reliable SARS-CoV-2 serosurvey results. Using the developed rigorous downstream qualitative serological assessment methods will help standardize serosurvey outcomes and meta-analyses for future serosurveys beyond SARS-CoV-2.
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Major CG, Rodríguez DM, Sánchez-González L, Rodríguez-Estrada V, Morales-Ortíz T, Torres C, Pérez-Rodríguez NM, Medina-Lópes NA, Alexander N, Mabey D, Ryff K, Tosado-Acevedo R, Muñoz-Jordán J, Adams LE, Rivera-Amill V, Rolfes M, Paz-Bailey G. Investigating SARS-CoV-2 Incidence and Morbidity in Ponce, Puerto Rico: Protocol and Baseline Results From a Community Cohort Study. JMIR Res Protoc 2024; 13:e53837. [PMID: 38640475 PMCID: PMC11034577 DOI: 10.2196/53837] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Accepted: 01/19/2024] [Indexed: 04/21/2024] Open
Abstract
BACKGROUND A better understanding of SARS-CoV-2 infection risk among Hispanic and Latino populations and in low-resource settings in the United States is needed to inform control efforts and strategies to improve health equity. Puerto Rico has a high poverty rate and other population characteristics associated with increased vulnerability to COVID-19, and there are limited data to date to determine community incidence. OBJECTIVE This study describes the protocol and baseline seroprevalence of SARS-CoV-2 in a prospective community-based cohort study (COPA COVID-19 [COCOVID] study) to investigate SARS-CoV-2 infection incidence and morbidity in Ponce, Puerto Rico. METHODS In June 2020, we implemented the COCOVID study within the Communities Organized to Prevent Arboviruses project platform among residents of 15 communities in Ponce, Puerto Rico, aged 1 year or older. Weekly, participants answered questionnaires on acute symptoms and preventive behaviors and provided anterior nasal swab samples for SARS-CoV-2 polymerase chain reaction testing; additional anterior nasal swabs were collected for expedited polymerase chain reaction testing from participants that reported 1 or more COVID-19-like symptoms. At enrollment and every 6 months during follow-up, participants answered more comprehensive questionnaires and provided venous blood samples for multiantigen SARS-CoV-2 immunoglobulin G antibody testing (an indicator of seroprevalence). Weekly follow-up activities concluded in April 2022 and 6-month follow-up visits concluded in August 2022. Primary study outcome measures include SARS-CoV-2 infection incidence and seroprevalence, relative risk of SARS-CoV-2 infection by participant characteristics, SARS-CoV-2 household attack rate, and COVID-19 illness characteristics and outcomes. In this study, we describe the characteristics of COCOVID participants overall and by SARS-CoV-2 seroprevalence status at baseline. RESULTS We enrolled a total of 1030 participants from 388 households. Relative to the general populations of Ponce and Puerto Rico, our cohort overrepresented middle-income households, employed and middle-aged adults, and older children (P<.001). Almost all participants (1021/1025, 99.61%) identified as Latino/a, 17.07% (175/1025) had annual household incomes less than US $10,000, and 45.66% (463/1014) reported 1 or more chronic medical conditions. Baseline SARS-CoV-2 seroprevalence was low (16/1030, 1.55%) overall and increased significantly with later study enrollment time (P=.003). CONCLUSIONS The COCOVID study will provide a valuable opportunity to better estimate the burden of SARS-CoV-2 and associated risk factors in a primarily Hispanic or Latino population, assess the limitations of surveillance, and inform mitigation measures in Puerto Rico and other similar populations. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) RR1-10.2196/53837.
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Affiliation(s)
- Chelsea G Major
- Division of Vector Borne Diseases, Centers for Disease Control and Prevention, San Juan, Puerto Rico
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Dania M Rodríguez
- Division of Vector Borne Diseases, Centers for Disease Control and Prevention, San Juan, Puerto Rico
| | - Liliana Sánchez-González
- Division of Vector Borne Diseases, Centers for Disease Control and Prevention, San Juan, Puerto Rico
| | | | | | - Carolina Torres
- Division of Vector Borne Diseases, Centers for Disease Control and Prevention, San Juan, Puerto Rico
- Kāpili Services, LLC, Alaka`ina Foundation Family of Companies, Orlando, FL, United States
| | - Nicole M Pérez-Rodríguez
- Division of Vector Borne Diseases, Centers for Disease Control and Prevention, San Juan, Puerto Rico
| | - Nicole A Medina-Lópes
- Division of Vector Borne Diseases, Centers for Disease Control and Prevention, San Juan, Puerto Rico
| | - Neal Alexander
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - David Mabey
- Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Kyle Ryff
- Division of Vector Borne Diseases, Centers for Disease Control and Prevention, San Juan, Puerto Rico
| | - Rafael Tosado-Acevedo
- Division of Vector Borne Diseases, Centers for Disease Control and Prevention, San Juan, Puerto Rico
| | - Jorge Muñoz-Jordán
- Division of Vector Borne Diseases, Centers for Disease Control and Prevention, San Juan, Puerto Rico
| | - Laura E Adams
- Division of Vector Borne Diseases, Centers for Disease Control and Prevention, San Juan, Puerto Rico
| | | | - Melissa Rolfes
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Gabriela Paz-Bailey
- Division of Vector Borne Diseases, Centers for Disease Control and Prevention, San Juan, Puerto Rico
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Yu EA, Stone M, Bravo MD, Grebe E, Bruhn RL, Lanteri MC, Townsend M, Kamel H, Jones JM, Busch MP, Custer B. Associations of Temporal Cardiometabolic Patterns and Incident SARS-CoV-2 Infection Among U.S. Blood Donors With Serologic Evidence of Vaccination. AJPM FOCUS 2024; 3:100186. [PMID: 38304025 PMCID: PMC10832374 DOI: 10.1016/j.focus.2024.100186] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/03/2024]
Abstract
Introduction Cardiometabolic diseases are associated with greater COVID-19 severity; however, the influences of cardiometabolic health on SARS-CoV-2 infections after vaccination remain unclear. Our objective was to investigate the associations between temporal blood pressure and total cholesterol patterns and incident SARS-CoV-2 infections among those with serologic evidence of vaccination. Methods In this prospective cohort of blood donors, blood samples were collected in 2020-2021 and assayed for binding antibodies of SARS-CoV-2 nucleocapsid protein antibody seropositivity. We categorized participants into intraindividual pattern subgroups of blood pressure and total cholesterol (persistently, intermittently, or not elevated [systolic blood pressure <130 mmHg, diastolic blood pressure <80 mmHg, total cholesterol <200 mg/dL]) across the study time points. Results Among 13,930 donors with 39,736 donations representing 1,127,071 person-days, there were 221 incident SARS-CoV-2 infections among those with serologic evidence of vaccination (1.6%). Intermittent hypertension was associated with greater SARS-CoV-2 infections among those with serologic evidence of vaccination risk (adjusted incidence rate ratio=2.07; 95% CI=1.44, 2.96; p<0.01) than among participants with consistent normotension on the basis of a multivariable Poisson regression. Among men, intermittently elevated total cholesterol (adjusted incidence rate ratio=1.90; 95% CI=1.32, 2.74; p<0.01) and higher BMI at baseline (adjusted hazard ratio=1.44; 95% CI=1.07, 1.93; p=0.01; per 10 units) were associated with greater SARS-CoV-2 infections among those with serologic evidence of vaccination probability; these associations were null among women (both p>0.05). Conclusions Our findings underscore that the benefits of cardiometabolic health, particularly blood pressure, include a lower risk of SARS-CoV-2 infection after vaccination.
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Affiliation(s)
- Elaine A. Yu
- Vitalant Research Institute, San Francisco, California
- Department of Laboratory Medicine, University of California San Francisco, San Francisco, California
| | - Mars Stone
- Vitalant Research Institute, San Francisco, California
- Department of Laboratory Medicine, University of California San Francisco, San Francisco, California
| | | | - Eduard Grebe
- Vitalant Research Institute, San Francisco, California
- Department of Laboratory Medicine, University of California San Francisco, San Francisco, California
| | - Roberta L. Bruhn
- Vitalant Research Institute, San Francisco, California
- Department of Laboratory Medicine, University of California San Francisco, San Francisco, California
| | - Marion C. Lanteri
- Department of Laboratory Medicine, University of California San Francisco, San Francisco, California
- Creative Testing Solutions, Tempe, Arizona
| | | | | | | | - Michael P. Busch
- Vitalant Research Institute, San Francisco, California
- Department of Laboratory Medicine, University of California San Francisco, San Francisco, California
- Vitalant, Scottsdale, Arizona
| | - Brian Custer
- Vitalant Research Institute, San Francisco, California
- Department of Laboratory Medicine, University of California San Francisco, San Francisco, California
- Vitalant, Scottsdale, Arizona
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8
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Drouin A, Plumb ID, McCullough M, James Gist J, Liu S, Theberge M, Katz J, Moreida M, Flaherty S, Chatwani B, Briggs Hagen M, Midgley CM, Fusco D. Clinical and laboratory characteristics of patients hospitalized with severe COVID-19 in New Orleans, August 2020 to September 2021. Sci Rep 2024; 14:6539. [PMID: 38503862 PMCID: PMC10951213 DOI: 10.1038/s41598-024-57306-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Accepted: 03/17/2024] [Indexed: 03/21/2024] Open
Abstract
Louisiana experienced high morbidity and mortality from COVID-19. To assess possible explanatory factors, we conducted a cohort study (ClinSeqSer) of patients hospitalized with COVID-19 in New Orleans during August 2020-September 2021. Following enrollment, we reviewed medical charts, and performed SARS-CoV-2 RT-PCR testing on nasal and saliva specimens. We used multivariable logistic regression to assess associations between patient characteristics and severe illness, defined as ≥ 6 L/min oxygen or intubation. Among 456 patients, median age was 56 years, 277 (60.5%) were Black non-Hispanic, 436 (95.2%) had underlying health conditions, and 358 were unvaccinated (92.0% of 389 verified). Overall, 187 patients (40.1%) had severe illness; 60 (13.1%) died during admission. In multivariable models, severe illness was associated with age ≥ 65 years (OR 2.08, 95% CI 1.22-3.56), hospitalization > 5 days after illness onset (OR 1.49, 95% CI 1.01-2.21), and SARS CoV-2 cycle threshold (Ct) result of < 32 in saliva (OR 4.79, 95% CI 1.22-18.77). Among patients who were predominantly Black non-Hispanic, unvaccinated and with underlying health conditions, approximately 1 in 3 patients had severe COVID-19. Older age and delayed time to admission might have contributed to high case-severity. An association between case-severity and low Ct value in saliva warrants further investigation.
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Affiliation(s)
- Arnaud Drouin
- Department of Medicine, Tulane University School of Medicine, 1430 Tulane Avenue, New Orleans, LA, 70130, USA
- University Medical Center, New Orleans, LA, USA
| | - Ian D Plumb
- Applied Epidemiology Studies Team, Epidemiology Branch, and on detail to the Global Respiratory Viruses Branch Coronavirus and Other Respiratory Viruses Division, Centers for Disease Control, Atlanta, GA, USA
| | | | | | - Sharon Liu
- Department of Medicine, Tulane University School of Medicine, 1430 Tulane Avenue, New Orleans, LA, 70130, USA
| | - Marc Theberge
- Department of Medicine, Tulane University School of Medicine, 1430 Tulane Avenue, New Orleans, LA, 70130, USA
| | - Joshua Katz
- Department of Medicine, Tulane University School of Medicine, 1430 Tulane Avenue, New Orleans, LA, 70130, USA
| | - Matthew Moreida
- Department of Medicine, Tulane University School of Medicine, 1430 Tulane Avenue, New Orleans, LA, 70130, USA
| | - Shelby Flaherty
- School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA
| | - Bhoomija Chatwani
- School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA
| | - Melissa Briggs Hagen
- Applied Epidemiology Studies Team, Epidemiology Branch, and on detail to the Global Respiratory Viruses Branch Coronavirus and Other Respiratory Viruses Division, Centers for Disease Control, Atlanta, GA, USA
| | - Claire M Midgley
- Applied Epidemiology Studies Team, Epidemiology Branch, and on detail to the Global Respiratory Viruses Branch Coronavirus and Other Respiratory Viruses Division, Centers for Disease Control, Atlanta, GA, USA
| | - Dahlene Fusco
- Department of Medicine, Tulane University School of Medicine, 1430 Tulane Avenue, New Orleans, LA, 70130, USA.
- University Medical Center, New Orleans, LA, USA.
- School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA.
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9
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O’Brien SF, Deeks SL, Hatchette T, Pambrun C, Drews SJ. SARS-CoV-2 seroprevalence in Nova Scotia blood donors. JOURNAL OF THE ASSOCIATION OF MEDICAL MICROBIOLOGY AND INFECTIOUS DISEASE CANADA = JOURNAL OFFICIEL DE L'ASSOCIATION POUR LA MICROBIOLOGIE MEDICALE ET L'INFECTIOLOGIE CANADA 2024; 9:32-45. [PMID: 38567363 PMCID: PMC10984316 DOI: 10.3138/jammi-2023-0017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Revised: 10/20/2023] [Accepted: 11/09/2023] [Indexed: 04/04/2024]
Abstract
Background SARS-CoV-2 seroprevalence monitors cumulative infection rates irrespective of case testing protocols. We aimed to describe Nova Scotia blood donor seroprevalence in relation to public health policy and reported data over the course of the COVID-19 pandemic (May 2020 to August 2022). Methods Monthly random Nova Scotia blood donation samples (24,258 in total) were tested for SARS-CoV-2 infection antibodies (anti-nucleocapsid) from May 2020 to August 2022, and vaccination antibodies (anti-spike) from January 2021 to August 2022. Multivariable logistic regression for infection antibodies and vaccination antibodies separately with month, age, sex, and racialization identified independent predictors. The provincial nucleic acid amplification test (NAAT)-positive case rate over the pandemic was calculated from publicly available data. Results Anti-N seroprevalence was 3.8% in January 2022, increasing to 50.8% in August 2022. The general population COVID-19 case rate was 3.5% in January 2022, increasing to 12.5% in August 2022. The percentage of NAAT-positive samples in public health laboratories increased from 1% in November 2021 to a peak of 30.7% in April 2022 with decreasing numbers of tests performed. Higher proportions of younger donors as well as Black, Indigenous, and racialized blood donors were more likely to have infection antibodies (p < 0.01). Vaccination antibodies increased to 100% over 2021, initially in older donors (60+ years), and followed by progressively younger age groups. Conclusions SARS-CoV-2 infection rates were relatively low in Nova Scotia until the more contagious Omicron variant dominated, after which about half of Nova Scotia donors had been infected despite most adults being vaccinated (although severity was much lower in vaccinated individuals). Most COVID-19 cases were detected by NAAT until Omicron arrived. When NAAT testing priorities focused on high-risk individuals, infection rates were better reflected by seroprevalence.
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Affiliation(s)
- Sheila F O’Brien
- Epidemiology & Surveillance, Canadian Blood Services, Ottawa, Ontario, Canada
- School of Epidemiology & Public Health, University of Ottawa, Ontario, Canada
| | - Shelley L Deeks
- Department of Health and Wellness, Government of Nova Scotia, Halifax, Nova Scotia, Canada
- Community Health and Epidemiology, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Todd Hatchette
- Division of Microbiology, Nova Scotia Health, Central Zone, Halifax, Nova Scotia, Canada
- Department of Pathology, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Chantale Pambrun
- Medical Affairs & Innovation, Canadian Blood Services, Ottawa, Ontario, Canada
| | - Steven J Drews
- Microbiology, Canadian Blood Services, Edmonton, Alberta, Canada
- Department of Pathology & Laboratory Medicine, University of Alberta, Edmonton, Alberta, Canada
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Vermeulen M, Mhlanga L, Sykes W, Cable R, Coleman C, Pietersen N, Swanevelder R, Glatt TN, Bingham J, van den Berg K, Grebe E, Welte A. The evolution and interpretation of seroprevalence of SARS-CoV-2 antibodies among South African blood donors from the Beta to Omicron variant-driven waves. Vox Sang 2024; 119:242-251. [PMID: 38156504 DOI: 10.1111/vox.13571] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 11/14/2023] [Accepted: 11/17/2023] [Indexed: 12/30/2023]
Abstract
BACKGROUND AND OBJECTIVES Confirmed COVID-19 diagnoses underestimate the total number of infections. Blood donors can provide representative seroprevalence estimates, which can be leveraged into reasonable estimates of total infection counts and infection fatality rate (IFR). MATERIALS AND METHODS Blood donors who donated after each of three epidemic waves (Beta, Delta and first Omicron waves) were tested for anti-SARS-CoV-2 nucleocapsid antibodies using the Roche Elecsys anti-SARS-CoV-2 total immunoglobulin assay. Roche Elecsys anti-spike antibody testing was done for the post-Omicron sampling. Prevalence of antibodies was estimated by age, sex, race and province and compared to official case reporting. Province and age group-specific IFRs were estimated using external excess mortality estimates. RESULTS The nationally weighted anti-nucleocapsid seroprevalence estimates after the Beta, Delta and Omicron waves were 47% (46.2%-48.6%), 71% (68.8%-73.5%) and 87% (85.5%-88.4%), respectively. There was no variation by age and sex, but there were statistically and epidemiologically significant differences by province (except at the latest time point) and race. There was a 13-fold higher seroprevalence than confirmed case counts at the first time point. Age-dependent IFR roughly doubled for every 10 years of age increase over 6 decades from 0.014% in children to 6.793% in octogenarians. CONCLUSION Discrepancies were found between seroprevalence and confirmed case counts. High seroprevalence rates found among Black African donors can be ascribed to historical inequities. Our IFR estimates were useful in refining previous large disagreements about the severity of the epidemic in South Africa. Blood donor-based serosurveys provided a valuable and efficient way to provide near real-time monitoring of the ongoing SARS-CoV-2 outbreak.
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Affiliation(s)
- Marion Vermeulen
- South African National Blood Service, Johannesburg, South Africa
- University of the Free State, Bloemfontein, South Africa
| | - Laurette Mhlanga
- DSI-NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Stellenbosch University, Stellenbosch, South Africa
- Northwestern University, Chicago, Illinois, USA
| | - Wendy Sykes
- South African National Blood Service, Johannesburg, South Africa
| | | | - Charl Coleman
- South African National Blood Service, Johannesburg, South Africa
| | | | | | - Tanya Nadia Glatt
- South African National Blood Service, Johannesburg, South Africa
- University of Johannesburg, Johannesburg, South Africa
| | - Jeremy Bingham
- DSI-NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Stellenbosch University, Stellenbosch, South Africa
| | - Karin van den Berg
- South African National Blood Service, Johannesburg, South Africa
- University of the Free State, Bloemfontein, South Africa
- University of Cape Town, Rondebosch, South Africa
| | - Eduard Grebe
- DSI-NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Stellenbosch University, Stellenbosch, South Africa
- Vitalant Research Institute, San Francisco, California, USA
- University of California San Francisco, San Francisco, California, USA
| | - Alex Welte
- DSI-NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Stellenbosch University, Stellenbosch, South Africa
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Benoit TJ, Kim Y, Deng Y, Li Z, Harding L, Wiegand R, Deng X, Jones JM, Ronaldo I, Clarke KEN. Association Between Social Vulnerability and SARS-CoV-2 Seroprevalence in Specimens Collected From Commercial Laboratories, United States, September 2021-February 2022. Public Health Rep 2024:333549231223140. [PMID: 38357883 DOI: 10.1177/00333549231223140] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/16/2024] Open
Abstract
OBJECTIVE We conducted a national US study of SARS-CoV-2 seroprevalence by Social Vulnerability Index (SVI) that included pediatric data and compared the Delta and Omicron periods during the COVID-19 pandemic. The objective of the current study was to assess the association between SVI and seroprevalence of infection-induced SARS-CoV-2 antibodies by period (Delta vs Omicron) and age group. METHODS We used results of infection-induced SARS-CoV-2 antibody assays of clinical sera specimens (N = 406 469) from 50 US states from September 2021 through February 2022 to estimate seroprevalence overall and by county SVI tercile. Bivariate analyses and multilevel logistic regression models assessed the association of seropositivity with SVI and its themes by age group (0-17, ≥18 y) and period (Delta: September-November 2021; Omicron: December 2021-February 2022). RESULTS Aggregate infection-induced SARS-CoV-2 antibody seroprevalence increased at all 3 SVI levels; it ranged from 25.8% to 33.5% in September 2021 and from 53.1% to 63.5% in February 2022. Of the 4 SVI themes, socioeconomic status had the strongest association with seroprevalence. During the Delta period, we found significantly more infections per reported case among people living in a county with high SVI (odds ratio [OR] = 2.76; 95% CI, 2.31-3.21) than in a county with low SVI (OR = 1.65; 95% CI, 1.33-1.97); we found no significant difference during the Omicron period. Otherwise, findings were consistent across subanalyses by age group and period. CONCLUSIONS Among both children and adults, and during both the Delta and Omicron periods, counties with high SVI had significantly higher SARS-CoV-2 antibody seroprevalence than counties with low SVI did. These disparities reinforce SVI's value in identifying communities that need tailored prevention efforts during public health emergencies and resources to recover from their effects.
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Affiliation(s)
- Tina J Benoit
- COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | | | | | - Zheng Li
- Office of Capacity Development and Applied Prevention Science, Agency for Toxic Substances and Disease Registry, Atlanta, GA, USA
| | | | - Ryan Wiegand
- COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | | | - Jefferson M Jones
- COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | | | - Kristie E N Clarke
- COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, GA, USA
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12
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Matias WR, Fulcher IR, Sauer SM, Nolan CP, Guillaume Y, Zhu J, Molano FJ, Uceta E, Collins S, Slater DM, Sánchez VM, Moheed S, Harris JB, Charles RC, Paxton RM, Gonsalves SF, Franke MF, Ivers LC. Disparities in SARS-CoV-2 Infection by Race, Ethnicity, Language, and Social Vulnerability: Evidence from a Citywide Seroprevalence Study in Massachusetts, USA. J Racial Ethn Health Disparities 2024; 11:110-120. [PMID: 36652163 PMCID: PMC9847437 DOI: 10.1007/s40615-022-01502-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Revised: 12/17/2022] [Accepted: 12/20/2022] [Indexed: 01/19/2023]
Abstract
OBJECTIVES Uncovering and addressing disparities in infectious disease outbreaks require a rapid, methodical understanding of local epidemiology. We conducted a seroprevalence study of SARS-CoV-2 infection in Holyoke, Massachusetts, a majority Hispanic city with high levels of socio-economic disadvantage to estimate seroprevalence and identify disparities in SARS-CoV-2 infection. METHODS We invited 2000 randomly sampled households between 11/5/2020 and 12/31/2020 to complete questionnaires and provide dried blood spots for SARS-CoV-2 antibody testing. We calculated seroprevalence based on the presence of IgG antibodies using a weighted Bayesian procedure that incorporated uncertainty in antibody test sensitivity and specificity and accounted for household clustering. RESULTS Two hundred eighty households including 472 individuals were enrolled. Three hundred twenty-eight individuals underwent antibody testing. Citywide seroprevalence of SARS-CoV-2 IgG was 13.1% (95% CI 6.9-22.3) compared to 9.8% of the population infected based on publicly reported cases. Seroprevalence was 16.1% (95% CI 6.2-31.8) among Hispanic individuals compared to 9.4% (95% CI 4.6-16.4) among non-Hispanic white individuals. Seroprevalence was higher among Spanish-speaking households (21.9%; 95% CI 8.3-43.9) compared to English-speaking households (10.2%; 95% CI 5.2-18.0) and among individuals in high social vulnerability index (SVI) areas based on the CDC SVI (14.4%; 95% CI 7.1-25.5) compared to low SVI areas (8.2%; 95% CI 3.1-16.9). CONCLUSIONS The SARS-CoV-2 IgG seroprevalence in a city with high levels of social vulnerability was 13.1% during the pre-vaccination period of the COVID-19 pandemic. Hispanic individuals and individuals in communities characterized by high SVI were at the highest risk of infection. Public health interventions should be designed to ensure that individuals in high social vulnerability communities have access to the tools to combat COVID-19.
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Affiliation(s)
- Wilfredo R Matias
- Division of Infectious Diseases, Massachusetts General Hospital, 55 Fruit St, BUL-130, Boston, MA, 02114, USA.
- Division of Infectious Diseases, Brigham and Women's Hospital, Boston, MA, USA.
- Center for Global Health, Massachusetts General Hospital, Boston, MA, USA.
| | - Isabel R Fulcher
- Department of Global Health and Social Medicine, Harvard Medical School, Boston, MA, USA
- Harvard Data Science Initiative, Cambridge, MA, USA
| | - Sara M Sauer
- Department of Global Health and Social Medicine, Harvard Medical School, Boston, MA, USA
| | - Cody P Nolan
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Yodeline Guillaume
- Center for Global Health, Massachusetts General Hospital, Boston, MA, USA
| | - Jack Zhu
- Center for Global Health, Massachusetts General Hospital, Boston, MA, USA
| | - Francisco J Molano
- Center for Global Health, Massachusetts General Hospital, Boston, MA, USA
| | - Elizabeth Uceta
- Center for Global Health, Massachusetts General Hospital, Boston, MA, USA
| | - Shannon Collins
- Center for Global Health, Massachusetts General Hospital, Boston, MA, USA
| | - Damien M Slater
- Division of Infectious Diseases, Massachusetts General Hospital, 55 Fruit St, BUL-130, Boston, MA, 02114, USA
| | - Vanessa M Sánchez
- Division of Infectious Diseases, Massachusetts General Hospital, 55 Fruit St, BUL-130, Boston, MA, 02114, USA
| | - Serina Moheed
- Division of Infectious Diseases, Massachusetts General Hospital, 55 Fruit St, BUL-130, Boston, MA, 02114, USA
| | - Jason B Harris
- Division of Infectious Diseases, Massachusetts General Hospital, 55 Fruit St, BUL-130, Boston, MA, 02114, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA
| | - Richelle C Charles
- Division of Infectious Diseases, Massachusetts General Hospital, 55 Fruit St, BUL-130, Boston, MA, 02114, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | | | | | - Molly F Franke
- Department of Global Health and Social Medicine, Harvard Medical School, Boston, MA, USA
| | - Louise C Ivers
- Division of Infectious Diseases, Massachusetts General Hospital, 55 Fruit St, BUL-130, Boston, MA, 02114, USA
- Center for Global Health, Massachusetts General Hospital, Boston, MA, USA
- Department of Global Health and Social Medicine, Harvard Medical School, Boston, MA, USA
- Harvard Global Health Institute, Cambridge, MA, USA
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13
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Wei SC, Freeman D, Himschoot A, Clarke KEN, Van Dyke ME, Adjemian J, Ahmad FB, Benoit TJ, Berney K, Gundlapalli AV, Hall AJ, Havers F, Henley SJ, Hilton C, Johns D, Opsomer JD, Pham HT, Stuckey MJ, Taylor CA, Jones JM. Who Gets Sick From COVID-19? Sociodemographic Correlates of Severe Adult Health Outcomes During Alpha- and Delta-Variant Predominant Periods: September 2020-November 2021. J Infect Dis 2024; 229:122-132. [PMID: 37615368 DOI: 10.1093/infdis/jiad357] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 08/10/2023] [Accepted: 08/17/2023] [Indexed: 08/25/2023] Open
Abstract
BACKGROUND Because COVID-19 case data do not capture most SARS-CoV-2 infections, the actual risk of severe disease and death per infection is unknown. Integrating sociodemographic data into analysis can show consequential health disparities. METHODS Data were merged from September 2020 to November 2021 from 6 national surveillance systems in matched geographic areas and analyzed to estimate numbers of COVID-19-associated cases, emergency department visits, and deaths per 100 000 infections. Relative risks of outcomes per infection were compared by sociodemographic factors in a data set including 1490 counties from 50 states and the District of Columbia, covering 71% of the US population. RESULTS Per infection with SARS-CoV-2, COVID-19-related morbidity and mortality were higher among non-Hispanic American Indian and Alaska Native persons, non-Hispanic Black persons, and Hispanic or Latino persons vs non-Hispanic White persons; males vs females; older people vs younger; residents in more socially vulnerable counties vs less; those in large central metro areas vs rural; and people in the South vs the Northeast. DISCUSSION Meaningful disparities in COVID-19 morbidity and mortality per infection were associated with sociodemography and geography. Addressing these disparities could have helped prevent the loss of tens of thousands of lives.
