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Salvatore PP, Lee CC, Sleweon S, McCormick DW, Nicolae L, Knipe K, Dixon T, Banta R, Ogle I, Young C, Dusseau C, Salmonson S, Ogden C, Godwin E, Ballom T, Rhodes T, Wynn NT, David E, Bessey TK, Kim G, Suppiah S, Tamin A, Harcourt JL, Sheth M, Lowe L, Browne H, Tate JE, Kirking HL, Hagan LM. Transmission potential of vaccinated and unvaccinated persons infected with the SARS-CoV-2 Delta variant in a federal prison, July-August 2021. Vaccine 2023; 41:1808-1818. [PMID: 36572604 PMCID: PMC9744684 DOI: 10.1016/j.vaccine.2022.11.045] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Accepted: 11/19/2022] [Indexed: 12/14/2022]
Abstract
BACKGROUND The extent to which vaccinated persons who become infected with SARS-CoV-2 contribute to transmission is unclear. During a SARS-CoV-2 Delta variant outbreak among incarcerated persons with high vaccination rates in a federal prison, we assessed markers of viral shedding in vaccinated and unvaccinated persons. METHODS Consenting incarcerated persons with confirmed SARS-CoV-2 infection provided mid-turbinate nasal specimens daily for 10 consecutive days and reported symptom data via questionnaire. Real-time reverse transcription-polymerase chain reaction (RT-PCR), viral whole genome sequencing, and viral culture was performed on these nasal specimens. Duration of RT-PCR positivity and viral culture positivity was assessed using survival analysis. RESULTS A total of 957 specimens were provided by 93 participants, of whom 78 (84 %) were vaccinated and 17 (16 %) were unvaccinated. No significant differences were detected in duration of RT-PCR positivity among vaccinated participants (median: 13 days) versus those unvaccinated (median: 13 days; p = 0.50), or in duration of culture positivity (medians: 5 days and 5 days; p = 0.29). Among vaccinated participants, overall duration of culture positivity was shorter among Moderna vaccine recipients versus Pfizer (p = 0.048) or Janssen (p = 0.003) vaccine recipients. In post-hoc analyses, Moderna vaccine recipients demonstrated significantly shorter duration of culture positivity compared to unvaccinated participants (p = 0.02). When restricted to participants without reported prior infection, the difference between Moderna vaccine recipients and unvaccinated participants was more pronounced (medians: 3 days and 6 days, p = 0.002). CONCLUSIONS Infectious periods for vaccinated and unvaccinated persons who become infected with SARS-CoV-2 are similar and can be highly variable, though some vaccinated persons are likely infectious for shorter durations. These findings are critically important, especially in congregate settings where viral transmission can lead to large outbreaks. In such settings, clinicians and public health practitioners should consider vaccinated, infected persons to be no less infectious than unvaccinated, infected persons.
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Affiliation(s)
- Phillip P Salvatore
- COVID-19 Pandemic Response Team, Centers for Disease Control and Prevention, Atlanta, GA, United States; United States Public Health Service, Rockville, MD, United States.
| | - Christine C Lee
- COVID-19 Pandemic Response Team, Centers for Disease Control and Prevention, Atlanta, GA, United States; Laboratory Leadership Service, Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Sadia Sleweon
- COVID-19 Pandemic Response Team, Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - David W McCormick
- COVID-19 Pandemic Response Team, Centers for Disease Control and Prevention, Atlanta, GA, United States; United States Public Health Service, Rockville, MD, United States; Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Lavinia Nicolae
- COVID-19 Pandemic Response Team, Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Kristen Knipe
- COVID-19 Pandemic Response Team, Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Tom Dixon
- Bureau of Prisons, U.S. Department of Justice, Washington, DC, United States
| | - Robert Banta
- United States Public Health Service, Rockville, MD, United States; Bureau of Prisons, U.S. Department of Justice, Washington, DC, United States
| | - Isaac Ogle
- United States Public Health Service, Rockville, MD, United States; Bureau of Prisons, U.S. Department of Justice, Washington, DC, United States
| | - Cristen Young
- Bureau of Prisons, U.S. Department of Justice, Washington, DC, United States
| | - Charles Dusseau
- United States Public Health Service, Rockville, MD, United States; Bureau of Prisons, U.S. Department of Justice, Washington, DC, United States
| | - Shawn Salmonson
- Bureau of Prisons, U.S. Department of Justice, Washington, DC, United States
| | - Charles Ogden
- United States Public Health Service, Rockville, MD, United States; Bureau of Prisons, U.S. Department of Justice, Washington, DC, United States
| | - Eric Godwin
- Bureau of Prisons, U.S. Department of Justice, Washington, DC, United States
| | - TeCora Ballom
- United States Public Health Service, Rockville, MD, United States; Bureau of Prisons, U.S. Department of Justice, Washington, DC, United States
| | - Tara Rhodes
- United States Public Health Service, Rockville, MD, United States; Bureau of Prisons, U.S. Department of Justice, Washington, DC, United States
| | - Nhien Tran Wynn
- COVID-19 Pandemic Response Team, Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Ebenezer David
