1
|
Perofsky AC, Hansen CL, Burstein R, Boyle S, Prentice R, Marshall C, Reinhart D, Capodanno B, Truong M, Schwabe-Fry K, Kuchta K, Pfau B, Acker Z, Lee J, Sibley TR, McDermot E, Rodriguez-Salas L, Stone J, Gamboa L, Han PD, Adler A, Waghmare A, Jackson ML, Famulare M, Shendure J, Bedford T, Chu HY, Englund JA, Starita LM, Viboud C. Impacts of human mobility on the citywide transmission dynamics of 18 respiratory viruses in pre- and post-COVID-19 pandemic years. Nat Commun 2024; 15:4164. [PMID: 38755171 PMCID: PMC11098821 DOI: 10.1038/s41467-024-48528-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Accepted: 05/02/2024] [Indexed: 05/18/2024] Open
Abstract
Many studies have used mobile device location data to model SARS-CoV-2 dynamics, yet relationships between mobility behavior and endemic respiratory pathogens are less understood. We studied the effects of population mobility on the transmission of 17 endemic viruses and SARS-CoV-2 in Seattle over a 4-year period, 2018-2022. Before 2020, visits to schools and daycares, within-city mixing, and visitor inflow preceded or coincided with seasonal outbreaks of endemic viruses. Pathogen circulation dropped substantially after the initiation of COVID-19 stay-at-home orders in March 2020. During this period, mobility was a positive, leading indicator of transmission of all endemic viruses and lagging and negatively correlated with SARS-CoV-2 activity. Mobility was briefly predictive of SARS-CoV-2 transmission when restrictions relaxed but associations weakened in subsequent waves. The rebound of endemic viruses was heterogeneously timed but exhibited stronger, longer-lasting relationships with mobility than SARS-CoV-2. Overall, mobility is most predictive of respiratory virus transmission during periods of dramatic behavioral change and at the beginning of epidemic waves.
Collapse
Affiliation(s)
- Amanda C Perofsky
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA.
- Fogarty International Center, National Institutes of Health, Bethesda, MD, USA.
| | - Chelsea L Hansen
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
- Fogarty International Center, National Institutes of Health, Bethesda, MD, USA
- PandemiX Center, Department of Science & Environment, Roskilde University, Roskilde, Denmark
| | - Roy Burstein
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle, WA, USA
| | - Shanda Boyle
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
| | - Robin Prentice
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
| | - Cooper Marshall
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
| | - David Reinhart
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
| | - Ben Capodanno
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
| | - Melissa Truong
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
| | - Kristen Schwabe-Fry
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
| | - Kayla Kuchta
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
| | - Brian Pfau
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
| | - Zack Acker
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
| | - Jover Lee
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Thomas R Sibley
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Evan McDermot
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
| | - Leslie Rodriguez-Salas
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
| | - Jeremy Stone
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
| | - Luis Gamboa
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
| | - Peter D Han
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Amanda Adler
- Seattle Children's Research Institute, Seattle, WA, USA
| | - Alpana Waghmare
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
- Seattle Children's Research Institute, Seattle, WA, USA
- Department of Pediatrics, University of Washington, Seattle, WA, USA
| | | | - Michael Famulare
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle, WA, USA
| | - Jay Shendure
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Howard Hughes Medical Institute, Seattle, WA, USA
| | - Trevor Bedford
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Howard Hughes Medical Institute, Seattle, WA, USA
| | - Helen Y Chu
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Janet A Englund
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
- Seattle Children's Research Institute, Seattle, WA, USA
- Department of Pediatrics, University of Washington, Seattle, WA, USA
| | - Lea M Starita
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Cécile Viboud
- Fogarty International Center, National Institutes of Health, Bethesda, MD, USA
| |
Collapse
|
2
|
Jackson ML, Thomas SC, Joyner MR, Hu M, Larry Lee YL, Capasso T, Polite NM, Kinnard CM, Mbaka MI, Williams A, Simmons JD, Butts CC. Time to Mobility Is Associated With Pulmonary Complications in Patients With Spine Fractures. Am Surg 2024:31348241241702. [PMID: 38566605 DOI: 10.1177/00031348241241702] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
INTRODUCTION Treatment of spine fractures may require periods of prolonged immobilization which prevents effective pulmonary toileting. We hypothesized that patients with longer time to mobilization, as measured by time to first physical therapy (PT) session, would have higher pulmonary complications. METHODS We performed a retrospective review of all trauma patients with cervical and thoracolumbar spinal fractures admitted to a level 1 trauma center over a 12-month period. Demographic data collection included age, gender, BMI, pulmonary comorbidities, concomitant rib fractures, admission GCS, Injury Severity Score (ISS), GCS at 24 h, treatment with cervical or thoracolumbar immobilization, and time to first PT evaluation. The primary outcome was the presence of any one of the following complications: unplanned intubation, pneumonia, or mortality at 30 days. Multivariable logistic regression analysis was used to assess significant predictors of pulmonary complication. RESULTS In total, 491 patients were identified. In terms of overall pulmonary complications, 10% developed pneumonia, 13% had unplanned intubation, and 6% died within 30 days. In total, 19% developed one or more complication. Overall, 25% of patients were seen by PT <48 h, 33% between 48 and 96 h, 19% at 96 h to 1 week, and 7% > 1 week. Multivariable logistic regression analysis showed that time to PT session (OR 1.010, 95% CI 1.005-1.016) and ISS (OR 1.063, 95% CI 1.026-1.102) were independently associated with pulmonary complication. CONCLUSION Time to mobility is independently associated with pulmonary complications in patients with spine fractures.
Collapse
Affiliation(s)
- Michael L Jackson
- General Surgery Residency Program, University of South Alabama, Mobile, AL, USA
| | - Samuel C Thomas
- General Surgery Residency Program, Brookwood Baptist Health, Birmingham, AL, USA
| | - Matthew R Joyner
- General Surgery Residency Program, University of Tennessee Knoxville, Knoxville, TN, USA
| | - Mengjie Hu
- Anesthesiology Residency Program, Wake Forest University, Winston-Salem, NC, USA
| | | | - Thomas Capasso
- Department of Surgery, University of South Alabama, Mobile, AL, USA
| | - Nathan M Polite
- Department of Surgery, University of South Alabama, Mobile, AL, USA
| | | | - Maryann I Mbaka
- Department of Surgery, University of South Alabama, Mobile, AL, USA
| | - Ashley Williams
- Department of Surgery, University of South Alabama, Mobile, AL, USA
| | - Jon D Simmons
- Department of Surgery, University of South Alabama, Mobile, AL, USA
| | - Charles C Butts
- Department of Surgery, University of South Alabama, Mobile, AL, USA
| |
Collapse
|
3
|
Frivold C, McCulloch DJ, Ekici S, Martin ET, Jackson ML, Chu HY. Acute respiratory infections among individuals seeking outpatient care in the states of Washington and Michigan by pregnancy status, 2011-2016. Influenza Other Respir Viruses 2023; 17:e13230. [PMID: 38076500 PMCID: PMC10700156 DOI: 10.1111/irv.13230] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 11/04/2023] [Accepted: 11/11/2023] [Indexed: 12/18/2023] Open
Abstract
Background Acute respiratory infections (ARIs) during pregnancy are associated with poor maternal and fetal outcomes. Methods Using U.S. Flu Vaccine Effectiveness Network data (2011-2016) from Washington and Michigan, we tested for respiratory viruses among pregnant and non-pregnant outpatients matched on age, site, and season (n = 191). Results Among all participants, detection of human coronaviruses and rhinovirus was common. We also observed differences in virus detection by pregnancy status; human coronaviruses and respiratory syncytial virus (RSV) were detected more frequently among pregnant and non-pregnant participants, respectively. Conclusions The role of respiratory viruses in maternal ARI morbidity should be further characterized to inform implementation of prevention interventions including maternal vaccines.
Collapse
Affiliation(s)
- Collrane Frivold
- Department of MedicineUniversity of WashingtonSeattleWashingtionUSA
- Department of EpidemiologyUniversity of WashingtonSeattleWashingtionUSA
| | | | - Seda Ekici
- Department of PediatricsUniversity of WashingtonSeattleWashingtionUSA
| | - Emily T. Martin
- Department of EpidemiologyUniversity of MichiganAnn ArborMichiganUSA
| | | | - Helen Y. Chu
- Department of MedicineUniversity of WashingtonSeattleWashingtionUSA
| |
Collapse
|
4
|
Daley MF, Reifler LM, Shoup JA, Glanz JM, Naleway AL, Jackson ML, Hambidge SJ, McLean H, Kharbanda EO, Klein NP, Lewin BJ, Weintraub ES, McNeil MM, Razzaghi H, Singleton JA. Influenza Vaccination Among Pregnant Women: Self-report Compared With Vaccination Data From Electronic Health Records, 2018-2020 Influenza Seasons. Public Health Rep 2023; 138:456-466. [PMID: 35674233 PMCID: PMC10240889 DOI: 10.1177/00333549221099932] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/03/2024] Open
Abstract
OBJECTIVES Having accurate influenza vaccination coverage estimates can guide public health activities. The objectives of this study were to (1) validate the accuracy of electronic health record (EHR)-based influenza vaccination data among pregnant women compared with survey self-report and (2) assess whether survey respondents differed from survey nonrespondents by demographic characteristics and EHR-based vaccination status. METHODS This study was conducted in the Vaccine Safety Datalink, a network of 8 large medical care organizations in the United States. Using EHR data, we identified all women pregnant during the 2018-2019 or 2019-2020 influenza seasons. Surveys were conducted among samples of women who did and did not appear vaccinated for influenza according to EHR data. Separate surveys were conducted after each influenza season, and respondents reported their influenza vaccination status. Analyses accounted for the stratified design, sampling probability, and response probability. RESULTS The survey response rate was 50.5% (630 of 1247) for 2018-2019 and 41.2% (721 of 1748) for 2019-2020. In multivariable analyses combining both survey years, non-Hispanic Black pregnant women had 3.80 (95% CI, 2.13-6.74) times the adjusted odds of survey nonresponse; odds of nonresponse were also higher for Hispanic pregnant women and women who had not received (per EHR data) influenza vaccine during current or prior influenza seasons. The sensitivity, specificity, and positive predictive value of EHR documentation of influenza vaccination compared with self-report were ≥92% for both survey years combined. The negative predictive value of EHR-based influenza vaccine status was 80.5% (95% CI, 76.7%-84.0%). CONCLUSIONS EHR-based influenza vaccination data among pregnant women were generally concordant with self-report. New data sources and novel approaches to mitigating nonresponse bias may be needed to enhance influenza vaccination surveillance efforts.
Collapse
Affiliation(s)
- Matthew F. Daley
- Institute for Health Research, Kaiser Permanente Colorado, Aurora, CO, USA
- Department of Pediatrics, University of Colorado School of Medicine, Aurora, CO, USA
| | - Liza M. Reifler
- Institute for Health Research, Kaiser Permanente Colorado, Aurora, CO, USA
| | - Jo Ann Shoup
- Institute for Health Research, Kaiser Permanente Colorado, Aurora, CO, USA
| | - Jason M. Glanz
- Institute for Health Research, Kaiser Permanente Colorado, Aurora, CO, USA
- Department of Epidemiology, Colorado School of Public Health, Aurora, CO, USA
| | - Allison L. Naleway
- Center for Health Research, Kaiser Permanente Northwest, Portland, OR, USA
| | - Michael L. Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Simon J. Hambidge
- Department of Pediatrics, University of Colorado School of Medicine, Aurora, CO, USA
- Department of General Pediatrics, Denver Health and Hospitals, Denver, CO, USA
| | - Huong McLean
- Marshfield Clinic Research Institute, Marshfield, WI, USA
| | | | | | - Bruno J. Lewin
- Kaiser Permanente Southern California, Pasadena, CA, USA
| | - Eric S. Weintraub
- Immunization Safety Office, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Michael M. McNeil
- Immunization Safety Office, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Hilda Razzaghi
- National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - James A. Singleton
- National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA
| |
Collapse
|
5
|
Hood N, Flannery B, Gaglani M, Beeram M, Wernli K, Jackson ML, Martin ET, Monto AS, Zimmerman R, Raviotta J, Belongia EA, McLean HQ, Kim S, Patel MM, Chung JR. Influenza Vaccine Effectiveness Among Children: 2011-2020. Pediatrics 2023; 151:e2022059922. [PMID: 36960655 PMCID: PMC10071433 DOI: 10.1542/peds.2022-059922] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 01/04/2023] [Indexed: 03/25/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Infants and children are at increased risk of severe influenza virus infection and its complications. Influenza vaccine effectiveness (VE) varies by age, influenza season, and influenza virus type/subtype. This study's objective was to examine the effectiveness of inactivated influenza vaccine against outpatient influenza illness in the pediatric population over 9 influenza seasons after the 2009 A(H1N1) pandemic. METHODS During the 2011-2012 through the 2019-2020 influenza seasons at outpatient clinics at 5 sites of the US Influenza Vaccine Effectiveness Network, children aged 6 months to 17 years with an acute respiratory illness were tested for influenza using real-time, reverse-transcriptase polymerase chain reaction. Vaccine effectiveness was estimated using a test-negative design. RESULTS Among 24 148 enrolled children, 28% overall tested positive for influenza, 3017 tested positive for influenza A(H3N2), 1459 for influenza A(H1N1)pdm09, and 2178 for influenza B. Among all enrollees, 39% overall were vaccinated, with 29% of influenza cases and 43% of influenza-negative controls vaccinated. Across all influenza seasons, the pooled VE for any influenza was 46% (95% confidence interval, 43-50). Overall and by type/subtype, VE against influenza illness was highest among children in the 6- to 59-month age group compared with older pediatric age groups. VE was lowest for influenza A(H3N2) virus infection. CONCLUSIONS Analysis of multiple seasons suggested substantial benefit against outpatient illness. Investigation of host-specific or virus-related mechanisms that may result in differences by age and virus type/subtype may help further efforts to promote increased vaccination coverage and other influenza-related preventative measures.