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Affiliation(s)
- Stanley C Wei
- COVID-19 Response Team, Centers for Disease Control and Prevention
| | - Dane Freeman
- Information and Communications Laboratory, Georgia Tech Research Institute
| | - Austin Himschoot
- Information and Communications Laboratory, Georgia Tech Research Institute
| | | | | | | | - Farida B Ahmad
- COVID-19 Response Team, Centers for Disease Control and Prevention
| | - Tina J Benoit
- COVID-19 Response Team, Centers for Disease Control and Prevention
| | - Kevin Berney
- Geospatial Research, Analysis, and Services Program, Agency for Toxic Substances and Disease Registry
| | | | - Aron J Hall
- COVID-19 Response Team, Centers for Disease Control and Prevention
| | - Fiona Havers
- COVID-19 Response Team, Centers for Disease Control and Prevention
| | - S Jane Henley
- COVID-19 Response Team, Centers for Disease Control and Prevention
| | - Charity Hilton
- Information and Communications Laboratory, Georgia Tech Research Institute
| | - Dylan Johns
- COVID-19 Response Team, Centers for Disease Control and Prevention
- Health, Environment, Economics, and Development, ICF International, Reston, Virginia
| | - Jean D Opsomer
- Center of Statistics and Data Science, WESTAT Inc, Rockville, Maryland, USA
| | - Huong T Pham
- COVID-19 Response Team, Centers for Disease Control and Prevention
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Mallela A, Chen Y, Lin YT, Miller EF, Neumann J, He Z, Nelson KE, Posner RG, Hlavacek WS. Impacts of vaccination and Severe Acute Respiratory Syndrome Coronavirus 2 variants Alpha and Delta on Coronavirus Disease 2019 transmission dynamics in four metropolitan areas of the United States. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2021.10.19.21265223. [PMID: 34704095 PMCID: PMC8547527 DOI: 10.1101/2021.10.19.21265223] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
To characterize Coronavirus Disease 2019 (COVID-19) transmission dynamics in each of the metropolitan statistical areas (MSAs) surrounding Dallas, Houston, New York City, and Phoenix in 2020 and 2021, we extended a previously reported compartmental model accounting for effects of multiple distinct periods of non-pharmaceutical interventions by adding consideration of vaccination and Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) variants Alpha (lineage B.1.1.7) and Delta (lineage B.1.617.2). For each MSA, we found region-specific parameterizations of the model using daily reports of new COVID-19 cases available from January 21, 2020 to October 31, 2021. In the process, we obtained estimates of the relative infectiousness of Alpha and Delta as well as their takeoff times in each MSA (the times at which sustained transmission began). The estimated infectiousness of Alpha ranged from 1.1x to 1.4x that of viral strains circulating in 2020 and early 2021. The estimated relative infectiousness of Delta was higher in all cases, ranging from 1.6x to 2.1x. The estimated Alpha takeoff times ranged from February 1 to February 28, 2021. The estimated Delta takeoff times ranged from June 2 to June 26, 2021. Estimated takeoff times are consistent with genomic surveillance data. One-Sentence Summary Using a compartmental model parameterized to reproduce available reports of new Coronavirus Disease 2019 (COVID-19) cases, we quantified the impacts of vaccination and Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) variants Alpha (lineage B.1.1.7) and Delta (lineage B.1.617.2) on regional epidemics in the metropolitan statistical areas (MSAs) surrounding Dallas, Houston, New York City, and Phoenix.
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15
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Roubinian NH, Greene J, Liu VX, Lee C, Mark DG, Vinson DR, Spencer BR, Bruhn R, Bravo M, Stone M, Custer B, Kleinman S, Busch MP, Norris PJ. Clinical outcomes in hospitalized plasma and platelet transfusion recipients prior to and following widespread blood donor SARS-CoV-2 infection and vaccination. Transfusion 2024; 64:53-67. [PMID: 38054619 PMCID: PMC10842807 DOI: 10.1111/trf.17616] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2023] [Revised: 11/06/2023] [Accepted: 11/09/2023] [Indexed: 12/07/2023]
Abstract
BACKGROUND The safety of transfusion of SARS-CoV-2 antibodies in high plasma volume blood components to recipients without COVID-19 is not established. We assessed whether transfusion of plasma or platelet products during periods of increasing prevalence of blood donor SARS-CoV-2 infection and vaccination was associated with changes in outcomes in hospitalized patients without COVID-19. METHODS We conducted a retrospective cohort study of hospitalized adults who received plasma or platelet transfusions at 21 hospitals during pre-COVID-19 (3/1/2018-2/29/2020), COVID-19 pre-vaccine (3/1/2020-2/28/2021), and COVID-19 post-vaccine (3/1/2021-8/31/2022) study periods. We used multivariable logistic regression with generalized estimating equations to adjust for demographics and comorbidities to calculate odds ratios (ORs) and 95% confidence intervals (CIs). RESULTS Among 21,750 hospitalizations of 18,584 transfusion recipients without COVID-19, there were 697 post-transfusion thrombotic events, and oxygen requirements were increased in 1751 hospitalizations. Intensive care unit length of stay (n = 11,683) was 3 days (interquartile range 1-5), hospital mortality occurred in 3223 (14.8%), and 30-day rehospitalization in 4144 (23.7%). Comparing the pre-COVID, pre-vaccine and post-vaccine study periods, there were no trends in thromboses (OR 0.9 [95% CI 0.8, 1.1]; p = .22) or oxygen requirements (OR 1.0 [95% CI 0.9, 1.1]; p = .41). In parallel, there were no trends across study periods for ICU length of stay (p = .83), adjusted hospital mortality (OR 1.0 [95% CI 0.9-1.0]; p = .36), or 30-day rehospitalization (p = .29). DISCUSSION Transfusion of plasma and platelet blood components collected during the pre-vaccine and post-vaccine periods of the COVID-19 pandemic was not associated with increased adverse outcomes in transfusion recipients without COVID-19.
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Affiliation(s)
- Nareg H Roubinian
- Kaiser Permanente Northern California Division of Research, Oakland, California, USA
- Vitalant Research Institute, San Francisco, California, USA
- Department of Laboratory Medicine, UCSF, San Francisco, California, USA
| | - John Greene
- Kaiser Permanente Northern California Division of Research, Oakland, California, USA
| | - Vincent X Liu
- Kaiser Permanente Northern California Division of Research, Oakland, California, USA
| | - Catherine Lee
- Kaiser Permanente Northern California Division of Research, Oakland, California, USA
| | - Dustin G Mark
- Kaiser Permanente Northern California Division of Research, Oakland, California, USA
| | - David R Vinson
- Kaiser Permanente Northern California Division of Research, Oakland, California, USA
| | - Bryan R Spencer
- American Red Cross, Scientific Affairs, Dedham, Massachusetts, USA
| | - Roberta Bruhn
- Vitalant Research Institute, San Francisco, California, USA
- Department of Laboratory Medicine, UCSF, San Francisco, California, USA
| | | | - Mars Stone
- Vitalant Research Institute, San Francisco, California, USA
- Department of Laboratory Medicine, UCSF, San Francisco, California, USA
| | - Brian Custer
- Vitalant Research Institute, San Francisco, California, USA
- Department of Laboratory Medicine, UCSF, San Francisco, California, USA
| | - Steve Kleinman
- University of British Columbia, Vancouver, British Columbia, Canada
| | - Michael P Busch
- Vitalant Research Institute, San Francisco, California, USA
- Department of Laboratory Medicine, UCSF, San Francisco, California, USA
| | - Philip J Norris
- Vitalant Research Institute, San Francisco, California, USA
- Department of Laboratory Medicine, UCSF, San Francisco, California, USA
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Chen YY, Yang MH, Lai JZ, Chen JW, Wang YL, Wei ST, Hou SM, Chen CJ, Wu HS. Seroprevalence of Anti-SARS-CoV-2 Remained Extremely Low in Taiwan Until the Vaccination Program Was Implemented. Open Forum Infect Dis 2024; 11:ofad614. [PMID: 38192381 PMCID: PMC10773475 DOI: 10.1093/ofid/ofad614] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Accepted: 12/13/2023] [Indexed: 01/10/2024] Open
Abstract
Background The Taiwanese government made a concerted effort to contain a coronavirus disease 2019 (COVID-19) nosocomial outbreak of variant B.1.429, shortly before universal vaccination program implementation. This study aimed to investigate seroprevalence in the highest-risk regions. Methods Between January and February 2021, we retrieved 10 000 repository serum samples from blood donors to examine for antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleocapsid (N) and spike (S) antigens. A positive result was confirmed if anti-N and anti-S antibodies were positive. Overall, 2000 donors residing in the highest-risk district and donating blood in January 2021 were further examined for SARS-CoV-2 RNA. We estimated seroprevalence and compared the epidemic curve between confirmed COVID-19 cases and blood donors with positive antibodies or viral RNA. Results Twenty-one cases with COVID-19 were confirmed in the nosocomial cluster, with an incidence of 1.27/100 000 in the COVID-affected districts. Among 4888 close contacts of the nosocomial cases, 20 (0.4%) became confirmed cases during isolation. Anti-SARS-CoV-2 was detected in 2 of the 10000 blood donors, showing a seroprevalence of 2/10000 (95% CI, 0.55-7.29). None of the 2000 donors who underwent tests for SARS-CoV-2 RNA were positive. The SARS-CoV-2 infection epidemic curve was observed sporadically in blood donors compared with the nosocomial cluster. Conclusions In early 2021, an extremely low anti-SARS-CoV-2 seroprevalence among blood donors was observed. Epidemic control measures through precise close contact tracing, testing, and isolation effectively contained SARS-CoV-2 transmission before universal vaccination program implementation.
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Affiliation(s)
| | | | | | - Jen-Wei Chen
- Taiwan Blood Services Foundation, Taipei, Taiwan
| | | | | | - Sheng-Mou Hou
- Taiwan Blood Services Foundation, Taipei, Taiwan
- Shin Kong Wu Ho-Su Memorial Hospital, Taipei, Taiwan
| | | | - Ho-Sheng Wu
- Hsinchu Blood Center, Hsinchu, Taiwan
- Taipei Medical University, Taipei, Taiwan
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17
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Weinberger DM, Bhaskaran K, Korves C, Lucas BP, Columbo JA, Vashi A, Davies L, Justice AC, Rentsch CT. Excess mortality in US Veterans during the COVID-19 pandemic: an individual-level cohort study. Int J Epidemiol 2023; 52:1725-1734. [PMID: 37802889 PMCID: PMC10749763 DOI: 10.1093/ije/dyad136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Accepted: 09/20/2023] [Indexed: 10/08/2023] Open
Abstract
BACKGROUND Most analyses of excess mortality during the COVID-19 pandemic have employed aggregate data. Individual-level data from the largest integrated healthcare system in the US may enhance understanding of excess mortality. METHODS We performed an observational cohort study following patients receiving care from the Department of Veterans Affairs (VA) between 1 March 2018 and 28 February 2022. We estimated excess mortality on an absolute scale (i.e. excess mortality rates, number of excess deaths) and a relative scale by measuring the hazard ratio (HR) for mortality comparing pandemic and pre-pandemic periods, overall and within demographic and clinical subgroups. Comorbidity burden and frailty were measured using the Charlson Comorbidity Index and Veterans Aging Cohort Study Index, respectively. RESULTS Of 5 905 747 patients, the median age was 65.8 years and 91% were men. Overall, the excess mortality rate was 10.0 deaths/1000 person-years (PY), with a total of 103 164 excess deaths and pandemic HR of 1.25 (95% CI 1.25-1.26). Excess mortality rates were highest among the most frail patients (52.0/1000 PY) and those with the highest comorbidity burden (16.3/1000 PY). However, the largest relative mortality increases were observed among the least frail (HR 1.31, 95% CI 1.30-1.32) and those with the lowest comorbidity burden (HR 1.44, 95% CI 1.43-1.46). CONCLUSIONS Individual-level data offered crucial clinical and operational insights into US excess mortality patterns during the COVID-19 pandemic. Notable differences emerged among clinical risk groups, emphasizing the need for reporting excess mortality in both absolute and relative terms to inform resource allocation in future outbreaks.
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Affiliation(s)
- Daniel M Weinberger
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
- Center for Interdisciplinary Research on AIDS, Yale School of Public Health, New Haven, CT, USA
| | - Krishnan Bhaskaran
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK
| | - Caroline Korves
- Department of Veterans Affairs Medical Center, Clinical Epidemiology Program, White River Junction, VT, USA
| | - Brian P Lucas
- Department of Veterans Affairs Medical Center, VA Outcomes Group, White River Junction, VT, USA
- The Dartmouth Institute for Health Policy & Clinical Practice, Geisel School of Medicine at Dartmouth, Hanover, NH, USA
| | - Jesse A Columbo
- Department of Veterans Affairs Medical Center, VA Outcomes Group, White River Junction, VT, USA
- The Dartmouth Institute for Health Policy & Clinical Practice, Geisel School of Medicine at Dartmouth, Hanover, NH, USA
- Section of Vascular Surgery, Dartmouth Hitchcock Medical Center, Lebanon, NH, USA
| | - Anita Vashi
- Center for Innovation to Implementation, VA Palo Alto Health Care System, Menlo Park, CA, USA
- Department of Emergency Medicine, University of California, San Francisco, CA, USA
| | - Louise Davies
- Department of Veterans Affairs Medical Center, VA Outcomes Group, White River Junction, VT, USA
- The Dartmouth Institute for Health Policy & Clinical Practice, Geisel School of Medicine at Dartmouth, Hanover, NH, USA
- Department of Surgery—Otolaryngology Head & Neck Surgery, Geisel School of Medicine at Dartmouth, Hanover, NH, USA
| | - Amy C Justice
- Center for Interdisciplinary Research on AIDS, Yale School of Public Health, New Haven, CT, USA
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
- Department of Veterans Affairs, VA Connecticut Healthcare System, West Haven, CT, USA
| | - Christopher T Rentsch
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
- Department of Veterans Affairs, VA Connecticut Healthcare System, West Haven, CT, USA
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18
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Taylor KM, Ricks KM, Kuehnert PA, Eick-Cost AA, Scheckelhoff MR, Wiesen AR, Clements TL, Hu Z, Zak SE, Olschner SP, Herbert AS, Bazaco SL, Creppage KE, Fan MT, Sanchez JL. Seroprevalence as an Indicator of Undercounting of COVID-19 Cases in a Large Well-Described Cohort. AJPM FOCUS 2023; 2:100141. [PMID: 37885754 PMCID: PMC10598697 DOI: 10.1016/j.focus.2023.100141] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 10/28/2023]
Abstract
Introduction Reported confirmed cases represent a small portion of overall true cases for many infectious diseases. The undercounting of true cases can be considerable when a significant portion of infected individuals are asymptomatic or minimally symptomatic, as is the case with COVID-19. Seroprevalence studies are an efficient way to assess the extent to which true cases are undercounted during a large-scale outbreak and can inform efforts to improve case identification and reporting. Methods A longitudinal seroprevalence study of active duty U.S. military members was conducted from May 2020 through June 2021. A random selection of service member serum samples submitted to the Department of Defense Serum Repository was analyzed for the presence of antibodies reactive to SARS-CoV-2. The monthly seroprevalence rates were compared with those of cumulative confirmed cases reported during the study period. Results Seroprevalence was 2.3% in May 2020 and increased to 74.0% by June 2021. The estimated true case count based on seroprevalence was 9.3 times greater than monthly reported cases at the beginning of the study period and fell to 1.7 by the end of the study. Conclusions In our sample, confirmed case counts significantly underestimated true cases of COVID-19. The increased availability of testing over the study period and enhanced efforts to detect asymptomatic and minimally symptomatic cases likely contributed to the fall in the seroprevalence to reported case ratio.
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Affiliation(s)
- Kevin M. Taylor
- Armed Forces Health Surveillance Division, Defense Health Agency, Silver Spring, Maryland
- Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, Maryland
| | - Keersten M. Ricks
- United States Army Medical Research Institute of Infectious Diseases, Frederick, Maryland
| | - Paul A. Kuehnert
- United States Army Medical Research Institute of Infectious Diseases, Frederick, Maryland
| | - Angelia A. Eick-Cost
- Armed Forces Health Surveillance Division, Defense Health Agency, Silver Spring, Maryland
| | - Mark R. Scheckelhoff
- Armed Forces Health Surveillance Division, Defense Health Agency, Silver Spring, Maryland
| | - Andrew R. Wiesen
- Health Readiness Policy and Oversight, Office of the Assistant Secretary of Defense for Health Affairs, Washington, District of Columbia
| | - Tamara L. Clements
- United States Army Medical Research Institute of Infectious Diseases, Frederick, Maryland
| | - Zheng Hu
- Armed Forces Health Surveillance Division, Defense Health Agency, Silver Spring, Maryland
| | - Samantha E. Zak
- United States Army Medical Research Institute of Infectious Diseases, Frederick, Maryland
| | - Scott P. Olschner
- United States Army Medical Research Institute of Infectious Diseases, Frederick, Maryland
| | - Andrew S. Herbert
- United States Army Medical Research Institute of Infectious Diseases, Frederick, Maryland
| | - Sara L. Bazaco
- Armed Forces Health Surveillance Division, Defense Health Agency, Silver Spring, Maryland
| | - Kathleen E. Creppage
- Armed Forces Health Surveillance Division, Defense Health Agency, Silver Spring, Maryland
| | - Michael T. Fan
- Armed Forces Health Surveillance Division, Defense Health Agency, Silver Spring, Maryland
| | - Jose L. Sanchez
- Armed Forces Health Surveillance Division, Defense Health Agency, Silver Spring, Maryland
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19
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Fonseca L, Pereira FM, Moura L, Brito A, Lobo F, Amaral AP, Costa M. COVID-19 in a Portuguese whole blood donor population. Heliyon 2023; 9:e20570. [PMID: 38027845 PMCID: PMC10651442 DOI: 10.1016/j.heliyon.2023.e20570] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Revised: 09/28/2023] [Accepted: 09/29/2023] [Indexed: 12/01/2023] Open
Abstract
Coronavirus disease 2019 (COVID-19) is an infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), leading to pneumonia and acute respiratory distress syndrome. The COVID-19 pandemic had a major impact on the stock of blood banks worldwide. This study aims to assess the prevalence of COVID-19 in a population of whole blood donors and analyze the possible association between blood group and susceptibility to the disease and the impact of adopting preventive measures against SARS-CoV-2 infection. Material and methods: This retrospective study included all whole blood donors from a Portuguese hospital between July and September 2021. A self-assessment questionnaire was used to collect data on COVID-19 infection, vaccination, and preventive measures. Statistical analysis was performed using Chi-square and Mann-Whitney U tests. Results: The prevalence of COVID-19 in the donor population was 11.96% (n = 97), with only 2 cases of serious illness requiring hospitalization. No association was found between blood group and disease susceptibility. Older men were less likely to adopt preventive measures. The vaccination rate was high, with 84.26% of donors having received at least one dose of the vaccine. Seven donors declined COVID-19 vaccination. Preventive measures did not differ based on COVID-19 infection status or vaccination. Discussion: Although there was a higher frequency of COVID-19 in group A donors, the blood group was not associated with susceptibility to infection. The donor population consisted of young individuals without comorbidities, showing a COVID-19 prevalence like the general population and few severe cases. The high vaccination rate and adoption of preventive measures likely contributed to these findings.
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Affiliation(s)
- Liliana Fonseca
- Serviço de Sangue e Medicina Transfusional, Centro Hospitalar Tondela-Viseu, Portugal
| | | | - Luís Moura
- Serviço de Sangue e Medicina Transfusional, Centro Hospitalar Tondela-Viseu, Portugal
| | - Arnaldo Brito
- Serviço de Sangue e Medicina Transfusional, Centro Hospitalar Tondela-Viseu, Portugal
| | - Filipe Lobo
- Serviço de Sangue e Medicina Transfusional, Centro Hospitalar Tondela-Viseu, Portugal
| | - Ana Palmira Amaral
- Serviço de Sangue e Medicina Transfusional, Centro Hospitalar Tondela-Viseu, Portugal
| | - Marina Costa
- Serviço de Sangue e Medicina Transfusional, Centro Hospitalar Tondela-Viseu, Portugal
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20
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Fantin R, Agarwala N, Aparicio A, Pfeiffer R, Waterboer T, Abdelnour A, Butt J, Flock J, Remans K, Prevots DR, Porras C, Hildesheim A, Loria V, Gail MH, Herrero R. Estimating the cumulative incidence of SARS-CoV-2 infection in Costa Rica: modelling seroprevalence data in a population-based cohort. LANCET REGIONAL HEALTH. AMERICAS 2023; 27:100616. [PMID: 37868648 PMCID: PMC10589740 DOI: 10.1016/j.lana.2023.100616] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Revised: 09/21/2023] [Accepted: 09/29/2023] [Indexed: 10/24/2023]
Abstract
Background The true incidence of SARS-CoV-2 infection in Costa Rica was likely much higher than officially reported, because infection is often associated with mild symptoms and testing was limited by official guidelines and socio-economic factors. Methods Using serology to define natural infection, we developed a statistical model to estimate the true cumulative incidence of SARS-CoV-2 in Costa Rica early in the pandemic. We estimated seroprevalence from 2223 blood samples collected from November 2020 to October 2021 from 1976 population-based controls from the RESPIRA study. Samples were tested for antibodies against SARS-CoV-2 nucleocapsid and the receptor-binding-domain of the spike proteins. Using a generalized linear model, we estimated the ratio of true infections to officially reported cases. Applying these ratios to officially reported totals by age, sex, and geographic area, we estimated the true number of infections in the study area, where 70% of Costa Ricans reside. We adjusted the seroprevalence estimates for antibody decay over time, estimated from 1562 blood samples from 996 PCR-confirmed COVID-19 cases. Findings The estimated total proportion infected (ETPI) was 4.0 times higher than the officially reported total proportion infected (OTPI). By December 16th, 2021, the ETPI was 47% [42-52] while the OTPI was 12%. In children and adolescents, the ETPI was 11.0 times higher than the OTPI. Interpretation Our findings suggest that nearly half the population had been infected by the end of 2021. By the end of 2022, it is likely that a large majority of the population had been infected. Funding This work was sponsored and funded by the National Institute of Allergy and Infectious Diseases through the National Cancer Institute, the Science, Innovation, Technology and Telecommunications Ministry of Costa Rica, and Costa Rican Biomedical Research Agency-Fundacion INCIENSA (grant N/A).
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Affiliation(s)
- Romain Fantin
- Agencia Costarricense de Investigaciones Biomédicas, Fundación INCIENSA, San José, Costa Rica
| | - Neha Agarwala
- Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Amada Aparicio
- Caja Costarricense de Seguro Social, San José, Costa Rica
| | - Ruth Pfeiffer
- Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Tim Waterboer
- Division of Infections and Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | | | - Julia Butt
- Division of Infections and Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Julia Flock
- European Molecular Biology Laboratory (EMBL), Heidelberg, Germany
| | - Kim Remans
- European Molecular Biology Laboratory (EMBL), Heidelberg, Germany
| | - D. Rebecca Prevots
- Epidemiology and Population Studies Unit, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, Rockville, MD, USA
| | - Carolina Porras
- Agencia Costarricense de Investigaciones Biomédicas, Fundación INCIENSA, San José, Costa Rica
| | - Allan Hildesheim
- Agencia Costarricense de Investigaciones Biomédicas, Fundación INCIENSA, San José, Costa Rica
| | - Viviana Loria
- Agencia Costarricense de Investigaciones Biomédicas, Fundación INCIENSA, San José, Costa Rica
| | - Mitchell H. Gail
- Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Rolando Herrero
- Agencia Costarricense de Investigaciones Biomédicas, Fundación INCIENSA, San José, Costa Rica
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21
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Dayan GH, Rouphael N, Walsh SR, Chen A, Grunenberg N, Allen M, Antony J, Asante KP, Bhate AS, Beresnev T, Bonaparte MI, Celle M, Ceregido MA, Corey L, Dobrianskyi D, Fu B, Grillet MH, Keshtkar-Jahromi M, Juraska M, Kee JJ, Kibuuka H, Koutsoukos M, Masotti R, Michael NL, Neuzil KM, Reynales H, Robb ML, Villagómez Martínez SM, Sawe F, Schuerman L, Tong T, Treanor J, Wartel TA, Diazgranados CA, Chicz RM, Gurunathan S, Savarino S, Sridhar S. Efficacy of a bivalent (D614 + B.1.351) SARS-CoV-2 recombinant protein vaccine with AS03 adjuvant in adults: a phase 3, parallel, randomised, modified double-blind, placebo-controlled trial. THE LANCET. RESPIRATORY MEDICINE 2023; 11:975-990. [PMID: 37716365 PMCID: PMC10872639 DOI: 10.1016/s2213-2600(23)00263-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 06/16/2023] [Accepted: 07/04/2023] [Indexed: 09/18/2023]
Abstract
BACKGROUND COVID-19 vaccines with alternative strain compositions are needed to provide broad protection against newly emergent SARS-CoV-2 variants of concern. This study aimed to describe the clinical efficacy and safety of a bivalent SARS-CoV-2 recombinant protein vaccine as a two-injection primary series during a period of circulation of the omicron (B.1.1.529) variant. METHODS We conducted a phase 3, parallel, randomised, modified double-blind, placebo-controlled trial in adults aged 18 years or older at 54 clinical research centres in eight countries (Colombia, Ghana, India, Kenya, Mexico, Nepal, Uganda, and Ukraine). Participants were recruited from the community and randomly assigned (1:1) by use of an interactive response technology system to receive two intramuscular 0·5 mL injections, 21 days apart, of the bivalent vaccine (5 μg of ancestral [D614] and 5 μg of beta [B.1.351] variant spike protein, with AS03 adjuvant) or placebo (0·9% normal saline). All participants, outcome assessors, and laboratory staff performing assays were masked to group assignments; those involved in the preparation and administration of the vaccines were unmasked. Participants were stratified by age (18-59 years and ≥60 years) and baseline SARS-CoV-2 rapid serodiagnostic test positivity. Symptomatic COVID-19 was defined as laboratory-confirmed (via nucleic acid amplification test or PCR test) COVID-19 with COVID-19-like illness symptoms. The primary efficacy endpoint was the clinical efficacy of the bivalent vaccine for prevention of symptomatic COVID-19 at least 14 days after the second injection (dose 2). Safety was assessed in all participants receiving at least one injection of the study vaccine or placebo. This trial is registered with ClinicalTrials.gov (NCT04904549) and is closed to recruitment. FINDINGS Between Oct 19, 2021, and Feb 15, 2022, 13 002 participants were enrolled and randomly assigned to receive the first dose of the study vaccine (n=6512) or placebo (n=6490). 12 924 participants (6472 in the vaccine group and 6452 in the placebo group) received at least one study injection, of whom 7542 (58·4%) were male and 9693 (75·0%) were SARS-CoV-2 non-naive. Of these 12 924 participants, 11 543 (89·3%) received both study injections (5788 in the vaccine group and 5755 in the placebo group). The efficacy-evaluable population after dose 2 comprised 11 416 participants (5736 in the vaccine group and 5680 in the placebo group). The median duration of follow-up was 85 days (IQR 50-95) after dose 1 and 58 days (29-70) after dose 2. 121 symptomatic COVID-19 cases were reported at least 14 days after dose 2 (32 in the vaccine group and 89 in the placebo group), with an overall vaccine efficacy of 64·7% (95% CI 46·6 to 77·2). Vaccine efficacy against symptomatic COVID-19 was 75·1% (95% CI 56·3 to 86·6) in SARS-CoV-2 non-naive participants and 30·9% (-39·3 to 66·7) in SARS-CoV-2-naive participants. Viral genome sequencing identified the infecting strain in 68 (56·2%) of 121 cases (omicron [BA.1 and BA.2] in 63; delta in four; and both omicron and delta in one). Immediate unsolicited adverse events were reported by four (<0·1%) participants in the vaccine group and seven (0·1%) participants in the placebo group. Immediate unsolicited adverse reactions within 30 min after any injection were reported by four (<0·1%) participants in the vaccine group and six (<0·1%) participants in the placebo group. In the reactogenicity subset with available data, solicited reactions (solicited injection-site reactions and solicited systemic reactions) within 7 days after any injection occurred in 1398 (57·8%) of 2420 vaccine recipients and 983 (40·9%) of 2403 placebo recipients. Grade 3 solicited reactions were reported by 196 (8·1%; 95% CI 7·0 to 9·3) of 2420 vaccine recipients and 118 (4·9%; 4·1 to 5·9) of 2403 placebo recipients within 7 days after any injection, with comparable frequencies after dose 1 and dose 2 in the vaccine group. At least one serious adverse event occurred in 30 (0·5%) participants in the vaccine group and 26 (0·4%) in the placebo group. The proportion of adverse events of special interest and deaths was less than 0·1% in both study groups. No adverse event of special interest, serious adverse event, or death was deemed to be treatment related. There were no reported cases of thrombosis with thrombocytopenia syndrome, myocarditis, pericarditis, Bell's Palsy, or Guillain-Barré syndrome, or other immune-mediated diseases. INTERPRETATION The bivalent variant vaccine conferred heterologous protection against symptomatic SARS-CoV-2 infection in the epidemiological context of the circulating contemporary omicron variant. These findings suggest that vaccines developed with an antigen from a non-predominant strain could confer cross-protection against newly emergent SARS-CoV-2 variants, although further investigation is warranted. FUNDING Sanofi, US Biomedical Advanced Research and Development Authority, and the US National Institute of Allergy and Infectious Diseases.