- COVID-19 Pandemic Response Team, Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Theresa K Bessey
- COVID-19 Pandemic Response Team, Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Gimin Kim
- COVID-19 Pandemic Response Team, Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Suganthi Suppiah
- COVID-19 Pandemic Response Team, Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Azaibi Tamin
- COVID-19 Pandemic Response Team, Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Jennifer L Harcourt
- COVID-19 Pandemic Response Team, Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Mili Sheth
- COVID-19 Pandemic Response Team, Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Luis Lowe
- COVID-19 Pandemic Response Team, Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Hannah Browne
- COVID-19 Pandemic Response Team, Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Jacqueline E Tate
- COVID-19 Pandemic Response Team, Centers for Disease Control and Prevention, Atlanta, GA, United States; United States Public Health Service, Rockville, MD, United States
| | - Hannah L Kirking
- COVID-19 Pandemic Response Team, Centers for Disease Control and Prevention, Atlanta, GA, United States; United States Public Health Service, Rockville, MD, United States
| | - Liesl M Hagan
- COVID-19 Pandemic Response Team, Centers for Disease Control and Prevention, Atlanta, GA, United States
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2
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Modelling the impact of repeat asymptomatic testing policies for staff on SARS-CoV-2 transmission potential. J Theor Biol 2023; 557:111335. [PMID: 36334850 PMCID: PMC9626407 DOI: 10.1016/j.jtbi.2022.111335] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Revised: 10/16/2022] [Accepted: 10/18/2022] [Indexed: 11/06/2022]
Abstract
Repeat asymptomatic testing in order to identify and quarantine infectious individuals has become a widely-used intervention to control SARS-CoV-2 transmission. In some workplaces, and in particular health and social care settings with vulnerable patients, regular asymptomatic testing has been deployed to staff to reduce the likelihood of workplace outbreaks. We have developed a model based on data available in the literature to predict the potential impact of repeat asymptomatic testing on SARS-CoV-2 transmission. The results highlight features that are important to consider when modelling testing interventions, including population heterogeneity of infectiousness and correlation with test-positive probability, as well as adherence behaviours in response to policy. Furthermore, the model based on the reduction in transmission potential presented here can be used to parameterise existing epidemiological models without them having to explicitly simulate the testing process. Overall, we find that even with different model paramterisations, in theory, regular asymptomatic testing is likely to be a highly effective measure to reduce transmission in workplaces, subject to adherence. This manuscript was submitted as part of a theme issue on "Modelling COVID-19 and Preparedness for Future Pandemics".
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3
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Viloria Winnett A, Porter MK, Romano AE, Savela ES, Akana R, Shelby N, Reyes JA, Schlenker NW, Cooper MM, Carter AM, Ji J, Barlow JT, Tognazzini C, Feaster M, Goh YY, Ismagilov RF. Morning SARS-CoV-2 Testing Yields Better Detection of Infection Due to Higher Viral Loads in Saliva and Nasal Swabs upon Waking. Microbiol Spectr 2022; 10:e0387322. [PMID: 36287073 PMCID: PMC9769854 DOI: 10.1128/spectrum.03873-22] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Accepted: 10/03/2022] [Indexed: 01/10/2023] Open
Abstract
Optimizing specimen collection methods to achieve the most reliable SARS-CoV-2 detection for a given diagnostic sensitivity would improve testing and minimize COVID-19 outbreaks. From September 2020 to April 2021, we performed a household-transmission study in which participants self-collected specimens every morning and evening throughout acute SARS-CoV-2 infection. Seventy mildly symptomatic participants collected saliva, and of those, 29 also collected nasal swab specimens. Viral load was quantified in 1,194 saliva and 661 nasal swab specimens using a high-analytical-sensitivity reverse transcription-quantitative PCR (RT-qPCR) assay. Viral loads in both saliva and nasal swab specimens were significantly higher in morning-collected specimens than in evening-collected specimens after symptom onset. This aspect of the biology of SARS-CoV-2 infection has implications for diagnostic testing. We infer that morning collection would have resulted in significantly improved detection and that this advantage would be most pronounced for tests with low to moderate analytical sensitivity. Collecting specimens for COVID-19 testing in the morning offers a simple and low-cost improvement to clinical diagnostic sensitivity of low- to moderate-analytical-sensitivity tests. IMPORTANCE Our findings suggest that collecting saliva and nasal swab specimens in the morning immediately after waking yields higher SARS-CoV-2 viral loads than collection later in the day. The higher viral loads from morning specimen collection are predicted to significantly improve detection of SARS-CoV-2 in symptomatic individuals, particularly when using moderate- to low-analytical-sensitivity COVID-19 diagnostic tests, such as rapid antigen tests.