Collapse
Affiliation(s)
- Nicole Hood
- Influenza Division, US Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Brendan Flannery
- Influenza Division, US Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Manjusha Gaglani
- Texas A&M University Health Science Center College of Medicine, Temple, Texas
- Baylor Scott & White Health Research Institute, Temple, Texas
| | - Madhava Beeram
- Texas A&M University Health Science Center College of Medicine, Temple, Texas
- Baylor Scott & White Health Research Institute, Temple, Texas
| | - Karen Wernli
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington
| | - Michael L. Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington
| | - Emily T. Martin
- School of Public Health, University of Michigan, Ann Arbor, Michigan
| | - Arnold S. Monto
- School of Public Health, University of Michigan, Ann Arbor, Michigan
| | - Richard Zimmerman
- School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Jonathan Raviotta
- School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | | | | | - Sara Kim
- Influenza Division, US Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Manish M. Patel
- Influenza Division, US Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Jessie R. Chung
- Influenza Division, US Centers for Disease Control and Prevention, Atlanta, Georgia
| |
Collapse
|
6
|
Shafer L, Ahmed F, Kim S, Wernli KJ, Jackson ML, Nowalk MP, Bear T, Zimmerman RK, Martin ET, Monto AS, Gaglani M, Reis M, Chung JR, Flannery B, Uzicanin A. Relationship between Telework Experience and Presenteeism during COVID-19 Pandemic, United States, March-November 2020. Emerg Infect Dis 2023; 29:278-285. [PMID: 36599411 PMCID: PMC9881775 DOI: 10.3201/eid2902.221014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023] Open
Abstract
Persons with COVID-19-like illnesses are advised to stay home to reduce the spread of SARS-CoV-2. We assessed relationships between telework experience and COVID-19 illness with work attendance when ill. Adults experiencing fever, cough, or loss of taste or smell who sought healthcare or COVID-19 testing in the United States during March-November 2020 were enrolled. Adults with telework experience before illness were more likely to work at all (onsite or remotely) during illness (87.8%) than those with no telework experience (49.9%) (adjusted odds ratio 5.48, 95% CI 3.40-8.83). COVID-19 case-patients were less likely to work onsite (22.1%) than were persons with other acute respiratory illnesses (37.3%) (adjusted odds ratio 0.36, 95% CI 0.24-0.53). Among COVID-19 case-patients with telework experience, only 6.5% worked onsite during illness. Telework experience before illness gave mildly ill workers the option to work and improved compliance with public health recommendations to stay home during illness.
Collapse
|
7
|
Daley MF, Reifler LM, Glanz JM, Hambidge SJ, Getahun D, Irving SA, Nordin JD, McClure DL, Klein NP, Jackson ML, Kamidani S, Duffy J, DeStefano F. Association Between Aluminum Exposure From Vaccines Before Age 24 Months and Persistent Asthma at Age 24 to 59 Months. Acad Pediatr 2023; 23:37-46. [PMID: 36180331 PMCID: PMC10109516 DOI: 10.1016/j.acap.2022.08.006] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Revised: 07/20/2022] [Accepted: 08/13/2022] [Indexed: 01/19/2023]
Abstract
OBJECTIVE To assess the association between cumulative aluminum exposure from vaccines before age 24 months and persistent asthma at age 24 to 59 months. METHODS A retrospective cohort study was conducted in the Vaccine Safety Datalink (VSD). Vaccination histories were used to calculate cumulative vaccine-associated aluminum in milligrams (mg). The persistent asthma definition required one inpatient or 2 outpatient asthma encounters, and ≥2 long-term asthma control medication dispenses. Cox proportional hazard models were used to evaluate the association between aluminum exposure and asthma incidence, stratified by eczema presence/absence. Adjusted hazard ratios (aHR) and 95% confidence intervals (CI) per 1 mg increase in aluminum exposure were calculated, adjusted for birth month/year, sex, race/ethnicity, VSD site, prematurity, medical complexity, food allergy, severe bronchiolitis, and health care utilization. RESULTS The cohort comprised 326,991 children, among whom 14,337 (4.4%) had eczema. For children with and without eczema, the mean (standard deviation [SD]) vaccine-associated aluminum exposure was 4.07 mg (SD 0.60) and 3.98 mg (SD 0.72), respectively. Among children with and without eczema, 6.0% and 2.1%, respectively, developed persistent asthma. Among children with eczema, vaccine-associated aluminum was positively associated with persistent asthma (aHR 1.26 per 1 mg increase in aluminum, 95% CI 1.07, 1.49); a positive association was also detected among children without eczema (aHR 1.19, 95% CI 1.14, 1.25). CONCLUSION In a large observational study, a positive association was found between vaccine-related aluminum exposure and persistent asthma. While recognizing the small effect sizes identified and the potential for residual confounding, additional investigation of this hypothesis appears warranted.
Collapse
Affiliation(s)
- Matthew F Daley
- Institute for Health Research, Kaiser Permanente Colorado (MF Daley, LM Reifler, and JM Glanz), Aurora, Colo; Department of Pediatrics, University of Colorado School of Medicine (MF Daley and SJ Hambidge), Aurora, Colo.
| | - Liza M Reifler
- Institute for Health Research, Kaiser Permanente Colorado (MF Daley, LM Reifler, and JM Glanz), Aurora, Colo
| | - Jason M Glanz
- Institute for Health Research, Kaiser Permanente Colorado (MF Daley, LM Reifler, and JM Glanz), Aurora, Colo; Colorado School of Public Health (JM Glanz), Aurora, Colo
| | - Simon J Hambidge
- Department of Pediatrics, University of Colorado School of Medicine (MF Daley and SJ Hambidge), Aurora, Colo; Community Health Services, Denver Health (SJ Hambidge), Denver, Colo
| | - Darios Getahun
- Department of Research and Evaluation, Kaiser Permanente Southern California (D Getahun), Pasadena, Calif; Department of Health Systems Science, Kaiser Permanente Bernard J. Tyson School of Medicine (D Getahun), Pasadena, Calif
| | - Stephanie A Irving
- Center for Health Research, Kaiser Permanente Northwest (SA Irving), Portland, Ore
| | | | - David L McClure
- Marshfield Clinic Research Institute (DL McClure), Marshfield, Wis
| | - Nicola P Klein
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California (NP Klein), Oakland, Calif
| | - Michael L Jackson
- Kaiser Permanente Washington Health Research Institute (ML Jackson), Seattle, Wash
| | - Satoshi Kamidani
- Center for Childhood Infections and Vaccines of Children's Healthcare of Atlanta and Department of Pediatrics, Emory University School of Medicine (S Kamidani), Atlanta, Ga; Immunization Safety Office, Centers for Disease Control and Prevention (S Kamidani, J Duffy, and F DeStefano), Atlanta, Ga
| | - Jonathan Duffy
- Immunization Safety Office, Centers for Disease Control and Prevention (S Kamidani, J Duffy, and F DeStefano), Atlanta, Ga
| | - Frank DeStefano
- Immunization Safety Office, Centers for Disease Control and Prevention (S Kamidani, J Duffy, and F DeStefano), Atlanta, Ga
| |
Collapse
|
8
|
Mukherjee S, Kshirsagar M, Becker N, Xu Y, Weeks WB, Patel S, Ferres JL, Jackson ML. Identifying long-term effects of SARS-CoV-2 and their association with social determinants of health in a cohort of over one million COVID-19 survivors. BMC Public Health 2022; 22:2394. [PMID: 36539760 PMCID: PMC9765366 DOI: 10.1186/s12889-022-14806-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Accepted: 12/05/2022] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Despite an abundance of information on the risk factors of SARS-CoV-2, there have been few US-wide studies of long-term effects. In this paper we analyzed a large medical claims database of US based individuals to identify common long-term effects as well as their associations with various social and medical risk factors. METHODS The medical claims database was obtained from a prominent US based claims data processing company, namely Change Healthcare. In addition to the claims data, the dataset also consisted of various social determinants of health such as race, income, education level and veteran status of the individuals. A self-controlled cohort design (SCCD) observational study was performed to identify ICD-10 codes whose proportion was significantly increased in the outcome period compared to the control period to identify significant long-term effects. A logistic regression-based association analysis was then performed between identified long-term effects and social determinants of health. RESULTS Among the over 1.37 million COVID patients in our datasets we found 36 out of 1724 3-digit ICD-10 codes to be statistically significantly increased in the post-COVID period (p-value < 0.05). We also found one combination of ICD-10 codes, corresponding to 'other anemias' and 'hypertension', that was statistically significantly increased in the post-COVID period (p-value < 0.05). Our logistic regression-based association analysis with social determinants of health variables, after adjusting for comorbidities and prior conditions, showed that age and gender were significantly associated with the multiple long-term effects. Race was only associated with 'other sepsis', income was only associated with 'Alopecia areata' (autoimmune disease causing hair loss), while education level was only associated with 'Maternal infectious and parasitic diseases' (p-value < 0.05). CONCLUSION We identified several long-term effects of SARS-CoV-2 through a self-controlled study on a cohort of over one million patients. Furthermore, we found that while age and gender are commonly associated with the long-term effects, other social determinants of health such as race, income and education levels have rare or no significant associations.
Collapse
Affiliation(s)
- Sumit Mukherjee
- Insitro Labs, work done while at Microsoft, South San Francisco, USA
| | - Meghana Kshirsagar
- grid.419815.00000 0001 2181 3404AI for Good Research Lab, Microsoft Corporation, 1 Microsoft Way, WA 98052 Redmond, USA
| | - Nicholas Becker
- grid.419815.00000 0001 2181 3404AI for Good Research Lab, Microsoft Corporation, 1 Microsoft Way, WA 98052 Redmond, USA ,grid.34477.330000000122986657University of Washington, Seattle, USA
| | - Yixi Xu
- grid.419815.00000 0001 2181 3404AI for Good Research Lab, Microsoft Corporation, 1 Microsoft Way, WA 98052 Redmond, USA
| | - William B. Weeks
- grid.419815.00000 0001 2181 3404AI for Good Research Lab, Microsoft Corporation, 1 Microsoft Way, WA 98052 Redmond, USA
| | - Shwetak Patel
- grid.34477.330000000122986657University of Washington, Seattle, USA
| | - Juan Lavista Ferres
- grid.419815.00000 0001 2181 3404AI for Good Research Lab, Microsoft Corporation, 1 Microsoft Way, WA 98052 Redmond, USA
| | - Michael L. Jackson
- grid.488833.c0000 0004 0615 7519Kaiser Permanente Washington, Seattle, USA
| |
Collapse
|
9
|
Nelson JC, Ulloa-Pérez E, Yu O, Cook AJ, Jackson ML, Belongia EA, Daley MF, Harpaz R, Kharbanda EO, Klein NP, Naleway AL, Tseng HF, Weintraub ES, Duffy J, Yih WK, Jackson LA. Active Postlicensure Safety Surveillance for Recombinant Zoster Vaccine Using Electronic Health Record Data. Am J Epidemiol 2022; 192:205-216. [PMID: 36193854 PMCID: PMC9896469 DOI: 10.1093/aje/kwac170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Revised: 07/28/2022] [Accepted: 09/30/2022] [Indexed: 02/06/2023] Open
Abstract
Recombinant zoster vaccine (RZV) (Shingrix; GlaxoSmithKline, Brentford, United Kingdom) is an adjuvanted glycoprotein vaccine that was licensed in 2017 to prevent herpes zoster (shingles) and its complications in older adults. In this prospective, postlicensure Vaccine Safety Datalink study using electronic health records, we sequentially monitored a real-world population of adults aged ≥50 years who received care in multiple US Vaccine Safety Datalink health systems to identify potentially increased risks of 10 prespecified health outcomes, including stroke, anaphylaxis, and Guillain-Barré syndrome (GBS). Among 647,833 RZV doses administered from January 2018 through December 2019, we did not detect a sustained increased risk of any monitored outcome for RZV recipients relative to either historical (2013-2017) recipients of zoster vaccine live, a live attenuated virus vaccine (Zostavax; Merck & Co., Inc., Kenilworth, New Jersey), or contemporary non-RZV vaccine recipients who had an annual well-person visit during the 2018-2019 study period. We confirmed prelicensure trial findings of increased risks of systemic and local reactions following RZV. Our study provides additional reassurance about the overall safety of RZV. Despite a large sample, uncertainty remains regarding potential associations with GBS due to the limited number of confirmed GBS cases that were observed.