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Affiliation(s)
| | | | | | | | | | - Mary Allen
- National Institute of Allergy and Infectious Diseases / National Institutes of Health, Bethesda, MD, USA
| | | | - Kwaku Poku Asante
- Research and Development Division, Ghana Health Service, Kintampo North Municipality, Ghana
| | | | - Tatiana Beresnev
- National Institute of Allergy and Infectious Diseases / National Institutes of Health, Bethesda, MD, USA
| | | | | | | | | | | | - Bo Fu
- National Institute of Allergy and Infectious Diseases / National Institutes of Health, Bethesda, MD, USA
| | | | - Maryam Keshtkar-Jahromi
- National Institutes of Health, Rockville, MD, USA; John Hopkins University School of Medicine, Baltimore, MD, USA
| | | | - Jia Jin Kee
- Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Hannah Kibuuka
- Makerere University Walter Reed Project, Kampala, Uganda
| | | | | | | | | | - Humberto Reynales
- Centro de Attencion e Investigation Medica S.A.S. - Caimed Chía, Chía, Colombia
| | - Merlin L Robb
- The Henry M Jackson Foundation for the Advancement of Military Medicine, Bethesda, MA, USA
| | | | - Fredrick Sawe
- Kenya Medical Research Institute - US Army Medical Research, Kericho, Kenya
| | | | - Tina Tong
- National Institute of Allergy and Infectious Diseases / National Institutes of Health, Bethesda, MD, USA
| | - John Treanor
- Tunnell Government Services in support of Biomedical Advanced Research and Development Authority, Administration for Strategic Preparedness and Response, Department of Health and Human Services, Washington, DC, USA
| | - T Anh Wartel
- International Vaccine Institute, Seoul, South Korea
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22
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Tomov L, Chervenkov L, Miteva DG, Batselova H, Velikova T. Applications of time series analysis in epidemiology: Literature review and our experience during COVID-19 pandemic. World J Clin Cases 2023; 11:6974-6983. [PMID: 37946767 PMCID: PMC10631421 DOI: 10.12998/wjcc.v11.i29.6974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 08/12/2023] [Accepted: 09/04/2023] [Indexed: 10/13/2023] Open
Abstract
Time series analysis is a valuable tool in epidemiology that complements the classical epidemiological models in two different ways: Prediction and forecast. Prediction is related to explaining past and current data based on various internal and external influences that may or may not have a causative role. Forecasting is an exploration of the possible future values based on the predictive ability of the model and hypothesized future values of the external and/or internal influences. The time series analysis approach has the advantage of being easier to use (in the cases of more straightforward and linear models such as Auto-Regressive Integrated Moving Average). Still, it is limited in forecasting time, unlike the classical models such as Susceptible-Exposed-Infectious-Removed. Its applicability in forecasting comes from its better accuracy for short-term prediction. In its basic form, it does not assume much theoretical knowledge of the mechanisms of spreading and mutating pathogens or the reaction of people and regulatory structures (governments, companies, etc.). Instead, it estimates from the data directly. Its predictive ability allows testing hypotheses for different factors that positively or negatively contribute to the pandemic spread; be it school closures, emerging variants, etc. It can be used in mortality or hospital risk estimation from new cases, seroprevalence studies, assessing properties of emerging variants, and estimating excess mortality and its relationship with a pandemic.
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Affiliation(s)
- Latchezar Tomov
- Department of Informatics, New Bulgarian University, Sofia 1618, Bulgaria
| | - Lyubomir Chervenkov
- Department of Diagnostic Imaging, Medical University Plovdiv, Plovdiv 4000, Bulgaria
| | - Dimitrina Georgieva Miteva
- Department of Genetics, Faculty of Biology, Sofia University "St. Kliment Ohridski", Sofia 1164, Bulgaria
| | - Hristiana Batselova
- Department of Epidemiology and Disaster Medicine, Medical University, University Hospital "St George", Plovdiv 4000, Bulgaria
| | - Tsvetelina Velikova
- Department of Medical Faculty, Sofia University, St. Kliment Ohridski, Sofia 1407, Bulgaria
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23
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Bloch EM, Busch MP, Corash LM, Dodd R, Hailu B, Kleinman S, O'Brien S, Petersen L, Stramer SL, Katz L. Leveraging Donor Populations to Study the Epidemiology and Pathogenesis of Transfusion-Transmitted and Emerging Infectious Diseases. Transfus Med Rev 2023; 37:150769. [PMID: 37919210 PMCID: PMC10841704 DOI: 10.1016/j.tmrv.2023.150769] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 08/22/2023] [Accepted: 08/24/2023] [Indexed: 11/04/2023]
Abstract
The tragedy of transfusion-associated hepatitis and HIV spurred a decades-long overhaul of the regulatory oversight and practice of blood transfusion. Consequent to improved donor selection, testing, process control, clinical transfusion practice and post-transfusion surveillance, transfusion in the United States and other high-income countries is now a very safe medical procedure. Nonetheless, pathogens continue to emerge and threaten the blood supply, highlighting the need for a proactive approach to blood transfusion safety. Blood donor populations and the global transfusion infrastructure are under-utilized resources for the study of infectious diseases. Blood donors are large, demographically diverse subsets of general populations for whom cross-sectional and longitudinal samples are readily accessible for serological and molecular testing. Blood donor collection networks span diverse geographies, including in low- and middle-income countries, where agents, especially zoonotic pathogens, are able to emerge and spread, given limited tools for recognition, surveillance and control. Routine laboratory storage and transportation, coupled with data capture, afford access to rich epidemiological data to assess the epidemiology and pathogenesis of established and emerging infections. Subsequent to the State of the Science in Transfusion Medicine symposium in 2022, our working group (WG), "Emerging Infections: Impact on Blood Science, the Blood Supply, Blood Safety, and Public Health" elected to focus on "leveraging donor populations to study the epidemiology and pathogenesis of transfusion-transmitted and emerging infectious diseases." The 5 landmark studies span (1) the implication of hepatitis C virus in post-transfusion hepatitis, (2) longitudinal evaluation of plasma donors with incident infections, thus informing the development of a widely used staging system for acute HIV infection, (3) explication of the dynamics of early West Nile Virus infection, (4) the deployment of combined molecular and serological donor screening for Babesia microti, to characterize its epidemiology and infectivity and facilitate routine donor screening, and (5) national serosurveillance for SARS-CoV-2 during the COVID-19 pandemic. The studies highlight the interplay between infectious diseases and transfusion medicine, including the imperative to ensure blood transfusion safety and the broader application of blood donor populations to the study of infectious diseases.
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Affiliation(s)
- Evan M Bloch
- Division of Transfusion Medicine, Department of Pathology, Johns Hopkins University, Baltimore, MD, USA.
| | - Michael P Busch
- Vitalant Research Institute, San Francisco, CA, USA; Department of Laboratory Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Laurence M Corash
- Cerus Corporation, Concord, CA, USA; Department of Laboratory Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Roger Dodd
- Scientific Affairs, American Red Cross, Gaithersburg, MD, USA
| | - Benyam Hailu
- Division of Blood Diseases Research, National Heart Lung and Blood Institute, Bethesda, MD, USA
| | | | - Sheila O'Brien
- Canadian Blood Services, Epidemiology and Surveillance, Microbiology, Ottawa, ON, Canada; School of Epidemiology and Public Health, University of Ottawa, Ottawa, ON, Canada
| | - Lyle Petersen
- Division of Vector-Borne Diseases, National Center for Emerging and Zoonotic Infectious Diseases, Fort Collins, Colorado, USA
| | - Susan L Stramer
- Scientific Affairs, American Red Cross, Gaithersburg, MD, USA
| | - Louis Katz
- ImpactLife Blood Services, Davenport, IA, USA
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24
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D'Alessandro A, Hod EA. Red Blood Cell Storage: From Genome to Exposome Towards Personalized Transfusion Medicine. Transfus Med Rev 2023; 37:150750. [PMID: 37574398 PMCID: PMC10834861 DOI: 10.1016/j.tmrv.2023.150750] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Revised: 06/02/2023] [Accepted: 06/04/2023] [Indexed: 08/15/2023]
Abstract
Over the last decade, the introduction of omics technologies-especially high-throughput genomics and metabolomics-has contributed significantly to our understanding of the role of donor genetics and nongenetic determinants of red blood cell storage biology. Here we briefly review the main advances in these areas, to the extent these contributed to the appreciation of the impact of donor sex, age, ethnicity, but also processing strategies and donor environmental, dietary or other exposures - the so-called exposome-to the onset and severity of the storage lesion. We review recent advances on the role of genetically encoded polymorphisms on red cell storage biology, and relate these findings with parameters of storage quality and post-transfusion efficacy, such as hemolysis, post-transfusion intra- and extravascular hemolysis and hemoglobin increments. Finally, we suggest that the combination of these novel technologies have the potential to drive further developments towards personalized (or precision) transfusion medicine approaches.
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Affiliation(s)
- Angelo D'Alessandro
- Department of Biochemistry and Molecular Genetics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
| | - Eldad A Hod
- Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, NY, USA
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25
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Kinoshita R, Arashiro T, Kitamura N, Arai S, Takahashi K, Suzuki T, Suzuki M, Yoneoka D. Infection-Induced SARS-CoV-2 Seroprevalence among Blood Donors, Japan, 2022. Emerg Infect Dis 2023; 29:1868-1871. [PMID: 37506681 PMCID: PMC10461656 DOI: 10.3201/eid2909.230365] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/30/2023] Open
Abstract
A nationwide survey of SARS-CoV-2 antinucleocapsid seroprevalence among blood donors in Japan revealed that, as of November 2022, infection-induced seroprevalence of the population was 28.6% (95% CI 27.6%-29.6%). Seroprevalence studies might complement routine surveillance and ongoing monitoring efforts to provide a more complete real-time picture of COVID-19 burden.
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Affiliation(s)
- Ryo Kinoshita
- National Institute of Infectious Diseases, Tokyo, Japan (R. Kinoshita, T. Arashiro, N. Kitamura, S. Arai, T. Suzuki, M. Suzuki, D. Yoneoka)
- Japanese Red Cross Society, Tokyo, Japan (K. Takahashi)
| | - Takeshi Arashiro
- National Institute of Infectious Diseases, Tokyo, Japan (R. Kinoshita, T. Arashiro, N. Kitamura, S. Arai, T. Suzuki, M. Suzuki, D. Yoneoka)
- Japanese Red Cross Society, Tokyo, Japan (K. Takahashi)
| | - Noriko Kitamura
- National Institute of Infectious Diseases, Tokyo, Japan (R. Kinoshita, T. Arashiro, N. Kitamura, S. Arai, T. Suzuki, M. Suzuki, D. Yoneoka)
- Japanese Red Cross Society, Tokyo, Japan (K. Takahashi)
| | - Satoru Arai
- National Institute of Infectious Diseases, Tokyo, Japan (R. Kinoshita, T. Arashiro, N. Kitamura, S. Arai, T. Suzuki, M. Suzuki, D. Yoneoka)
- Japanese Red Cross Society, Tokyo, Japan (K. Takahashi)
| | - Koki Takahashi
- National Institute of Infectious Diseases, Tokyo, Japan (R. Kinoshita, T. Arashiro, N. Kitamura, S. Arai, T. Suzuki, M. Suzuki, D. Yoneoka)
- Japanese Red Cross Society, Tokyo, Japan (K. Takahashi)
| | - Tadaki Suzuki
- National Institute of Infectious Diseases, Tokyo, Japan (R. Kinoshita, T. Arashiro, N. Kitamura, S. Arai, T. Suzuki, M. Suzuki, D. Yoneoka)
- Japanese Red Cross Society, Tokyo, Japan (K. Takahashi)
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26
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Qasmieh SA, Robertson MM, Nash D. "Boosting" Surveillance for a More Impactful Public Health Response During Protracted and Evolving Infectious Disease Threats: Insights From the COVID-19 Pandemic. Health Secur 2023; 21:S47-S55. [PMID: 37643313 PMCID: PMC10818055 DOI: 10.1089/hs.2023.0046] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/31/2023] Open
Affiliation(s)
- Saba A. Qasmieh
- Saba A. Qasmieh, MPH, is a Research Scientist, Institute for Implementation Science in Population Health, and a PhD Student, Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, University of New York, New York, NY
| | - McKaylee M. Robertson
- McKaylee M. Robertson, PhD, MPH, is an Investigator, Institute for Implementation Science in Population Health, University of New York, New York, NY
| | - Denis Nash
- Denis Nash, PhD, MPH, is Executive Director, Institute for Implementation Science in Population Health, and Distinguished Professor of Epidemiology, Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, University of New York, New York, NY
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27
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Patel EU, Mehta SH, Genberg BL, Baker OR, Schluth CG, Astemborski J, Fernandez RE, Quinn TC, Kirk GD, Laeyendecker O. Prevalence and correlates of SARS-CoV-2 seropositivity among people who inject drugs in Baltimore, Maryland. DRUG AND ALCOHOL DEPENDENCE REPORTS 2023; 8:100184. [PMID: 37637232 PMCID: PMC10450408 DOI: 10.1016/j.dadr.2023.100184] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 08/07/2023] [Accepted: 08/08/2023] [Indexed: 08/29/2023]
Abstract
Background SARS-CoV-2 serosurveys can help characterize disparities in SARS-CoV-2 infection and identify gaps in population immunity. Data on SARS-CoV-2 seroprevalence among people who inject drugs (PWID) are limited. Methods We conducted a cross-sectional study between December 2020 and July 2022 among 561 participants in the AIDS Linked to the IntraVenous Experience (ALIVE) study-a community-based cohort of current and former PWID in Baltimore, Maryland. Serum samples were assayed for infection-induced anti-nucleocapsid (anti-N) and infection and/or vaccination-induced anti-spike-1 (anti-S) SARS-CoV-2 IgG. We estimated adjusted prevalence ratios (aPR) via modified Poisson regression models. Results The median age was 59 years, 35% were female, 84% were non-Hispanic Black, and 16% reported recent injection drug use. Anti-N antibody prevalence was 26% and anti-S antibody prevalence was 63%. Anti-N and anti-S antibody prevalence increased over time. Being employed (aPR=1.53 [95%CI=1.11-2.11]) was associated with higher anti-N prevalence, while a cancer history (aPR=0.40 [95%CI=0.17-0.90]) was associated with lower anti-N prevalence. HIV infection was associated with higher anti-S prevalence (aPR=1.13 [95%CI=1.02-1.27]), while younger age and experiencing homelessness (aPR=0.78 [95%CI=0.60-0.99]) were factors associated with lower anti-S prevalence. Substance use-related behaviors were not significantly associated with anti-N or anti-S prevalence. Conclusions SARS-CoV-2 seroprevalence increased over time among current and former PWID, suggesting cumulative increases in the incidence of SARS-CoV-2 infection and vaccination; however, there were disparities in infection-induced seroprevalence and infection and/or vaccine-induced seroprevalence within this study sample. Dedicated prevention and vaccination programs are needed to prevent disparities in infection and gaps in population immunity among PWID during emerging epidemics.
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Affiliation(s)
- Eshan U. Patel
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Shruti H. Mehta
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Becky L. Genberg
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Owen R. Baker
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Catherine G. Schluth
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Jacquie Astemborski
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Reinaldo E. Fernandez
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Thomas C. Quinn
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases, Baltimore, MD, USA
| | - Gregory D. Kirk
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Oliver Laeyendecker
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases, Baltimore, MD, USA
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28
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Yu EA, Jackman RP, Glesby MJ, Narayan KV. Bidirectionality between Cardiometabolic Diseases and COVID-19: Role of Humoral Immunity. Adv Nutr 2023; 14:1145-1158. [PMID: 37302794 PMCID: PMC10256583 DOI: 10.1016/j.advnut.2023.06.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2022] [Revised: 05/26/2023] [Accepted: 06/06/2023] [Indexed: 06/13/2023] Open
Abstract
Cardiometabolic diseases and abnormalities have recently emerged as independent risk factors of coronavirus disease 2019 (COVID-19) severity, including hospitalizations, invasive mechanical ventilation, and mortality. Determining whether and how this observation translates to more effective long-term pandemic mitigation strategies remains a challenge due to key research gaps. Specific pathways by which cardiometabolic pathophysiology affects humoral immunity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and vice versa, remain unclear. This review summarizes current evidence of the bidirectional influences between cardiometabolic diseases (diabetes, adiposity, hypertension, CVDs) and SARS-CoV-2 antibodies induced from infection and vaccination based on human studies. Ninety-two studies among >408,000 participants in 37 countries on 5 continents (Europe, Asia, Africa, and North and South America) were included in this review. Obesity was associated with higher neutralizing antibody titers following SARS-CoV-2 infection. Most studies conducted prior to vaccinations found positive or null associations between binding antibodies (levels, seropositivity) and diabetes; after vaccinations, antibody responses did not differ by diabetes. Hypertension and CVDs were not associated with SARS-CoV-2 antibodies. Findings underscore the importance of elucidating the extent that tailored recommendations for COVID-19 prevention, vaccination effectiveness, screening, and diagnoses among people with obesity could reduce disease burden caused by SARS-CoV-2.
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Affiliation(s)
- Elaine A Yu
- Vitalant Research Institute, San Francisco, CA; University of California, San Francisco, San Francisco, CA.
| | - Rachael P Jackman
- Vitalant Research Institute, San Francisco, CA; University of California, San Francisco, San Francisco, CA
| | - Marshall J Glesby
- Division of Infectious Diseases, Weill Cornell Medicine, New York, NY
| | - Km Venkat Narayan
- Rollins School of Public Health, Emory University, Atlanta, GA; Emory Global Diabetes Research Center of Woodruff Health Sciences Center, Emory University, Atlanta, GA
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29
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Greenwald MA, Grebe E, Green V, Jones AL, Linnen JM, Williamson P, Busch MP, Kuehnert MJ. Low rate of detection of SARS-CoV-2 RNA in deceased tissue donors. Cell Tissue Bank 2023; 24:585-596. [PMID: 36484950 PMCID: PMC9734833 DOI: 10.1007/s10561-022-10054-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Accepted: 11/18/2022] [Indexed: 12/13/2022]
Abstract
Given the possibility for disease transmission, this study was performed to determine whether there is detectable SARS-CoV-2 viral RNA in the blood of deceased tissue donors. A retrospective analysis of blood samples from eligible deceased tissue donors from Oct 2019 through June 2020 was performed. Plasma aliquots were initially tested with a SARS-CoV-2 NAT Assay; positive samples were further tested using an alternate NAT and an antibody assay. The proportion of donors with confirmed RNAemia and 95% confidence intervals were computed. Of donor samples collected in 2019, 894 yielded valid results, with 6 initially positive, none of which confirmed positive by alternate NAT. Of donor samples collected in 2020, 2562 yielded valid initial NAT results, with 21 (0.8%) initially positive. Among those, 3 were confirmed by alternate NAT, 17 were not confirmed, and 1 had an invalid alternate NAT result. The rate of SARS-CoV-2 RNAemia in deceased tissue donors is approximately 1 per 1000, and it is unknown whether this RNAemia reflects the presence of infectious virus. Given these results, the risk of transmission through tissue is thought likely to be low.
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Affiliation(s)
- Melissa A. Greenwald
- Donor Alliance, Denver, CO USA
- Uniformed Services University of the Health Sciences, Bethesda, MD USA
- MA Greenwald Consulting, Chicago, IL USA
| | - Eduard Grebe
- Vitalant Research Institute, San Francisco, CA USA
- University of California San Francisco, San Francisco, CA USA
- DSI-NRF Centre of Excellence in Epidemiological Modelling and Analysis, Stellenbosch University, Stellenbosch, South Africa
| | | | | | | | | | - Michael P. Busch
- Vitalant Research Institute, San Francisco, CA USA
- University of California San Francisco, San Francisco, CA USA
| | - Matthew J. Kuehnert
- Musculoskeletal Transplant Foundation, Edison, NJ USA
- Hackensack Meridian School of Medicine, Hackensack, NJ USA
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30
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Brown AC, Koshute PT, Cowley HP, Robinette MS, Gravelyn SR, Patel SV, Ju EY, Frommer CT, Zambidis AE, Schneider EJ, Zhao MY, Mugo BK, Clarke W, Kruczynski K, Pisanic N, Heaney CD, Colella TA. A Saliva-Based Serological and Behavioral Analysis of SARS-CoV-2 Antibody Prevalence in Howard County, Maryland. Microbiol Spectr 2023; 11:e0276522. [PMID: 37289070 PMCID: PMC10433989 DOI: 10.1128/spectrum.02765-22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Accepted: 05/10/2023] [Indexed: 06/09/2023] Open
Abstract
The objective of the study was to estimate severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seroprevalence in the Howard County, Maryland, general population and demographic subpopulations attributable to natural infection or coronavirus disease 2019 (COVID-19) vaccination and to identify self-reported social behaviors that may affect the likelihood of recent or past SARS-CoV-2 infection. A cross-sectional, saliva-based serological study of 2,880 residents of Howard County, Maryland, was carried out from July through September 2021. Natural SARS-CoV-2 infection prevalence was estimated by inferring infections among individuals according to anti-nucleocapsid immunoglobin G levels and calculating averages weighted by sample proportions of various demographics. Antibody levels between BNT162b2 (Pfizer-BioNTech) and mRNA-1273 (Moderna) recipients were compared. Antibody decay rate was calculated by fitting exponential decay curves to cross-sectional indirect immunoassay data. Regression analysis was carried out to identify demographic factors, social behaviors, and attitudes that may be linked to an increased likelihood of natural infection. The estimated overall prevalence of natural infection in Howard County, Maryland, was 11.9% (95% confidence interval, 9.2% to 15.1%), compared with 7% reported COVID-19 cases. Antibody prevalence indicating natural infection was highest among Hispanic and non-Hispanic Black participants and lowest among non-Hispanic White and non-Hispanic Asian participants. Participants from census tracts with lower average household income also had higher natural infection rates. After accounting for multiple comparisons and correlations between participants, none of the behavior or attitude factors had significant effects on natural infection. At the same time, recipients of the mRNA-1273 vaccine had higher antibody levels than those of BNT162b2 vaccine recipients. Older study participants had overall lower antibody levels compared with younger study participants. The true prevalence of SARS-CoV-2 infection is higher than the number of reported COVID-19 cases in Howard County, Maryland. A disproportionate impact of infection-induced SARS-CoV-2 positivity was observed across different ethnic/racial subpopulations and incomes, and differences in antibody levels across different demographics were identified. Taken together, this information may inform public health policy to protect vulnerable populations. IMPORTANCE We employed a highly innovative noninvasive multiplex oral fluid SARS-CoV-2 IgG assay to ascertain our seroprevalence estimates. This laboratory-developed test has been applied in NCI's SeroNet consortium, possesses high sensitivity and specificity according to FDA Emergency Use Authorization guidelines, correlates strongly with SARS-CoV-2 neutralizing antibody responses, and is Clinical Laboratory Improvement Amendments-approved by the Johns Hopkins Hospital Department of Pathology. It represents a broadly scalable public health tool to improve understanding of recent and past SARS-CoV-2 exposure and infection without drawing any blood. To our knowledge, this is the first application of a high-performance salivary SARS-CoV-2 IgG assay to estimate population-level seroprevalence, including identifying COVID-19 disparities. We also are the first to report differences in SARS-CoV-2 IgG responses by COVID-19 vaccine manufacturers (BNT162b2 [Pfizer-BioNTech] and mRNA-1273 [Moderna]). Our findings demonstrate remarkable consistency with those of blood-based SARS-CoV-2 IgG assays in terms of differences in the magnitude of SARS-CoV-2 IgG responses between COVID-19 vaccines.
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Affiliation(s)
- Alan C. Brown
- Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland, USA
| | - Phillip T. Koshute
- Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland, USA
| | - Hannah P. Cowley
- Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland, USA
| | | | - Sarah R. Gravelyn
- Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland, USA
| | - Shraddha V. Patel
- Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland, USA
| | - Eunice Y. Ju
- Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland, USA
| | - Carolyn T. Frommer
- Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland, USA
| | | | - Eric J. Schneider
- Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland, USA
| | - Martina Y. Zhao
- Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland, USA
| | - Benny K. Mugo
- Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland, USA
| | | | - Kate Kruczynski
- Johns Hopkins Environmental Health Microbiology and Immunology Laboratory (JH-EHMIL), Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Nora Pisanic
- Johns Hopkins Environmental Health Microbiology and Immunology Laboratory (JH-EHMIL), Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Christopher D. Heaney
- Johns Hopkins Environmental Health Microbiology and Immunology Laboratory (JH-EHMIL), Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Teresa A. Colella
- Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland, USA
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Sulaeman H, Grebe E, Dave H, McCann L, Di Germanio C, Sanghavi A, Sclar V, Bougie DW, Chatelain G, Biggerstaff BJ, Jones JM, Thornburg NJ, Kleinman S, Stone M, Busch MP. Evaluation of Ortho VITROS and Roche Elecsys S and NC Immunoassays for SARS-CoV-2 Serosurveillance Applications. Microbiol Spectr 2023; 11:e0323422. [PMID: 37347180 PMCID: PMC10434072 DOI: 10.1128/spectrum.03234-22] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Accepted: 05/04/2023] [Indexed: 06/23/2023] Open
Abstract
SARS-CoV-2 seroprevalence studies are instrumental in monitoring epidemic activity and require well-characterized, high-throughput assays, and appropriate testing algorithms. The U.S. Nationwide Blood Donor Seroprevalence Study performed monthly cross-sectional serological testing from July 2020 to December 2021, implementing evolving testing algorithms in response to changes in pandemic activity. With high vaccine uptake, anti-Spike (S) reactivity rates reached >80% by May 2021, and the study pivoted from reflex Roche anti-nucleocapsid (NC) testing of Ortho S-reactive specimens to parallel Ortho S/NC testing. We evaluated the performance of the Ortho NC assay as a replacement for the Roche NC assay and compared performance of parallel S/NC testing on both platforms. Qualitative and quantitative agreement of Ortho NC with Roche NC assays was evaluated on preselected S/NC concordant and discordant specimens. All 190 Ortho S+/Roche NC+ specimens were reactive on the Ortho NC assay; 34% of 367 Ortho S+/Roche NC- specimens collected prior to vaccine availability and 43% of 37 Ortho S-/Roche NC+ specimens were reactive on the Ortho NC assay. Performance of parallel S/NC testing using Ortho and Roche platforms was evaluated on 200 specimens collected in 2019 and 3,903 study specimens collected in 2021. All 200 pre-COVID-19 specimens tested negative on the four assays. Cross-platform agreement between Roche and Ortho platforms was 96.4% (3,769/3,903); most discordant results had reactivity close to the cutoffs on the alternate assays. These findings, and higher efficiency and throughput, support the use of parallel S/NC testing on either Roche or Ortho platforms for large serosurveillance studies. IMPORTANCE Seroprevalence studies like the U.S. Nationwide Blood Donor Seroprevalence Study (NBDS) have been critical in monitoring SARS-CoV-2 epidemic activity. These studies rely on serological assays to detect antibodies indicating prior infection. It is critical that the assays and testing algorithms used in seroprevalence studies have adequate performance (high sensitivity, high specificity, ability to discriminate vaccine-induced and infection-induced antibodies, etc.), as well as appropriate characteristics to support large-scale studies, such as high throughput and low cost. In this study we evaluated the performance of Ortho's anti-nucleocapsid assay as a replacement for the Roche anti-nucleocapsid assay and compared performance of parallel anti-spike and anti-nucleocapsid testing on both platforms. These data demonstrate similar performance of the Ortho and Roche anti-nucleocapsid assays and that parallel anti-spike and anti-nucleocapsid testing on either platform could be used for serosurveillance applications.