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Affiliation(s)
| | | | - Anna E. Romano
- California Institute of Technology, Pasadena, California, USA
| | - Emily S. Savela
- California Institute of Technology, Pasadena, California, USA
| | - Reid Akana
- California Institute of Technology, Pasadena, California, USA
| | - Natasha Shelby
- California Institute of Technology, Pasadena, California, USA
| | | | | | | | | | - Jenny Ji
- California Institute of Technology, Pasadena, California, USA
| | - Jacob T. Barlow
- California Institute of Technology, Pasadena, California, USA
| | - Colten Tognazzini
- City of Pasadena Public Health Department, Pasadena, California, USA
| | - Matthew Feaster
- City of Pasadena Public Health Department, Pasadena, California, USA
| | - Ying-Ying Goh
- City of Pasadena Public Health Department, Pasadena, California, USA
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4
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Allender MC, Adkesson MJ, Langan JN, Delk KW, Meehan T, Aitken‐Palmer C, McEntire MM, Killian ML, Torchetti M, Morales SA, Austin C, Fredrickson R, Olmstead C, Ke R, Smith R, Hostnik ET, Terio K, Wang L. Multi-species outbreak of SARS-CoV-2 Delta variant in a zoological institution, with the detection in two new families of carnivores. Transbound Emerg Dis 2022; 69:e3060-e3075. [PMID: 35839756 PMCID: PMC9349917 DOI: 10.1111/tbed.14662] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Revised: 07/06/2022] [Accepted: 07/13/2022] [Indexed: 02/05/2023]
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has a worldwide distribution in humans and many other mammalian species. In late September 2021, 12 animals maintained by the Chicago Zoological Society's Brookfield Zoo were observed with variable clinical signs. The Delta variant of SARS-CoV-2 was detected in faeces and nasal swabs by qRT-PCR, including the first detection in animals from the families Procyonidae and Viverridae. Test positivity rate was 12.5% for 35 animals tested. All animals had been vaccinated with at least one dose of a recombinant vaccine designed for animals and all recovered with variable supportive treatment. Sequence analysis showed that six zoo animal strains were closely correlated with 18 human SARS-CoV-2 strains, suggestive of potential human-to-animal transmission events. This report documents the expanding host range of COVID-19 during the ongoing pandemic.
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Affiliation(s)
- Matthew C. Allender
- Brookfield ZooChicago Zoological SocietyBrookfieldIllinoisUSA
- Veterinary Diagnostic LabUniversity of Illinois Wildlife Epidemiology LaboratoryUrbanaIllinoisUSA
| | | | - Jennifer N. Langan
- Brookfield ZooChicago Zoological SocietyBrookfieldIllinoisUSA
- Department of Veterinary Clinical Medicine, College of Veterinary MedicineUniversity of IllinoisUrbanaIllinoisUSA
| | - Katie W. Delk
- Brookfield ZooChicago Zoological SocietyBrookfieldIllinoisUSA
| | - Thomas Meehan
- Brookfield ZooChicago Zoological SocietyBrookfieldIllinoisUSA
| | | | - Michael M. McEntire
- Illinois Zoological and Aquatic Animal ResidencyUniversity of IllinoisUrbanaIllinoisUSA
| | - Mary L. Killian
- National Veterinary Services Laboratories, Animal and Plant Health Inspection ServiceUnited States Department of AgricultureAmesIowaUSA
| | - Mia Torchetti
- National Veterinary Services Laboratories, Animal and Plant Health Inspection ServiceUnited States Department of AgricultureAmesIowaUSA
| | | | - Connie Austin
- Illinois Department of Public HealthSpringfieldIllinoisUSA
| | - Richard Fredrickson
- Veterinary Diagnostic Laboratory and Department of Veterinary Clinical Medicine, College of Veterinary MedicineUniversity of IllinoisUrbanaIllinoisUSA
| | - Colleen Olmstead
- Veterinary Diagnostic Laboratory and Department of Veterinary Clinical Medicine, College of Veterinary MedicineUniversity of IllinoisUrbanaIllinoisUSA
| | - Ruian Ke
- T‐6, Theoretical Biology and Biophysics, T DivisionLos Alamos National LaboratoryLos AlamosNew MexicoUSA
| | - Rebecca Smith
- Department of PathobiologyUniversity of Illinois at Urbana–ChampaignUrbanaIllinoisUSA
| | - Eric T. Hostnik
- Brookfield ZooChicago Zoological SocietyBrookfieldIllinoisUSA
- Department of Veterinary Clinical SciencesOhio State UniversityColumbusOhioUSA
| | - Karen Terio
- Zoological Pathology Program, College of Veterinary MedicineUniversity of IllinoisBrookfieldIllinoisUSA
| | - Leyi Wang
- Veterinary Diagnostic Laboratory and Department of Veterinary Clinical Medicine, College of Veterinary MedicineUniversity of IllinoisUrbanaIllinoisUSA
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5
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Iddon C, Jones B, Sharpe P, Cevik M, Fitzgerald S. A population framework for predicting the proportion of people infected by the far-field airborne transmission of SARS-CoV-2 indoors. BUILDING AND ENVIRONMENT 2022; 221:109309. [PMID: 35757305 PMCID: PMC9212805 DOI: 10.1016/j.buildenv.2022.109309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Revised: 06/09/2022] [Accepted: 06/14/2022] [Indexed: 06/15/2023]
Abstract
The number of occupants in a space influences the risk of far-field airborne transmission of SARS-CoV-2 because the likelihood of having infectious and susceptible people both correlate with the number of occupants. This paper explores the relationship between occupancy and the probability of infection, and how this affects an individual person and a population of people. Mass-balance and dose-response models determine far-field transmission risks for an individual person and a population of people after sub-dividing a large reference space into 10 identical comparator spaces. For a single infected person, the dose received by an individual person in the comparator space is 10 times higher because the equivalent ventilation rate per infected person is lower when the per capita ventilation rate is preserved. However, accounting for population dispersion, such as the community prevalence of the virus, the probability of an infected person being present and uncertainty in their viral load, shows the transmission probability increases with occupancy and the reference space has a higher transmission risk. Also, far-field transmission is likely to be a rare event that requires a high emission rate, and there are a set of Goldilocks conditions that are just right when equivalent ventilation is effective at mitigating against transmission. These conditions depend on the viral load, because when they are very high or low, equivalent ventilation has little effect on transmission risk. Nevertheless, resilient buildings should deliver the equivalent ventilation rate required by standards as minimum.