Collapse
Affiliation(s)
- Jennifer C Nelson
- Correspondence to Dr. Jennifer C. Nelson, Biostatistics Division, Kaiser Permanente Washington Health Research Institute, 1730 Minor Avenue, Suite 1600, Seattle, WA 98101 (e-mail: )
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
10
|
Chung JR, Kim SS, Belongia EA, McLean HQ, King JP, Nowalk MP, Zimmerman RK, Moehling Geffel K, Martin ET, Monto AS, Lamerato LE, Gaglani M, Hoffman E, Volz M, Jackson ML, Jackson LA, Patel MM, Flannery B. Vaccine effectiveness against COVID-19 among symptomatic persons aged ≥12 years with reported contact with COVID-19 cases, February-September 2021. Influenza Other Respir Viruses 2022; 16:673-679. [PMID: 35170231 PMCID: PMC9111783 DOI: 10.1111/irv.12973] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Accepted: 01/30/2022] [Indexed: 02/03/2023] Open
Abstract
BACKGROUND Individuals in contact with persons with COVID-19 are at high risk of developing COVID-19; protection offered by COVID-19 vaccines in the context of known exposure is poorly understood. METHODS Symptomatic outpatients aged ≥12 years reporting acute onset of COVID-19-like illness and tested for SARS-CoV-2 between February 1 and September 30, 2021 were enrolled. Participants were stratified by self-report of having known contact with a COVID-19 case in the 14 days prior to illness onset. Vaccine effectiveness was evaluated using the test-negative study design and multivariable logistic regression. RESULTS Among 2229 participants, 283/451 (63%) of those reporting contact and 331/1778 (19%) without known contact tested SARS-CoV-2-positive. Adjusted vaccine effectiveness was 71% (95% confidence interval [CI], 49%-83%) among fully vaccinated participants reporting a known contact versus 80% (95% CI, 72%-86%) among those with no known contact (p-value for interaction = 0.2). CONCLUSIONS This study contributes to growing evidence of the benefits of vaccinations in preventing COVID-19 and support vaccination recommendations and the importance of efforts to increase vaccination coverage.
Collapse
Affiliation(s)
| | - Sara S. Kim
- Centers for Disease Control and PreventionAtlantaGeorgiaUSA
| | | | | | | | - Mary Patricia Nowalk
- University of Pittsburgh Schools of the Health Sciences and University of Pittsburgh Medical CenterPittsburghPennsylvaniaUSA
| | - Richard K. Zimmerman
- University of Pittsburgh Schools of the Health Sciences and University of Pittsburgh Medical CenterPittsburghPennsylvaniaUSA
| | - Krissy Moehling Geffel
- University of Pittsburgh Schools of the Health Sciences and University of Pittsburgh Medical CenterPittsburghPennsylvaniaUSA
| | - Emily T. Martin
- School of Public HealthUniversity of MichiganAnn ArborMichiganUSA
| | - Arnold S. Monto
- School of Public HealthUniversity of MichiganAnn ArborMichiganUSA
| | | | - Manjusha Gaglani
- Baylor Scott and White HealthDallasTXUSA
- Texas A&M University College of MedicineTempleTexasUSA
| | | | | | - Michael L. Jackson
- Kaiser Permanente Washington Health Research InstituteSeattleWashingtonUSA
| | - Lisa A. Jackson
- Kaiser Permanente Washington Health Research InstituteSeattleWashingtonUSA
| | | | | |
Collapse
|
11
|
Chung JR, Kim SS, Flannery B, Smith ME, Dunnigan K, Raiyani C, Murthy K, Gaglani M, Jackson ML, Jackson LA, Bear T, Moehling Geffel K, Nowalk MP, Zimmerman RK, Martin ET, Lamerato L, McLean HQ, King JP, Belongia EA, Thompson MG, Patel M. Vaccine-associated attenuation of subjective severity among outpatients with influenza. Vaccine 2022; 40:4322-4327. [PMID: 35710506 PMCID: PMC9638984 DOI: 10.1016/j.vaccine.2022.06.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 05/24/2022] [Accepted: 06/05/2022] [Indexed: 11/18/2022]
Abstract
Influenza vaccines can mitigate illness severity, including reduced risk of ICU admission and death, in people with breakthrough infection. Less is known about vaccine attenuation of mild/moderate influenza illness. We compared subjective severity scores in vaccinated and unvaccinated persons with medically attended illness and laboratory-confirmed influenza. Participants were prospectively recruited when presenting for care at five US sites over nine seasons. Participants aged ≥ 16 years completed the EQ-5D-5L visual analog scale (VAS) at enrollment. After controlling for potential confounders in a multivariable model, including age and general health status, VAS scores were significantly higher among 2,830 vaccinated participants compared with 3,459 unvaccinated participants, indicating vaccinated participants felt better at the time of presentation for care. No differences in VAS scores were observed by the type of vaccine received among persons aged ≥ 65 years. Our findings suggest vaccine-associated attenuation of milder influenza illness is possible.
Collapse
Affiliation(s)
- Jessie R Chung
- U.S. Centers for Disease Control and Prevention, Influenza Division, Atlanta, GA, United States.
| | - Sara S Kim
- U.S. Centers for Disease Control and Prevention, Influenza Division, Atlanta, GA, United States
| | - Brendan Flannery
- U.S. Centers for Disease Control and Prevention, Influenza Division, Atlanta, GA, United States
| | | | | | | | | | - Manjusha Gaglani
- Baylor Scott & White Health, Temple, TX, United States; Texas A&M University College of Medicine, Temple, TX, United States
| | - Michael L Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, United States
| | - Lisa A Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, United States
| | - Todd Bear
- University of Pittsburgh, United States
| | | | | | | | - Emily T Martin
- University of Michigan School of Public Health, Ann Arbor, MI, United States
| | - Lois Lamerato
- Henry Ford Health System, Detroit, MI, United States
| | - Huong Q McLean
- Marshfield Clinic Research Institute, Marshfield, WI, United States
| | - Jennifer P King
- Marshfield Clinic Research Institute, Marshfield, WI, United States
| | | | - Mark G Thompson
- U.S. Centers for Disease Control and Prevention, Influenza Division, Atlanta, GA, United States
| | - Manish Patel
- U.S. Centers for Disease Control and Prevention, Influenza Division, Atlanta, GA, United States
| |
Collapse
|
12
|
Jordan MR, Hensley LA, Jackson ML. Weakness After an Intra-articular Steroid Injection: A Case Report of Acute Steroid-induced Myopathy. Clin Pract Cases Emerg Med 2022; 6:166-168. [PMID: 35701348 PMCID: PMC9197743 DOI: 10.5811/cpcem.2022.2.55995] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2022] [Accepted: 02/21/2022] [Indexed: 11/06/2022] Open
Abstract
INTRODUCTION Weakness is a common chief complaint in the emergency department, and the use of glucocorticoids is pervasive in medicine. Muscle weakness, or myopathy, is a well documented side effect of chronic glucocorticoid use. However, acute myopathy, with an onset shortly after initiation of glucocorticoids, is much rarer. CASE REPORT We present a case of acute steroid-induced myopathy after a single intra-articular dose of triamcinolone in a young, healthy, active male. To our knowledge, this is the first case described in the medical literature of acute steroid-induced myopathy following a single intra-articular injection. CONCLUSION In a patient who presents with proximal muscle weakness and has a history of glucocorticoid use, the diagnosis of steroid-induced myopathy should be considered. Acute steroid-induced myopathy should be high on the differential in a patient who presents with typical symptoms and has been prescribed glucocorticoids for less than 14 days or, in rare cases, may have recently received a single dose of glucocorticoids. Treatment is supportive and outpatient management is typically indicated, as respiratory muscle involvement is rare.
Collapse
Affiliation(s)
- Matthew R. Jordan
- Navy Medicine Readiness and Training Command, Department of Emergency Medicine, Camp Lejeune, North Carolina
| | - Lauren A. Hensley
- Navy Medicine Readiness and Training Command, Department of Internal Medicine, Portsmouth, Virginia
| | - Michael L. Jackson
- Navy Medicine Readiness and Training Command, Department of Emergency Medicine, Portsmouth, Virginia
| |
Collapse
|
13
|
Griggs EP, Flannery B, Foppa IM, Gaglani M, Murthy K, Jackson ML, Jackson LA, Belongia EA, McLean HQ, Martin ET, Monto AS, Zimmerman RK, Balasubramani GK, Chung JR, Patel M. Role of Age in the Spread of Influenza, 2011-2019: Data From the US Influenza Vaccine Effectiveness Network. Am J Epidemiol 2022; 191:465-471. [PMID: 34274963 DOI: 10.1093/aje/kwab205] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Revised: 07/09/2021] [Accepted: 07/12/2021] [Indexed: 01/29/2023] Open
Abstract
Intraseason timing of influenza infection among persons of different ages could reflect relative contributions to propagation of seasonal epidemics and has not been examined among ambulatory patients. Using data from the US Influenza Vaccine Effectiveness Network, we calculated risk ratios derived from comparing weekly numbers of influenza cases prepeak with those postpeak during the 2010-2011 through 2018-2019 influenza seasons. We sought to determine age-specific differences during the ascent versus descent of an influenza season by influenza virus type and subtype. We estimated 95% credible intervals around the risk ratios using Bayesian joint posterior sampling of weekly cases. Our population consisted of ambulatory patients with laboratory-confirmed influenza who enrolled in an influenza vaccine effectiveness study at 5 US sites during 9 influenza seasons after the 2009 influenza A virus subtype H1N1 (H1N1) pandemic. We observed that young children aged <5 years tended to more often be infected with H1N1 during the prepeak period, while adults aged ≥65 years tended to more often be infected with H1N1 during the postpeak period. However, for influenza A virus subtype H3N2, children aged <5 years were more often infected during the postpeak period. These results may reflect a contribution of different age groups to seasonal spread, which may differ by influenza virus type and subtype.
Collapse
|
14
|
Burstein R, Althouse BM, Adler A, Akullian A, Brandstetter E, Cho S, Emanuels A, Fay K, Gamboa L, Han P, Huden K, Ilcisin M, Izzo M, Jackson ML, Kim AE, Kimball L, Lacombe K, Lee J, Logue JK, Rogers J, Chung E, Sibley TR, Van Raay K, Wenger E, Wolf CR, Boeckh M, Chu H, Duchin J, Rieder M, Shendure J, Starita LM, Viboud C, Bedford T, Englund JA, Famulare M. Interactions among 17 respiratory pathogens: a cross-sectional study using clinical and community surveillance data. medRxiv 2022:2022.02.04.22270474. [PMID: 35169816 PMCID: PMC8845514 DOI: 10.1101/2022.02.04.22270474] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
Background Co-circulating respiratory pathogens can interfere with or promote each other, leading to important effects on disease epidemiology. Estimating the magnitude of pathogen-pathogen interactions from clinical specimens is challenging because sampling from symptomatic individuals can create biased estimates. Methods We conducted an observational, cross-sectional study using samples collected by the Seattle Flu Study between 11 November 2018 and 20 August 2021. Samples that tested positive via RT-qPCR for at least one of 17 potential respiratory pathogens were included in this study. Semi-quantitative cycle threshold (Ct) values were used to measure pathogen load. Differences in pathogen load between monoinfected and coinfected samples were assessed using linear regression adjusting for age, season, and recruitment channel. Results 21,686 samples were positive for at least one potential pathogen. Most prevalent were rhinovirus (33·5%), Streptococcus pneumoniae (SPn, 29·0%), SARS-CoV-2 (13.8%) and influenza A/H1N1 (9·6%). 140 potential pathogen pairs were included for analysis, and 56 (40%) pairs yielded significant Ct differences (p < 0.01) between monoinfected and co-infected samples. We observed no virus-virus pairs showing evidence of significant facilitating interactions, and found significant viral load decrease among 37 of 108 (34%) assessed pairs. Samples positive with SPn and a virus were consistently associated with increased SPn load. Conclusions Viral load data can be used to overcome sampling bias in studies of pathogen-pathogen interactions. When applied to respiratory pathogens, we found evidence of viral-SPn facilitation and several examples of viral-viral interference. Multipathogen surveillance is a cost-efficient data collection approach, with added clinical and epidemiological informational value over single-pathogen testing, but requires careful analysis to mitigate selection bias.