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Affiliation(s)
- Hasan Sulaeman
- Vitalant Research Institute, San Francisco, California, USA
| | - Eduard Grebe
- Vitalant Research Institute, San Francisco, California, USA
- SACEMA, Stellenbosch University, Stellenbosch, South Africa
| | - Honey Dave
- Vitalant Research Institute, San Francisco, California, USA
| | - Lily McCann
- Vitalant Research Institute, San Francisco, California, USA
| | | | - Aditi Sanghavi
- Vitalant Research Institute, San Francisco, California, USA
| | - Victoria Sclar
- Vitalant Research Institute, San Francisco, California, USA
| | | | | | | | - Jefferson M. Jones
- COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Natalie J. Thornburg
- COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Steve Kleinman
- University of British Columbia, Victoria, British Columbia, Canada
| | - Mars Stone
- Vitalant Research Institute, San Francisco, California, USA
- Department of Laboratory Medicine, University of California, San Francisco, California, USA
| | - Michael P. Busch
- Vitalant Research Institute, San Francisco, California, USA
- Department of Laboratory Medicine, University of California, San Francisco, California, USA
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32
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Dai YC, Lin YC, Ching LL, Tsai JJ, Ishikawa K, Tsai WY, Chen JJ, Nerurkar VR, Wang WK. Determining the Time of Booster Dose Based on the Half-Life and Neutralization Titers against SARS-CoV-2 Variants of Concern in Fully Vaccinated Individuals. Microbiol Spectr 2023; 11:e0408122. [PMID: 37428104 PMCID: PMC10434144 DOI: 10.1128/spectrum.04081-22] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Accepted: 06/20/2023] [Indexed: 07/11/2023] Open
Abstract
Although mRNA-based COVID-19 vaccines reduce the risk of severe disease, hospitalization and death, vaccine effectiveness (VE) against infection and disease from variants of concern (VOC) wanes over time. Neutralizing antibodies (NAb) are surrogates of protection and are enhanced by a booster dose, but their kinetics and durability remain understudied. Current recommendation of a booster dose does not consider the existing NAb in each individual. Here, we investigated 50% neutralization (NT50) titers against VOC among COVID-19-naive participants receiving the Moderna (n = 26) or Pfizer (n = 25) vaccine for up to 7 months following the second dose, and determined their half-lives. We found that the time it took for NT50 titers to decline to 24, equivalent to 50% inhibitory dilution of 10 international units/mL, was longer in the Moderna (325/324/235/274 days for the D614G/alpha/beta/delta variants) group than in the Pfizer (253/252/174/226 days) group, which may account for the slower decline in VE of the Moderna vaccine observed in real-world settings and supports our hypothesis that measuring the NT50 titers against VOC, together with information on NAb half-lives, can be used to dictate the time of booster vaccination. Our study provides a framework to determine the optimal time of a booster dose against VOC at the individual level. In response to future VOC with high morbidity and mortality, a quick evaluation of NAb half-lives using longitudinal serum samples from clinical trials or research programs of different primary-series vaccinations and/or one or two boosters could provide references for determining the time of booster in different individuals. IMPORTANCE Despite improved understanding of the biology of SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2), the evolutionary trajectory of the virus is uncertain, and the concern of future antigenically distinct variants remains. Current recommendations for a COVID-19 vaccine booster dose are primarily based on neutralization capacity, effectiveness against circulating variants of concern (VOC), and other host factors. We hypothesized that measuring neutralizing antibody titers against SARS-CoV-2 VOC together with half-life information can be used to dictate the time of booster vaccination. Through detailed analysis of neutralizing antibodies against VOC among COVID-19-naive vaccinees receiving either of two mRNA vaccines, we found that the time it took for 50% neutralization titers to decline to a reference level of protection was longer in the Moderna than in the Pfizer group, which supports our hypothesis. In response to future VOC with potentially high morbidity and mortality, our proof-of-concept study provides a framework to determine the optimal time of a booster dose at the individual level.
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Affiliation(s)
- Yu-Ching Dai
- Department of Tropical Medicine, Medical Microbiology and Pharmacology, John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, Hawaii, USA
| | - Yen-Chia Lin
- Department of Tropical Medicine, Medical Microbiology and Pharmacology, John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, Hawaii, USA
| | - Lauren L. Ching
- Department of Tropical Medicine, Medical Microbiology and Pharmacology, John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, Hawaii, USA
- Pacific Center for Emerging Infectious Diseases, John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, Hawaii, USA
| | - Jih-Jin Tsai
- Tropical Medicine Center, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan
- Division of Infectious Diseases, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan
- School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Kyle Ishikawa
- Department of Quantitative Health Sciences, John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, Hawaii, USA
| | - Wen-Yang Tsai
- Department of Tropical Medicine, Medical Microbiology and Pharmacology, John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, Hawaii, USA
- Pacific Center for Emerging Infectious Diseases, John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, Hawaii, USA
| | - John J. Chen
- Department of Quantitative Health Sciences, John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, Hawaii, USA
| | - Vivek R. Nerurkar
- Department of Tropical Medicine, Medical Microbiology and Pharmacology, John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, Hawaii, USA
- Pacific Center for Emerging Infectious Diseases, John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, Hawaii, USA
| | - Wei-Kung Wang
- Department of Tropical Medicine, Medical Microbiology and Pharmacology, John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, Hawaii, USA
- Pacific Center for Emerging Infectious Diseases, John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, Hawaii, USA
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Murphy TJ, Swail H, Jain J, Anderson M, Awadalla P, Behl L, Brown PE, Charlton CL, Colwill K, Drews SJ, Gingras AC, Hinshaw D, Jha P, Kanji JN, Kirsh VA, Lang ALS, Langlois MA, Lee S, Lewin A, O'Brien SF, Pambrun C, Skead K, Stephens DA, Stein DR, Tipples G, Van Caeseele PG, Evans TG, Oxlade O, Mazer BD, Buckeridge DL. The evolution of SARS-CoV-2 seroprevalence in Canada: a time-series study, 2020-2023. CMAJ 2023; 195:E1030-E1037. [PMID: 37580072 PMCID: PMC10426348 DOI: 10.1503/cmaj.230249] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/04/2023] [Indexed: 08/16/2023] Open
Abstract
BACKGROUND During the first year of the COVID-19 pandemic, the proportion of reported cases of COVID-19 among Canadians was under 6%. Although high vaccine coverage was achieved in Canada by fall 2021, the Omicron variant caused unprecedented numbers of infections, overwhelming testing capacity and making it difficult to quantify the trajectory of population immunity. METHODS Using a time-series approach and data from more than 900 000 samples collected by 7 research studies collaborating with the COVID-19 Immunity Task Force (CITF), we estimated trends in SARS-CoV-2 seroprevalence owing to infection and vaccination for the Canadian population over 3 intervals: prevaccination (March to November 2020), vaccine roll-out (December 2020 to November 2021), and the arrival of the Omicron variant (December 2021 to March 2023). We also estimated seroprevalence by geographical region and age. RESULTS By November 2021, 9.0% (95% credible interval [CrI] 7.3%-11%) of people in Canada had humoral immunity to SARS-CoV-2 from an infection. Seroprevalence increased rapidly after the arrival of the Omicron variant - by Mar. 15, 2023, 76% (95% CrI 74%-79%) of the population had detectable antibodies from infections. The rapid rise in infection-induced antibodies occurred across Canada and was most pronounced in younger age groups and in the Western provinces: Manitoba, Saskatchewan, Alberta and British Columbia. INTERPRETATION Data up to March 2023 indicate that most people in Canada had acquired antibodies against SARS-CoV-2 through natural infection and vaccination. However, given variations in population seropositivity by age and geography, the potential for waning antibody levels, and new variants that may escape immunity, public health policy and clinical decisions should be tailored to local patterns of population immunity.
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Affiliation(s)
- Tanya J Murphy
- COVID-19 Immunity Task Force (Murphy, Swail, Jain, Evans, Oxlade, Mazer, Buckeridge), School of Population and Global Health, McGill University, Montréal, Que.; Department of Community Health and Epidemiology (Anderson, Behl), University of Saskatchewan; Saskatchewan Health Authority (Anderson), Population Health, Saskatoon, Sask.; Department of Molecular Genetics (Awadalla), University of Toronto; Department of Computational Biology (Awadalla), Ontario Institute for Cancer Research; Centre for Global Health Research (Brown), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Charlton, Hinshaw, Tipples), Alberta Precision Laboratories, University of Alberta Hospital; Department of Laboratory Medicine and Pathology (Charlton, Tipples), and Li Ka Shing Institute of Virology, University of Alberta, Edmonton, Alta.; Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital (Colwill, Gingras), Sinai Health System, Toronto, Ont.; Canadian Blood Services (Drews); Department of Laboratory Medicine and Pathology (O'Brien, Pambrun, Drews), University of Alberta, Edmonton, Alta.; Department of Molecular Genetics (Gingras, Skead), University of Toronto; Centre for Global Health Research (Jha), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Kanji), Alberta Precision Laboratories, Foothills Medical Centre, and Section of Medical Microbiology (Kanji), Department of Pathology and Laboratory Medicine, and Division of Infectious Diseases, Department of Medicine, University of Calgary, Calgary, Alta.; Ontario Health Study (Kirsh, Skead), Ontario Institute for Cancer Research; Department of Molecular Genetics (Kirsh, Skead), and Dalla Lana School of Public Health (Kirsh), University of Toronto, Toronto, Ont.; Roy Romanow Provincial Lab (Lang), Saskatchewan Health Authority; College of Medicine (Lang), University of Saskatchewan, Saskatoon, Sask.; Department of Biochemistry, Microbiology and Immunology (Langlois), and Centre for Infection, Immunity and Inflammation (Langlois), University of Ottawa, Ottawa, Ont.; Division of Infectious Diseases-Regina (Lee), University of Saskatchewan; Saskatchewan Health Authority (Lee), Saskatoon, Sask.; Medical Affair and Innovation (Lewin), Héma-Québec, Montréal, Que.; Departments of Epidemiology and Community Medicine (O'Brien), and Pathology and Laboratory Medicine (Pambrun), Faculty of Medicine, University of Ottawa, Ottawa, Ont.; Department of Mathematics & Statistics (Stephens), McGill University, Montréal, Que.; Department of Medical Microbiology (Stein, Van Caeseele), University of Manitoba, and Cadham Provincial Laboratory, Winnipeg, Man.; School of Population and Global Health (Evans), McGill University; The Research Institute of the McGill University Health Centre (Mazer, Buckeridge), Montréal, Que
| | - Hanna Swail
- COVID-19 Immunity Task Force (Murphy, Swail, Jain, Evans, Oxlade, Mazer, Buckeridge), School of Population and Global Health, McGill University, Montréal, Que.; Department of Community Health and Epidemiology (Anderson, Behl), University of Saskatchewan; Saskatchewan Health Authority (Anderson), Population Health, Saskatoon, Sask.; Department of Molecular Genetics (Awadalla), University of Toronto; Department of Computational Biology (Awadalla), Ontario Institute for Cancer Research; Centre for Global Health Research (Brown), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Charlton, Hinshaw, Tipples), Alberta Precision Laboratories, University of Alberta Hospital; Department of Laboratory Medicine and Pathology (Charlton, Tipples), and Li Ka Shing Institute of Virology, University of Alberta, Edmonton, Alta.; Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital (Colwill, Gingras), Sinai Health System, Toronto, Ont.; Canadian Blood Services (Drews); Department of Laboratory Medicine and Pathology (O'Brien, Pambrun, Drews), University of Alberta, Edmonton, Alta.; Department of Molecular Genetics (Gingras, Skead), University of Toronto; Centre for Global Health Research (Jha), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Kanji), Alberta Precision Laboratories, Foothills Medical Centre, and Section of Medical Microbiology (Kanji), Department of Pathology and Laboratory Medicine, and Division of Infectious Diseases, Department of Medicine, University of Calgary, Calgary, Alta.; Ontario Health Study (Kirsh, Skead), Ontario Institute for Cancer Research; Department of Molecular Genetics (Kirsh, Skead), and Dalla Lana School of Public Health (Kirsh), University of Toronto, Toronto, Ont.; Roy Romanow Provincial Lab (Lang), Saskatchewan Health Authority; College of Medicine (Lang), University of Saskatchewan, Saskatoon, Sask.; Department of Biochemistry, Microbiology and Immunology (Langlois), and Centre for Infection, Immunity and Inflammation (Langlois), University of Ottawa, Ottawa, Ont.; Division of Infectious Diseases-Regina (Lee), University of Saskatchewan; Saskatchewan Health Authority (Lee), Saskatoon, Sask.; Medical Affair and Innovation (Lewin), Héma-Québec, Montréal, Que.; Departments of Epidemiology and Community Medicine (O'Brien), and Pathology and Laboratory Medicine (Pambrun), Faculty of Medicine, University of Ottawa, Ottawa, Ont.; Department of Mathematics & Statistics (Stephens), McGill University, Montréal, Que.; Department of Medical Microbiology (Stein, Van Caeseele), University of Manitoba, and Cadham Provincial Laboratory, Winnipeg, Man.; School of Population and Global Health (Evans), McGill University; The Research Institute of the McGill University Health Centre (Mazer, Buckeridge), Montréal, Que
| | - Jaspreet Jain
- COVID-19 Immunity Task Force (Murphy, Swail, Jain, Evans, Oxlade, Mazer, Buckeridge), School of Population and Global Health, McGill University, Montréal, Que.; Department of Community Health and Epidemiology (Anderson, Behl), University of Saskatchewan; Saskatchewan Health Authority (Anderson), Population Health, Saskatoon, Sask.; Department of Molecular Genetics (Awadalla), University of Toronto; Department of Computational Biology (Awadalla), Ontario Institute for Cancer Research; Centre for Global Health Research (Brown), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Charlton, Hinshaw, Tipples), Alberta Precision Laboratories, University of Alberta Hospital; Department of Laboratory Medicine and Pathology (Charlton, Tipples), and Li Ka Shing Institute of Virology, University of Alberta, Edmonton, Alta.; Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital (Colwill, Gingras), Sinai Health System, Toronto, Ont.; Canadian Blood Services (Drews); Department of Laboratory Medicine and Pathology (O'Brien, Pambrun, Drews), University of Alberta, Edmonton, Alta.; Department of Molecular Genetics (Gingras, Skead), University of Toronto; Centre for Global Health Research (Jha), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Kanji), Alberta Precision Laboratories, Foothills Medical Centre, and Section of Medical Microbiology (Kanji), Department of Pathology and Laboratory Medicine, and Division of Infectious Diseases, Department of Medicine, University of Calgary, Calgary, Alta.; Ontario Health Study (Kirsh, Skead), Ontario Institute for Cancer Research; Department of Molecular Genetics (Kirsh, Skead), and Dalla Lana School of Public Health (Kirsh), University of Toronto, Toronto, Ont.; Roy Romanow Provincial Lab (Lang), Saskatchewan Health Authority; College of Medicine (Lang), University of Saskatchewan, Saskatoon, Sask.; Department of Biochemistry, Microbiology and Immunology (Langlois), and Centre for Infection, Immunity and Inflammation (Langlois), University of Ottawa, Ottawa, Ont.; Division of Infectious Diseases-Regina (Lee), University of Saskatchewan; Saskatchewan Health Authority (Lee), Saskatoon, Sask.; Medical Affair and Innovation (Lewin), Héma-Québec, Montréal, Que.; Departments of Epidemiology and Community Medicine (O'Brien), and Pathology and Laboratory Medicine (Pambrun), Faculty of Medicine, University of Ottawa, Ottawa, Ont.; Department of Mathematics & Statistics (Stephens), McGill University, Montréal, Que.; Department of Medical Microbiology (Stein, Van Caeseele), University of Manitoba, and Cadham Provincial Laboratory, Winnipeg, Man.; School of Population and Global Health (Evans), McGill University; The Research Institute of the McGill University Health Centre (Mazer, Buckeridge), Montréal, Que
| | - Maureen Anderson
- COVID-19 Immunity Task Force (Murphy, Swail, Jain, Evans, Oxlade, Mazer, Buckeridge), School of Population and Global Health, McGill University, Montréal, Que.; Department of Community Health and Epidemiology (Anderson, Behl), University of Saskatchewan; Saskatchewan Health Authority (Anderson), Population Health, Saskatoon, Sask.; Department of Molecular Genetics (Awadalla), University of Toronto; Department of Computational Biology (Awadalla), Ontario Institute for Cancer Research; Centre for Global Health Research (Brown), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Charlton, Hinshaw, Tipples), Alberta Precision Laboratories, University of Alberta Hospital; Department of Laboratory Medicine and Pathology (Charlton, Tipples), and Li Ka Shing Institute of Virology, University of Alberta, Edmonton, Alta.; Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital (Colwill, Gingras), Sinai Health System, Toronto, Ont.; Canadian Blood Services (Drews); Department of Laboratory Medicine and Pathology (O'Brien, Pambrun, Drews), University of Alberta, Edmonton, Alta.; Department of Molecular Genetics (Gingras, Skead), University of Toronto; Centre for Global Health Research (Jha), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Kanji), Alberta Precision Laboratories, Foothills Medical Centre, and Section of Medical Microbiology (Kanji), Department of Pathology and Laboratory Medicine, and Division of Infectious Diseases, Department of Medicine, University of Calgary, Calgary, Alta.; Ontario Health Study (Kirsh, Skead), Ontario Institute for Cancer Research; Department of Molecular Genetics (Kirsh, Skead), and Dalla Lana School of Public Health (Kirsh), University of Toronto, Toronto, Ont.; Roy Romanow Provincial Lab (Lang), Saskatchewan Health Authority; College of Medicine (Lang), University of Saskatchewan, Saskatoon, Sask.; Department of Biochemistry, Microbiology and Immunology (Langlois), and Centre for Infection, Immunity and Inflammation (Langlois), University of Ottawa, Ottawa, Ont.; Division of Infectious Diseases-Regina (Lee), University of Saskatchewan; Saskatchewan Health Authority (Lee), Saskatoon, Sask.; Medical Affair and Innovation (Lewin), Héma-Québec, Montréal, Que.; Departments of Epidemiology and Community Medicine (O'Brien), and Pathology and Laboratory Medicine (Pambrun), Faculty of Medicine, University of Ottawa, Ottawa, Ont.; Department of Mathematics & Statistics (Stephens), McGill University, Montréal, Que.; Department of Medical Microbiology (Stein, Van Caeseele), University of Manitoba, and Cadham Provincial Laboratory, Winnipeg, Man.; School of Population and Global Health (Evans), McGill University; The Research Institute of the McGill University Health Centre (Mazer, Buckeridge), Montréal, Que
| | - Philip Awadalla
- COVID-19 Immunity Task Force (Murphy, Swail, Jain, Evans, Oxlade, Mazer, Buckeridge), School of Population and Global Health, McGill University, Montréal, Que.; Department of Community Health and Epidemiology (Anderson, Behl), University of Saskatchewan; Saskatchewan Health Authority (Anderson), Population Health, Saskatoon, Sask.; Department of Molecular Genetics (Awadalla), University of Toronto; Department of Computational Biology (Awadalla), Ontario Institute for Cancer Research; Centre for Global Health Research (Brown), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Charlton, Hinshaw, Tipples), Alberta Precision Laboratories, University of Alberta Hospital; Department of Laboratory Medicine and Pathology (Charlton, Tipples), and Li Ka Shing Institute of Virology, University of Alberta, Edmonton, Alta.; Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital (Colwill, Gingras), Sinai Health System, Toronto, Ont.; Canadian Blood Services (Drews); Department of Laboratory Medicine and Pathology (O'Brien, Pambrun, Drews), University of Alberta, Edmonton, Alta.; Department of Molecular Genetics (Gingras, Skead), University of Toronto; Centre for Global Health Research (Jha), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Kanji), Alberta Precision Laboratories, Foothills Medical Centre, and Section of Medical Microbiology (Kanji), Department of Pathology and Laboratory Medicine, and Division of Infectious Diseases, Department of Medicine, University of Calgary, Calgary, Alta.; Ontario Health Study (Kirsh, Skead), Ontario Institute for Cancer Research; Department of Molecular Genetics (Kirsh, Skead), and Dalla Lana School of Public Health (Kirsh), University of Toronto, Toronto, Ont.; Roy Romanow Provincial Lab (Lang), Saskatchewan Health Authority; College of Medicine (Lang), University of Saskatchewan, Saskatoon, Sask.; Department of Biochemistry, Microbiology and Immunology (Langlois), and Centre for Infection, Immunity and Inflammation (Langlois), University of Ottawa, Ottawa, Ont.; Division of Infectious Diseases-Regina (Lee), University of Saskatchewan; Saskatchewan Health Authority (Lee), Saskatoon, Sask.; Medical Affair and Innovation (Lewin), Héma-Québec, Montréal, Que.; Departments of Epidemiology and Community Medicine (O'Brien), and Pathology and Laboratory Medicine (Pambrun), Faculty of Medicine, University of Ottawa, Ottawa, Ont.; Department of Mathematics & Statistics (Stephens), McGill University, Montréal, Que.; Department of Medical Microbiology (Stein, Van Caeseele), University of Manitoba, and Cadham Provincial Laboratory, Winnipeg, Man.; School of Population and Global Health (Evans), McGill University; The Research Institute of the McGill University Health Centre (Mazer, Buckeridge), Montréal, Que
| | - Lesley Behl
- COVID-19 Immunity Task Force (Murphy, Swail, Jain, Evans, Oxlade, Mazer, Buckeridge), School of Population and Global Health, McGill University, Montréal, Que.; Department of Community Health and Epidemiology (Anderson, Behl), University of Saskatchewan; Saskatchewan Health Authority (Anderson), Population Health, Saskatoon, Sask.; Department of Molecular Genetics (Awadalla), University of Toronto; Department of Computational Biology (Awadalla), Ontario Institute for Cancer Research; Centre for Global Health Research (Brown), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Charlton, Hinshaw, Tipples), Alberta Precision Laboratories, University of Alberta Hospital; Department of Laboratory Medicine and Pathology (Charlton, Tipples), and Li Ka Shing Institute of Virology, University of Alberta, Edmonton, Alta.; Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital (Colwill, Gingras), Sinai Health System, Toronto, Ont.; Canadian Blood Services (Drews); Department of Laboratory Medicine and Pathology (O'Brien, Pambrun, Drews), University of Alberta, Edmonton, Alta.; Department of Molecular Genetics (Gingras, Skead), University of Toronto; Centre for Global Health Research (Jha), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Kanji), Alberta Precision Laboratories, Foothills Medical Centre, and Section of Medical Microbiology (Kanji), Department of Pathology and Laboratory Medicine, and Division of Infectious Diseases, Department of Medicine, University of Calgary, Calgary, Alta.; Ontario Health Study (Kirsh, Skead), Ontario Institute for Cancer Research; Department of Molecular Genetics (Kirsh, Skead), and Dalla Lana School of Public Health (Kirsh), University of Toronto, Toronto, Ont.; Roy Romanow Provincial Lab (Lang), Saskatchewan Health Authority; College of Medicine (Lang), University of Saskatchewan, Saskatoon, Sask.; Department of Biochemistry, Microbiology and Immunology (Langlois), and Centre for Infection, Immunity and Inflammation (Langlois), University of Ottawa, Ottawa, Ont.; Division of Infectious Diseases-Regina (Lee), University of Saskatchewan; Saskatchewan Health Authority (Lee), Saskatoon, Sask.; Medical Affair and Innovation (Lewin), Héma-Québec, Montréal, Que.; Departments of Epidemiology and Community Medicine (O'Brien), and Pathology and Laboratory Medicine (Pambrun), Faculty of Medicine, University of Ottawa, Ottawa, Ont.; Department of Mathematics & Statistics (Stephens), McGill University, Montréal, Que.; Department of Medical Microbiology (Stein, Van Caeseele), University of Manitoba, and Cadham Provincial Laboratory, Winnipeg, Man.; School of Population and Global Health (Evans), McGill University; The Research Institute of the McGill University Health Centre (Mazer, Buckeridge), Montréal, Que
| | - Patrick E Brown
- COVID-19 Immunity Task Force (Murphy, Swail, Jain, Evans, Oxlade, Mazer, Buckeridge), School of Population and Global Health, McGill University, Montréal, Que.; Department of Community Health and Epidemiology (Anderson, Behl), University of Saskatchewan; Saskatchewan Health Authority (Anderson), Population Health, Saskatoon, Sask.; Department of Molecular Genetics (Awadalla), University of Toronto; Department of Computational Biology (Awadalla), Ontario Institute for Cancer Research; Centre for Global Health Research (Brown), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Charlton, Hinshaw, Tipples), Alberta Precision Laboratories, University of Alberta Hospital; Department of Laboratory Medicine and Pathology (Charlton, Tipples), and Li Ka Shing Institute of Virology, University of Alberta, Edmonton, Alta.; Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital (Colwill, Gingras), Sinai Health System, Toronto, Ont.; Canadian Blood Services (Drews); Department of Laboratory Medicine and Pathology (O'Brien, Pambrun, Drews), University of Alberta, Edmonton, Alta.; Department of Molecular Genetics (Gingras, Skead), University of Toronto; Centre for Global Health Research (Jha), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Kanji), Alberta Precision Laboratories, Foothills Medical Centre, and Section of Medical Microbiology (Kanji), Department of Pathology and Laboratory Medicine, and Division of Infectious Diseases, Department of Medicine, University of Calgary, Calgary, Alta.; Ontario Health Study (Kirsh, Skead), Ontario Institute for Cancer Research; Department of Molecular Genetics (Kirsh, Skead), and Dalla Lana School of Public Health (Kirsh), University of Toronto, Toronto, Ont.; Roy Romanow Provincial Lab (Lang), Saskatchewan Health Authority; College of Medicine (Lang), University of Saskatchewan, Saskatoon, Sask.; Department of Biochemistry, Microbiology and Immunology (Langlois), and Centre for Infection, Immunity and Inflammation (Langlois), University of Ottawa, Ottawa, Ont.; Division of Infectious Diseases-Regina (Lee), University of Saskatchewan; Saskatchewan Health Authority (Lee), Saskatoon, Sask.; Medical Affair and Innovation (Lewin), Héma-Québec, Montréal, Que.; Departments of Epidemiology and Community Medicine (O'Brien), and Pathology and Laboratory Medicine (Pambrun), Faculty of Medicine, University of Ottawa, Ottawa, Ont.; Department of Mathematics & Statistics (Stephens), McGill University, Montréal, Que.; Department of Medical Microbiology (Stein, Van Caeseele), University of Manitoba, and Cadham Provincial Laboratory, Winnipeg, Man.; School of Population and Global Health (Evans), McGill University; The Research Institute of the McGill University Health Centre (Mazer, Buckeridge), Montréal, Que
| | - Carmen L Charlton
- COVID-19 Immunity Task Force (Murphy, Swail, Jain, Evans, Oxlade, Mazer, Buckeridge), School of Population and Global Health, McGill University, Montréal, Que.; Department of Community Health and Epidemiology (Anderson, Behl), University of Saskatchewan; Saskatchewan Health Authority (Anderson), Population Health, Saskatoon, Sask.; Department of Molecular Genetics (Awadalla), University of Toronto; Department of Computational Biology (Awadalla), Ontario Institute for Cancer Research; Centre for Global Health Research (Brown), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Charlton, Hinshaw, Tipples), Alberta Precision Laboratories, University of Alberta Hospital; Department of Laboratory Medicine and Pathology (Charlton, Tipples), and Li Ka Shing Institute of Virology, University of Alberta, Edmonton, Alta.; Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital (Colwill, Gingras), Sinai Health System, Toronto, Ont.; Canadian Blood Services (Drews); Department of Laboratory Medicine and Pathology (O'Brien, Pambrun, Drews), University of Alberta, Edmonton, Alta.; Department of Molecular Genetics (Gingras, Skead), University of Toronto; Centre for Global Health Research (Jha), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Kanji), Alberta Precision Laboratories, Foothills Medical Centre, and Section of Medical Microbiology (Kanji), Department of Pathology and Laboratory Medicine, and Division of Infectious Diseases, Department of Medicine, University of Calgary, Calgary, Alta.; Ontario Health Study (Kirsh, Skead), Ontario Institute for Cancer Research; Department of Molecular Genetics (Kirsh, Skead), and Dalla Lana School of Public Health (Kirsh), University of Toronto, Toronto, Ont.; Roy Romanow Provincial Lab (Lang), Saskatchewan Health Authority; College of Medicine (Lang), University of Saskatchewan, Saskatoon, Sask.; Department of Biochemistry, Microbiology and Immunology (Langlois), and Centre for Infection, Immunity and Inflammation (Langlois), University of Ottawa, Ottawa, Ont.; Division of Infectious Diseases-Regina (Lee), University of Saskatchewan; Saskatchewan Health Authority (Lee), Saskatoon, Sask.; Medical Affair and Innovation (Lewin), Héma-Québec, Montréal, Que.; Departments of Epidemiology and Community Medicine (O'Brien), and Pathology and Laboratory Medicine (Pambrun), Faculty of Medicine, University of Ottawa, Ottawa, Ont.; Department of Mathematics & Statistics (Stephens), McGill University, Montréal, Que.; Department of Medical Microbiology (Stein, Van Caeseele), University of Manitoba, and Cadham Provincial Laboratory, Winnipeg, Man.; School of Population and Global Health (Evans), McGill University; The Research Institute of the McGill University Health Centre (Mazer, Buckeridge), Montréal, Que
| | - Karen Colwill