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Affiliation(s)
- Christopher Iddon
- Department of Architecture and Built Environment, University of Nottingham, Nottingham, UK
| | - Benjamin Jones
- Department of Architecture and Built Environment, University of Nottingham, Nottingham, UK
| | - Patrick Sharpe
- Department of Architecture and Built Environment, University of Nottingham, Nottingham, UK
| | - Muge Cevik
- Department of Infection and Global Health, School of Medicine, University of St Andrews, St Andrews, UK
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6
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Desikan R, Padmanabhan P, Kierzek AM, van der Graaf PH. Mechanistic Models of COVID-19: Insights into Disease Progression, Vaccines, and Therapeutics. Int J Antimicrob Agents 2022; 60:106606. [PMID: 35588969 PMCID: PMC9110059 DOI: 10.1016/j.ijantimicag.2022.106606] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Revised: 04/27/2022] [Accepted: 05/08/2022] [Indexed: 12/02/2022]
Abstract
The COVID-19 pandemic has severely impacted health systems and economies worldwide. Significant global efforts are therefore ongoing to improve vaccine efficacies, optimize vaccine deployment, and develop new antiviral therapies to combat the pandemic. Mechanistic viral dynamics and quantitative systems pharmacology models of SARS-CoV-2 infection, vaccines, immunomodulatory agents, and antiviral therapeutics have played a key role in advancing our understanding of SARS-CoV-2 pathogenesis and transmission, the interplay between innate and adaptive immunity to influence the outcomes of infection, effectiveness of treatments, mechanisms and performance of COVID-19 vaccines, and the impact of emerging SARS-CoV-2 variants. Here, we review some of the critical insights provided by these models and discuss the challenges ahead.
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Affiliation(s)
- Rajat Desikan
- Quantitative Systems Pharmacology (QSP) group, Certara, Sheffield and Canterbury, United Kingdom.
| | - Pranesh Padmanabhan
- Clem Jones Centre for Ageing Dementia Research, Queensland Brain Institute, The University of Queensland, Brisbane, Australia
| | - Andrzej M Kierzek
- Quantitative Systems Pharmacology (QSP) group, Certara, Sheffield and Canterbury, United Kingdom; School of Biosciences and Medicine, University of Surrey, Guildford, United Kingdom
| | - Piet H van der Graaf
- Quantitative Systems Pharmacology (QSP) group, Certara, Sheffield and Canterbury, United Kingdom; Systems Pharmacology and Pharmacy, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands.
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7
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Lin Y, Yang B, Cobey S, Lau EHY, Adam DC, Wong JY, Bond HS, Cheung JK, Ho F, Gao H, Ali ST, Leung NHL, Tsang TK, Wu P, Leung GM, Cowling BJ. Incorporating temporal distribution of population-level viral load enables real-time estimation of COVID-19 transmission. Nat Commun 2022; 13:1155. [PMID: 35241662 PMCID: PMC8894407 DOI: 10.1038/s41467-022-28812-9] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Accepted: 02/14/2022] [Indexed: 12/20/2022] Open
Abstract
Many locations around the world have used real-time estimates of the time-varying effective reproductive number (\documentclass[12pt]{minimal}
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\begin{document}$${R}_{t}$$\end{document}Rt) of COVID-19 to provide evidence of transmission intensity to inform control strategies. Estimates of \documentclass[12pt]{minimal}
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\begin{document}$${R}_{t}$$\end{document}Rt are typically based on statistical models applied to case counts and typically suffer lags of more than a week because of the latent period and reporting delays. Noting that viral loads tend to decline over time since illness onset, analysis of the distribution of viral loads among confirmed cases can provide insights into epidemic trajectory. Here, we analyzed viral load data on confirmed cases during two local epidemics in Hong Kong, identifying a strong correlation between temporal changes in the distribution of viral loads (measured by RT-qPCR cycle threshold values) and estimates of \documentclass[12pt]{minimal}
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\begin{document}$${R}_{t}$$\end{document}Rt based on case counts. We demonstrate that cycle threshold values could be used to improve real-time \documentclass[12pt]{minimal}
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\begin{document}$${R}_{t}$$\end{document}Rt estimation, enabling more timely tracking of epidemic dynamics. The time-varying effective reproductive number (Rt) is useful for monitoring transmission of infections such as COVID-19, but reporting delays impact case count-based estimation methods. Here, the authors demonstrate and validate a method for estimation of Rt based on viral load data from Hong Kong that does not require accurate daily counts.