Collapse
Affiliation(s)
- Roy Burstein
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle WA USA
| | - Benjamin M. Althouse
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle WA USA
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle WA USA
- Department of Biology, New Mexico State University, Las Cruces, NM
| | - Amanda Adler
- Seattle Children’s Research Institute, Seattle WA USA
| | - Adam Akullian
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle WA USA
| | | | - Shari Cho
- Brotman Baty Institute for Precision Medicine, Seattle WA USA
| | - Anne Emanuels
- Department of Medicine, University of Washington, Seattle WA USA
| | - Kairsten Fay
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle WA USA
| | - Luis Gamboa
- Brotman Baty Institute for Precision Medicine, Seattle WA USA
| | - Peter Han
- Brotman Baty Institute for Precision Medicine, Seattle WA USA
| | - Kristen Huden
- Department of Medicine, University of Washington, Seattle WA USA
| | - Misja Ilcisin
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle WA USA
| | - Mandy Izzo
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle WA USA
| | | | - Ashley E. Kim
- Department of Medicine, University of Washington, Seattle WA USA
| | - Louise Kimball
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle WA USA
| | | | - Jover Lee
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle WA USA
| | | | - Julia Rogers
- Department of Medicine, University of Washington, Seattle WA USA
| | - Erin Chung
- Department of Pediatrics, University of Washington, Seattle Children’s Hospital, Seattle
| | - Thomas R. Sibley
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle WA USA
| | | | - Edward Wenger
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle WA USA
| | - Caitlin R. Wolf
- Department of Medicine, University of Washington, Seattle WA USA
| | - Michael Boeckh
- Department of Medicine, University of Washington, Seattle WA USA
- Brotman Baty Institute for Precision Medicine, Seattle WA USA
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle WA USA
| | - Helen Chu
- Department of Medicine, University of Washington, Seattle WA USA
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle WA USA
| | - Jeff Duchin
- Department of Medicine, University of Washington, Seattle WA USA
- Public Health Seattle & King County, Seattle WA USA
| | - Mark Rieder
- Brotman Baty Institute for Precision Medicine, Seattle WA USA
| | - Jay Shendure
- Brotman Baty Institute for Precision Medicine, Seattle WA USA
- Department of Genome Sciences, University of Washington, Seattle WA USA
- Howard Hughes Medical Institute, Seattle WA USA
| | - Lea M. Starita
- Brotman Baty Institute for Precision Medicine, Seattle WA USA
- Department of Genome Sciences, University of Washington, Seattle WA USA
| | - Cecile Viboud
- Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, MD, USA
| | - Trevor Bedford
- Brotman Baty Institute for Precision Medicine, Seattle WA USA
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle WA USA
- Howard Hughes Medical Institute, Seattle WA USA
| | - Janet A. Englund
- Seattle Children’s Research Institute, Seattle WA USA
- Brotman Baty Institute for Precision Medicine, Seattle WA USA
| | - Michael Famulare
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle WA USA
| |
Collapse
|
15
|
Groom HC, Crane B, Naleway AL, Weintraub E, Daley MF, Wain K, Beth Kurilo M, Burganowski R, DeSilva MB, Donahue JG, Glenn SC, Goddard K, Jackson ML, Kharbanda EO, Lewis N, Lou Y, Lugg M, Scotty E, Sy LS, Williams JT, Irving SA. Monitoring vaccine safety using the vaccine safety Datalink: Assessing capacity to integrate data from Immunization Information systems. Vaccine 2022; 40:752-756. [PMID: 34980508 PMCID: PMC8719644 DOI: 10.1016/j.vaccine.2021.12.048] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Revised: 12/08/2021] [Accepted: 12/20/2021] [Indexed: 01/25/2023]
Abstract
BACKGROUND The Vaccine Safety Datalink (VSD) uses vaccination data from electronic health records (EHR) at eight integrated health systems to monitor vaccine safety. Accurate capture of data from vaccines administered outside of the health system is critical for vaccine safety research, especially for COVID-19 vaccines, where many are administered in non-traditional settings. However, timely access and inclusion of data from Immunization Information Systems (IIS) into VSD safety assessments is not well understood. METHODS We surveyed the eight data-contributing VSD sites to assess: 1) status of sending data to IIS; 2) status of receiving data from IIS; and 3) integration of IIS data into the site EHR. Sites reported separately for COVID-19 vaccination to capture any differences in capacity to receive and integrate data on COVID-19 vaccines versus other vaccines. RESULTS All VSD sites send data to and receive data from their state IIS. All eight sites (100%) routinely integrate IIS data for COVID-19 vaccines into VSD research studies. Six sites (75%) also routinely integrate all other vaccination data; two sites integrate data from IIS following a reconciliation process, which can result in delays to integration into VSD datasets. CONCLUSIONS COVID-19 vaccines are being administered in a variety of non-traditional settings, where IIS are commonly used as centralized reporting systems. All eight VSD sites receive and integrate COVID-19 vaccine data from IIS, which positions the VSD well for conducting quality assessments of vaccine safety. Efforts to improve the timely receipt of all vaccination data will improve capacity to conduct vaccine safety assessments within the VSD.
Collapse
Affiliation(s)
- Holly C. Groom
- Kaiser Permanente Center for Health Research, Portland, OR,Corresponding author
| | - Bradley Crane
- Kaiser Permanente Center for Health Research, Portland, OR
| | | | - Eric Weintraub
- Immunization Safety Office, Centers for Disease Control and Prevention, Atlanta, GA
| | - Matthew F. Daley
- Institute for Health Research, Kaiser Permanente Colorado, Denver, CO
| | - Kris Wain
- Institute for Health Research, Kaiser Permanente Colorado, Denver, CO
| | | | | | | | - James G. Donahue
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California, Oakland, CA
| | | | - Kristin Goddard
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California, Oakland, CA
| | | | | | - Ned Lewis
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California, Oakland, CA
| | - Yingbo Lou
- Ambulatory Care Services, Denver Health, Denver, CO
| | - Marlene Lugg
- Kaiser Permanente Southern California, Pasadena, CA
| | - Erica Scotty
- Marshfield Clinic Research Institute, Marshfield, WI
| | - Lina S. Sy
- Kaiser Permanente Southern California, Pasadena, CA
| | | | | |
Collapse
|
16
|
Casto AM, Rogers JH, Link AC, Boeckh M, Jackson ML, Uyeki TM, Englund JA, Starita LM, Chu HY. Phylogenomics of SARS-CoV-2 in Emergency Shelters for People Experiencing Homelessness. J Infect Dis 2022; 226:217-224. [PMID: 35091746 PMCID: PMC8807325 DOI: 10.1093/infdis/jiac021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Accepted: 01/25/2022] [Indexed: 11/12/2022] Open
Abstract
Abstract
Residents and staff of emergency shelters for people experiencing homelessness (PEH) are at high risk of infection with SARS-CoV-2. The importance of shelter-related transmission of SARS-CoV-2 in this population remains unclear. It is also unknown whether there is significant spread of shelter-related viruses into surrounding communities. We analyzed genome sequence data for 28 SARS-CoV-2-positive specimens collected from 8 shelters in King County, Washington between March and October, 2020. We identified at least 12 separate SARS-CoV-2 introduction events into these 8 shelters and estimated that 57% (16 out of 28) of the examined cases of SARS-CoV-2 infection were the result of intra-shelter transmission. However, we identified just a few SARS-CoV-2 specimens from Washington that were possible descendants of shelter viruses. Our data suggest that SARS-CoV-2 spread in shelters is common, but we did not observe evidence of wide-spread transmission of shelter-related viruses into the general population.
Collapse
Affiliation(s)
- Amanda M Casto
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, WA, USA
- Vaccine and Infectious Diseases Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Julia H Rogers
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Amy C Link
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Michael Boeckh
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, WA, USA
- Vaccine and Infectious Diseases Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Brotman Baty Institute for Precision Medicine, Seattle, WA, USA
| | - Michael L Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Timothy M Uyeki
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Janet A Englund
- Brotman Baty Institute for Precision Medicine, Seattle, WA, USA
- Seattle Children’s Research Institute, Seattle, WA, USA
| | - Lea M Starita
- Brotman Baty Institute for Precision Medicine, Seattle, WA, USA
| | - Helen Y Chu
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, WA, USA
| |
Collapse
|
17
|
Rogers JH, Cox SN, Hughes JP, Link AC, Chow EJ, Fosse I, Lukoff M, Shim MM, Uyeki TM, Ogokeh C, Jackson ML, Boeckh M, Englund JA, Mosites E, Rolfes MA, Chu HY. Trends in COVID-19 vaccination intent and factors associated with deliberation and reluctance among adult homeless shelter residents and staff, 1 November 2020 to 28 February 2021 - King County, Washington. Vaccine 2022; 40:122-132. [PMID: 34863618 PMCID: PMC8590934 DOI: 10.1016/j.vaccine.2021.11.026] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Revised: 10/17/2021] [Accepted: 11/08/2021] [Indexed: 12/01/2022]
Abstract
Introduction Little is known about COVID-19 vaccination intent among people experiencing homelessness. This study assesses surveyed COVID-19 vaccination intent among adult homeless shelter residents and staff and identifies factors associated with vaccine deliberation (responded “undecided”) and reluctance (responded “no”), including time trends. Methods From 11/1/2020–2/28/21, we conducted repeated cross-sectional surveys at nine shelters in King County, WA as part of ongoing community-based SARS-CoV-2 surveillance. We used a multinomial model to identify characteristics associated with vaccine deliberation and reluctance. Results A total of 969 unique staff (n = 297) and residents (n = 672) participated and provided 3966 survey responses. Among residents, 53.7% (n = 361) were vaccine accepting, 28.1% reluctant, 17.6% deliberative, and 0.6% already vaccinated, whereas among staff 56.2% were vaccine accepting, 14.1% were reluctant, 16.5% were deliberative, and 13.1% already vaccinated at their last survey. We observed higher odds of vaccine deliberation or reluctance among Black/African American individuals, those who did not receive a seasonal influenza vaccine, and those with lower educational attainment. There was no significant trend towards vaccine acceptance. Conclusions Strong disparities in vaccine intent based on race, education, and prior vaccine history were observed. Increased vaccine intent over the study period was not detected. An intersectional, person-centered approach to addressing health inequities by public health authorities planning vaccination campaigns in shelters is recommended. Clinical Trial Registry Number: NCT04141917.
Collapse
Affiliation(s)
- Julia H Rogers
- Department of Medicine, Division of Allergy & Infectious Diseases, University of Washington, Seattle, WA, USA; Department of Epidemiology, University of Washington, Seattle, WA, USA.
| | - Sarah N Cox
- Department of Medicine, Division of Allergy & Infectious Diseases, University of Washington, Seattle, WA, USA; Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - James P Hughes
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Amy C Link
- Department of Medicine, Division of Allergy & Infectious Diseases, University of Washington, Seattle, WA, USA
| | - Eric J Chow
- Department of Medicine, Division of Allergy & Infectious Diseases, University of Washington, Seattle, WA, USA
| | | | | | - M Mia Shim
- Public Health - Seattle & King County, WA, USA; Department of Medicine, Division of General Internal Medicine, University of Washington, Seattle, WA, USA
| | - Timothy M Uyeki
- Centers for Disease Control and Prevention, Atlanta, GA, USA
| | | | - Michael L Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | | | - Janet A Englund
- Seattle Children's Research Institute, University of Washington, Seattle, WA, USA
| | - Emily Mosites
- Centers for Disease Control and Prevention, Atlanta, GA, USA
| | | | - Helen Y Chu
- Department of Medicine, Division of Allergy & Infectious Diseases, University of Washington, Seattle, WA, USA
| |
Collapse
|
18
|
DeSilva MB, Haapala J, Vazquez-Benitez G, Daley MF, Nordin JD, Klein NP, Henninger ML, Williams JTB, Hambidge SJ, Jackson ML, Donahue JG, Qian L, Lindley MC, Gee J, Weintraub ES, Kharbanda EO. Association of the COVID-19 Pandemic With Routine Childhood Vaccination Rates and Proportion Up to Date With Vaccinations Across 8 US Health Systems in the Vaccine Safety Datalink. JAMA Pediatr 2022; 176:68-77. [PMID: 34617975 PMCID: PMC8498937 DOI: 10.1001/jamapediatrics.2021.4251] [Citation(s) in RCA: 59] [Impact Index Per Article: 29.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
IMPORTANCE The COVID-19 pandemic has affected routine vaccine delivery in the US and globally. The magnitude of these disruptions and their association with childhood vaccination coverage are unclear. OBJECTIVES To compare trends in pediatric vaccination before and during the pandemic and to evaluate the proportion of children up to date (UTD) with vaccinations by age, race, and ethnicity. DESIGN, SETTING, AND PARTICIPANTS This surveillance study used a prepandemic-postpandemic control design with data from 8 health systems in California, Oregon, Washington, Colorado, Minnesota, and Wisconsin in the Vaccine Safety Datalink. Children from age groups younger than 24 months and 4 to 6, 11 to 13, and 16 to 18 years were included if they had at least 1 week of health system enrollment from January 5, 2020, through October 3, 2020, over periods before the US COVID-19 pandemic (January 5, 2020, through March 14, 2020), during age-limited preventive care (March 15, 2020, through May 16, 2020), and during expanded primary care (May 17, 2020, through October 3, 2020). These individuals were compared with those enrolled during analogous weeks in 2019. EXPOSURES This study evaluated UTD status among children reaching specific ages in February, May, and September 2020, compared with those reaching these ages in 2019. MAIN OUTCOMES AND MEASURES Weekly vaccination rates for routine age-specific vaccines and the proportion of children UTD for all age-specific recommended vaccines. RESULTS Of 1 399 708 children in 2019 and 1 402 227 in 2020, 1 371 718 were female (49.0%) and 1 429 979 were male (51.0%); 334 216 Asian individuals (11.9%), 900 226 were Hispanic individuals (32.1%), and 201 619 non-Hispanic Black individuals (7.2%). Compared with the prepandemic period and 2019, the age-limited preventive care period was associated with lower weekly vaccination rates, with ratios of rate ratios of 0.82 (95% CI, 0.80-0.85) among those younger than 24 months, 0.18 (95% CI, 0.16-0.20) among those aged 4 to 6 years, 0.16 (95% CI, 0.14-0.17) among those aged 11 to 13 years, and 0.10 (95% CI, 0.08-0.13) among those aged 16 to 18 years. Vaccination rates during expanded primary care remained lower for most ages (ratios of rate ratios: <24 months, 0.96 [95% CI, 0.93-0.98]; 11-13 years, 0.81 [95% CI, 0.76-0.86]; 16-18 years, 0.57 [95% CI, 0.51-0.63]). In September 2020, 74% (95% CI, 73%-76%) of infants aged 7 months and 57% (95% CI, 56%-58%) of infants aged 18 months were UTD vs 81% (95% CI, 80%-82%) and 61% (95% CI, 60%-62%), respectively, in September 2019. The proportion UTD was lowest in non-Hispanic Black children across most age groups, both during and prior to the COVID-19 pandemic (eg, in May 2019, 70% [95% CI, 64%-75%] of non-Hispanic Black infants aged 7 months were UTD vs 82% [95% CI, 81%-83%] in all infants aged 7 months combined). CONCLUSIONS AND RELEVANCE As of September 2020, childhood vaccination rates and the proportion who were UTD remained lower than 2019 levels. Interventions are needed to promote catch-up vaccination, particularly in populations at risk for underimmunization.