- COVID-19 Immunity Task Force (Murphy, Swail, Jain, Evans, Oxlade, Mazer, Buckeridge), School of Population and Global Health, McGill University, Montréal, Que.; Department of Community Health and Epidemiology (Anderson, Behl), University of Saskatchewan; Saskatchewan Health Authority (Anderson), Population Health, Saskatoon, Sask.; Department of Molecular Genetics (Awadalla), University of Toronto; Department of Computational Biology (Awadalla), Ontario Institute for Cancer Research; Centre for Global Health Research (Brown), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Charlton, Hinshaw, Tipples), Alberta Precision Laboratories, University of Alberta Hospital; Department of Laboratory Medicine and Pathology (Charlton, Tipples), and Li Ka Shing Institute of Virology, University of Alberta, Edmonton, Alta.; Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital (Colwill, Gingras), Sinai Health System, Toronto, Ont.; Canadian Blood Services (Drews); Department of Laboratory Medicine and Pathology (O'Brien, Pambrun, Drews), University of Alberta, Edmonton, Alta.; Department of Molecular Genetics (Gingras, Skead), University of Toronto; Centre for Global Health Research (Jha), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Kanji), Alberta Precision Laboratories, Foothills Medical Centre, and Section of Medical Microbiology (Kanji), Department of Pathology and Laboratory Medicine, and Division of Infectious Diseases, Department of Medicine, University of Calgary, Calgary, Alta.; Ontario Health Study (Kirsh, Skead), Ontario Institute for Cancer Research; Department of Molecular Genetics (Kirsh, Skead), and Dalla Lana School of Public Health (Kirsh), University of Toronto, Toronto, Ont.; Roy Romanow Provincial Lab (Lang), Saskatchewan Health Authority; College of Medicine (Lang), University of Saskatchewan, Saskatoon, Sask.; Department of Biochemistry, Microbiology and Immunology (Langlois), and Centre for Infection, Immunity and Inflammation (Langlois), University of Ottawa, Ottawa, Ont.; Division of Infectious Diseases-Regina (Lee), University of Saskatchewan; Saskatchewan Health Authority (Lee), Saskatoon, Sask.; Medical Affair and Innovation (Lewin), Héma-Québec, Montréal, Que.; Departments of Epidemiology and Community Medicine (O'Brien), and Pathology and Laboratory Medicine (Pambrun), Faculty of Medicine, University of Ottawa, Ottawa, Ont.; Department of Mathematics & Statistics (Stephens), McGill University, Montréal, Que.; Department of Medical Microbiology (Stein, Van Caeseele), University of Manitoba, and Cadham Provincial Laboratory, Winnipeg, Man.; School of Population and Global Health (Evans), McGill University; The Research Institute of the McGill University Health Centre (Mazer, Buckeridge), Montréal, Que
| | - Steven J Drews
- COVID-19 Immunity Task Force (Murphy, Swail, Jain, Evans, Oxlade, Mazer, Buckeridge), School of Population and Global Health, McGill University, Montréal, Que.; Department of Community Health and Epidemiology (Anderson, Behl), University of Saskatchewan; Saskatchewan Health Authority (Anderson), Population Health, Saskatoon, Sask.; Department of Molecular Genetics (Awadalla), University of Toronto; Department of Computational Biology (Awadalla), Ontario Institute for Cancer Research; Centre for Global Health Research (Brown), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Charlton, Hinshaw, Tipples), Alberta Precision Laboratories, University of Alberta Hospital; Department of Laboratory Medicine and Pathology (Charlton, Tipples), and Li Ka Shing Institute of Virology, University of Alberta, Edmonton, Alta.; Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital (Colwill, Gingras), Sinai Health System, Toronto, Ont.; Canadian Blood Services (Drews); Department of Laboratory Medicine and Pathology (O'Brien, Pambrun, Drews), University of Alberta, Edmonton, Alta.; Department of Molecular Genetics (Gingras, Skead), University of Toronto; Centre for Global Health Research (Jha), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Kanji), Alberta Precision Laboratories, Foothills Medical Centre, and Section of Medical Microbiology (Kanji), Department of Pathology and Laboratory Medicine, and Division of Infectious Diseases, Department of Medicine, University of Calgary, Calgary, Alta.; Ontario Health Study (Kirsh, Skead), Ontario Institute for Cancer Research; Department of Molecular Genetics (Kirsh, Skead), and Dalla Lana School of Public Health (Kirsh), University of Toronto, Toronto, Ont.; Roy Romanow Provincial Lab (Lang), Saskatchewan Health Authority; College of Medicine (Lang), University of Saskatchewan, Saskatoon, Sask.; Department of Biochemistry, Microbiology and Immunology (Langlois), and Centre for Infection, Immunity and Inflammation (Langlois), University of Ottawa, Ottawa, Ont.; Division of Infectious Diseases-Regina (Lee), University of Saskatchewan; Saskatchewan Health Authority (Lee), Saskatoon, Sask.; Medical Affair and Innovation (Lewin), Héma-Québec, Montréal, Que.; Departments of Epidemiology and Community Medicine (O'Brien), and Pathology and Laboratory Medicine (Pambrun), Faculty of Medicine, University of Ottawa, Ottawa, Ont.; Department of Mathematics & Statistics (Stephens), McGill University, Montréal, Que.; Department of Medical Microbiology (Stein, Van Caeseele), University of Manitoba, and Cadham Provincial Laboratory, Winnipeg, Man.; School of Population and Global Health (Evans), McGill University; The Research Institute of the McGill University Health Centre (Mazer, Buckeridge), Montréal, Que
| | - Anne-Claude Gingras
- COVID-19 Immunity Task Force (Murphy, Swail, Jain, Evans, Oxlade, Mazer, Buckeridge), School of Population and Global Health, McGill University, Montréal, Que.; Department of Community Health and Epidemiology (Anderson, Behl), University of Saskatchewan; Saskatchewan Health Authority (Anderson), Population Health, Saskatoon, Sask.; Department of Molecular Genetics (Awadalla), University of Toronto; Department of Computational Biology (Awadalla), Ontario Institute for Cancer Research; Centre for Global Health Research (Brown), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Charlton, Hinshaw, Tipples), Alberta Precision Laboratories, University of Alberta Hospital; Department of Laboratory Medicine and Pathology (Charlton, Tipples), and Li Ka Shing Institute of Virology, University of Alberta, Edmonton, Alta.; Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital (Colwill, Gingras), Sinai Health System, Toronto, Ont.; Canadian Blood Services (Drews); Department of Laboratory Medicine and Pathology (O'Brien, Pambrun, Drews), University of Alberta, Edmonton, Alta.; Department of Molecular Genetics (Gingras, Skead), University of Toronto; Centre for Global Health Research (Jha), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Kanji), Alberta Precision Laboratories, Foothills Medical Centre, and Section of Medical Microbiology (Kanji), Department of Pathology and Laboratory Medicine, and Division of Infectious Diseases, Department of Medicine, University of Calgary, Calgary, Alta.; Ontario Health Study (Kirsh, Skead), Ontario Institute for Cancer Research; Department of Molecular Genetics (Kirsh, Skead), and Dalla Lana School of Public Health (Kirsh), University of Toronto, Toronto, Ont.; Roy Romanow Provincial Lab (Lang), Saskatchewan Health Authority; College of Medicine (Lang), University of Saskatchewan, Saskatoon, Sask.; Department of Biochemistry, Microbiology and Immunology (Langlois), and Centre for Infection, Immunity and Inflammation (Langlois), University of Ottawa, Ottawa, Ont.; Division of Infectious Diseases-Regina (Lee), University of Saskatchewan; Saskatchewan Health Authority (Lee), Saskatoon, Sask.; Medical Affair and Innovation (Lewin), Héma-Québec, Montréal, Que.; Departments of Epidemiology and Community Medicine (O'Brien), and Pathology and Laboratory Medicine (Pambrun), Faculty of Medicine, University of Ottawa, Ottawa, Ont.; Department of Mathematics & Statistics (Stephens), McGill University, Montréal, Que.; Department of Medical Microbiology (Stein, Van Caeseele), University of Manitoba, and Cadham Provincial Laboratory, Winnipeg, Man.; School of Population and Global Health (Evans), McGill University; The Research Institute of the McGill University Health Centre (Mazer, Buckeridge), Montréal, Que
| | - Deena Hinshaw
- COVID-19 Immunity Task Force (Murphy, Swail, Jain, Evans, Oxlade, Mazer, Buckeridge), School of Population and Global Health, McGill University, Montréal, Que.; Department of Community Health and Epidemiology (Anderson, Behl), University of Saskatchewan; Saskatchewan Health Authority (Anderson), Population Health, Saskatoon, Sask.; Department of Molecular Genetics (Awadalla), University of Toronto; Department of Computational Biology (Awadalla), Ontario Institute for Cancer Research; Centre for Global Health Research (Brown), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Charlton, Hinshaw, Tipples), Alberta Precision Laboratories, University of Alberta Hospital; Department of Laboratory Medicine and Pathology (Charlton, Tipples), and Li Ka Shing Institute of Virology, University of Alberta, Edmonton, Alta.; Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital (Colwill, Gingras), Sinai Health System, Toronto, Ont.; Canadian Blood Services (Drews); Department of Laboratory Medicine and Pathology (O'Brien, Pambrun, Drews), University of Alberta, Edmonton, Alta.; Department of Molecular Genetics (Gingras, Skead), University of Toronto; Centre for Global Health Research (Jha), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Kanji), Alberta Precision Laboratories, Foothills Medical Centre, and Section of Medical Microbiology (Kanji), Department of Pathology and Laboratory Medicine, and Division of Infectious Diseases, Department of Medicine, University of Calgary, Calgary, Alta.; Ontario Health Study (Kirsh, Skead), Ontario Institute for Cancer Research; Department of Molecular Genetics (Kirsh, Skead), and Dalla Lana School of Public Health (Kirsh), University of Toronto, Toronto, Ont.; Roy Romanow Provincial Lab (Lang), Saskatchewan Health Authority; College of Medicine (Lang), University of Saskatchewan, Saskatoon, Sask.; Department of Biochemistry, Microbiology and Immunology (Langlois), and Centre for Infection, Immunity and Inflammation (Langlois), University of Ottawa, Ottawa, Ont.; Division of Infectious Diseases-Regina (Lee), University of Saskatchewan; Saskatchewan Health Authority (Lee), Saskatoon, Sask.; Medical Affair and Innovation (Lewin), Héma-Québec, Montréal, Que.; Departments of Epidemiology and Community Medicine (O'Brien), and Pathology and Laboratory Medicine (Pambrun), Faculty of Medicine, University of Ottawa, Ottawa, Ont.; Department of Mathematics & Statistics (Stephens), McGill University, Montréal, Que.; Department of Medical Microbiology (Stein, Van Caeseele), University of Manitoba, and Cadham Provincial Laboratory, Winnipeg, Man.; School of Population and Global Health (Evans), McGill University; The Research Institute of the McGill University Health Centre (Mazer, Buckeridge), Montréal, Que
| | - Prabhat Jha
- COVID-19 Immunity Task Force (Murphy, Swail, Jain, Evans, Oxlade, Mazer, Buckeridge), School of Population and Global Health, McGill University, Montréal, Que.; Department of Community Health and Epidemiology (Anderson, Behl), University of Saskatchewan; Saskatchewan Health Authority (Anderson), Population Health, Saskatoon, Sask.; Department of Molecular Genetics (Awadalla), University of Toronto; Department of Computational Biology (Awadalla), Ontario Institute for Cancer Research; Centre for Global Health Research (Brown), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Charlton, Hinshaw, Tipples), Alberta Precision Laboratories, University of Alberta Hospital; Department of Laboratory Medicine and Pathology (Charlton, Tipples), and Li Ka Shing Institute of Virology, University of Alberta, Edmonton, Alta.; Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital (Colwill, Gingras), Sinai Health System, Toronto, Ont.; Canadian Blood Services (Drews); Department of Laboratory Medicine and Pathology (O'Brien, Pambrun, Drews), University of Alberta, Edmonton, Alta.; Department of Molecular Genetics (Gingras, Skead), University of Toronto; Centre for Global Health Research (Jha), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Kanji), Alberta Precision Laboratories, Foothills Medical Centre, and Section of Medical Microbiology (Kanji), Department of Pathology and Laboratory Medicine, and Division of Infectious Diseases, Department of Medicine, University of Calgary, Calgary, Alta.; Ontario Health Study (Kirsh, Skead), Ontario Institute for Cancer Research; Department of Molecular Genetics (Kirsh, Skead), and Dalla Lana School of Public Health (Kirsh), University of Toronto, Toronto, Ont.; Roy Romanow Provincial Lab (Lang), Saskatchewan Health Authority; College of Medicine (Lang), University of Saskatchewan, Saskatoon, Sask.; Department of Biochemistry, Microbiology and Immunology (Langlois), and Centre for Infection, Immunity and Inflammation (Langlois), University of Ottawa, Ottawa, Ont.; Division of Infectious Diseases-Regina (Lee), University of Saskatchewan; Saskatchewan Health Authority (Lee), Saskatoon, Sask.; Medical Affair and Innovation (Lewin), Héma-Québec, Montréal, Que.; Departments of Epidemiology and Community Medicine (O'Brien), and Pathology and Laboratory Medicine (Pambrun), Faculty of Medicine, University of Ottawa, Ottawa, Ont.; Department of Mathematics & Statistics (Stephens), McGill University, Montréal, Que.; Department of Medical Microbiology (Stein, Van Caeseele), University of Manitoba, and Cadham Provincial Laboratory, Winnipeg, Man.; School of Population and Global Health (Evans), McGill University; The Research Institute of the McGill University Health Centre (Mazer, Buckeridge), Montréal, Que
| | - Jamil N Kanji
- COVID-19 Immunity Task Force (Murphy, Swail, Jain, Evans, Oxlade, Mazer, Buckeridge), School of Population and Global Health, McGill University, Montréal, Que.; Department of Community Health and Epidemiology (Anderson, Behl), University of Saskatchewan; Saskatchewan Health Authority (Anderson), Population Health, Saskatoon, Sask.; Department of Molecular Genetics (Awadalla), University of Toronto; Department of Computational Biology (Awadalla), Ontario Institute for Cancer Research; Centre for Global Health Research (Brown), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Charlton, Hinshaw, Tipples), Alberta Precision Laboratories, University of Alberta Hospital; Department of Laboratory Medicine and Pathology (Charlton, Tipples), and Li Ka Shing Institute of Virology, University of Alberta, Edmonton, Alta.; Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital (Colwill, Gingras), Sinai Health System, Toronto, Ont.; Canadian Blood Services (Drews); Department of Laboratory Medicine and Pathology (O'Brien, Pambrun, Drews), University of Alberta, Edmonton, Alta.; Department of Molecular Genetics (Gingras, Skead), University of Toronto; Centre for Global Health Research (Jha), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Kanji), Alberta Precision Laboratories, Foothills Medical Centre, and Section of Medical Microbiology (Kanji), Department of Pathology and Laboratory Medicine, and Division of Infectious Diseases, Department of Medicine, University of Calgary, Calgary, Alta.; Ontario Health Study (Kirsh, Skead), Ontario Institute for Cancer Research; Department of Molecular Genetics (Kirsh, Skead), and Dalla Lana School of Public Health (Kirsh), University of Toronto, Toronto, Ont.; Roy Romanow Provincial Lab (Lang), Saskatchewan Health Authority; College of Medicine (Lang), University of Saskatchewan, Saskatoon, Sask.; Department of Biochemistry, Microbiology and Immunology (Langlois), and Centre for Infection, Immunity and Inflammation (Langlois), University of Ottawa, Ottawa, Ont.; Division of Infectious Diseases-Regina (Lee), University of Saskatchewan; Saskatchewan Health Authority (Lee), Saskatoon, Sask.; Medical Affair and Innovation (Lewin), Héma-Québec, Montréal, Que.; Departments of Epidemiology and Community Medicine (O'Brien), and Pathology and Laboratory Medicine (Pambrun), Faculty of Medicine, University of Ottawa, Ottawa, Ont.; Department of Mathematics & Statistics (Stephens), McGill University, Montréal, Que.; Department of Medical Microbiology (Stein, Van Caeseele), University of Manitoba, and Cadham Provincial Laboratory, Winnipeg, Man.; School of Population and Global Health (Evans), McGill University; The Research Institute of the McGill University Health Centre (Mazer, Buckeridge), Montréal, Que
| | - Victoria A Kirsh
- COVID-19 Immunity Task Force (Murphy, Swail, Jain, Evans, Oxlade, Mazer, Buckeridge), School of Population and Global Health, McGill University, Montréal, Que.; Department of Community Health and Epidemiology (Anderson, Behl), University of Saskatchewan; Saskatchewan Health Authority (Anderson), Population Health, Saskatoon, Sask.; Department of Molecular Genetics (Awadalla), University of Toronto; Department of Computational Biology (Awadalla), Ontario Institute for Cancer Research; Centre for Global Health Research (Brown), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Charlton, Hinshaw, Tipples), Alberta Precision Laboratories, University of Alberta Hospital; Department of Laboratory Medicine and Pathology (Charlton, Tipples), and Li Ka Shing Institute of Virology, University of Alberta, Edmonton, Alta.; Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital (Colwill, Gingras), Sinai Health System, Toronto, Ont.; Canadian Blood Services (Drews); Department of Laboratory Medicine and Pathology (O'Brien, Pambrun, Drews), University of Alberta, Edmonton, Alta.; Department of Molecular Genetics (Gingras, Skead), University of Toronto; Centre for Global Health Research (Jha), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Kanji), Alberta Precision Laboratories, Foothills Medical Centre, and Section of Medical Microbiology (Kanji), Department of Pathology and Laboratory Medicine, and Division of Infectious Diseases, Department of Medicine, University of Calgary, Calgary, Alta.; Ontario Health Study (Kirsh, Skead), Ontario Institute for Cancer Research; Department of Molecular Genetics (Kirsh, Skead), and Dalla Lana School of Public Health (Kirsh), University of Toronto, Toronto, Ont.; Roy Romanow Provincial Lab (Lang), Saskatchewan Health Authority; College of Medicine (Lang), University of Saskatchewan, Saskatoon, Sask.; Department of Biochemistry, Microbiology and Immunology (Langlois), and Centre for Infection, Immunity and Inflammation (Langlois), University of Ottawa, Ottawa, Ont.; Division of Infectious Diseases-Regina (Lee), University of Saskatchewan; Saskatchewan Health Authority (Lee), Saskatoon, Sask.; Medical Affair and Innovation (Lewin), Héma-Québec, Montréal, Que.; Departments of Epidemiology and Community Medicine (O'Brien), and Pathology and Laboratory Medicine (Pambrun), Faculty of Medicine, University of Ottawa, Ottawa, Ont.; Department of Mathematics & Statistics (Stephens), McGill University, Montréal, Que.; Department of Medical Microbiology (Stein, Van Caeseele), University of Manitoba, and Cadham Provincial Laboratory, Winnipeg, Man.; School of Population and Global Health (Evans), McGill University; The Research Institute of the McGill University Health Centre (Mazer, Buckeridge), Montréal, Que
| | - Amanda L S Lang
- COVID-19 Immunity Task Force (Murphy, Swail, Jain, Evans, Oxlade, Mazer, Buckeridge), School of Population and Global Health, McGill University, Montréal, Que.; Department of Community Health and Epidemiology (Anderson, Behl), University of Saskatchewan; Saskatchewan Health Authority (Anderson), Population Health, Saskatoon, Sask.; Department of Molecular Genetics (Awadalla), University of Toronto; Department of Computational Biology (Awadalla), Ontario Institute for Cancer Research; Centre for Global Health Research (Brown), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Charlton, Hinshaw, Tipples), Alberta Precision Laboratories, University of Alberta Hospital; Department of Laboratory Medicine and Pathology (Charlton, Tipples), and Li Ka Shing Institute of Virology, University of Alberta, Edmonton, Alta.; Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital (Colwill, Gingras), Sinai Health System, Toronto, Ont.; Canadian Blood Services (Drews); Department of Laboratory Medicine and Pathology (O'Brien, Pambrun, Drews), University of Alberta, Edmonton, Alta.; Department of Molecular Genetics (Gingras, Skead), University of Toronto; Centre for Global Health Research (Jha), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Kanji), Alberta Precision Laboratories, Foothills Medical Centre, and Section of Medical Microbiology (Kanji), Department of Pathology and Laboratory Medicine, and Division of Infectious Diseases, Department of Medicine, University of Calgary, Calgary, Alta.; Ontario Health Study (Kirsh, Skead), Ontario Institute for Cancer Research; Department of Molecular Genetics (Kirsh, Skead), and Dalla Lana School of Public Health (Kirsh), University of Toronto, Toronto, Ont.; Roy Romanow Provincial Lab (Lang), Saskatchewan Health Authority; College of Medicine (Lang), University of Saskatchewan, Saskatoon, Sask.; Department of Biochemistry, Microbiology and Immunology (Langlois), and Centre for Infection, Immunity and Inflammation (Langlois), University of Ottawa, Ottawa, Ont.; Division of Infectious Diseases-Regina (Lee), University of Saskatchewan; Saskatchewan Health Authority (Lee), Saskatoon, Sask.; Medical Affair and Innovation (Lewin), Héma-Québec, Montréal, Que.; Departments of Epidemiology and Community Medicine (O'Brien), and Pathology and Laboratory Medicine (Pambrun), Faculty of Medicine, University of Ottawa, Ottawa, Ont.; Department of Mathematics & Statistics (Stephens), McGill University, Montréal, Que.; Department of Medical Microbiology (Stein, Van Caeseele), University of Manitoba, and Cadham Provincial Laboratory, Winnipeg, Man.; School of Population and Global Health (Evans), McGill University; The Research Institute of the McGill University Health Centre (Mazer, Buckeridge), Montréal, Que
| | - Marc-André Langlois
- COVID-19 Immunity Task Force (Murphy, Swail, Jain, Evans, Oxlade, Mazer, Buckeridge), School of Population and Global Health, McGill University, Montréal, Que.; Department of Community Health and Epidemiology (Anderson, Behl), University of Saskatchewan; Saskatchewan Health Authority (Anderson), Population Health, Saskatoon, Sask.; Department of Molecular Genetics (Awadalla), University of Toronto; Department of Computational Biology (Awadalla), Ontario Institute for Cancer Research; Centre for Global Health Research (Brown), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Charlton, Hinshaw, Tipples), Alberta Precision Laboratories, University of Alberta Hospital; Department of Laboratory Medicine and Pathology (Charlton, Tipples), and Li Ka Shing Institute of Virology, University of Alberta, Edmonton, Alta.; Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital (Colwill, Gingras), Sinai Health System, Toronto, Ont.; Canadian Blood Services (Drews); Department of Laboratory Medicine and Pathology (O'Brien, Pambrun, Drews), University of Alberta, Edmonton, Alta.; Department of Molecular Genetics (Gingras, Skead), University of Toronto; Centre for Global Health Research (Jha), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Kanji), Alberta Precision Laboratories, Foothills Medical Centre, and Section of Medical Microbiology (Kanji), Department of Pathology and Laboratory Medicine, and Division of Infectious Diseases, Department of Medicine, University of Calgary, Calgary, Alta.; Ontario Health Study (Kirsh, Skead), Ontario Institute for Cancer Research; Department of Molecular Genetics (Kirsh, Skead), and Dalla Lana School of Public Health (Kirsh), University of Toronto, Toronto, Ont.; Roy Romanow Provincial Lab (Lang), Saskatchewan Health Authority; College of Medicine (Lang), University of Saskatchewan, Saskatoon, Sask.; Department of Biochemistry, Microbiology and Immunology (Langlois), and Centre for Infection, Immunity and Inflammation (Langlois), University of Ottawa, Ottawa, Ont.; Division of Infectious Diseases-Regina (Lee), University of Saskatchewan; Saskatchewan Health Authority (Lee), Saskatoon, Sask.; Medical Affair and Innovation (Lewin), Héma-Québec, Montréal, Que.; Departments of Epidemiology and Community Medicine (O'Brien), and Pathology and Laboratory Medicine (Pambrun), Faculty of Medicine, University of Ottawa, Ottawa, Ont.; Department of Mathematics & Statistics (Stephens), McGill University, Montréal, Que.; Department of Medical Microbiology (Stein, Van Caeseele), University of Manitoba, and Cadham Provincial Laboratory, Winnipeg, Man.; School of Population and Global Health (Evans), McGill University; The Research Institute of the McGill University Health Centre (Mazer, Buckeridge), Montréal, Que
| | - Stephen Lee
- COVID-19 Immunity Task Force (Murphy, Swail, Jain, Evans, Oxlade, Mazer, Buckeridge), School of Population and Global Health, McGill University, Montréal, Que.; Department of Community Health and Epidemiology (Anderson, Behl), University of Saskatchewan; Saskatchewan Health Authority (Anderson), Population Health, Saskatoon, Sask.; Department of Molecular Genetics (Awadalla), University of Toronto; Department of Computational Biology (Awadalla), Ontario Institute for Cancer Research; Centre for Global Health Research (Brown), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Charlton, Hinshaw, Tipples), Alberta Precision Laboratories, University of Alberta Hospital; Department of Laboratory Medicine and Pathology (Charlton, Tipples), and Li Ka Shing Institute of Virology, University of Alberta, Edmonton, Alta.; Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital (Colwill, Gingras), Sinai Health System, Toronto, Ont.; Canadian Blood Services (Drews); Department of Laboratory Medicine and Pathology (O'Brien, Pambrun, Drews), University of Alberta, Edmonton, Alta.; Department of Molecular Genetics (Gingras, Skead), University of Toronto; Centre for Global Health Research (Jha), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Kanji), Alberta Precision Laboratories, Foothills Medical Centre, and Section of Medical Microbiology (Kanji), Department of Pathology and Laboratory Medicine, and Division of Infectious Diseases, Department of Medicine, University of Calgary, Calgary, Alta.; Ontario Health Study (Kirsh, Skead), Ontario Institute for Cancer Research; Department of Molecular Genetics (Kirsh, Skead), and Dalla Lana School of Public Health (Kirsh), University of Toronto, Toronto, Ont.; Roy Romanow Provincial Lab (Lang), Saskatchewan Health Authority; College of Medicine (Lang), University of Saskatchewan, Saskatoon, Sask.; Department of Biochemistry, Microbiology and Immunology (Langlois), and Centre for Infection, Immunity and Inflammation (Langlois), University of Ottawa, Ottawa, Ont.; Division of Infectious Diseases-Regina (Lee), University of Saskatchewan; Saskatchewan Health Authority (Lee), Saskatoon, Sask.; Medical Affair and Innovation (Lewin), Héma-Québec, Montréal, Que.; Departments of Epidemiology and Community Medicine (O'Brien), and Pathology and Laboratory Medicine (Pambrun), Faculty of Medicine, University of Ottawa, Ottawa, Ont.; Department of Mathematics & Statistics (Stephens), McGill University, Montréal, Que.; Department of Medical Microbiology (Stein, Van Caeseele), University of Manitoba, and Cadham Provincial Laboratory, Winnipeg, Man.; School of Population and Global Health (Evans), McGill University; The Research Institute of the McGill University Health Centre (Mazer, Buckeridge), Montréal, Que
| | - Antoine Lewin
- COVID-19 Immunity Task Force (Murphy, Swail, Jain, Evans, Oxlade, Mazer, Buckeridge), School of Population and Global Health, McGill University, Montréal, Que.; Department of Community Health and Epidemiology (Anderson, Behl), University of Saskatchewan; Saskatchewan Health Authority (Anderson), Population Health, Saskatoon, Sask.; Department of Molecular Genetics (Awadalla), University of Toronto; Department of Computational Biology (Awadalla), Ontario Institute for Cancer Research; Centre for Global Health Research (Brown), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Charlton, Hinshaw, Tipples), Alberta Precision Laboratories, University of Alberta Hospital; Department of Laboratory Medicine and Pathology (Charlton, Tipples), and Li Ka Shing Institute of Virology, University of Alberta, Edmonton, Alta.; Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital (Colwill, Gingras), Sinai Health System, Toronto, Ont.; Canadian Blood Services (Drews); Department of Laboratory Medicine and Pathology (O'Brien, Pambrun, Drews), University of Alberta, Edmonton, Alta.; Department of Molecular Genetics (Gingras, Skead), University of Toronto; Centre for Global Health Research (Jha), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Kanji), Alberta Precision Laboratories, Foothills Medical Centre, and Section of Medical Microbiology (Kanji), Department of Pathology and Laboratory Medicine, and Division of Infectious Diseases, Department of Medicine, University of Calgary, Calgary, Alta.; Ontario Health Study (Kirsh, Skead), Ontario Institute for Cancer Research; Department of Molecular Genetics (Kirsh, Skead), and Dalla Lana School of Public Health (Kirsh), University of Toronto, Toronto, Ont.; Roy Romanow Provincial Lab (Lang), Saskatchewan Health Authority; College of Medicine (Lang), University of Saskatchewan, Saskatoon, Sask.; Department of Biochemistry, Microbiology and Immunology (Langlois), and Centre for Infection, Immunity and Inflammation (Langlois), University of Ottawa, Ottawa, Ont.; Division of Infectious Diseases-Regina (Lee), University of Saskatchewan; Saskatchewan Health Authority (Lee), Saskatoon, Sask.; Medical Affair and Innovation (Lewin), Héma-Québec, Montréal, Que.; Departments of Epidemiology and Community Medicine (O'Brien), and Pathology and Laboratory Medicine (Pambrun), Faculty of Medicine, University of Ottawa, Ottawa, Ont.; Department of Mathematics & Statistics (Stephens), McGill University, Montréal, Que.; Department of Medical Microbiology (Stein, Van Caeseele), University of Manitoba, and Cadham Provincial Laboratory, Winnipeg, Man.; School of Population and Global Health (Evans), McGill University; The Research Institute of the McGill University Health Centre (Mazer, Buckeridge), Montréal, Que
| | - Sheila F O'Brien