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Affiliation(s)
- Yun Lin
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Bingyi Yang
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Sarah Cobey
- Department of Ecology and Evolution, University of Chicago, Chicago, IL, USA
| | - Eric H Y Lau
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China.,Laboratory of Data Discovery for Health Limited, Hong Kong Science and Technology Park, New Territories, Hong Kong, China
| | - Dillon C Adam
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Jessica Y Wong
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Helen S Bond
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Justin K Cheung
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Faith Ho
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Huizhi Gao
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Sheikh Taslim Ali
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China.,Laboratory of Data Discovery for Health Limited, Hong Kong Science and Technology Park, New Territories, Hong Kong, China
| | - Nancy H L Leung
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Tim K Tsang
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China.,Laboratory of Data Discovery for Health Limited, Hong Kong Science and Technology Park, New Territories, Hong Kong, China
| | - Peng Wu
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China.,Laboratory of Data Discovery for Health Limited, Hong Kong Science and Technology Park, New Territories, Hong Kong, China
| | - Gabriel M Leung
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China.,Laboratory of Data Discovery for Health Limited, Hong Kong Science and Technology Park, New Territories, Hong Kong, China
| | - Benjamin J Cowling
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China. .,Laboratory of Data Discovery for Health Limited, Hong Kong Science and Technology Park, New Territories, Hong Kong, China.
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8
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Savela ES, Viloria Winnett A, Romano AE, Porter MK, Shelby N, Akana R, Ji J, Cooper MM, Schlenker NW, Reyes JA, Carter AM, Barlow JT, Tognazzini C, Feaster M, Goh YY, Ismagilov RF. Quantitative SARS-CoV-2 Viral-Load Curves in Paired Saliva Samples and Nasal Swabs Inform Appropriate Respiratory Sampling Site and Analytical Test Sensitivity Required for Earliest Viral Detection. J Clin Microbiol 2022; 60:e0178521. [PMID: 34911366 PMCID: PMC8849374 DOI: 10.1128/jcm.01785-21] [Citation(s) in RCA: 49] [Impact Index Per Article: 24.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Accepted: 12/10/2021] [Indexed: 11/20/2022] Open
Abstract
Early detection of SARS-CoV-2 infection is critical to reduce asymptomatic and presymptomatic transmission, curb the spread of variants, and maximize treatment efficacy. Low-analytical-sensitivity nasal-swab testing is commonly used for surveillance and symptomatic testing, but the ability of these tests to detect the earliest stages of infection has not been established. In this study, conducted between September 2020 and June 2021 in the greater Los Angeles County, California, area, initially SARS-CoV-2-negative household contacts of individuals diagnosed with COVID-19 prospectively self-collected paired anterior-nares nasal-swab and saliva samples twice daily for viral-load quantification by high-sensitivity reverse-transcription quantitative PCR (RT-qPCR) and digital-RT-PCR assays. We captured viral-load profiles from the incidence of infection for seven individuals and compared diagnostic sensitivities between respiratory sites. Among unvaccinated persons, testing saliva with a high-analytical-sensitivity assay detected infection up to 4.5 days before viral loads in nasal swabs reached concentrations detectable by low-analytical-sensitivity nasal-swab tests. For most participants, nasal swabs reached higher peak viral loads than saliva but were undetectable or at lower loads during the first few days of infection. High-analytical-sensitivity saliva testing was most reliable for earliest detection. Our study illustrates the value of acquiring early (within hours after a negative high-sensitivity test) viral-load profiles to guide the appropriate analytical sensitivity and respiratory site for detecting earliest infections. Such data are challenging to acquire but critical to designing optimal testing strategies with emerging variants in the current pandemic and to respond to future viral pandemics.