Collapse
Affiliation(s)
| | | | | | - Matthew F. Daley
- Institute for Health Research, Kaiser Permanente Colorado, Denver, Colorado
| | | | | | | | | | | | | | | | - Lei Qian
- Kaiser Permanente Southern California, Pasadena
| | - Megan C. Lindley
- Immunization Services Division, National Center for Immunization and Respiratory Diseases, US Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Julianne Gee
- Immunization Safety Office, US Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Eric S. Weintraub
- Immunization Safety Office, US Centers for Disease Control and Prevention, Atlanta, Georgia
| | | |
Collapse
|
19
|
Emanuels A, Heimonen J, O’Hanlon J, Kim AE, Wilcox N, McCulloch DJ, Brandstetter E, Wolf CR, Logue JK, Han PD, Pfau B, Newman KL, Hughes JP, Jackson ML, Uyeki TM, Boeckh M, Starita LM, Nickerson DA, Bedford T, Englund JA, Chu HY. Remote Household Observation for Noninfluenza Respiratory Viral Illness. Clin Infect Dis 2021; 73:e4411-e4418. [PMID: 33197930 PMCID: PMC7717193 DOI: 10.1093/cid/ciaa1719] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2020] [Indexed: 01/03/2023] Open
Abstract
BACKGROUND Noninfluenza respiratory viruses are responsible for a substantial burden of disease in the United States. Household transmission is thought to contribute significantly to subsequent transmission through the broader community. In the context of the coronavirus disease 2019 (COVID-19) pandemic, contactless surveillance methods are of particular importance. METHODS From November 2019 to April 2020, 303 households in the Seattle area were remotely monitored in a prospective longitudinal study for symptoms of respiratory viral illness. Enrolled participants reported weekly symptoms and submitted respiratory samples by mail in the event of an acute respiratory illness (ARI). Specimens were tested for 14 viruses, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), using reverse-transcription polymerase chain reaction. Participants completed all study procedures at home without physical contact with research staff. RESULTS In total, 1171 unique participants in 303 households were monitored for ARI. Of participating households, 128 (42%) included a child aged <5 years and 202 (67%) included a child aged 5-12 years. Of the 678 swabs collected during the surveillance period, 237 (35%) tested positive for 1 or more noninfluenza respiratory viruses. Rhinovirus, common human coronaviruses, and respiratory syncytial virus were the most common. Four cases of SARS-CoV-2 were detected in 3 households. CONCLUSIONS This study highlights the circulation of respiratory viruses within households during the winter months during the emergence of the SARS-CoV-2 pandemic. Contactless methods of recruitment, enrollment, and sample collection were utilized throughout this study and demonstrate the feasibility of home-based, remote monitoring for respiratory infections.
Collapse
Affiliation(s)
- Anne Emanuels
- Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Jessica Heimonen
- Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Jessica O’Hanlon
- Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Ashley E Kim
- Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Naomi Wilcox
- Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Denise J McCulloch
- Department of Medicine, University of Washington, Seattle, Washington, USA
| | | | - Caitlin R Wolf
- Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Jennifer K Logue
- Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Peter D Han
- Brotman Baty Institute, Seattle, Washington, USA
| | - Brian Pfau
- Brotman Baty Institute, Seattle, Washington, USA
| | - Kira L Newman
- Department of Medicine, University of Washington, Seattle, Washington, USA
| | - James P Hughes
- Department of Biostatistics, University of Washington, Seattle, Washington, USA
| | - Michael L Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington, USA
| | - Timothy M Uyeki
- Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Michael Boeckh
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Lea M Starita
- Brotman Baty Institute, Seattle, Washington, USA
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
| | - Deborah A Nickerson
- Brotman Baty Institute, Seattle, Washington, USA
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
| | - Trevor Bedford
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Janet A Englund
- Department of Medicine, University of Washington, Seattle, Washington, USA
- Seattle Children’s Research Institute, Seattle, Washington, USA
| | - Helen Y Chu
- Department of Medicine, University of Washington, Seattle, Washington, USA
| |
Collapse
|
20
|
Tenforde MW, Kondor RJG, Chung JR, Zimmerman RK, Nowalk MP, Jackson ML, Jackson LA, Monto AS, Martin ET, Belongia EA, McLean HQ, Gaglani M, Rao A, Kim SS, Stark TJ, Barnes JR, Wentworth DE, Patel MM, Flannery B. Effect of Antigenic Drift on Influenza Vaccine Effectiveness in the United States-2019-2020. Clin Infect Dis 2021; 73:e4244-e4250. [PMID: 33367650 PMCID: PMC8664438 DOI: 10.1093/cid/ciaa1884] [Citation(s) in RCA: 63] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND At the start of the 2019-2020 influenza season, concern arose that circulating B/Victoria viruses of the globally emerging clade V1A.3 were antigenically drifted from the strain included in the vaccine. Intense B/Victoria activity was followed by circulation of genetically diverse A(H1N1)pdm09 viruses that were also antigenically drifted. We measured vaccine effectiveness (VE) in the United States against illness from these emerging viruses. METHODS We enrolled outpatients aged ≥6 months with acute respiratory illness at 5 sites. Respiratory specimens were tested for influenza by reverse-transcriptase polymerase chain reaction (RT-PCR). Using the test-negative design, we determined influenza VE by virus subtype/lineage and genetic subclades by comparing odds of vaccination in influenza cases versus test-negative controls. RESULTS Among 8845 enrollees, 2722 (31%) tested positive for influenza, including 1209 (44%) for B/Victoria and 1405 (51%) for A(H1N1)pdm09. Effectiveness against any influenza illness was 39% (95% confidence interval [CI]: 32-44), 45% (95% CI: 37-52) against B/Victoria and 30% (95% CI: 21-39) against A(H1N1)pdm09-associated illness. Vaccination offered no protection against A(H1N1)pdm09 viruses with antigenically drifted clade 6B.1A 183P-5A+156K HA genes (VE 7%; 95% CI: -14 to 23%) which predominated after January. CONCLUSIONS Vaccination provided protection against influenza illness, mainly due to infections from B/Victoria viruses. Vaccine protection against illness from A(H1N1)pdm09 was lower than historically observed effectiveness of 40%-60%, due to late-season vaccine mismatch following emergence of antigenically drifted viruses. The effect of drift on vaccine protection is not easy to predict and, even in drifted years, significant protection can be observed.
Collapse
Affiliation(s)
| | | | - Jessie R Chung
- Centers for Disease Control and Prevention, Atlanta GA, USA
| | | | | | - Michael L Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle WA, USA
| | - Lisa A Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle WA, USA
| | | | | | | | - Huong Q McLean
- Marshfield Clinic Research Institute, Marshfield WI, USA
| | - Manjusha Gaglani
- Baylor Scott & White Health, Texas A&M University College of Medicine, Temple TX, USA
| | - Arundhati Rao
- Baylor Scott & White Health, Texas A&M University College of Medicine, Temple TX, USA
| | - Sara S Kim
- Centers for Disease Control and Prevention, Atlanta GA, USA
| | - Thomas J Stark
- Centers for Disease Control and Prevention, Atlanta GA, USA
| | - John R Barnes
- Centers for Disease Control and Prevention, Atlanta GA, USA
| | | | - Manish M Patel
- Centers for Disease Control and Prevention, Atlanta GA, USA
| | | |
Collapse
|
21
|
Kim SS, Chung JR, Belongia EA, McLean HQ, King JP, Nowalk MP, Zimmerman RK, Balasubramani GK, Martin ET, Monto AS, Lamerato LE, Gaglani M, Smith ME, Dunnigan KM, Jackson ML, Jackson LA, Tenforde MW, Verani JR, Kobayashi M, Schrag SJ, Patel MM, Flannery B. Messenger RNA Vaccine Effectiveness Against Coronavirus Disease 2019 Among Symptomatic Outpatients Aged ≥16 Years in the United States, February-May 2021. J Infect Dis 2021; 224:1694-1698. [PMID: 34498052 PMCID: PMC8522410 DOI: 10.1093/infdis/jiab451] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Accepted: 09/07/2021] [Indexed: 01/10/2023] Open
Abstract
Evaluations of vaccine effectiveness (VE) are important to monitor as coronavirus disease 2019 (COVID-19) vaccines are introduced in the general population. Research staff enrolled symptomatic participants seeking outpatient medical care for COVID-19-like illness or severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing from a multisite network. VE was evaluated using the test-negative design. Among 236 SARS-CoV-2 nucleic acid amplification test-positive and 576 test-negative participants aged ≥16 years, the VE of messenger RNA vaccines against COVID-19 was 91% (95% confidence interval, 83%-95%) for full vaccination and 75% (55%-87%) for partial vaccination. Vaccination was associated with prevention of most COVID-19 cases among people seeking outpatient medical care.
Collapse
Affiliation(s)
- Sara S Kim
- Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Jessie R Chung
- Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | | | - Huong Q McLean
- Marshfield Clinic Research Institute, Marshfield, Wisconsin, USA
| | - Jennifer P King
- Marshfield Clinic Research Institute, Marshfield, Wisconsin, USA
| | - Mary Patricia Nowalk
- University of Pittsburgh Schools of the Health Sciences, Pittsburgh, Pennsylvania, USA
| | - Richard K Zimmerman
- University of Pittsburgh Schools of the Health Sciences, Pittsburgh, Pennsylvania, USA
| | | | | | | | | | - Manjusha Gaglani
- Baylor Scott and White Health
- Texas A&M University College of Medicine, Temple, Texas, USA
| | | | | | - Michael L Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington, USA
| | - Lisa A Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington, USA
| | - Mark W Tenforde
- Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | | | - Miwako Kobayashi
- Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | | | - Manish M Patel
- Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Brendan Flannery
- Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| |
Collapse
|
22
|
Jackson ML, Starita L, Kiniry E, Phillips CH, Wellwood S, Cho S, Kiavand A, Truong M, Han P, Richardson M, Wolf CR, Heimonen J, Nickerson DA, Chu HY. Incidence of Medically Attended Acute Respiratory Illnesses Due to Respiratory Viruses Across the Life Course During the 2018/19 Influenza Season. Clin Infect Dis 2021; 73:802-807. [PMID: 33590002 PMCID: PMC7929037 DOI: 10.1093/cid/ciab131] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2020] [Indexed: 11/25/2022] Open
Abstract
Background While multiple respiratory viruses circulate in humans, few studies have compared the incidence of different viruses across the life course. We estimated the incidence of outpatient illness due to 12 different viruses during November 2018 through April 2019 in a fully enumerated population. Methods We conducted active surveillance for ambulatory care visits for acute respiratory illness (ARI) among members of Kaiser Permanente Washington (KPWA). Enrolled patients provided respiratory swab specimens which were tested for 12 respiratory viruses using RT-PCR. We estimated the cumulative incidence of infection due to each virus overall and by age group. Results The KPWA population under surveillance included 202,562 individuals, of whom 2,767 (1.4%) were enrolled in the study. Influenza A(H3N2) was the most commonly detected virus, with an overall incidence 21 medically attended illnesses per 1,000 population; the next most common viruses were influenza A(H1N1) (18 per 1,000), coronaviruses (13 per 1,000), respiratory syncytial virus (RSV, 13 per 1,000), and rhinovirus (9 per 1,000). RSV was the most common cause of medically attended ARI among children aged 1-4 years; coronaviruses were the most common among adults aged ≥65 years. Conclusions Consistent with other studies focused on single viruses, we found that influenza and RSV were major causes of acute respiratory illness in persons of all ages. In comparison, coronaviruses and rhinovirus were also important pathogens. Prior to the emergence of SARS-CoV-2, coronaviruses were the second-most common cause of medically attended ARI during the 2018/19 influenza season.