- COVID-19 Immunity Task Force (Murphy, Swail, Jain, Evans, Oxlade, Mazer, Buckeridge), School of Population and Global Health, McGill University, Montréal, Que.; Department of Community Health and Epidemiology (Anderson, Behl), University of Saskatchewan; Saskatchewan Health Authority (Anderson), Population Health, Saskatoon, Sask.; Department of Molecular Genetics (Awadalla), University of Toronto; Department of Computational Biology (Awadalla), Ontario Institute for Cancer Research; Centre for Global Health Research (Brown), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Charlton, Hinshaw, Tipples), Alberta Precision Laboratories, University of Alberta Hospital; Department of Laboratory Medicine and Pathology (Charlton, Tipples), and Li Ka Shing Institute of Virology, University of Alberta, Edmonton, Alta.; Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital (Colwill, Gingras), Sinai Health System, Toronto, Ont.; Canadian Blood Services (Drews); Department of Laboratory Medicine and Pathology (O'Brien, Pambrun, Drews), University of Alberta, Edmonton, Alta.; Department of Molecular Genetics (Gingras, Skead), University of Toronto; Centre for Global Health Research (Jha), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Kanji), Alberta Precision Laboratories, Foothills Medical Centre, and Section of Medical Microbiology (Kanji), Department of Pathology and Laboratory Medicine, and Division of Infectious Diseases, Department of Medicine, University of Calgary, Calgary, Alta.; Ontario Health Study (Kirsh, Skead), Ontario Institute for Cancer Research; Department of Molecular Genetics (Kirsh, Skead), and Dalla Lana School of Public Health (Kirsh), University of Toronto, Toronto, Ont.; Roy Romanow Provincial Lab (Lang), Saskatchewan Health Authority; College of Medicine (Lang), University of Saskatchewan, Saskatoon, Sask.; Department of Biochemistry, Microbiology and Immunology (Langlois), and Centre for Infection, Immunity and Inflammation (Langlois), University of Ottawa, Ottawa, Ont.; Division of Infectious Diseases-Regina (Lee), University of Saskatchewan; Saskatchewan Health Authority (Lee), Saskatoon, Sask.; Medical Affair and Innovation (Lewin), Héma-Québec, Montréal, Que.; Departments of Epidemiology and Community Medicine (O'Brien), and Pathology and Laboratory Medicine (Pambrun), Faculty of Medicine, University of Ottawa, Ottawa, Ont.; Department of Mathematics & Statistics (Stephens), McGill University, Montréal, Que.; Department of Medical Microbiology (Stein, Van Caeseele), University of Manitoba, and Cadham Provincial Laboratory, Winnipeg, Man.; School of Population and Global Health (Evans), McGill University; The Research Institute of the McGill University Health Centre (Mazer, Buckeridge), Montréal, Que
| | - Chantale Pambrun
- COVID-19 Immunity Task Force (Murphy, Swail, Jain, Evans, Oxlade, Mazer, Buckeridge), School of Population and Global Health, McGill University, Montréal, Que.; Department of Community Health and Epidemiology (Anderson, Behl), University of Saskatchewan; Saskatchewan Health Authority (Anderson), Population Health, Saskatoon, Sask.; Department of Molecular Genetics (Awadalla), University of Toronto; Department of Computational Biology (Awadalla), Ontario Institute for Cancer Research; Centre for Global Health Research (Brown), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Charlton, Hinshaw, Tipples), Alberta Precision Laboratories, University of Alberta Hospital; Department of Laboratory Medicine and Pathology (Charlton, Tipples), and Li Ka Shing Institute of Virology, University of Alberta, Edmonton, Alta.; Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital (Colwill, Gingras), Sinai Health System, Toronto, Ont.; Canadian Blood Services (Drews); Department of Laboratory Medicine and Pathology (O'Brien, Pambrun, Drews), University of Alberta, Edmonton, Alta.; Department of Molecular Genetics (Gingras, Skead), University of Toronto; Centre for Global Health Research (Jha), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Kanji), Alberta Precision Laboratories, Foothills Medical Centre, and Section of Medical Microbiology (Kanji), Department of Pathology and Laboratory Medicine, and Division of Infectious Diseases, Department of Medicine, University of Calgary, Calgary, Alta.; Ontario Health Study (Kirsh, Skead), Ontario Institute for Cancer Research; Department of Molecular Genetics (Kirsh, Skead), and Dalla Lana School of Public Health (Kirsh), University of Toronto, Toronto, Ont.; Roy Romanow Provincial Lab (Lang), Saskatchewan Health Authority; College of Medicine (Lang), University of Saskatchewan, Saskatoon, Sask.; Department of Biochemistry, Microbiology and Immunology (Langlois), and Centre for Infection, Immunity and Inflammation (Langlois), University of Ottawa, Ottawa, Ont.; Division of Infectious Diseases-Regina (Lee), University of Saskatchewan; Saskatchewan Health Authority (Lee), Saskatoon, Sask.; Medical Affair and Innovation (Lewin), Héma-Québec, Montréal, Que.; Departments of Epidemiology and Community Medicine (O'Brien), and Pathology and Laboratory Medicine (Pambrun), Faculty of Medicine, University of Ottawa, Ottawa, Ont.; Department of Mathematics & Statistics (Stephens), McGill University, Montréal, Que.; Department of Medical Microbiology (Stein, Van Caeseele), University of Manitoba, and Cadham Provincial Laboratory, Winnipeg, Man.; School of Population and Global Health (Evans), McGill University; The Research Institute of the McGill University Health Centre (Mazer, Buckeridge), Montréal, Que
| | - Kimberly Skead
- COVID-19 Immunity Task Force (Murphy, Swail, Jain, Evans, Oxlade, Mazer, Buckeridge), School of Population and Global Health, McGill University, Montréal, Que.; Department of Community Health and Epidemiology (Anderson, Behl), University of Saskatchewan; Saskatchewan Health Authority (Anderson), Population Health, Saskatoon, Sask.; Department of Molecular Genetics (Awadalla), University of Toronto; Department of Computational Biology (Awadalla), Ontario Institute for Cancer Research; Centre for Global Health Research (Brown), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Charlton, Hinshaw, Tipples), Alberta Precision Laboratories, University of Alberta Hospital; Department of Laboratory Medicine and Pathology (Charlton, Tipples), and Li Ka Shing Institute of Virology, University of Alberta, Edmonton, Alta.; Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital (Colwill, Gingras), Sinai Health System, Toronto, Ont.; Canadian Blood Services (Drews); Department of Laboratory Medicine and Pathology (O'Brien, Pambrun, Drews), University of Alberta, Edmonton, Alta.; Department of Molecular Genetics (Gingras, Skead), University of Toronto; Centre for Global Health Research (Jha), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Kanji), Alberta Precision Laboratories, Foothills Medical Centre, and Section of Medical Microbiology (Kanji), Department of Pathology and Laboratory Medicine, and Division of Infectious Diseases, Department of Medicine, University of Calgary, Calgary, Alta.; Ontario Health Study (Kirsh, Skead), Ontario Institute for Cancer Research; Department of Molecular Genetics (Kirsh, Skead), and Dalla Lana School of Public Health (Kirsh), University of Toronto, Toronto, Ont.; Roy Romanow Provincial Lab (Lang), Saskatchewan Health Authority; College of Medicine (Lang), University of Saskatchewan, Saskatoon, Sask.; Department of Biochemistry, Microbiology and Immunology (Langlois), and Centre for Infection, Immunity and Inflammation (Langlois), University of Ottawa, Ottawa, Ont.; Division of Infectious Diseases-Regina (Lee), University of Saskatchewan; Saskatchewan Health Authority (Lee), Saskatoon, Sask.; Medical Affair and Innovation (Lewin), Héma-Québec, Montréal, Que.; Departments of Epidemiology and Community Medicine (O'Brien), and Pathology and Laboratory Medicine (Pambrun), Faculty of Medicine, University of Ottawa, Ottawa, Ont.; Department of Mathematics & Statistics (Stephens), McGill University, Montréal, Que.; Department of Medical Microbiology (Stein, Van Caeseele), University of Manitoba, and Cadham Provincial Laboratory, Winnipeg, Man.; School of Population and Global Health (Evans), McGill University; The Research Institute of the McGill University Health Centre (Mazer, Buckeridge), Montréal, Que
| | - David A Stephens
- COVID-19 Immunity Task Force (Murphy, Swail, Jain, Evans, Oxlade, Mazer, Buckeridge), School of Population and Global Health, McGill University, Montréal, Que.; Department of Community Health and Epidemiology (Anderson, Behl), University of Saskatchewan; Saskatchewan Health Authority (Anderson), Population Health, Saskatoon, Sask.; Department of Molecular Genetics (Awadalla), University of Toronto; Department of Computational Biology (Awadalla), Ontario Institute for Cancer Research; Centre for Global Health Research (Brown), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Charlton, Hinshaw, Tipples), Alberta Precision Laboratories, University of Alberta Hospital; Department of Laboratory Medicine and Pathology (Charlton, Tipples), and Li Ka Shing Institute of Virology, University of Alberta, Edmonton, Alta.; Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital (Colwill, Gingras), Sinai Health System, Toronto, Ont.; Canadian Blood Services (Drews); Department of Laboratory Medicine and Pathology (O'Brien, Pambrun, Drews), University of Alberta, Edmonton, Alta.; Department of Molecular Genetics (Gingras, Skead), University of Toronto; Centre for Global Health Research (Jha), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Kanji), Alberta Precision Laboratories, Foothills Medical Centre, and Section of Medical Microbiology (Kanji), Department of Pathology and Laboratory Medicine, and Division of Infectious Diseases, Department of Medicine, University of Calgary, Calgary, Alta.; Ontario Health Study (Kirsh, Skead), Ontario Institute for Cancer Research; Department of Molecular Genetics (Kirsh, Skead), and Dalla Lana School of Public Health (Kirsh), University of Toronto, Toronto, Ont.; Roy Romanow Provincial Lab (Lang), Saskatchewan Health Authority; College of Medicine (Lang), University of Saskatchewan, Saskatoon, Sask.; Department of Biochemistry, Microbiology and Immunology (Langlois), and Centre for Infection, Immunity and Inflammation (Langlois), University of Ottawa, Ottawa, Ont.; Division of Infectious Diseases-Regina (Lee), University of Saskatchewan; Saskatchewan Health Authority (Lee), Saskatoon, Sask.; Medical Affair and Innovation (Lewin), Héma-Québec, Montréal, Que.; Departments of Epidemiology and Community Medicine (O'Brien), and Pathology and Laboratory Medicine (Pambrun), Faculty of Medicine, University of Ottawa, Ottawa, Ont.; Department of Mathematics & Statistics (Stephens), McGill University, Montréal, Que.; Department of Medical Microbiology (Stein, Van Caeseele), University of Manitoba, and Cadham Provincial Laboratory, Winnipeg, Man.; School of Population and Global Health (Evans), McGill University; The Research Institute of the McGill University Health Centre (Mazer, Buckeridge), Montréal, Que.
| | - Derek R Stein
- COVID-19 Immunity Task Force (Murphy, Swail, Jain, Evans, Oxlade, Mazer, Buckeridge), School of Population and Global Health, McGill University, Montréal, Que.; Department of Community Health and Epidemiology (Anderson, Behl), University of Saskatchewan; Saskatchewan Health Authority (Anderson), Population Health, Saskatoon, Sask.; Department of Molecular Genetics (Awadalla), University of Toronto; Department of Computational Biology (Awadalla), Ontario Institute for Cancer Research; Centre for Global Health Research (Brown), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Charlton, Hinshaw, Tipples), Alberta Precision Laboratories, University of Alberta Hospital; Department of Laboratory Medicine and Pathology (Charlton, Tipples), and Li Ka Shing Institute of Virology, University of Alberta, Edmonton, Alta.; Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital (Colwill, Gingras), Sinai Health System, Toronto, Ont.; Canadian Blood Services (Drews); Department of Laboratory Medicine and Pathology (O'Brien, Pambrun, Drews), University of Alberta, Edmonton, Alta.; Department of Molecular Genetics (Gingras, Skead), University of Toronto; Centre for Global Health Research (Jha), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Kanji), Alberta Precision Laboratories, Foothills Medical Centre, and Section of Medical Microbiology (Kanji), Department of Pathology and Laboratory Medicine, and Division of Infectious Diseases, Department of Medicine, University of Calgary, Calgary, Alta.; Ontario Health Study (Kirsh, Skead), Ontario Institute for Cancer Research; Department of Molecular Genetics (Kirsh, Skead), and Dalla Lana School of Public Health (Kirsh), University of Toronto, Toronto, Ont.; Roy Romanow Provincial Lab (Lang), Saskatchewan Health Authority; College of Medicine (Lang), University of Saskatchewan, Saskatoon, Sask.; Department of Biochemistry, Microbiology and Immunology (Langlois), and Centre for Infection, Immunity and Inflammation (Langlois), University of Ottawa, Ottawa, Ont.; Division of Infectious Diseases-Regina (Lee), University of Saskatchewan; Saskatchewan Health Authority (Lee), Saskatoon, Sask.; Medical Affair and Innovation (Lewin), Héma-Québec, Montréal, Que.; Departments of Epidemiology and Community Medicine (O'Brien), and Pathology and Laboratory Medicine (Pambrun), Faculty of Medicine, University of Ottawa, Ottawa, Ont.; Department of Mathematics & Statistics (Stephens), McGill University, Montréal, Que.; Department of Medical Microbiology (Stein, Van Caeseele), University of Manitoba, and Cadham Provincial Laboratory, Winnipeg, Man.; School of Population and Global Health (Evans), McGill University; The Research Institute of the McGill University Health Centre (Mazer, Buckeridge), Montréal, Que
| | - Graham Tipples
- COVID-19 Immunity Task Force (Murphy, Swail, Jain, Evans, Oxlade, Mazer, Buckeridge), School of Population and Global Health, McGill University, Montréal, Que.; Department of Community Health and Epidemiology (Anderson, Behl), University of Saskatchewan; Saskatchewan Health Authority (Anderson), Population Health, Saskatoon, Sask.; Department of Molecular Genetics (Awadalla), University of Toronto; Department of Computational Biology (Awadalla), Ontario Institute for Cancer Research; Centre for Global Health Research (Brown), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Charlton, Hinshaw, Tipples), Alberta Precision Laboratories, University of Alberta Hospital; Department of Laboratory Medicine and Pathology (Charlton, Tipples), and Li Ka Shing Institute of Virology, University of Alberta, Edmonton, Alta.; Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital (Colwill, Gingras), Sinai Health System, Toronto, Ont.; Canadian Blood Services (Drews); Department of Laboratory Medicine and Pathology (O'Brien, Pambrun, Drews), University of Alberta, Edmonton, Alta.; Department of Molecular Genetics (Gingras, Skead), University of Toronto; Centre for Global Health Research (Jha), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Kanji), Alberta Precision Laboratories, Foothills Medical Centre, and Section of Medical Microbiology (Kanji), Department of Pathology and Laboratory Medicine, and Division of Infectious Diseases, Department of Medicine, University of Calgary, Calgary, Alta.; Ontario Health Study (Kirsh, Skead), Ontario Institute for Cancer Research; Department of Molecular Genetics (Kirsh, Skead), and Dalla Lana School of Public Health (Kirsh), University of Toronto, Toronto, Ont.; Roy Romanow Provincial Lab (Lang), Saskatchewan Health Authority; College of Medicine (Lang), University of Saskatchewan, Saskatoon, Sask.; Department of Biochemistry, Microbiology and Immunology (Langlois), and Centre for Infection, Immunity and Inflammation (Langlois), University of Ottawa, Ottawa, Ont.; Division of Infectious Diseases-Regina (Lee), University of Saskatchewan; Saskatchewan Health Authority (Lee), Saskatoon, Sask.; Medical Affair and Innovation (Lewin), Héma-Québec, Montréal, Que.; Departments of Epidemiology and Community Medicine (O'Brien), and Pathology and Laboratory Medicine (Pambrun), Faculty of Medicine, University of Ottawa, Ottawa, Ont.; Department of Mathematics & Statistics (Stephens), McGill University, Montréal, Que.; Department of Medical Microbiology (Stein, Van Caeseele), University of Manitoba, and Cadham Provincial Laboratory, Winnipeg, Man.; School of Population and Global Health (Evans), McGill University; The Research Institute of the McGill University Health Centre (Mazer, Buckeridge), Montréal, Que
| | - Paul G Van Caeseele
- COVID-19 Immunity Task Force (Murphy, Swail, Jain, Evans, Oxlade, Mazer, Buckeridge), School of Population and Global Health, McGill University, Montréal, Que.; Department of Community Health and Epidemiology (Anderson, Behl), University of Saskatchewan; Saskatchewan Health Authority (Anderson), Population Health, Saskatoon, Sask.; Department of Molecular Genetics (Awadalla), University of Toronto; Department of Computational Biology (Awadalla), Ontario Institute for Cancer Research; Centre for Global Health Research (Brown), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Charlton, Hinshaw, Tipples), Alberta Precision Laboratories, University of Alberta Hospital; Department of Laboratory Medicine and Pathology (Charlton, Tipples), and Li Ka Shing Institute of Virology, University of Alberta, Edmonton, Alta.; Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital (Colwill, Gingras), Sinai Health System, Toronto, Ont.; Canadian Blood Services (Drews); Department of Laboratory Medicine and Pathology (O'Brien, Pambrun, Drews), University of Alberta, Edmonton, Alta.; Department of Molecular Genetics (Gingras, Skead), University of Toronto; Centre for Global Health Research (Jha), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Kanji), Alberta Precision Laboratories, Foothills Medical Centre, and Section of Medical Microbiology (Kanji), Department of Pathology and Laboratory Medicine, and Division of Infectious Diseases, Department of Medicine, University of Calgary, Calgary, Alta.; Ontario Health Study (Kirsh, Skead), Ontario Institute for Cancer Research; Department of Molecular Genetics (Kirsh, Skead), and Dalla Lana School of Public Health (Kirsh), University of Toronto, Toronto, Ont.; Roy Romanow Provincial Lab (Lang), Saskatchewan Health Authority; College of Medicine (Lang), University of Saskatchewan, Saskatoon, Sask.; Department of Biochemistry, Microbiology and Immunology (Langlois), and Centre for Infection, Immunity and Inflammation (Langlois), University of Ottawa, Ottawa, Ont.; Division of Infectious Diseases-Regina (Lee), University of Saskatchewan; Saskatchewan Health Authority (Lee), Saskatoon, Sask.; Medical Affair and Innovation (Lewin), Héma-Québec, Montréal, Que.; Departments of Epidemiology and Community Medicine (O'Brien), and Pathology and Laboratory Medicine (Pambrun), Faculty of Medicine, University of Ottawa, Ottawa, Ont.; Department of Mathematics & Statistics (Stephens), McGill University, Montréal, Que.; Department of Medical Microbiology (Stein, Van Caeseele), University of Manitoba, and Cadham Provincial Laboratory, Winnipeg, Man.; School of Population and Global Health (Evans), McGill University; The Research Institute of the McGill University Health Centre (Mazer, Buckeridge), Montréal, Que
| | - Timothy G Evans
- COVID-19 Immunity Task Force (Murphy, Swail, Jain, Evans, Oxlade, Mazer, Buckeridge), School of Population and Global Health, McGill University, Montréal, Que.; Department of Community Health and Epidemiology (Anderson, Behl), University of Saskatchewan; Saskatchewan Health Authority (Anderson), Population Health, Saskatoon, Sask.; Department of Molecular Genetics (Awadalla), University of Toronto; Department of Computational Biology (Awadalla), Ontario Institute for Cancer Research; Centre for Global Health Research (Brown), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Charlton, Hinshaw, Tipples), Alberta Precision Laboratories, University of Alberta Hospital; Department of Laboratory Medicine and Pathology (Charlton, Tipples), and Li Ka Shing Institute of Virology, University of Alberta, Edmonton, Alta.; Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital (Colwill, Gingras), Sinai Health System, Toronto, Ont.; Canadian Blood Services (Drews); Department of Laboratory Medicine and Pathology (O'Brien, Pambrun, Drews), University of Alberta, Edmonton, Alta.; Department of Molecular Genetics (Gingras, Skead), University of Toronto; Centre for Global Health Research (Jha), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Kanji), Alberta Precision Laboratories, Foothills Medical Centre, and Section of Medical Microbiology (Kanji), Department of Pathology and Laboratory Medicine, and Division of Infectious Diseases, Department of Medicine, University of Calgary, Calgary, Alta.; Ontario Health Study (Kirsh, Skead), Ontario Institute for Cancer Research; Department of Molecular Genetics (Kirsh, Skead), and Dalla Lana School of Public Health (Kirsh), University of Toronto, Toronto, Ont.; Roy Romanow Provincial Lab (Lang), Saskatchewan Health Authority; College of Medicine (Lang), University of Saskatchewan, Saskatoon, Sask.; Department of Biochemistry, Microbiology and Immunology (Langlois), and Centre for Infection, Immunity and Inflammation (Langlois), University of Ottawa, Ottawa, Ont.; Division of Infectious Diseases-Regina (Lee), University of Saskatchewan; Saskatchewan Health Authority (Lee), Saskatoon, Sask.; Medical Affair and Innovation (Lewin), Héma-Québec, Montréal, Que.; Departments of Epidemiology and Community Medicine (O'Brien), and Pathology and Laboratory Medicine (Pambrun), Faculty of Medicine, University of Ottawa, Ottawa, Ont.; Department of Mathematics & Statistics (Stephens), McGill University, Montréal, Que.; Department of Medical Microbiology (Stein, Van Caeseele), University of Manitoba, and Cadham Provincial Laboratory, Winnipeg, Man.; School of Population and Global Health (Evans), McGill University; The Research Institute of the McGill University Health Centre (Mazer, Buckeridge), Montréal, Que
| | - Olivia Oxlade
- COVID-19 Immunity Task Force (Murphy, Swail, Jain, Evans, Oxlade, Mazer, Buckeridge), School of Population and Global Health, McGill University, Montréal, Que.; Department of Community Health and Epidemiology (Anderson, Behl), University of Saskatchewan; Saskatchewan Health Authority (Anderson), Population Health, Saskatoon, Sask.; Department of Molecular Genetics (Awadalla), University of Toronto; Department of Computational Biology (Awadalla), Ontario Institute for Cancer Research; Centre for Global Health Research (Brown), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Charlton, Hinshaw, Tipples), Alberta Precision Laboratories, University of Alberta Hospital; Department of Laboratory Medicine and Pathology (Charlton, Tipples), and Li Ka Shing Institute of Virology, University of Alberta, Edmonton, Alta.; Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital (Colwill, Gingras), Sinai Health System, Toronto, Ont.; Canadian Blood Services (Drews); Department of Laboratory Medicine and Pathology (O'Brien, Pambrun, Drews), University of Alberta, Edmonton, Alta.; Department of Molecular Genetics (Gingras, Skead), University of Toronto; Centre for Global Health Research (Jha), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Kanji), Alberta Precision Laboratories, Foothills Medical Centre, and Section of Medical Microbiology (Kanji), Department of Pathology and Laboratory Medicine, and Division of Infectious Diseases, Department of Medicine, University of Calgary, Calgary, Alta.; Ontario Health Study (Kirsh, Skead), Ontario Institute for Cancer Research; Department of Molecular Genetics (Kirsh, Skead), and Dalla Lana School of Public Health (Kirsh), University of Toronto, Toronto, Ont.; Roy Romanow Provincial Lab (Lang), Saskatchewan Health Authority; College of Medicine (Lang), University of Saskatchewan, Saskatoon, Sask.; Department of Biochemistry, Microbiology and Immunology (Langlois), and Centre for Infection, Immunity and Inflammation (Langlois), University of Ottawa, Ottawa, Ont.; Division of Infectious Diseases-Regina (Lee), University of Saskatchewan; Saskatchewan Health Authority (Lee), Saskatoon, Sask.; Medical Affair and Innovation (Lewin), Héma-Québec, Montréal, Que.; Departments of Epidemiology and Community Medicine (O'Brien), and Pathology and Laboratory Medicine (Pambrun), Faculty of Medicine, University of Ottawa, Ottawa, Ont.; Department of Mathematics & Statistics (Stephens), McGill University, Montréal, Que.; Department of Medical Microbiology (Stein, Van Caeseele), University of Manitoba, and Cadham Provincial Laboratory, Winnipeg, Man.; School of Population and Global Health (Evans), McGill University; The Research Institute of the McGill University Health Centre (Mazer, Buckeridge), Montréal, Que
| | - Bruce D Mazer
- COVID-19 Immunity Task Force (Murphy, Swail, Jain, Evans, Oxlade, Mazer, Buckeridge), School of Population and Global Health, McGill University, Montréal, Que.; Department of Community Health and Epidemiology (Anderson, Behl), University of Saskatchewan; Saskatchewan Health Authority (Anderson), Population Health, Saskatoon, Sask.; Department of Molecular Genetics (Awadalla), University of Toronto; Department of Computational Biology (Awadalla), Ontario Institute for Cancer Research; Centre for Global Health Research (Brown), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Charlton, Hinshaw, Tipples), Alberta Precision Laboratories, University of Alberta Hospital; Department of Laboratory Medicine and Pathology (Charlton, Tipples), and Li Ka Shing Institute of Virology, University of Alberta, Edmonton, Alta.; Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital (Colwill, Gingras), Sinai Health System, Toronto, Ont.; Canadian Blood Services (Drews); Department of Laboratory Medicine and Pathology (O'Brien, Pambrun, Drews), University of Alberta, Edmonton, Alta.; Department of Molecular Genetics (Gingras, Skead), University of Toronto; Centre for Global Health Research (Jha), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Kanji), Alberta Precision Laboratories, Foothills Medical Centre, and Section of Medical Microbiology (Kanji), Department of Pathology and Laboratory Medicine, and Division of Infectious Diseases, Department of Medicine, University of Calgary, Calgary, Alta.; Ontario Health Study (Kirsh, Skead), Ontario Institute for Cancer Research; Department of Molecular Genetics (Kirsh, Skead), and Dalla Lana School of Public Health (Kirsh), University of Toronto, Toronto, Ont.; Roy Romanow Provincial Lab (Lang), Saskatchewan Health Authority; College of Medicine (Lang), University of Saskatchewan, Saskatoon, Sask.; Department of Biochemistry, Microbiology and Immunology (Langlois), and Centre for Infection, Immunity and Inflammation (Langlois), University of Ottawa, Ottawa, Ont.; Division of Infectious Diseases-Regina (Lee), University of Saskatchewan; Saskatchewan Health Authority (Lee), Saskatoon, Sask.; Medical Affair and Innovation (Lewin), Héma-Québec, Montréal, Que.; Departments of Epidemiology and Community Medicine (O'Brien), and Pathology and Laboratory Medicine (Pambrun), Faculty of Medicine, University of Ottawa, Ottawa, Ont.; Department of Mathematics & Statistics (Stephens), McGill University, Montréal, Que.; Department of Medical Microbiology (Stein, Van Caeseele), University of Manitoba, and Cadham Provincial Laboratory, Winnipeg, Man.; School of Population and Global Health (Evans), McGill University; The Research Institute of the McGill University Health Centre (Mazer, Buckeridge), Montréal, Que
| | - David L Buckeridge
- COVID-19 Immunity Task Force (Murphy, Swail, Jain, Evans, Oxlade, Mazer, Buckeridge), School of Population and Global Health, McGill University, Montréal, Que.; Department of Community Health and Epidemiology (Anderson, Behl), University of Saskatchewan; Saskatchewan Health Authority (Anderson), Population Health, Saskatoon, Sask.; Department of Molecular Genetics (Awadalla), University of Toronto; Department of Computational Biology (Awadalla), Ontario Institute for Cancer Research; Centre for Global Health Research (Brown), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Charlton, Hinshaw, Tipples), Alberta Precision Laboratories, University of Alberta Hospital; Department of Laboratory Medicine and Pathology (Charlton, Tipples), and Li Ka Shing Institute of Virology, University of Alberta, Edmonton, Alta.; Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital (Colwill, Gingras), Sinai Health System, Toronto, Ont.; Canadian Blood Services (Drews); Department of Laboratory Medicine and Pathology (O'Brien, Pambrun, Drews), University of Alberta, Edmonton, Alta.; Department of Molecular Genetics (Gingras, Skead), University of Toronto; Centre for Global Health Research (Jha), Unity Health Toronto and University of Toronto, Toronto, Ont.; Public Health Laboratory (Kanji), Alberta Precision Laboratories, Foothills Medical Centre, and Section of Medical Microbiology (Kanji), Department of Pathology and Laboratory Medicine, and Division of Infectious Diseases, Department of Medicine, University of Calgary, Calgary, Alta.; Ontario Health Study (Kirsh, Skead), Ontario Institute for Cancer Research; Department of Molecular Genetics (Kirsh, Skead), and Dalla Lana School of Public Health (Kirsh), University of Toronto, Toronto, Ont.; Roy Romanow Provincial Lab (Lang), Saskatchewan Health Authority; College of Medicine (Lang), University of Saskatchewan, Saskatoon, Sask.; Department of Biochemistry, Microbiology and Immunology (Langlois), and Centre for Infection, Immunity and Inflammation (Langlois), University of Ottawa, Ottawa, Ont.; Division of Infectious Diseases-Regina (Lee), University of Saskatchewan; Saskatchewan Health Authority (Lee), Saskatoon, Sask.; Medical Affair and Innovation (Lewin), Héma-Québec, Montréal, Que.; Departments of Epidemiology and Community Medicine (O'Brien), and Pathology and Laboratory Medicine (Pambrun), Faculty of Medicine, University of Ottawa, Ottawa, Ont.; Department of Mathematics & Statistics (Stephens), McGill University, Montréal, Que.; Department of Medical Microbiology (Stein, Van Caeseele), University of Manitoba, and Cadham Provincial Laboratory, Winnipeg, Man.; School of Population and Global Health (Evans), McGill University; The Research Institute of the McGill University Health Centre (Mazer, Buckeridge), Montréal, Que
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Kwedi Nolna S, Niba M, Djadda C, Masumbe Netongo P. Seroprevalence of anti-SARS-CoV-2 IgG antibodies in HIV-positive and HIV-negative patients in clinical settings in Douala, Cameroon. FRONTIERS IN EPIDEMIOLOGY 2023; 3:1212220. [PMID: 38455949 PMCID: PMC10910930 DOI: 10.3389/fepid.2023.1212220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Accepted: 07/24/2023] [Indexed: 03/09/2024]
Abstract
Background The asymptomatic nature of COVID-19 coupled with differential testing are confounders in the assessment of SARS-CoV-2 incidence among people living with HIV (PLWH). As various comorbidities increase the risk of SARS-CoV-2 infection, it is crucial to assess the potential contribution of HIV to the risk of acquiring COVID-19. Our study aimed to compare the anti-SARS-CoV-2 IgG seroprevalence among people living with and without HIV. Methods PLWH were enrolled in the HIV units of two health facilities in Douala, Cameroon. Participants were consecutively enrolled, among which 47 were people living with HIV and 31 were HIV-negative patients. SARS-CoV-2 antibody tests were performed on all participants. Overall, medical consultation was conducted. For HIV-positive participants only, viral load, antiretroviral regimen, duration of HIV infection, and duration of antiretroviral treatment were retrieved from medical records. Results We found an overall SARS-CoV-2 IgG seroprevalence of 42.31% within the study population, with a SARS-CoV-2 IgG seroprevalence of 44.6% for PLWH and 38.7% among those without HIV infection; no significant statistical difference was observed. Adjusting for sex, HIV status, and BCG vaccination, the odds of previous SARS-CoV-2 infection were higher among married persons in the study population. Sex, BCG vaccination, and HIV status were not found to be associated with SARS-CoV-2 IgG seropositivity. Conclusions Our findings support the lack of association between HIV status and susceptibility to SARS-CoV-2 infection. The ARV regimen, suppressed viral load, and Tenofovir boasted ARV regimen might not affect the body's immune response after exposure to SARS-CoV-2 among PLWH. Thus, if HIV is well treated, the susceptibility to COVID-19 in PLWH would be like that of the general population.