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Affiliation(s)
- Emily S. Savela
- California Institute of Technology, Pasadena, California, USA
| | | | - Anna E. Romano
- California Institute of Technology, Pasadena, California, USA
| | | | - Natasha Shelby
- California Institute of Technology, Pasadena, California, USA
| | - Reid Akana
- California Institute of Technology, Pasadena, California, USA
| | - Jenny Ji
- California Institute of Technology, Pasadena, California, USA
| | | | | | | | | | - Jacob T. Barlow
- California Institute of Technology, Pasadena, California, USA
| | - Colten Tognazzini
- City of Pasadena Public Health Department, Pasadena, California, USA
| | - Matthew Feaster
- City of Pasadena Public Health Department, Pasadena, California, USA
| | - Ying-Ying Goh
- City of Pasadena Public Health Department, Pasadena, California, USA
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9
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Padmanabhan P, Desikan R, Dixit NM. Modeling how antibody responses may determine the efficacy of COVID-19 vaccines. NATURE COMPUTATIONAL SCIENCE 2022; 2:123-131. [PMID: 38177523 DOI: 10.1038/s43588-022-00198-0] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Accepted: 01/20/2022] [Indexed: 01/06/2024]
Abstract
Predicting the efficacy of COVID-19 vaccines would aid vaccine development and usage strategies, which is of importance given their limited supplies. Here we develop a multiscale mathematical model that proposes mechanistic links between COVID-19 vaccine efficacies and the neutralizing antibody (NAb) responses they elicit. We hypothesized that the collection of all NAbs would constitute a shape space and that responses of individuals are random samples from this space. We constructed the shape space by analyzing reported in vitro dose-response curves of ~80 NAbs. Sampling NAb subsets from the space, we recapitulated the responses of convalescent patients. We assumed that vaccination would elicit similar NAb responses. We developed a model of within-host SARS-CoV-2 dynamics, applied it to virtual patient populations and, invoking the NAb responses above, predicted vaccine efficacies. Our predictions quantitatively captured the efficacies from clinical trials. Our study thus suggests plausible mechanistic underpinnings of COVID-19 vaccines and generates testable hypotheses for establishing them.
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Affiliation(s)
- Pranesh Padmanabhan
- Clem Jones Centre for Ageing Dementia Research, Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia.
| | - Rajat Desikan
- Department of Chemical Engineering, Indian Institute of Science, Bangalore, India
- Certara QSP, Certara UK Limited, Sheffield, UK
| | - Narendra M Dixit
- Department of Chemical Engineering, Indian Institute of Science, Bangalore, India.
- Centre for Biosystems Science and Engineering, Indian Institute of Science, Bangalore, India.
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10
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Kriegel M, Hartmann A, Buchholz U, Seifried J, Baumgarte S, Gastmeier P. SARS-CoV-2 Aerosol Transmission Indoors: A Closer Look at Viral Load, Infectivity, the Effectiveness of Preventive Measures and a Simple Approach for Practical Recommendations. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 19:220. [PMID: 35010484 PMCID: PMC8750733 DOI: 10.3390/ijerph19010220] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Revised: 12/15/2021] [Accepted: 12/16/2021] [Indexed: 12/12/2022]
Abstract
There is uncertainty about the viral loads of infectious individuals required to transmit COVID-19 via aerosol. In addition, there is a lack of both quantification of the influencing parameters on airborne transmission and simple-to-use models for assessing the risk of infection in practice, which furthermore quantify the influence of non-medical preventive measures. In this study, a dose-response model was adopted to analyze 25 documented outbreaks at infection rates of 4-100%. We show that infection was only possible if the viral load was higher than 108 viral copies/mL. Based on mathematical simplifications of our approach to predict the probable situational attack rate (PARs) of a group of persons in a room, and valid assumptions, we provide simplified equations to calculate, among others, the maximum possible number of persons and the person-related virus-free air supply flow necessary to keep the number of newly infected persons to less than one. A comparison of different preventive measures revealed that testing contributes the most to the joint protective effect, besides wearing masks and increasing ventilation. In addition, we conclude that absolute volume flow rate or person-related volume flow rate are more intuitive parameters for evaluating ventilation for infection prevention than air exchange rate.
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Affiliation(s)
- Martin Kriegel
- Hermann-Rietschel-Institut, Technical University of Berlin, 10623 Berlin, Germany;
| | - Anne Hartmann
- Hermann-Rietschel-Institut, Technical University of Berlin, 10623 Berlin, Germany;
| | - Udo Buchholz
- Department for Infectious Disease Epidemiology, Robert Koch Institute, 13353 Berlin, Germany; (U.B.); (J.S.)
| | - Janna Seifried
- Department for Infectious Disease Epidemiology, Robert Koch Institute, 13353 Berlin, Germany; (U.B.); (J.S.)