Collapse
Affiliation(s)
- Michael L Jackson
- Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, Washington, USA
| | - Lea Starita
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
| | - Erika Kiniry
- Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, Washington, USA
| | - C Hallie Phillips
- Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, Washington, USA
| | - Stacie Wellwood
- Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, Washington, USA
| | - Shari Cho
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
| | - Anahita Kiavand
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
| | - Melissa Truong
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
| | - Peter Han
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
| | - Matthew Richardson
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
| | - Caitlin R Wolf
- Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Jessica Heimonen
- Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Deborah A Nickerson
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
| | - Helen Y Chu
- Department of Medicine, University of Washington, Seattle, Washington, USA
| | | |
Collapse
|
23
|
Kim SS, Flannery B, Foppa IM, Chung JR, Nowalk MP, Zimmerman RK, Gaglani M, Monto AS, Martin ET, Belongia EA, McLean HQ, Jackson ML, Jackson LA, Patel M. Effects of Prior Season Vaccination on Current Season Vaccine Effectiveness in the United States Flu Vaccine Effectiveness Network, 2012-2013 Through 2017-2018. Clin Infect Dis 2021; 73:497-505. [PMID: 32505128 DOI: 10.1093/cid/ciaa706] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Accepted: 06/01/2020] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND We compared effects of prior vaccination and added or lost protection from current season vaccination among those previously vaccinated. METHODS Our analysis included data from the US Flu Vaccine Effectiveness Network among participants ≥9 years old with acute respiratory illness from 2012-2013 through 2017-2018. Vaccine protection was estimated using multivariate logistic regression with an interaction term for effect of prior season vaccination on current season vaccine effectiveness. Models were adjusted for age, calendar time, high-risk status, site, and season for combined estimates. We estimated protection by combinations of current and prior vaccination compared to unvaccinated in both seasons or current vaccination among prior vaccinated. RESULTS A total of 31 819 participants were included. Vaccine protection against any influenza averaged 42% (95% confidence interval [CI], 38%-47%) among those vaccinated only the current season, 37% (95% CI, 33-40) among those vaccinated both seasons, and 26% (95% CI, 18%-32%) among those vaccinated only the prior season, compared with participants vaccinated neither season. Current season vaccination reduced the odds of any influenza among patients unvaccinated the prior season by 42% (95% CI, 37%-46%), including 57%, 27%, and 55% against A(H1N1), A(H3N2), and influenza B, respectively. Among participants vaccinated the prior season, current season vaccination further reduced the odds of any influenza by 15% (95% CI, 7%-23%), including 29% against A(H1N1) and 26% against B viruses, but not against A(H3N2). CONCLUSIONS Our findings support Advisory Committee on Immunization Practices recommendations for annual influenza vaccination. Benefits of current season vaccination varied among participants with and without prior season vaccination, by virus type/subtype and season.
Collapse
Affiliation(s)
- Sara S Kim
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.,Oak Ridge Institute for Science and Education, Oak Ridge, Tennessee, USA
| | - Brendan Flannery
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Ivo M Foppa
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Jessie R Chung
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Mary Patricia Nowalk
- University of Pittsburgh Schools of the Health Sciences, Pittsburgh, Pennsylvania, USA
| | - Richard K Zimmerman
- University of Pittsburgh Schools of the Health Sciences, Pittsburgh, Pennsylvania, USA
| | - Manjusha Gaglani
- Baylor Scott and White Health, Texas A&M University College of Medicine, Temple, Texas, USA
| | - Arnold S Monto
- University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Emily T Martin
- University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | | | - Huong Q McLean
- Marshfield Clinical Research Institute, Marshfield, Wisconsin, USA
| | - Michael L Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington, USA
| | - Lisa A Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington, USA
| | - Manish Patel
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| |
Collapse
|
24
|
Tenforde MW, Chung J, Smith ER, Talbot HK, Trabue CH, Zimmerman RK, Silveira FP, Gaglani M, Murthy K, Monto AS, Martin ET, McLean HQ, Belongia EA, Jackson LA, Jackson ML, Ferdinands JM, Flannery B, Patel MM. Influenza Vaccine Effectiveness in Inpatient and Outpatient Settings in the United States, 2015-2018. Clin Infect Dis 2021; 73:386-392. [PMID: 32270198 DOI: 10.1093/cid/ciaa407] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2020] [Accepted: 04/07/2020] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND Demonstration of influenza vaccine effectiveness (VE) against hospitalized illness in addition to milder outpatient illness may strengthen vaccination messaging. Our objective was to compare patient characteristics and VE between United States (US) inpatient and outpatient VE networks. METHODS We tested adults with acute respiratory illness (ARI) for influenza within 1 outpatient-based and 1 hospital-based VE network from 2015 through 2018. We compared age, sex, and high-risk conditions. The test-negative design was used to compare vaccination odds in influenza-positive cases vs influenza-negative controls. We estimated VE using logistic regression adjusting for site, age, sex, race/ethnicity, peak influenza activity, time to testing from, season (overall VE), and underlying conditions. VE differences (ΔVE) were assessed with 95% confidence intervals (CIs) determined through bootstrapping with significance defined as excluding the null. RESULTS The networks enrolled 14 573 (4144 influenza-positive) outpatients and 6769 (1452 influenza-positive) inpatients. Inpatients were older (median, 62 years vs 49 years) and had more high-risk conditions (median, 4 vs 1). Overall VE across seasons was 31% (95% CI, 26%-37%) among outpatients and 36% (95% CI, 27%-44%) among inpatients. Strain-specific VE (95% CI) among outpatients vs inpatients was 37% (25%-47%) vs 53% (37%-64%) against H1N1pdm09; 19% (9%-27%) vs 23% (8%-35%) against H3N2; and 46% (38%-53%) vs 46% (31%-58%) against B viruses. ΔVE was not significant for any comparison across all sites. CONCLUSIONS Inpatients and outpatients with ARI represent distinct populations. Despite comparatively poor health among inpatients, influenza vaccination was effective in preventing influenza-associated hospitalizations.
Collapse
Affiliation(s)
- Mark W Tenforde
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Jessie Chung
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Emily R Smith
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.,Oak Ridge Institute for Science and Education, Oak Ridge, Tennessee, USA
| | - H Keipp Talbot
- Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Christopher H Trabue
- University of Tennessee Health Science Center, Saint Thomas Health, Nashville, Tennessee, USA
| | | | | | - Manjusha Gaglani
- Baylor Scott and White Health, Texas A&M University College of Medicine, Temple, Texas, USA
| | - Kempapura Murthy
- Baylor Scott and White Health, Texas A&M University College of Medicine, Temple, Texas, USA
| | - Arnold S Monto
- University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Emily T Martin
- University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Huong Q McLean
- Marshfield Clinic Research Institute, Marshfield, Wisconsin, USA
| | | | - Lisa A Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington, USA
| | - Michael L Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington, USA
| | - Jill M Ferdinands
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Brendan Flannery
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Manish M Patel
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| |
Collapse
|
25
|
Toor J, Echeverria-Londono S, Li X, Abbas K, Carter ED, Clapham HE, Clark A, de Villiers MJ, Eilertson K, Ferrari M, Gamkrelidze I, Hallett TB, Hinsley WR, Hogan D, Huber JH, Jackson ML, Jean K, Jit M, Karachaliou A, Klepac P, Kraay A, Lessler J, Li X, Lopman BA, Mengistu T, Metcalf CJE, Moore SM, Nayagam S, Papadopoulos T, Perkins TA, Portnoy A, Razavi H, Razavi-Shearer D, Resch S, Sanderson C, Sweet S, Tam Y, Tanvir H, Tran Minh Q, Trotter CL, Truelove SA, Vynnycky E, Walker N, Winter A, Woodruff K, Ferguson NM, Gaythorpe KAM. Lives saved with vaccination for 10 pathogens across 112 countries in a pre-COVID-19 world. eLife 2021; 10:e67635. [PMID: 34253291 PMCID: PMC8277373 DOI: 10.7554/elife.67635] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Accepted: 05/26/2021] [Indexed: 12/12/2022] Open
Abstract
Background Vaccination is one of the most effective public health interventions. We investigate the impact of vaccination activities for Haemophilus influenzae type b, hepatitis B, human papillomavirus, Japanese encephalitis, measles, Neisseria meningitidis serogroup A, rotavirus, rubella, Streptococcus pneumoniae, and yellow fever over the years 2000-2030 across 112 countries. Methods Twenty-one mathematical models estimated disease burden using standardised demographic and immunisation data. Impact was attributed to the year of vaccination through vaccine-activity-stratified impact ratios. Results We estimate 97 (95%CrI[80, 120]) million deaths would be averted due to vaccination activities over 2000-2030, with 50 (95%CrI[41, 62]) million deaths averted by activities between 2000 and 2019. For children under-5 born between 2000 and 2030, we estimate 52 (95%CrI[41, 69]) million more deaths would occur over their lifetimes without vaccination against these diseases. Conclusions This study represents the largest assessment of vaccine impact before COVID-19-related disruptions and provides motivation for sustaining and improving global vaccination coverage in the future. Funding VIMC is jointly funded by Gavi, the Vaccine Alliance, and the Bill and Melinda Gates Foundation (BMGF) (BMGF grant number: OPP1157270 / INV-009125). Funding from Gavi is channelled via VIMC to the Consortium's modelling groups (VIMC-funded institutions represented in this paper: Imperial College London, London School of Hygiene and Tropical Medicine, Oxford University Clinical Research Unit, Public Health England, Johns Hopkins University, The Pennsylvania State University, Center for Disease Analysis Foundation, Kaiser Permanente Washington, University of Cambridge, University of Notre Dame, Harvard University, Conservatoire National des Arts et Métiers, Emory University, National University of Singapore). Funding from BMGF was used for salaries of the Consortium secretariat (authors represented here: TBH, MJ, XL, SE-L, JT, KW, NMF, KAMG); and channelled via VIMC for travel and subsistence costs of all Consortium members (all authors). We also acknowledge funding from the UK Medical Research Council and Department for International Development, which supported aspects of VIMC's work (MRC grant number: MR/R015600/1).JHH acknowledges funding from National Science Foundation Graduate Research Fellowship; Richard and Peggy Notebaert Premier Fellowship from the University of Notre Dame. BAL acknowledges funding from NIH/NIGMS (grant number R01 GM124280) and NIH/NIAID (grant number R01 AI112970). The Lives Saved Tool (LiST) receives funding support from the Bill and Melinda Gates Foundation.This paper was compiled by all coauthors, including two coauthors from Gavi. Other funders had no role in study design, data collection, data analysis, data interpretation, or writing of the report. All authors had full access to all the data in the study and had final responsibility for the decision to submit for publication.