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Affiliation(s)
- Sylvie Kwedi Nolna
- Epidemiology Department, Faculty of Medicine and Biomedical Sciences, University of Yaoundé 1, Yaoundé, Cameroon
- Capacity for Leadership Excellence and Research (CLEAR), Yaoundé, Cameroon
| | - Miriam Niba
- Capacity for Leadership Excellence and Research (CLEAR), Yaoundé, Cameroon
| | - Cedric Djadda
- Capacity for Leadership Excellence and Research (CLEAR), Yaoundé, Cameroon
| | - Palmer Masumbe Netongo
- Department of Biochemistry, Faculty of Sciences, University of Yaoundé 1, Yaoundé, Cameroon
- Molecular Diagnostics Research Group, Biotechnology Centre-University of Yaounde I, Yaoundé, Cameroon
- School of Science, Navajo Technical University, Crownpoint, NM, United States
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Bosserman RE, Farnsworth CW, O’Neil CA, Cass C, Park D, Ballman C, Wallace MA, Struttmann E, Stewart H, Arter O, Peacock K, Fraser VJ, Budge PJ, Olsen MA, Burnham CAD, Babcock HM, Kwon JH. Seroprevalence of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) antibodies among healthcare personnel in the Midwestern United States, September 2020-April 2021. ANTIMICROBIAL STEWARDSHIP & HEALTHCARE EPIDEMIOLOGY : ASHE 2023; 3:e133. [PMID: 37592963 PMCID: PMC10428156 DOI: 10.1017/ash.2022.375] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 12/15/2022] [Accepted: 12/15/2022] [Indexed: 08/19/2023]
Abstract
Objective To determine the prevalence of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) IgG nucleocapsid (N) antibodies among healthcare personnel (HCP) with no prior history of COVID-19 and to identify factors associated with seropositivity. Design Prospective cohort study. Setting An academic, tertiary-care hospital in St. Louis, Missouri. Participants The study included 400 HCP aged ≥18 years who potentially worked with coronavirus disease 2019 (COVID-19) patients and had no known history of COVID-19; 309 of these HCP also completed a follow-up visit 70-160 days after enrollment. Enrollment visits took place between September and December 2020. Follow-up visits took place between December 2020 and April 2021. Methods At each study visit, participants underwent SARS-CoV-2 IgG N-antibody testing using the Abbott SARS-CoV-2 IgG assay and completed a survey providing information about demographics, job characteristics, comorbidities, symptoms, and potential SARS-CoV-2 exposures. Results Participants were predominately women (64%) and white (79%), with median age of 34.5 years (interquartile range [IQR], 30-45). Among the 400 HCP, 18 (4.5%) were seropositive for IgG N-antibodies at enrollment. Also, 34 (11.0%) of 309 were seropositive at follow-up. HCP who reported having a household contact with COVID-19 had greater likelihood of seropositivity at both enrollment and at follow-up. Conclusions In this cohort of HCP during the first wave of the COVID-19 pandemic, ∼1 in 20 had serological evidence of prior, undocumented SARS-CoV-2 infection at enrollment. Having a household contact with COVID-19 was associated with seropositivity.
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Affiliation(s)
- Rachel E. Bosserman
- Division of Infectious Diseases, Department of Medicine, Washington University School of Medicine, St. Louis, Missouri
| | - Christopher W. Farnsworth
- Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, Missouri
| | - Caroline A. O’Neil
- Division of Infectious Diseases, Department of Medicine, Washington University School of Medicine, St. Louis, Missouri
| | - Candice Cass
- Division of Infectious Diseases, Department of Medicine, Washington University School of Medicine, St. Louis, Missouri
| | - Daniel Park
- Division of Infectious Diseases, Department of Medicine, Washington University School of Medicine, St. Louis, Missouri
| | - Claire Ballman
- Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, Missouri
| | - Meghan A. Wallace
- Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, Missouri
| | - Emily Struttmann
- Division of Infectious Diseases, Department of Medicine, Washington University School of Medicine, St. Louis, Missouri
| | - Henry Stewart
- Division of Infectious Diseases, Department of Medicine, Washington University School of Medicine, St. Louis, Missouri
| | - Olivia Arter
- Division of Infectious Diseases, Department of Medicine, Washington University School of Medicine, St. Louis, Missouri
| | - Kate Peacock
- Division of Infectious Diseases, Department of Medicine, Washington University School of Medicine, St. Louis, Missouri
| | - Victoria J. Fraser
- Division of Infectious Diseases, Department of Medicine, Washington University School of Medicine, St. Louis, Missouri
| | - Philip J. Budge
- Division of Infectious Diseases, Department of Medicine, Washington University School of Medicine, St. Louis, Missouri
| | - Margaret A. Olsen
- Division of Infectious Diseases, Department of Medicine, Washington University School of Medicine, St. Louis, Missouri
| | - Carey-Ann D. Burnham
- Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, Missouri
| | - Hilary M. Babcock
- Division of Infectious Diseases, Department of Medicine, Washington University School of Medicine, St. Louis, Missouri
| | - Jennie H. Kwon
- Division of Infectious Diseases, Department of Medicine, Washington University School of Medicine, St. Louis, Missouri
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Hou CW, Williams S, Taylor K, Boyle V, Bobbett B, Kouvetakis J, Nguyen K, McDonald A, Harris V, Nussle B, Scharf P, Jehn ML, Lant T, Magee M, Chung Y, LaBaer J, Murugan V. Serological survey to estimate SARS-CoV-2 infection and antibody seroprevalence at a large public university: A cross-sectional study. BMJ Open 2023; 13:e072627. [PMID: 37536960 PMCID: PMC10401225 DOI: 10.1136/bmjopen-2023-072627] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Accepted: 06/26/2023] [Indexed: 08/05/2023] Open
Abstract
OBJECTIVE This study investigated the seroprevalence of SARS-CoV-2 antibodies among adults over 18 years. DESIGN Prospective cohort study. SETTINGS A large public university. PARTICIPANTS This study took volunteers over 5 days and recruited 1064 adult participants. PRIMARY OUTCOME MEASURES Seroprevalence of SARS-CoV-2-specific antibodies due to previous exposure to SARS-CoV-2 and/or vaccination. RESULTS The seroprevalence of the antireceptor binding domain (RBD) antibody was 90% by a lateral flow assay and 88% by a semiquantitative chemiluminescent immunoassay. The seroprevalence for antinucleocapsid was 20%. In addition, individuals with previous natural COVID-19 infection plus vaccination had higher anti-RBD antibody levels compared with those who had vaccination only or infection only. Individuals who had a breakthrough infection had the highest anti-RBD antibody levels. CONCLUSION Accurate estimates of the cumulative incidence of SARS-CoV-2 infection can inform the development of university risk mitigation protocols such as encouraging booster shots, extending mask mandates or reverting to online classes. It could help us to have clear guidance to act at the first sign of the next surge as well, especially since there is a surge of COVID-19 subvariant infections.
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Affiliation(s)
- Ching-Wen Hou
- Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, Arizona, USA
| | - Stacy Williams
- Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, Arizona, USA
| | - Kylee Taylor
- Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, Arizona, USA
| | - Veronica Boyle
- Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, Arizona, USA
| | - Bradley Bobbett
- Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, Arizona, USA
| | - Joseph Kouvetakis
- Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, Arizona, USA
| | - Keana Nguyen
- Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, Arizona, USA
| | - Aaron McDonald
- Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, Arizona, USA
| | - Valerie Harris
- Office of VP Research Development, Arizona State University, Tempe, AZ, USA
| | - Benjamin Nussle
- Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, Arizona, USA
| | - Phillip Scharf
- College of Liberal Arts and Sciences, Arizona State University, Tempe, AZ, USA
| | - Megan L Jehn
- School of Human Evolution and Social Change, Arizona State University, Tempe, AZ, USA
| | - Timothy Lant
- Office of VP Research Development, Arizona State University, Tempe, AZ, USA
| | - Mitchell Magee
- Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, Arizona, USA
| | - Yunro Chung
- Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, Arizona, USA
- College of Health Solutions, Arizona State University, Phoenix, AZ, USA
| | - Joshua LaBaer
- Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, Arizona, USA
| | - Vel Murugan
- Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, Arizona, USA
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Musa S, Catovic Baralija E, Ivey Sawin V, Nardone A, Palo M, Skocibusic S, Blazevic M, Cilovic Lagarija S, Ahmetovic‐Karic G, Ljuca A, Dostovic‐Halilovic S, Nedic R, Subissi L, Ibrahim R, Boshevska G, Bergeri I, Pebody R, Vaughan A. Evolution of seroprevalence to SARS-CoV-2 in blood donors in Sarajevo Canton, Federation of Bosnia and Herzegovina: Cross-sectional and longitudinal studies. Influenza Other Respir Viruses 2023; 17:e13182. [PMID: 37621919 PMCID: PMC10444603 DOI: 10.1111/irv.13182] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Revised: 06/29/2023] [Accepted: 07/23/2023] [Indexed: 08/26/2023] Open
Abstract
Background Sarajevo Canton in the Federation of Bosnia and Herzegovina has recorded several waves of high SARS-CoV-2 transmission and has struggled to reach adequate vaccination coverage. We describe the evolution of infection- and vaccine-induced SARS-CoV-2 antibody response and persistence. Methods We conducted repeated cross-sectional analyses of blood donors aged 18-65 years in Sarajevo Canton in November-December 2020 and 2021. We analyzed serum samples for anti-nucleocapsid (anti-N) and anti-spike (anti-S) antibodies. To assess immune durability, we conducted longitudinal analyses of seropositive participants at 6 and 12 months. Results One thousand fifteen participants were included in Phase 1 (November-December 2020) and 1152 in Phase 2 (November-December 2021). Seroprevalence increased significantly from 19.2% (95% CI: 17.2%-21.4%) in Phase 1 to 91.6% (95% CI: 89.8%-93.1%) in Phase 2. Anti-S IgG titers were significantly higher among vaccinated (58.5%) than unvaccinated infected participants across vaccine products (p < 0.001), though highest among those who received an mRNA vaccine. At 6 months, 78/82 (95.1%) participants maintained anti-spike seropositivity; at 12 months, 58/58 (100.0%) participants were seropositive, and 33 (56.9%) had completed the primary vaccine series within 6 months. Among 11 unvaccinated participants who were not re-infected at 12 months, anti-S IgG declined from median 770.1 (IQR 615.0-1321.7) to 290.8 (IQR 175.7-400.3). Anti-N IgG antibodies waned earlier, from 35.4% seropositive at 6 months to 24.1% at 12 months. Conclusions SARS-CoV-2 seroprevalence increased significantly over 12 months from end of 2020 to end of 2021. Although individuals with previous infection may have residual protection, COVID-19 vaccination is vital to strengthening population immunity.
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Affiliation(s)
- Sanjin Musa
- Institute for Public Health of the Federation of Bosnia and HerzegovinaSarajevoBosnia and Herzegovina
- Sarajevo School of Science and Technology Sarajevo Medical SchoolSarajevoBosnia and Herzegovina
| | - Elma Catovic Baralija
- Institute for Transfusion Medicine of the Federation of Bosnia and HerzegovinaSarajevoBosnia and Herzegovina
| | - Veronica Ivey Sawin
- Institute for Public Health of the Federation of Bosnia and HerzegovinaSarajevoBosnia and Herzegovina
| | | | - Mirza Palo
- World Health Organization Office in Bosnia and HerzegovinaSarajevoBosnia and Herzegovina
| | - Sinisa Skocibusic
- Institute for Public Health of the Federation of Bosnia and HerzegovinaSarajevoBosnia and Herzegovina
| | - Mia Blazevic
- Institute for Public Health of the Federation of Bosnia and HerzegovinaSarajevoBosnia and Herzegovina
| | - Seila Cilovic Lagarija
- Institute for Public Health of the Federation of Bosnia and HerzegovinaSarajevoBosnia and Herzegovina
| | - Gorana Ahmetovic‐Karic
- Institute for Transfusion Medicine of the Federation of Bosnia and HerzegovinaSarajevoBosnia and Herzegovina
| | - Alma Ljuca
- Institute for Transfusion Medicine of the Federation of Bosnia and HerzegovinaSarajevoBosnia and Herzegovina
| | - Sanela Dostovic‐Halilovic
- Institute for Transfusion Medicine of the Federation of Bosnia and HerzegovinaSarajevoBosnia and Herzegovina
| | - Rozalija Nedic
- Institute for Public Health of the Federation of Bosnia and HerzegovinaSarajevoBosnia and Herzegovina
| | | | - Rawi Ibrahim
- World Health Organization Regional Office for EuropeCopenhagenDenmark
| | | | | | - Richard Pebody
- World Health Organization Regional Office for EuropeCopenhagenDenmark
| | - Aisling Vaughan
- World Health Organization Regional Office for EuropeCopenhagenDenmark
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Basto-Abreu A, Carnalla M, Torres-Ibarra L, Sanchez-Pájaro A, Romero-Martínez M, Martínez-Barnetche J, López-Martínez I, Aparicio-Antonio R, Shamah-Levy T, Alpuche-Aranda C, Rivera JA, Barrientos-Gutiérrez T. SARS-CoV-2 seroprevalence and vaccine coverage from August to November 2021: A nationally representative survey in Mexico. J Med Virol 2023; 95:e29038. [PMID: 37615363 DOI: 10.1002/jmv.29038] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 08/01/2023] [Accepted: 08/04/2023] [Indexed: 08/25/2023]
Abstract
We aimed to estimate self-reported vaccine coverage and SARS-CoV-2 anti-N and anti-S seroprevalence in Mexico overall and for five vaccine types. We used a nationally representative survey with 7236 dried blood spot samples for adults 18 years and older collected from August to November 2021. Anti-N and anti-S seroprevalence were estimated adjusting for the sensitivity and specificity of the immunoassay test. A multivariate Poisson regression model was used to estimate seroprevalence by vaccine type and by age group adjusting for confounders and test performance. Vaccination coverage was 74%, being higher in women compared to men, high socioeconomic status (SES) compared to low and middle SES, graduates compared to people with high school, and formal workers compared to other employment statuses. Anti-N seroprevalence was 59.2%, compared to 84.1% anti-S seroprevalence. Anti-S seroprevalence was higher for vaccinated than unvaccinated participants. All vaccines were associated with more than 70% anti-S seroprevalence, with the lowest being observed for CoronaVac and Ad5-nCoV. Fully vaccinated participants over 60 years presented a lower seroprevalence (77.6%) compared to younger adults (91.1%), with larger differences for ChAdOx1 and CoronaVac vaccines. Between August and November 2021, three out of four Mexican adults had been vaccinated. Vaccination was associated with a higher positivity to anti-S antibodies. While antibodies do not reflect immunity, our results suggest that booster doses should be offered to people over 60 years of age and to adults who received Ad5-nCoV or CoronaVac as primary vaccination schemes.
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Affiliation(s)
- Ana Basto-Abreu
- Center for Population Health Research, National Institute of Public Health, Cuernavaca, Mexico
| | - Martha Carnalla
- Center for Population Health Research, National Institute of Public Health, Cuernavaca, Mexico
| | - Leticia Torres-Ibarra
- Center for Population Health Research, National Institute of Public Health, Cuernavaca, Mexico
| | - Andres Sanchez-Pájaro
- Center for Population Health Research, National Institute of Public Health, Cuernavaca, Mexico
| | - Martin Romero-Martínez
- Center for Research in Evaluation and Surveys, National Institute of Public Health, Cuernavaca, Mexico
| | - Jesus Martínez-Barnetche
- Center for Research on Infectious Diseases, National Institute of Public Health, Cuernavaca, Mexico
| | | | | | - Teresa Shamah-Levy
- Center for Research in Evaluation and Surveys, National Institute of Public Health, Cuernavaca, Mexico
| | - Celia Alpuche-Aranda
- Center for Research on Infectious Diseases, National Institute of Public Health, Cuernavaca, Mexico
| | - Juan A Rivera
- National Institute of Public Health, Cuernavaca, Mexico
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Vo M, Feng Z, Glasser JW, Clarke KEN, Jones JN. Analysis of metapopulation models of the transmission of SARS-CoV-2 in the United States. J Math Biol 2023; 87:24. [PMID: 37421486 DOI: 10.1007/s00285-023-01948-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Revised: 04/18/2023] [Accepted: 06/08/2023] [Indexed: 07/10/2023]
Abstract
During the COVID-19 pandemic, renewal equation estimates of time-varying effective reproduction numbers were useful to policymakers in evaluating the need for and impact of mitigation measures. Our objective here is to illustrate the utility of mechanistic expressions for the basic and effective (or intrinsic and realized) reproduction numbers, [Formula: see text] and related quantities derived from a Susceptible-Exposed-Infectious-Removed (SEIR) model including features of COVID-19 that might affect transmission of SARS-CoV-2, including asymptomatic, pre-symptomatic, and symptomatic infections, with which people may be hospitalized. Expressions from homogeneous host population models can be analyzed to determine the effort needed to reduce [Formula: see text] from [Formula: see text] to 1 and contributions of modeled mitigation measures. Our model is stratified by age, 0-4, 5-9, …, 75+ years, and location, the 50 states plus District of Columbia. Expressions from such heterogeneous host population models include subpopulation reproduction numbers, contributions from the above-mentioned infectious states, metapopulation numbers, subpopulation contributions, and equilibrium prevalence. While the population-immunity at which [Formula: see text] has captured the popular imagination, the metapopulation [Formula: see text] could be attained in an infinite number of ways even if only one intervention (e.g., vaccination) were capable of reducing [Formula: see text] However, gradients of expressions derived from heterogeneous host population models,[Formula: see text] can be evaluated to identify optimal allocations of limited resources among subpopulations. We illustrate the utility of such analytical results by simulating two hypothetical vaccination strategies, one uniform and other indicated by [Formula: see text] as well as the actual program estimated from one of the CDC's nationwide seroprevalence surveys conducted from mid-summer 2020 through the end of 2021.
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Affiliation(s)
- MyVan Vo
- Department of Mathematics, Purdue University, West Lafayette, USA
| | - Zhilan Feng
- Department of Mathematics, Purdue University, West Lafayette, USA
- Division of Mathematical Sciences, NSF, Alexandria, USA
| | - John W Glasser
- Coronavirus and Other Respiratory Viruses Division, National Center for Immunization and Respiratory Diseases, CDC, 1600 Clifton Road NE, Atlanta, GA, 30333, USA.
| | - Kristie E N Clarke
- Center for Surveillance, Epidemiology, and Laboratory Services, CDC, Atlanta, USA
| | - Jefferson N Jones
- Coronavirus and Other Respiratory Viruses Division, National Center for Immunization and Respiratory Diseases, CDC, 1600 Clifton Road NE, Atlanta, GA, 30333, USA
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Brown ER, O’Brien MP, Snow B, Isa F, Forleo-Neto E, Chan KC, Hou P, Cohen MS, Herman G, Barnabas RV. A Prospective Study of Key Correlates for Household Transmission of Severe Acute Respiratory Syndrome Coronavirus 2. Open Forum Infect Dis 2023; 10:ofad271. [PMID: 37416758 PMCID: PMC10319621 DOI: 10.1093/ofid/ofad271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Accepted: 05/22/2023] [Indexed: 07/08/2023] Open
Abstract
Background Randomized controlled trials evaluated monoclonal antibodies for the treatment (Study 2067) and prevention (Study 2069) of coronavirus disease 2019 (COVID-19). Household contacts of the infected index case in Study 2067 were enrolled in Study 2069 and prospectively followed; these cohorts provided a unique opportunity to evaluate correlates of transmission, specifically viral load. Methods This post hoc analysis was designed to identify and evaluate correlates of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission, adjusting for potential confounding factors related to source SARS-CoV-2 viral load and risk of SARS-CoV-2 acquisition in this population. Correlates of transmission were evaluated in potential transmission pairs (any infected household member plus susceptible household contact). Results In total, 943 participants were included. In multivariable regression, 2 potential correlates were determined to have a statistically significant (P < .05) association with transmission risk. A 10-fold increase in viral load was associated with a 40% increase in odds of transmission; sharing a bedroom with the index participant was associated with a 199% increase in odds of transmission. Conclusions In this prospective, post hoc analysis that controlled for confounders, the 2 key correlates for transmission of SARS-CoV-2 within a household are sharing a bedroom and increased viral load, consistent with increased exposure to the infected individual.
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Affiliation(s)
- Elizabeth R Brown
- Vaccine and Infectious Disease and Public Health Services Divisions, Fred Hutchinson Cancer Center, Seattle, Washington, USA
- Department of Biostatistics, University of Washington, Seattle, Washington, USA
| | - Meagan P O’Brien
- Global Development, Regeneron Pharmaceuticals, Inc, Tarrytown, New York, USA
| | - Brian Snow
- Global Development, Regeneron Pharmaceuticals, Inc, Tarrytown, New York, USA
| | - Flonza Isa
- Global Development, Regeneron Pharmaceuticals, Inc, Tarrytown, New York, USA
| | - Eduardo Forleo-Neto
- Global Development, Regeneron Pharmaceuticals, Inc, Tarrytown, New York, USA
| | - Kuo-Chen Chan
- Global Development, Regeneron Pharmaceuticals, Inc, Tarrytown, New York, USA
| | - Peijie Hou
- Global Development, Regeneron Pharmaceuticals, Inc, Tarrytown, New York, USA
| | - Myron S Cohen
- Institute for Global Health and Infectious Diseases, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Gary Herman
- Global Development, Regeneron Pharmaceuticals, Inc, Tarrytown, New York, USA
| | - Ruanne V Barnabas
- Division of Infectious Diseases, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
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Figueiredo GM, Tengan FM, Campos SR, Luna EJ. Seroprevalence of SARS-CoV-2 in Brazil: A systematic review and meta-analysis. Clinics (Sao Paulo) 2023; 78:100233. [PMID: 37348256 DOI: 10.1016/j.clinsp.2023.100233] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/10/2022] [Revised: 04/19/2023] [Accepted: 06/01/2023] [Indexed: 06/24/2023] Open
Abstract
OBJECTIVES To summarize the data on SARS-CoV-2 seroprevalence surveys conducted in Brazil before the introduction of vaccines METHODS: The authors conducted a systematic review and meta-analysis on the seroprevalence of SARS-CoV-2 infection in Brazil. The present review followed the PRISMA guidelines. The authors searched Medline, Embase, and LILACS databases for serologic surveys conducted in the Brazilian population, in the period from 01/10/2019 to 07/11/2021, without language restrictions. The authors included studies that presented data concerning SARS-CoV-2 antibodies seroprevalence in Brazil and had a sample size ≥50 individuals. Considering the expected heterogeneity between studies, all analyses were performed using the random effects model, and heterogeneity was assessed using the I2 statistic RESULTS: Of 586 publications identified in the initial searches, 54 were included in the review and meta-analysis, which contained the results of 135 surveys, with 336,620 participants. The estimated seroprevalence was 11.0%, ranging from 1.0% to 83.0%, with a substantial heterogeneity (I2 = 99.55%). In subgroup analyses, the authors observed that the prevalence of SARS-CoV-2 antibodies was 13.0% in blood donors, 9.0% in the population-based surveys, 13% in schoolchildren, and 11.0% in healthcare workers. CONCLUSIONS Seroprevalence increases over time. Large differences were observed among the regions of the country. It was higher in the Northern region, decreasing towards the South. The present results may contribute to the analysis of the spread of SARS-CoV-2 infection in the Brazilian population before vaccination, one of the factors that may be influencing the clinical presentation of COVID-19 cases related to the new variants, as well as the effectiveness of the vaccination program.