| | | | - Petra Gastmeier
- Institute for Hygiene and Environmental Medicine, Charité-University Medicine Berlin, 12203 Berlin, Germany;
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11
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Ke R, Zitzmann C, Ho DD, Ribeiro RM, Perelson AS. In vivo kinetics of SARS-CoV-2 infection and its relationship with a person's infectiousness. Proc Natl Acad Sci U S A 2021; 118:e2111477118. [PMID: 34857628 PMCID: PMC8670484 DOI: 10.1073/pnas.2111477118] [Citation(s) in RCA: 85] [Impact Index Per Article: 28.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/25/2021] [Indexed: 01/11/2023] Open
Abstract
The within-host viral kinetics of SARS-CoV-2 infection and how they relate to a person's infectiousness are not well understood. This limits our ability to quantify the impact of interventions on viral transmission. Here, we develop viral dynamic models of SARS-CoV-2 infection and fit them to data to estimate key within-host parameters such as the infected cell half-life and the within-host reproductive number. We then develop a model linking viral load (VL) to infectiousness and show a person's infectiousness increases sublinearly with VL and that the logarithm of the VL in the upper respiratory tract is a better surrogate of infectiousness than the VL itself. Using data on VL and the predicted infectiousness, we further incorporated data on antigen and RT-PCR tests and compared their usefulness in detecting infection and preventing transmission. We found that RT-PCR tests perform better than antigen tests assuming equal testing frequency; however, more frequent antigen testing may perform equally well with RT-PCR tests at a lower cost but with many more false-negative tests. Overall, our models provide a quantitative framework for inferring the impact of therapeutics and vaccines that lower VL on the infectiousness of individuals and for evaluating rapid testing strategies.
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Affiliation(s)
- Ruian Ke
- Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM 87545
- New Mexico Consortium, Los Alamos, NM 87544
| | - Carolin Zitzmann
- Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM 87545
| | - David D Ho
- Aaron Diamond AIDS Research Center, Columbia University Vagelos College of Physicians and Surgeons, New York, NY 10032
| | - Ruy M Ribeiro
- Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM 87545
| | - Alan S Perelson
- Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM 87545;
- New Mexico Consortium, Los Alamos, NM 87544
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12
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Marc A, Kerioui M, Blanquart F, Bertrand J, Mitjà O, Corbacho-Monné M, Marks M, Guedj J. Quantifying the relationship between SARS-CoV-2 viral load and infectiousness. eLife 2021; 10:e69302. [PMID: 34569939 PMCID: PMC8476126 DOI: 10.7554/elife.69302] [Citation(s) in RCA: 69] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2021] [Accepted: 09/01/2021] [Indexed: 12/16/2022] Open
Abstract
The relationship between SARS-CoV-2 viral load and infectiousness is poorly known. Using data from a cohort of cases and high-risk contacts, we reconstructed viral load at the time of contact and inferred the probability of infection. The effect of viral load was larger in household contacts than in non-household contacts, with a transmission probability as large as 48% when the viral load was greater than 1010 copies per mL. The transmission probability peaked at symptom onset, with a mean probability of transmission of 29%, with large individual variations. The model also projects the effects of variants on disease transmission. Based on the current knowledge that viral load is increased by two- to eightfold with variants of concern and assuming no changes in the pattern of contacts across variants, the model predicts that larger viral load levels could lead to a relative increase in the probability of transmission of 24% to 58% in household contacts, and of 15% to 39% in non-household contacts.
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Affiliation(s)
| | | | - François Blanquart
- Université de Paris, IAME, INSERMParisFrance
- Centre for Interdisciplinary Research in Biology (CIRB), Collège de France, CNRS, INSERM, PSL Research UniversityParisFrance
| | | | - Oriol Mitjà
- Fight AIDS and Infectious Diseases Foundation, Hospital Universitari Germans Trias i PujolBadalonaSpain
- Lihir Medical Centre, International SOSLondolovitPapua New Guinea
| | - Marc Corbacho-Monné
- Fight AIDS and Infectious Diseases Foundation, Hospital Universitari Germans Trias i PujolBadalonaSpain
- Hospital Universitari Parc TaulíSabadellSpain
- Facultat de Medicina–Universitat de BarcelonaBarcelonaSpain
| | - Michael Marks
- London School of Hygiene and Tropical MedicineLondonUnited Kingdom
- Hospital for Tropical DiseasesLondonUnited Kingdom
- Division of infection and Immunity, University College LondonLondonUnited Kingdom
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13
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Ke R, Martinez PP, Smith RL, Gibson LL, Achenbach CJ, McFall S, Qi C, Jacob J, Dembele E, Bundy C, Simons LM, Ozer EA, Hultquist JF, Lorenzo-Redondo R, Opdycke AK, Hawkins C, Murphy RL, Mirza A, Conte M, Gallagher N, Luo CH, Jarrett J, Conte A, Zhou R, Farjo M, Rendon G, Fields CJ, Wang L, Fredrickson R, Baughman ME, Chiu KK, Choi H, Scardina KR, Owens AN, Broach J, Barton B, Lazar P, Robinson ML, Mostafa HH, Manabe YC, Pekosz A, McManus DD, Brooke CB. Longitudinal analysis of SARS-CoV-2 vaccine breakthrough infections reveal limited infectious virus shedding and restricted tissue distribution. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2021:2021.08.30.21262701. [PMID: 34494028 PMCID: PMC8423226 DOI: 10.1101/2021.08.30.21262701] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
The global effort to vaccinate people against SARS-CoV-2 in the midst of an ongoing pandemic has raised questions about the nature of vaccine breakthrough infections and the potential for vaccinated individuals to transmit the virus. These questions have become even more urgent as new variants of concern with enhanced transmissibility, such as Delta, continue to emerge. To shed light on how vaccine breakthrough infections compare with infections in immunologically naive individuals, we examined viral dynamics and infectious virus shedding through daily longitudinal sampling in a small cohort of adults infected with SARS-CoV-2 at varying stages of vaccination. The durations of both infectious virus shedding and symptoms were significantly reduced in vaccinated individuals compared with unvaccinated individuals. We also observed that breakthrough infections are associated with strong tissue compartmentalization and are only detectable in saliva in some cases. These data indicate that vaccination shortens the duration of time of high transmission potential, minimizes symptom duration, and may restrict tissue dissemination.