Collapse
Affiliation(s)
- Jaspreet Toor
- MRC Centre for Global Infectious Disease Analysis; and the Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College LondonLondonUnited Kingdom
| | - Susy Echeverria-Londono
- MRC Centre for Global Infectious Disease Analysis; and the Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College LondonLondonUnited Kingdom
| | - Xiang Li
- MRC Centre for Global Infectious Disease Analysis; and the Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College LondonLondonUnited Kingdom
| | - Kaja Abbas
- London School of Hygiene and Tropical MedicineLondonUnited Kingdom
| | - Emily D Carter
- Bloomberg School of Public Health, Johns Hopkins UniversityBaltimoreUnited States
| | - Hannah E Clapham
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore; Oxford University Clinical Research Unit, Vietnam; Nuffield Department of Medicine, Oxford UniversityOxfordUnited Kingdom
| | - Andrew Clark
- London School of Hygiene and Tropical MedicineLondonUnited Kingdom
| | - Margaret J de Villiers
- MRC Centre for Global Infectious Disease Analysis; and the Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College LondonLondonUnited Kingdom
| | | | | | | | - Timothy B Hallett
- MRC Centre for Global Infectious Disease Analysis; and the Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College LondonLondonUnited Kingdom
| | - Wes R Hinsley
- MRC Centre for Global Infectious Disease Analysis; and the Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College LondonLondonUnited Kingdom
| | | | - John H Huber
- Department of Biological Sciences, University of Notre DameNotre DameUnited States
| | | | - Kevin Jean
- MRC Centre for Global Infectious Disease Analysis; and the Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College LondonLondonUnited Kingdom
- Laboratoire MESuRS and Unite PACRI, Institut Pasteur, Conservatoire National des Arts et MetiersParisFrance
| | - Mark Jit
- London School of Hygiene and Tropical MedicineLondonUnited Kingdom
- University of Hong Kong, Hong Kong Special Administrative RegionHong KongChina
| | | | - Petra Klepac
- London School of Hygiene and Tropical MedicineLondonUnited Kingdom
| | - Alicia Kraay
- Rollins School of Public Health, Emory UniversityAtlantaUnited States
| | - Justin Lessler
- Bloomberg School of Public Health, Johns Hopkins UniversityBaltimoreUnited States
| | - Xi Li
- IndependentAtlantaUnited States
| | - Benjamin A Lopman
- Rollins School of Public Health, Emory UniversityAtlantaUnited States
| | | | | | - Sean M Moore
- Department of Biological Sciences, University of Notre DameNotre DameUnited States
| | - Shevanthi Nayagam
- MRC Centre for Global Infectious Disease Analysis; and the Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College LondonLondonUnited Kingdom
- Section of Hepatology and Gastroenterology, Department of Metabolism, Digestion and Reproduction, Imperial College LondonLondonUnited Kingdom
| | - Timos Papadopoulos
- Public Health EnglandLondonUnited Kingdom
- University of SouthamptonSouthamptonUnited Kingdom
| | - T Alex Perkins
- Department of Biological Sciences, University of Notre DameNotre DameUnited States
| | - Allison Portnoy
- Center for Health Decision Science, Harvard T H Chan School of Public Health, Harvard UniversityCambridgeUnited States
| | - Homie Razavi
- Center for Disease Analysis FoundationLafayetteUnited States
| | | | - Stephen Resch
- Center for Health Decision Science, Harvard T H Chan School of Public Health, Harvard UniversityCambridgeUnited States
| | - Colin Sanderson
- London School of Hygiene and Tropical MedicineLondonUnited Kingdom
| | - Steven Sweet
- Center for Health Decision Science, Harvard T H Chan School of Public Health, Harvard UniversityCambridgeUnited States
| | - Yvonne Tam
- Bloomberg School of Public Health, Johns Hopkins UniversityBaltimoreUnited States
| | - Hira Tanvir
- London School of Hygiene and Tropical MedicineLondonUnited Kingdom
| | - Quan Tran Minh
- Department of Biological Sciences, University of Notre DameNotre DameUnited States
| | | | - Shaun A Truelove
- Bloomberg School of Public Health, Johns Hopkins UniversityBaltimoreUnited States
| | | | - Neff Walker
- Bloomberg School of Public Health, Johns Hopkins UniversityBaltimoreUnited States
| | - Amy Winter
- Bloomberg School of Public Health, Johns Hopkins UniversityBaltimoreUnited States
| | - Kim Woodruff
- MRC Centre for Global Infectious Disease Analysis; and the Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College LondonLondonUnited Kingdom
| | - Neil M Ferguson
- MRC Centre for Global Infectious Disease Analysis; and the Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College LondonLondonUnited Kingdom
| | - Katy AM Gaythorpe
- MRC Centre for Global Infectious Disease Analysis; and the Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College LondonLondonUnited Kingdom
| |
Collapse
|
26
|
Daley MF, Reifler LM, Shoup JA, Narwaney KJ, Kharbanda EO, Groom HC, Jackson ML, Jacobsen SJ, McLean HQ, Klein NP, Williams JTB, Weintraub ES, McNeil MM, Glanz JM. Temporal Trends in Undervaccination: A Population-Based Cohort Study. Am J Prev Med 2021; 61:64-72. [PMID: 34148627 PMCID: PMC8899861 DOI: 10.1016/j.amepre.2021.01.037] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Revised: 12/28/2020] [Accepted: 01/20/2021] [Indexed: 10/21/2022]
Abstract
INTRODUCTION Monitoring the trends in undervaccination, including that because of parental vaccine refusal or delay, can inform public health responses directed at improving vaccine confidence and vaccination coverage. METHODS A retrospective cohort study was conducted in the Vaccine Safety Datalink. The cohort included all children born in 2004-2017 with ≥3 well-child visits between ages 2 and 23 months. Using electronic health record-based vaccination data, the average days undervaccinated was calculated for each child. Undervaccination patterns were assessed through age 23 months. Temporal trends were inspected for inflection points and were analyzed using linear regression. Nested within the cohort study, a survey was conducted to compare parent reports of vaccine refusal or delay with observed vaccination patterns. Data were analyzed in 2020. RESULTS The study cohort consisted of 808,170 children. The percentage of children with average days undervaccinated=0 (fully vaccinated, no delays) rose from a nadir of 47.1% for the birth year 2008 to 68.4% for the birth year 2017 (ptrend<0.001). The percentage with no vaccines rose from 0.35% for the birth year 2004 to 1.28% for the birth year 2017 (ptrend<0.001). Consistent vaccine limiting was observed in 2.04% for the birth year 2017. Omission of measles, mumps, and rubella vaccine peaked at 4.76% in the birth year 2007 and declined thereafter (ptrend<0.001). On the parent survey (response rate 60.2%), a high proportion of parents of the most undervaccinated children reported refusing or delaying vaccines. CONCLUSIONS In a 14-year cohort study, vaccination timeliness has improved. However, the small but increasing number of children who received no vaccines by age 23 months warrants additional attention.
Collapse
Affiliation(s)
- Matthew F Daley
- Institute for Health Research, Kaiser Permanente Colorado, Aurora, Colorado; Department of Pediatrics, University of Colorado School of Medicine, University of Colorado Anschutz Medical Campus Aurora, Colorado.
| | - Liza M Reifler
- Institute for Health Research, Kaiser Permanente Colorado, Aurora, Colorado
| | - Jo Ann Shoup
- Institute for Health Research, Kaiser Permanente Colorado, Aurora, Colorado
| | - Komal J Narwaney
- Institute for Health Research, Kaiser Permanente Colorado, Aurora, Colorado
| | | | - Holly C Groom
- Center for Health Research, Kaiser Permanente Northwest, Portland, Oregon
| | - Michael L Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington
| | | | - Huong Q McLean
- Marshfield Clinic Research Institute, Marshfield, Wisconsin
| | - Nicola P Klein
- Kaiser Permanente Vaccine Study Center, Oakland, California
| | - Joshua T B Williams
- Department of General Pediatrics, Denver Health and Hospitals, Denver, Colorado
| | - Eric S Weintraub
- Immunization Safety Office, Division of Healthcare Quality Promotion, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Michael M McNeil
- Immunization Safety Office, Division of Healthcare Quality Promotion, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Jason M Glanz
- Institute for Health Research, Kaiser Permanente Colorado, Aurora, Colorado; Department of Epidemiology, Colorado School of Public Health, Aurora, Colorado
| |
Collapse
|
27
|
Gaythorpe KAM, Abbas K, Huber J, Karachaliou A, Thakkar N, Woodruff K, Li X, Echeverria-Londono S, Ferrari M, Jackson ML, McCarthy K, Perkins TA, Trotter C, Jit M. Impact of COVID-19-related disruptions to measles, meningococcal A, and yellow fever vaccination in 10 countries. eLife 2021; 10:e67023. [PMID: 34165077 PMCID: PMC8263060 DOI: 10.7554/elife.67023] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Accepted: 06/23/2021] [Indexed: 12/30/2022] Open
Abstract
Background Childhood immunisation services have been disrupted by the COVID-19 pandemic. WHO recommends considering outbreak risk using epidemiological criteria when deciding whether to conduct preventive vaccination campaigns during the pandemic. Methods We used two to three models per infection to estimate the health impact of 50% reduced routine vaccination coverage in 2020 and delay of campaign vaccination from 2020 to 2021 for measles vaccination in Bangladesh, Chad, Ethiopia, Kenya, Nigeria, and South Sudan, for meningococcal A vaccination in Burkina Faso, Chad, Niger, and Nigeria, and for yellow fever vaccination in the Democratic Republic of Congo, Ghana, and Nigeria. Our counterfactual comparative scenario was sustaining immunisation services at coverage projections made prior to COVID-19 (i.e. without any disruption). Results Reduced routine vaccination coverage in 2020 without catch-up vaccination may lead to an increase in measles and yellow fever disease burden in the modelled countries. Delaying planned campaigns in Ethiopia and Nigeria by a year may significantly increase the risk of measles outbreaks (both countries did complete their supplementary immunisation activities (SIAs) planned for 2020). For yellow fever vaccination, delay in campaigns leads to a potential disease burden rise of >1 death per 100,000 people per year until the campaigns are implemented. For meningococcal A vaccination, short-term disruptions in 2020 are unlikely to have a significant impact due to the persistence of direct and indirect benefits from past introductory campaigns of the 1- to 29-year-old population, bolstered by inclusion of the vaccine into the routine immunisation schedule accompanied by further catch-up campaigns. Conclusions The impact of COVID-19-related disruption to vaccination programs varies between infections and countries. Planning and implementation of campaigns should consider country and infection-specific epidemiological factors and local immunity gaps worsened by the COVID-19 pandemic when prioritising vaccines and strategies for catch-up vaccination. Funding Bill and Melinda Gates Foundation and Gavi, the Vaccine Alliance.
Collapse
Affiliation(s)
- Katy AM Gaythorpe
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College LondonLondonUnited Kingdom
| | - Kaja Abbas
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical MedicineLondonUnited Kingdom
| | - John Huber
- Department of Biological Sciences, University of Notre DameSouth BendUnited States
| | | | - Niket Thakkar
- Institute for Disease Modeling, Bill & Melinda Gates FoundationSeattleUnited States
| | - Kim Woodruff
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College LondonLondonUnited Kingdom
| | - Xiang Li
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College LondonLondonUnited Kingdom
| | - Susy Echeverria-Londono
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College LondonLondonUnited Kingdom
| | | | | | - Kevin McCarthy
- Institute for Disease Modeling, Bill & Melinda Gates FoundationSeattleUnited States
| | - T Alex Perkins
- Department of Biological Sciences, University of Notre DameSouth BendUnited States
| | - Caroline Trotter
- Department of Veterinary Medicine, University of CambridgeCambridgeUnited Kingdom
| | - Mark Jit
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical MedicineLondonUnited Kingdom
- School of Public Health, University of Hong KongHong Kong SARChina
| |
Collapse
|
28
|
Somayaji R, Neradilek MB, Szpiro AA, Lofy KH, Jackson ML, Goss CH, Duchin JS, Neuzil KM, Ortiz JR. Effects of Air Pollution and Other Environmental Exposures on Estimates of Severe Influenza Illness, Washington, USA. Emerg Infect Dis 2021; 26. [PMID: 32310747 PMCID: PMC7181929 DOI: 10.3201/eid2605.190599] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Abstract
Ecologic models of influenza burden may be confounded by other exposures that share winter seasonality. We evaluated the effects of air pollution and other environmental exposures in ecologic models estimating influenza-associated hospitalizations. We linked hospitalization data, viral surveillance, and environmental data, including temperature, relative humidity, dew point, and fine particulate matter for 3 counties in Washington, USA, for 2001-2012. We used negative binomial regression models to estimate the incidence of influenza-associated respiratory and circulatory (RC) hospitalizations and to assess the effect of adjusting for environmental exposures on RC hospitalization estimates. The modeled overall incidence rate of influenza-associated RC hospitalizations was 31/100,000 person-years. The environmental parameters were statistically associated with RC hospitalizations but did not appreciably affect the event rate estimates. Modeled influenza-associated RC hospitalization rates were similar to published estimates, and inclusion of environmental covariates in the model did not have a clinically important effect on severe influenza estimates.
Collapse
|
29
|
McCulloch DJ, Jackson ML, Hughes JP, Lester S, Mills L, Freeman B, Rasheed MAU, Thornburg NJ, Chu HY. Seroprevalence of SARS-CoV-2 antibodies in Seattle, Washington: October 2019-April 2020. PLoS One 2021; 16:e0252235. [PMID: 34043706 PMCID: PMC8158900 DOI: 10.1371/journal.pone.0252235] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Accepted: 05/11/2021] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND The first US case of SARS-CoV-2 infection was detected on January 20, 2020. However, some serology studies suggest SARS-CoV-2 may have been present in the United States prior to that, as early as December 2019. The extent of domestic COVID-19 detection prior to 2020 has not been well-characterized. OBJECTIVES To estimate the prevalence of SARS-CoV-2 antibody among healthcare users in the greater Seattle, Washington area from October 2019 through early April 2020. STUDY DESIGN We tested residual samples from 766 Seattle-area adults for SARS-CoV-2 antibodies utilizing an ELISA against prefusion-stabilized Spike (S) protein. RESULTS No antibody-positive samples were found between October 2, 2019 and March 13, 2020. Prevalence rose to 1.2% in late March and early April 2020. CONCLUSIONS The absence of SARS-CoV-2 antibody-positive samples in October 2019 through mid-March, 2020, provides evidence against widespread circulation of COVID-19 among healthcare users in the Seattle area during that time. A small proportion of this metropolitan-area cohort had been infected with SARS-CoV-2 by spring of 2020.