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Affiliation(s)
- Gerusa Maria Figueiredo
- Departamento de Medicina Preventiva da Faculdade de Medicina da Universidade de São Paulo, São Paulo, SP, Brazil.
| | - Fátima Mitiko Tengan
- Departamento de Moléstias Infecciosas e Parasitarias da Faculdade de Medicina da Universidade de São Paulo, São Paulo, SP, Brazil.
| | - Sergio Roberto Campos
- Departamento de Medicina Preventiva da Faculdade de Medicina da Universidade de São Paulo, São Paulo, SP, Brazil.
| | - Expedito José Luna
- Departamento de Medicina Preventiva da Faculdade de Medicina da Universidade de São Paulo, São Paulo, SP, Brazil.
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Jones JM, Manrique IM, Stone MS, Grebe E, Saa P, Germanio CD, Spencer BR, Notari E, Bravo M, Lanteri MC, Green V, Briggs-Hagen M, Coughlin MM, Stramer SL, Opsomer J, Busch MP. Estimates of SARS-CoV-2 Seroprevalence and Incidence of Primary SARS-CoV-2 Infections Among Blood Donors, by COVID-19 Vaccination Status - United States, April 2021-September 2022. MMWR. MORBIDITY AND MORTALITY WEEKLY REPORT 2023; 72:601-605. [PMID: 37262007 DOI: 10.15585/mmwr.mm7222a3] [Citation(s) in RCA: 22] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
Changes in testing behaviors and reporting requirements have hampered the ability to estimate the U.S. SARS-CoV-2 incidence (1). Hybrid immunity (immunity derived from both previous infection and vaccination) has been reported to provide better protection than that from infection or vaccination alone (2). To estimate the incidence of infection and the prevalence of infection- or vaccination-induced antibodies (or both), data from a nationwide, longitudinal cohort of blood donors were analyzed. During the second quarter of 2021 (April-June), an estimated 68.4% of persons aged ≥16 years had infection- or vaccination-induced SARS-CoV-2 antibodies, including 47.5% from vaccination alone, 12.0% from infection alone, and 8.9% from both. By the third quarter of 2022 (July-September), 96.4% had SARS-CoV-2 antibodies from previous infection or vaccination, including 22.6% from infection alone and 26.1% from vaccination alone; 47.7% had hybrid immunity. Prevalence of hybrid immunity was lowest among persons aged ≥65 years (36.9%), the group with the highest risk for severe disease if infected, and was highest among those aged 16-29 years (59.6%). Low prevalence of infection-induced and hybrid immunity among older adults reflects the success of public health infection prevention efforts while also highlighting the importance of older adults staying up to date with recommended COVID-19 vaccination, including at least 1 bivalent dose.*,†.
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Sciaudone M, Cutshaw MK, McClean CM, Lacayo R, Kharabora O, Murray K, Strohminger S, Zivanovich MM, Gurnett R, Markmann AJ, Salgado EM, Bhowmik DR, Castro-Arroyo E, Boyce RM, Aiello AE, Richardson D, Juliano JJ, Bowman NM. Seroepidemiology and risk factors for SARS-CoV-2 infection among household members of food processing and farm workers in North Carolina. IJID REGIONS 2023; 7:164-169. [PMID: 37034427 PMCID: PMC10032047 DOI: 10.1016/j.ijregi.2023.03.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 03/15/2023] [Accepted: 03/17/2023] [Indexed: 03/24/2023]
Abstract
Background Racial and ethnic minorities have borne a disproportionate burden from coronavirus disease 2019 (COVID-19). Certain essential occupations, including food processing and farm work, employ large numbers of Hispanic migrant workers and have been shown to carry an especially high risk of infection. Methods This observational cohort study measured the seroprevalence of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and assessed the risk factors for seropositivity among food processing and farm workers, and members of their households, in North Carolina, USA. Participants completed questionnaires, blood samples were collected, and an enzyme-linked immunosorbent assay was used to assess SARS-CoV-2 seropositivity. Univariate and multi-variate analyses were undertaken to identify risk factors associated with seropositivity, using generalized estimating equations to account for household clustering. Findings Among the 218 participants, 94.5% were Hispanic, and SARS-CoV-2 seropositivity was 50.0%. Most seropositive individuals did not report a history of illness compatible with COVID-19. Attending church, having a prior history of COVID-19, having a seropositive household member, and speaking Spanish as one's primary language were associated with SARS-CoV-2 seropositivity, while preventive behaviours were not. Interpretation These findings underscore the substantial burden of COVID-19 among a population of mostly Hispanic essential workers and their households in rural North Carolina. This study contributes to a large body of evidence showing that Hispanic Americans have suffered a disproportionate burden of COVID-19. This study also highlights the epidemiologic importance of viral transmission within the household.
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Affiliation(s)
- Michael Sciaudone
- Department of Medicine, Section of Infectious Diseases, Tulane University School of Medicine, New Orleans, Louisiana, USA
- Center for Intelligent Molecular Diagnostics, Tulane University School of Medicine, New Orleans, Louisiana, USA
| | | | | | - Roberto Lacayo
- Infectious Disease Epidemiology and Ecology Laboratory, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
| | - Oksana Kharabora
- Infectious Disease Epidemiology and Ecology Laboratory, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
| | - Katherine Murray
- Infectious Disease Epidemiology and Ecology Laboratory, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
| | - Stephen Strohminger
- Infectious Disease Epidemiology and Ecology Laboratory, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
| | - Miriana Moreno Zivanovich
- Infectious Disease Epidemiology and Ecology Laboratory, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
| | - Rachel Gurnett
- Infectious Disease Epidemiology and Ecology Laboratory, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
| | - Alena J. Markmann
- Department of Medicine, Division of Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
| | - Emperatriz Morales Salgado
- Infectious Disease Epidemiology and Ecology Laboratory, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
| | - D. Ryan Bhowmik
- Department of Microbiology and Immunology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
| | - Edwin Castro-Arroyo
- Infectious Disease Epidemiology and Ecology Laboratory, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
| | - Ross M. Boyce
- Institute for Global Health and Infectious Diseases, University of North Carolina, Chapel Hill, North Carolina, USA
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina, USA
- Carolina Population Center, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Allison E. Aiello
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York, USA
- Robert N Butler Columbia Aging Center, Mailman School of Public Health, Columbia University, New York, New York, USA
| | - David Richardson
- Department of Environmental and Occupational Health, Program in Public Health, University of California – Irvine, Irvine, California, USA
| | - Jonathan J. Juliano
- Department of Medicine, Division of Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina, USA
- Curriculum in Genetics and Molecular Biology, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Natalie M. Bowman
- Department of Medicine, Division of Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
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Fox SJ, Javan E, Pasco R, Gibson GC, Betke B, Herrera-Diestra JL, Woody S, Pierce K, Johnson KE, Johnson-León M, Lachmann M, Meyers LA. Disproportionate impacts of COVID-19 in a large US city. PLoS Comput Biol 2023; 19:e1011149. [PMID: 37262052 DOI: 10.1371/journal.pcbi.1011149] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Accepted: 05/02/2023] [Indexed: 06/03/2023] Open
Abstract
COVID-19 has disproportionately impacted individuals depending on where they live and work, and based on their race, ethnicity, and socioeconomic status. Studies have documented catastrophic disparities at critical points throughout the pandemic, but have not yet systematically tracked their severity through time. Using anonymized hospitalization data from March 11, 2020 to June 1, 2021 and fine-grain infection hospitalization rates, we estimate the time-varying burden of COVID-19 by age group and ZIP code in Austin, Texas. During this 15-month period, we estimate an overall 23.7% (95% CrI: 22.5-24.8%) infection rate and 29.4% (95% CrI: 28.0-31.0%) case reporting rate. Individuals over 65 were less likely to be infected than younger age groups (11.2% [95% CrI: 10.3-12.0%] vs 25.1% [95% CrI: 23.7-26.4%]), but more likely to be hospitalized (1,965 per 100,000 vs 376 per 100,000) and have their infections reported (53% [95% CrI: 49-57%] vs 28% [95% CrI: 27-30%]). We used a mixed effect poisson regression model to estimate disparities in infection and reporting rates as a function of social vulnerability. We compared ZIP codes ranking in the 75th percentile of vulnerability to those in the 25th percentile, and found that the more vulnerable communities had 2.5 (95% CrI: 2.0-3.0) times the infection rate and only 70% (95% CrI: 60%-82%) the reporting rate compared to the less vulnerable communities. Inequality persisted but declined significantly over the 15-month study period. Our results suggest that further public health efforts are needed to mitigate local COVID-19 disparities and that the CDC's social vulnerability index may serve as a reliable predictor of risk on a local scale when surveillance data are limited.
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Affiliation(s)
- Spencer J Fox
- Department of Epidemiology & Biostatistics, University of Georgia, Athens, Georgia, United States of America
- Institute of Bioinformatics, University of Georgia, Athens, Georgia, United States of America
- Center for the Ecology of Infectious Diseases, University of Georgia, Athens, Georgia, United States of America
| | - Emily Javan
- Department of Integrative Biology, The University of Texas at Austin, Austin, Texas, United States of America
| | - Remy Pasco
- Department of Industrial Engineering, The University of Texas at Austin, Austin, Texas, United States of America
| | - Graham C Gibson
- Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America
| | - Briana Betke
- Department of Integrative Biology, The University of Texas at Austin, Austin, Texas, United States of America
| | - José L Herrera-Diestra
- Department of Integrative Biology, The University of Texas at Austin, Austin, Texas, United States of America
| | - Spencer Woody
- Department of Integrative Biology, The University of Texas at Austin, Austin, Texas, United States of America
| | - Kelly Pierce
- The Texas Advanced Computing Center, The University of Texas at Austin, Austin, Texas, United States of America
| | - Kaitlyn E Johnson
- The Rockefeller Foundation, New York, New York, United States of America
| | - Maureen Johnson-León
- Department of Integrative Biology, The University of Texas at Austin, Austin, Texas, United States of America
| | - Michael Lachmann
- The Santa Fe Institute, Santa Fe, New Mexico, United States of America
| | - Lauren Ancel Meyers
- Department of Integrative Biology, The University of Texas at Austin, Austin, Texas, United States of America
- The Santa Fe Institute, Santa Fe, New Mexico, United States of America
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Weinberger DM, Bhaskaran K, Korves C, Lucas BP, Columbo JA, Vashi A, Davies L, Justice AC, Rentsch CT. Absolute and relative excess mortality across demographic and clinical subgroups during the COVID-19 pandemic: an individual-level cohort study from a nationwide healthcare system of US Veterans. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.05.12.23289900. [PMID: 37293086 PMCID: PMC10246058 DOI: 10.1101/2023.05.12.23289900] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Background Most analyses of excess mortality during the COVID-19 pandemic have employed aggregate data. Individual-level data from the largest integrated healthcare system in the US may enhance understanding of excess mortality. Methods We performed an observational cohort study following patients receiving care from the Department of Veterans Affairs (VA) between 1 March 2018 and 28 February 2022. We estimated excess mortality on an absolute scale (i.e., excess mortality rates, number of excess deaths), and a relative scale by measuring the hazard ratio (HR) for mortality comparing pandemic and pre-pandemic periods, overall, and within demographic and clinical subgroups. Comorbidity burden and frailty were measured using the Charlson Comorbidity Index and Veterans Aging Cohort Study Index, respectively. Results Of 5,905,747 patients, median age was 65.8 years and 91% were men. Overall, the excess mortality rate was 10.0 deaths/1000 person-years (PY), with a total of 103,164 excess deaths and pandemic HR of 1.25 (95% CI 1.25-1.26). Excess mortality rates were highest among the most frail patients (52.0/1000 PY) and those with the highest comorbidity burden (16.3/1000 PY). However, the largest relative mortality increases were observed among the least frail (HR 1.31, 95% CI 1.30-1.32) and those with the lowest comorbidity burden (HR 1.44, 95% CI 1.43-1.46). Conclusions Individual-level data offered crucial clinical and operational insights into US excess mortality patterns during the COVID-19 pandemic. Notable differences emerged among clinical risk groups, emphasising the need for reporting excess mortality in both absolute and relative terms to inform resource allocation in future outbreaks.
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Affiliation(s)
- Daniel M. Weinberger
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, US
- Center for Interdisciplinary Research on AIDS, Yale School of Public Health, New Haven, CT, US
| | - Krishnan Bhaskaran
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK
| | - Caroline Korves
- Clinical Epidemiology Program, Department of Veterans Affairs Medical Center, White River Junction, VT
| | - Brian P. Lucas
- VA Outcomes Group, Department of Veterans Affairs Medical Center, White River Junction, VT, US
- The Dartmouth Institute for Health Policy & Clinical Practice, Geisel School of Medicine at Dartmouth, Hanover, NH, US
| | - Jesse A. Columbo
- VA Outcomes Group, Department of Veterans Affairs Medical Center, White River Junction, VT, US
- The Dartmouth Institute for Health Policy & Clinical Practice, Geisel School of Medicine at Dartmouth, Hanover, NH, US
- Section of Vascular Surgery, Dartmouth Hitchcock Medical Center, Lebanon, NH, US
| | - Anita Vashi
- Center for Innovation to Implementation, VA Palo Alto Health Care System, Menlo Park, CA, US
- Department of Emergency Medicine, University of California, San Francisco, CA, US
| | - Louise Davies
- VA Outcomes Group, Department of Veterans Affairs Medical Center, White River Junction, VT, US
- The Dartmouth Institute for Health Policy & Clinical Practice, Geisel School of Medicine at Dartmouth, Hanover, NH, US
- Department of Surgery - Otolaryngology Head & Neck Surgery, Geisel School of Medicine at Dartmouth, Hanover, NH, US
| | - Amy C. Justice
- Center for Interdisciplinary Research on AIDS, Yale School of Public Health, New Haven, CT, US
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT, US
- VA Connecticut Healthcare System, Department of Veterans Affairs, West Haven, CT, US
| | - Christopher T. Rentsch
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT, US
- VA Connecticut Healthcare System, Department of Veterans Affairs, West Haven, CT, US
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46
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Byrum JR, Waltari E, Janson O, Guo SM, Folkesson J, Chhun BB, Vinden J, Ivanov IE, Forst ML, Li H, Larson AG, Blackmon L, Liu Z, Wu W, Ahyong V, Tato CM, McCutcheon KM, Hoh R, Kelly JD, Martin JN, Peluso MJ, Henrich TJ, Deeks SG, Prakash M, Greenhouse B, Mehta SB, Pak JE. MultiSero: An Open-Source Multiplex-ELISA Platform for Measuring Antibody Responses to Infection. Pathogens 2023; 12:671. [PMID: 37242341 PMCID: PMC10221076 DOI: 10.3390/pathogens12050671] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 04/24/2023] [Accepted: 04/27/2023] [Indexed: 05/28/2023] Open
Abstract
A multiplexed enzyme-linked immunosorbent assay (ELISA) that simultaneously measures antibody binding to multiple antigens can extend the impact of serosurveillance studies, particularly if the assay approaches the simplicity, robustness, and accuracy of a conventional single-antigen ELISA. Here, we report on the development of multiSero, an open-source multiplex ELISA platform for measuring antibody responses to viral infection. Our assay consists of three parts: (1) an ELISA against an array of proteins in a 96-well format; (2) automated imaging of each well of the ELISA array using an open-source plate reader; and (3) automated measurement of optical densities for each protein within the array using an open-source analysis pipeline. We validated the platform by comparing antibody binding to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) antigens in 217 human sera samples, showing high sensitivity (0.978), specificity (0.977), positive predictive value (0.978), and negative predictive value (0.977) for classifying seropositivity, a high correlation of multiSero determined antibody titers with commercially available SARS-CoV-2 antibody tests, and antigen-specific changes in antibody titer dynamics upon vaccination. The open-source format and accessibility of our multiSero platform can contribute to the adoption of multiplexed ELISA arrays for serosurveillance studies, for SARS-CoV-2 and other pathogens of significance.
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Affiliation(s)
- Janie R. Byrum
- Chan Zuckerberg Biohub—San Francisco, San Francisco, CA 94158, USA
| | - Eric Waltari
- Chan Zuckerberg Biohub—San Francisco, San Francisco, CA 94158, USA
| | - Owen Janson
- Division of HIV, Infectious Disease, and Global Medicine, University of California, San Francisco, CA 94143, USA
- EPPIcenter Program, University of California, San Francisco, CA 94143, USA
| | - Syuan-Ming Guo
- Chan Zuckerberg Biohub—San Francisco, San Francisco, CA 94158, USA
| | - Jenny Folkesson
- Chan Zuckerberg Biohub—San Francisco, San Francisco, CA 94158, USA
| | - Bryant B. Chhun
- Chan Zuckerberg Biohub—San Francisco, San Francisco, CA 94158, USA
| | - Joanna Vinden
- Infectious Diseases and Immunity Graduate Program, University of California, Berkeley, CA 94720-3370, USA
| | - Ivan E. Ivanov
- Chan Zuckerberg Biohub—San Francisco, San Francisco, CA 94158, USA
| | - Marcus L. Forst
- Chan Zuckerberg Biohub—San Francisco, San Francisco, CA 94158, USA
- Department of Applied Physics, Stanford University, Stanford, CA 94305, USA
| | - Hongquan Li
- Department of Electrical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Adam G. Larson
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Lena Blackmon
- Chan Zuckerberg Biohub—San Francisco, San Francisco, CA 94158, USA
| | - Ziwen Liu
- Chan Zuckerberg Biohub—San Francisco, San Francisco, CA 94158, USA
| | - Wesley Wu
- Chan Zuckerberg Biohub—San Francisco, San Francisco, CA 94158, USA
| | - Vida Ahyong
- Chan Zuckerberg Biohub—San Francisco, San Francisco, CA 94158, USA
| | - Cristina M. Tato
- Chan Zuckerberg Biohub—San Francisco, San Francisco, CA 94158, USA
| | | | - Rebecca Hoh
- Division of HIV, Infectious Disease, and Global Medicine, University of California, San Francisco, CA 94143, USA
| | - J. Daniel Kelly
- Department of Epidemiology and Biostatistics, University of California, San Francisco, CA 94158, USA
| | - Jeffrey N. Martin
- Department of Epidemiology and Biostatistics, University of California, San Francisco, CA 94158, USA
| | - Michael J. Peluso
- Division of HIV, Infectious Disease, and Global Medicine, University of California, San Francisco, CA 94143, USA
| | - Timothy J. Henrich
- Division of Experimental Medicine, University of California, San Francisco, CA 94110, USA
| | - Steven G. Deeks
- Division of HIV, Infectious Disease, and Global Medicine, University of California, San Francisco, CA 94143, USA
| | - Manu Prakash
- Chan Zuckerberg Biohub—San Francisco, San Francisco, CA 94158, USA
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Bryan Greenhouse
- Chan Zuckerberg Biohub—San Francisco, San Francisco, CA 94158, USA
- Division of HIV, Infectious Disease, and Global Medicine, University of California, San Francisco, CA 94143, USA
- EPPIcenter Program, University of California, San Francisco, CA 94143, USA
| | - Shalin B. Mehta
- Chan Zuckerberg Biohub—San Francisco, San Francisco, CA 94158, USA
| | - John E. Pak
- Chan Zuckerberg Biohub—San Francisco, San Francisco, CA 94158, USA
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Dean NE, Howard DH, Lopman BA. Serological Studies and the Value of Information. Am J Public Health 2023; 113:517-519. [PMID: 36893371 PMCID: PMC10088957 DOI: 10.2105/ajph.2023.307245] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/22/2023] [Indexed: 03/11/2023]
Affiliation(s)
- Natalie E Dean
- Natalie E. Dean, David H. Howard, and Benjamin A. Lopman are with the Rollins School of Public Health, Emory University, Atlanta, GA
| | - David H Howard
- Natalie E. Dean, David H. Howard, and Benjamin A. Lopman are with the Rollins School of Public Health, Emory University, Atlanta, GA
| | - Benjamin A Lopman
- Natalie E. Dean, David H. Howard, and Benjamin A. Lopman are with the Rollins School of Public Health, Emory University, Atlanta, GA
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48
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Owusu-Boaitey N, Russell TW, Meyerowitz-Katz G, Levin AT, Herrera-Esposito D. Dynamics of SARS-CoV-2 seroassay sensitivity: a systematic review and modelling study. Euro Surveill 2023; 28:2200809. [PMID: 37227301 PMCID: PMC10283460 DOI: 10.2807/1560-7917.es.2023.28.21.2200809] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Accepted: 03/10/2023] [Indexed: 05/26/2023] Open
Abstract
BackgroundSerological surveys have been the gold standard to estimate numbers of SARS-CoV-2 infections, the dynamics of the epidemic, and disease severity. Serological assays have decaying sensitivity with time that can bias their results, but there is a lack of guidelines to account for this phenomenon for SARS-CoV-2.AimOur goal was to assess the sensitivity decay of seroassays for detecting SARS-CoV-2 infections, the dependence of this decay on assay characteristics, and to provide a simple method to correct for this phenomenon.MethodsWe performed a systematic review and meta-analysis of SARS-CoV-2 serology studies. We included studies testing previously diagnosed, unvaccinated individuals, and excluded studies of cohorts highly unrepresentative of the general population (e.g. hospitalised patients).ResultsOf the 488 screened studies, 76 studies reporting on 50 different seroassays were included in the analysis. Sensitivity decay depended strongly on the antigen and the analytic technique used by the assay, with average sensitivities ranging between 26% and 98% at 6 months after infection, depending on assay characteristics. We found that a third of the included assays departed considerably from manufacturer specifications after 6 months.ConclusionsSeroassay sensitivity decay depends on assay characteristics, and for some types of assays, it can make manufacturer specifications highly unreliable. We provide a tool to correct for this phenomenon and to assess the risk of decay for a given assay. Our analysis can guide the design and interpretation of serosurveys for SARS-CoV-2 and other pathogens and quantify systematic biases in the existing serology literature.
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Affiliation(s)
- Nana Owusu-Boaitey
- Case Western Reserve University School of Medicine, Cleveland, United States
- These authors contributed equally to this work
| | - Timothy W Russell
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | | | - Andrew T Levin
- Dartmouth College, Hanover, United States
- National Bureau for Economic Research, Cambridge, United States
- Centre for Economic Policy Research, London, United Kingdom
| | - Daniel Herrera-Esposito
- These authors contributed equally to this work
- Department of Psychology, University of Pennsylvania, Philadelphia, United States
- Laboratorio de Neurociencias, Universidad de la República, Montevideo, Uruguay
- Centro Interdisciplinario en Ciencia de Datos y Aprendizaje Automático, Universidad de la República, Montevideo, Uruguay
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49
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Gallian P, Hozé N, Brisbarre N, Saba Villarroel PM, Nurtop E, Isnard C, Pastorino B, Richard P, Morel P, Cauchemez S, de Lamballerie X. SARS-CoV-2 IgG seroprevalence surveys in blood donors before the vaccination campaign, France 2020-2021. iScience 2023; 26:106222. [PMID: 36818722 PMCID: PMC9930380 DOI: 10.1016/j.isci.2023.106222] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 12/20/2022] [Accepted: 02/11/2023] [Indexed: 02/17/2023] Open
Abstract
We conducted a cross-sectional study for SARS-CoV-2 anti-S1 IgG prevalence in French blood donors (n = 32605), from March-2020 to January-2021. A mathematical model combined seroprevalence with a daily number of hospital admissions to estimate the probability of hospitalization upon infection and determine the number of infections while correcting for antibody decay. There was an overall seroprevalence increase over the study period and we estimate that ∼15% of the French population had been infected by SARS-CoV-2 by January-2021. The infection/hospitalization ratio increased with age, from 0.31% (18-30yo) to 4.5% (61-70yo). Half of the IgG-S1 positive individuals had no detectable antibodies 4 to 5 months after infection. The seroprevalence in group O donors (7.43%) was lower (p = 0.003) than in A, B, and AB donors (8.90%). We conclude, based on seroprevalence data and mathematical modeling, that a large proportion of the French population was unprotected against severe disease prior to the vaccination campaign.
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Affiliation(s)
- Pierre Gallian
- Établissement Français du Sang, La Plaine Saint Denis 93218, France.,Unité des Virus Émergents (UVE: Aix-Marseille University - IRD 190 - Inserm 1207), 13005 Marseille, France
| | - Nathanaël Hozé
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, Université Paris Cité, UMR2000, CNRS, 75015 Paris, France
| | - Nadège Brisbarre
- Unité des Virus Émergents (UVE: Aix-Marseille University - IRD 190 - Inserm 1207), 13005 Marseille, France.,Établissement Français du Sang Provence Alpes Côte d'Azur et Corse, 13005 Marseille France
| | | | - Elif Nurtop
- Unité des Virus Émergents (UVE: Aix-Marseille University - IRD 190 - Inserm 1207), 13005 Marseille, France
| | - Christine Isnard
- Unité des Virus Émergents (UVE: Aix-Marseille University - IRD 190 - Inserm 1207), 13005 Marseille, France.,Établissement Français du Sang Provence Alpes Côte d'Azur et Corse, 13005 Marseille France
| | - Boris Pastorino
- Unité des Virus Émergents (UVE: Aix-Marseille University - IRD 190 - Inserm 1207), 13005 Marseille, France
| | - Pascale Richard
- Établissement Français du Sang, La Plaine Saint Denis 93218, France
| | - Pascal Morel
- Établissement Français du Sang, La Plaine Saint Denis 93218, France.,UMR RIGHT 1098, Inserm, Établissement Français du Sang, University of Franche-Comté, 25000 Besançon, France
| | - Simon Cauchemez
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, Université Paris Cité, UMR2000, CNRS, 75015 Paris, France
| | - Xavier de Lamballerie
- Unité des Virus Émergents (UVE: Aix-Marseille University - IRD 190 - Inserm 1207), 13005 Marseille, France
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50
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García-Carreras B, Hitchings MDT, Johansson MA, Biggerstaff M, Slayton RB, Healy JM, Lessler J, Quandelacy T, Salje H, Huang AT, Cummings DAT. Accounting for assay performance when estimating the temporal dynamics in SARS-CoV-2 seroprevalence in the U.S. Nat Commun 2023; 14:2235. [PMID: 37076502 PMCID: PMC10115837 DOI: 10.1038/s41467-023-37944-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Accepted: 04/06/2023] [Indexed: 04/21/2023] Open
Abstract
Reconstructing the incidence of SARS-CoV-2 infection is central to understanding the state of the pandemic. Seroprevalence studies are often used to assess cumulative infections as they can identify asymptomatic infection. Since July 2020, commercial laboratories have conducted nationwide serosurveys for the U.S. CDC. They employed three assays, with different sensitivities and specificities, potentially introducing biases in seroprevalence estimates. Using models, we show that accounting for assays explains some of the observed state-to-state variation in seroprevalence, and when integrating case and death surveillance data, we show that when using the Abbott assay, estimates of proportions infected can differ substantially from seroprevalence estimates. We also found that states with higher proportions infected (before or after vaccination) had lower vaccination coverages, a pattern corroborated using a separate dataset. Finally, to understand vaccination rates relative to the increase in cases, we estimated the proportions of the population that received a vaccine prior to infection.
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Affiliation(s)
- Bernardo García-Carreras
- Department of Biology, University of Florida, Gainesville, FL, USA.
- Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA.
| | - Matt D T Hitchings
- Department of Biostatistics, University of Florida, Gainesville, FL, USA
| | - Michael A Johansson
- COVID-19 Response, US Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Matthew Biggerstaff
- COVID-19 Response, US Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Rachel B Slayton
- COVID-19 Response, US Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Jessica M Healy
- COVID-19 Response, US Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Justin Lessler
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- UNC Carolina Population Center, Chapel Hill, NC, USA
| | | | - Henrik Salje
- Department of Genetics, University of Cambridge, Cambridge, UK
| | - Angkana T Huang
- Department of Genetics, University of Cambridge, Cambridge, UK
| | - Derek A T Cummings
- Department of Biology, University of Florida, Gainesville, FL, USA
- Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA
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