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14
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Savela ES, Winnett A, Romano AE, Porter MK, Shelby N, Akana R, Ji J, Cooper MM, Schlenker NW, Reyes JA, Carter AM, Barlow JT, Tognazzini C, Feaster M, Goh YY, Ismagilov RF. Quantitative SARS-CoV-2 viral-load curves in paired saliva and nasal swabs inform appropriate respiratory sampling site and analytical test sensitivity required for earliest viral detection. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2021:2021.04.02.21254771. [PMID: 33851180 PMCID: PMC8043477 DOI: 10.1101/2021.04.02.21254771] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Early detection of SARS-CoV-2 infection is critical to reduce asymptomatic and pre-symptomatic transmission, curb the spread of variants by travelers, and maximize treatment efficacy. Low-sensitivity nasal-swab testing (antigen and some nucleic-acid-amplification tests) is commonly used for surveillance and symptomatic testing, but the ability of low-sensitivity nasal-swab tests to detect the earliest stages of infection has not been established. In this case-ascertained study, initially-SARS-CoV-2-negative household contacts of individuals diagnosed with COVID-19 prospectively self-collected paired anterior-nares nasal-swab and saliva samples twice daily for viral-load quantification by high-sensitivity RT-qPCR and digital-RT-PCR assays. We captured viral-load profiles from the incidence of infection for seven individuals and compared diagnostic sensitivities between respiratory sites. Among unvaccinated persons, high-sensitivity saliva testing detected infection up to 4.5 days before viral loads in nasal swabs reached the limit of detection of low-sensitivity nasal-swab tests. For most participants, nasal swabs reached higher peak viral loads than saliva, but were undetectable or at lower loads during the first few days of infection. High-sensitivity saliva testing was most reliable for earliest detection. Our study illustrates the value of acquiring early (within hours after a negative high-sensitivity test) viral-load profiles to guide the appropriate analytical sensitivity and respiratory site for detecting earliest infections. Such data are challenging to acquire but critical to design optimal testing strategies in the current pandemic and will be required for responding to future viral pandemics. As new variants and viruses emerge, up-to-date data on viral kinetics are necessary to adjust testing strategies for reliable early detection of infections.
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Affiliation(s)
- Emily S. Savela
- California Institute of Technology, 1200 E. California Blvd., Pasadena, CA, USA 91125
| | - Alexander Winnett
- California Institute of Technology, 1200 E. California Blvd., Pasadena, CA, USA 91125
| | - Anna E. Romano
- California Institute of Technology, 1200 E. California Blvd., Pasadena, CA, USA 91125
| | - Michael K. Porter
- California Institute of Technology, 1200 E. California Blvd., Pasadena, CA, USA 91125
| | - Natasha Shelby
- California Institute of Technology, 1200 E. California Blvd., Pasadena, CA, USA 91125
| | - Reid Akana
- California Institute of Technology, 1200 E. California Blvd., Pasadena, CA, USA 91125
| | - Jenny Ji
- California Institute of Technology, 1200 E. California Blvd., Pasadena, CA, USA 91125
| | - Matthew M. Cooper
- California Institute of Technology, 1200 E. California Blvd., Pasadena, CA, USA 91125
| | - Noah W. Schlenker
- California Institute of Technology, 1200 E. California Blvd., Pasadena, CA, USA 91125
| | - Jessica A. Reyes
- California Institute of Technology, 1200 E. California Blvd., Pasadena, CA, USA 91125
| | - Alyssa M. Carter
- California Institute of Technology, 1200 E. California Blvd., Pasadena, CA, USA 91125
| | - Jacob T. Barlow
- California Institute of Technology, 1200 E. California Blvd., Pasadena, CA, USA 91125
| | - Colten Tognazzini
- City of Pasadena Public Health Department, 1845 N. Fair Oaks Ave., Pasadena, CA, USA 91103
| | - Matthew Feaster
- City of Pasadena Public Health Department, 1845 N. Fair Oaks Ave., Pasadena, CA, USA 91103
| | - Ying-Ying Goh
- City of Pasadena Public Health Department, 1845 N. Fair Oaks Ave., Pasadena, CA, USA 91103
| | - Rustem F. Ismagilov
- California Institute of Technology, 1200 E. California Blvd., Pasadena, CA, USA 91125
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