Collapse
Affiliation(s)
- Denise J. McCulloch
- School of Medicine, University of Washington, Seattle, Washington, United States of America
| | - Michael L. Jackson
- Kaiser Permanente Washington, Seattle, Washington, United States of America
| | - James P. Hughes
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, Washington, United States of America
| | - Sandra Lester
- Synergy America, Inc., Duluth, Georgia, United States of America
| | - Lisa Mills
- Eagle Global Scientific, LLC, Atlanta, Georgia, United States of America
| | - Brandi Freeman
- Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | | | - Natalie J. Thornburg
- Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Helen Y. Chu
- School of Medicine, University of Washington, Seattle, Washington, United States of America
| |
Collapse
|
30
|
Flannery B, Meece JK, Williams JV, Martin ET, Gaglani M, Jackson ML, Talbot HK. Systematic Testing for Influenza and Coronavirus Disease 2019 Among Patients With Respiratory Illness. Clin Infect Dis 2021; 72:e426-e428. [PMID: 32687197 PMCID: PMC7454355 DOI: 10.1093/cid/ciaa1023] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Affiliation(s)
- Brendan Flannery
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Jennifer K Meece
- Marshfield Clinic Research Institute, Marshfield, Wisconsin, USA
| | - John V Williams
- UPMC Children’s Hospital of Pittsburgh, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | | | | | - Michael L Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington, USA
| | - H Keipp Talbot
- Division of Infectious Disease, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| |
Collapse
|
31
|
Heimonen J, McCulloch DJ, O'Hanlon J, Kim AE, Emanuels A, Wilcox N, Brandstetter E, Stewart M, McCune D, Fry S, Parsons S, Hughes JP, Jackson ML, Uyeki TM, Boeckh M, Starita LM, Bedford T, Englund JA, Chu HY. A remote household-based approach to influenza self-testing and antiviral treatment. Influenza Other Respir Viruses 2021; 15:469-477. [PMID: 33939275 PMCID: PMC8189204 DOI: 10.1111/irv.12859] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Revised: 03/19/2021] [Accepted: 03/28/2021] [Indexed: 11/28/2022] Open
Abstract
Background Households represent important settings for transmission of influenza and other respiratory viruses. Current influenza diagnosis and treatment relies upon patient visits to healthcare facilities, which may lead to under‐diagnosis and treatment delays. This study aimed to assess the feasibility of an at‐home approach to influenza diagnosis and treatment via home testing, telehealth care, and rapid antiviral home delivery. Methods We conducted a pilot interventional study of remote influenza diagnosis and treatment in Seattle‐area households with children during the 2019‐2020 influenza season using pre‐positioned nasal swabs and home influenza tests. Home monitoring for respiratory symptoms occurred weekly; if symptoms were reported within 48 hours of onset, participants collected mid‐nasal swabs and used a rapid home‐based influenza immunoassay. An additional home‐collected swab was returned to a laboratory for confirmatory influenza RT‐PCR testing. Baloxavir antiviral treatment was prescribed and delivered to symptomatic and age‐eligible participants, following a telehealth encounter. Results 124 households comprising 481 individuals self‐monitored for respiratory symptoms, with 58 home tests administered. 12 home tests were positive for influenza, of which eight were true positives confirmed by RT‐PCR. The sensitivity and specificity of the home influenza test were 72.7% and 96.2%, respectively. There were eight home deliveries of baloxavir, with 7 (87.5%) occurring within 3 hours of prescription and all within 48 hours of symptom onset. Conclusions We demonstrate the feasibility of self‐testing combined with rapid home delivery of influenza antiviral treatment. This approach may be an important control strategy for influenza epidemics and pandemics.
Collapse
Affiliation(s)
- Jessica Heimonen
- Department of Medicine, University of Washington, Seattle, WA, USA
| | | | - Jessica O'Hanlon
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - Ashley E Kim
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - Anne Emanuels
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - Naomi Wilcox
- Department of Medicine, University of Washington, Seattle, WA, USA
| | | | | | | | - Scott Fry
- Ellume, East Brisbane, Qld, Australia
| | | | - James P Hughes
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Michael L Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Timothy M Uyeki
- Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Michael Boeckh
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Lea M Starita
- Brotman Baty Institute, Seattle, WA, USA.,Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Trevor Bedford
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Janet A Englund
- Seattle Children's Research Institute and Department of Pediatrics, University of Washington, Seattle, WA, USA
| | - Helen Y Chu
- Department of Medicine, University of Washington, Seattle, WA, USA
| |
Collapse
|
32
|
Gaglani M, Vasudevan A, Raiyani C, Murthy K, Chen W, Reis M, Belongia EA, McLean HQ, Jackson ML, Jackson LA, Zimmerman RK, Nowalk MP, Monto AS, Martin ET, Chung JR, Spencer S, Fry AM, Flannery B. Effectiveness of Trivalent and Quadrivalent Inactivated Vaccines Against Influenza B in the United States, 2011-2012 to 2016-2017. Clin Infect Dis 2021; 72:1147-1157. [PMID: 32006430 PMCID: PMC8028105 DOI: 10.1093/cid/ciaa102] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2019] [Accepted: 01/30/2020] [Indexed: 11/13/2022] Open
Abstract
Background Since 2013, quadrivalent influenza vaccines containing 2 B viruses gradually replaced trivalent vaccines in the United States. We compared the vaccine effectiveness of quadrivalent to trivalent inactivated vaccines (IIV4 to IIV3, respectively) against illness due to influenza B during the transition, when IIV4 use increased rapidly. Methods The US Influenza Vaccine Effectiveness (Flu VE) Network analyzed 25 019 of 42 600 outpatients aged ≥6 months who enrolled within 7 days of illness onset during 6 seasons from 2011–2012. Upper respiratory specimens were tested for the influenza virus type and B lineage. Using logistic regression, we estimated IIV4 or IIV3 effectiveness by comparing the odds of an influenza B infection overall and the odds of B lineage among vaccinated versus unvaccinated participants. Over 4 seasons from 2013–2014, we compared the relative odds of an influenza B infection among IIV4 versus IIV3 recipients. Results Trivalent vaccines included the predominantly circulating B lineage in 4 of 6 seasons. During 4 influenza seasons when both IIV4 and IIV3 were widely used, the overall effectiveness against any influenza B was 53% (95% confidence interval [CI], 45–59) for IIV4 versus 45% (95% CI, 34–54) for IIV3. IIV4 was more effective than IIV3 against the B lineage not included in IIV3, but comparative effectiveness against illnesses related to any influenza B favored neither vaccine valency. Conclusions The uptake of quadrivalent inactivated influenza vaccines was not associated with increased protection against any influenza B illness, despite the higher effectiveness of quadrivalent vaccines against the added B virus lineage. Public health impact and cost-benefit analyses are needed globally.
Collapse
Affiliation(s)
- Manjusha Gaglani
- Baylor Scott & White Health, Texas A&M University College of Medicine, Temple, Texas, USA
| | - Anupama Vasudevan
- Baylor Scott & White Health, Texas A&M University College of Medicine, Temple, Texas, USA
| | - Chandni Raiyani
- Baylor Scott & White Health, Texas A&M University College of Medicine, Temple, Texas, USA
| | - Kempapura Murthy
- Baylor Scott & White Health, Texas A&M University College of Medicine, Temple, Texas, USA
| | - Wencong Chen
- Baylor Scott & White Health, Texas A&M University College of Medicine, Temple, Texas, USA
| | - Michael Reis
- Baylor Scott & White Health, Texas A&M University College of Medicine, Temple, Texas, USA
| | | | - Huong Q McLean
- Marshfield Clinic Research Institute, Marshfield, Wisconsin, USA
| | - Michael L Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington, USA
| | - Lisa A Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington, USA
| | - Richard K Zimmerman
- University of Pittsburgh, Schools of Health Sciences, Pittsburgh, Pennsylvania, USA
| | - Mary Patricia Nowalk
- University of Pittsburgh, Schools of Health Sciences, Pittsburgh, Pennsylvania, USA
| | - Arnold S Monto
- University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Emily T Martin
- University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Jessie R Chung
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Sarah Spencer
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Alicia M Fry
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Brendan Flannery
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| |
Collapse
|
33
|
Smith ER, Fry AM, Hicks LA, Fleming-Dutra KE, Flannery B, Ferdinands J, Rolfes MA, Martin ET, Monto AS, Zimmerman RK, Nowalk MP, Jackson ML, McLean HQ, Olson SC, Gaglani M, Patel MM. Reducing Antibiotic Use in Ambulatory Care Through Influenza Vaccination. Clin Infect Dis 2021; 71:e726-e734. [PMID: 32322875 DOI: 10.1093/cid/ciaa464] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2020] [Accepted: 04/20/2020] [Indexed: 01/21/2023] Open
Abstract
BACKGROUND Improving appropriate antibiotic use is crucial for combating antibiotic resistance and unnecessary adverse drug reactions. Acute respiratory illness (ARI) commonly causes outpatient visits and accounts for ~41% of antibiotics used in the United States. We examined the influence of influenza vaccination on reducing antibiotic prescriptions among outpatients with ARI. METHODS We enrolled outpatients aged ≥6 months with ARI from 50-60 US clinics during 5 winters (2013-2018) and tested for influenza with RT-PCR; results were unavailable for clinical decision making and clinical influenza testing was infrequent. We collected antibiotic prescriptions and diagnosis codes for ARI syndromes. We calculated vaccine effectiveness (VE) by comparing vaccination odds among influenza-positive cases with test-negative controls. We estimated ARI visits and antibiotic prescriptions averted by influenza vaccination using estimates of VE, coverage, and prevalence of antibiotic prescriptions and influenza. RESULTS Among 37 487 ARI outpatients, 9659 (26%) were influenza positive. Overall, 36% of ARI and 26% of influenza-positive patients were prescribed antibiotics. The top 3 prevalent ARI syndromes included: viral upper respiratory tract infection (47%), pharyngitis (18%), and allergy or asthma (11%). Among patients testing positive for influenza, 77% did not receive an ICD-CM diagnostic code for influenza. Overall, VE against influenza-associated ARI was 35% (95% CI, 32-39%). Vaccination prevented 5.6% of all ARI syndromes, ranging from 2.8% (sinusitis) to 11% (clinical influenza). Influenza vaccination averted 1 in 25 (3.8%; 95% CI, 3.6-4.1%) antibiotic prescriptions among ARI outpatients during influenza seasons. CONCLUSIONS Vaccination and accurate influenza diagnosis may curb unnecessary antibiotic use and reduce the global threat of antibiotic resistance.
Collapse
Affiliation(s)
- Emily R Smith
- Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Alicia M Fry
- Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Lauri A Hicks
- Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | | | - Brendan Flannery
- Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Jill Ferdinands
- Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Melissa A Rolfes
- Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | | | | | | | | | - Michael L Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington, USA
| | - Huong Q McLean
- Marshfield Clinic Research Institute, Marshfield, Wisconsin, USA
| | - Scott C Olson
- Marshfield Clinic Research Institute, Marshfield, Wisconsin, USA
| | - Manjusha Gaglani
- Baylor Scott & White Health, Texas A&M University, Temple, Texas, USA
| | - Manish M Patel
- Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| |
Collapse
|
34
|
Honn KA, Halverson T, Jackson ML, Krusmark M, Chavali VP, Gunzelmann G, Van Dongen HPA. New insights into the cognitive effects of sleep deprivation by decomposition of a cognitive throughput task. Sleep 2021; 43:5813478. [PMID: 32227081 DOI: 10.1093/sleep/zsz319] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2019] [Revised: 12/09/2019] [Indexed: 12/16/2022] Open
Abstract
STUDY OBJECTIVES A cognitive throughput task known as the Digit Symbol Substitution Test (DSST) (or Symbol Digit Modalities Test) has been used as an assay of general cognitive slowing during sleep deprivation. Here, the effects of total sleep deprivation (TSD) on specific cognitive processes involved in DSST performance, including visual search, spatial memory, paired-associate learning, and motor response, were investigated through targeted task manipulations. METHODS A total of 12 DSST variants, designed to manipulate the use of specific cognitive processes, were implemented in two laboratory-based TSD studies with N = 59 and N = 26 subjects, respectively. In each study, the Psychomotor Vigilance Test (PVT) was administered alongside the DSST variants. RESULTS TSD reduced cognitive throughput on all DSST variants, with response time distributions exhibiting rightward skewing. All DSST variants showed practice effects, which were however minimized by inclusion of a pause between trials. Importantly, TSD-induced impairment on the DSST variants was not uniform, with a principal component analysis revealing three factors. Diffusion model decomposition of cognitive processes revealed that inter-individual differences during TSD on a two-alternative forced choice DSST variant were different from those on the PVT. CONCLUSIONS While reduced cognitive throughput has been interpreted to reflect general cognitive slowing, such TSD-induced impairment appears to reflect cognitive instability, like on the PVT, rather than general slowing. Further, comparisons between task variants revealed not one, but three distinct underlying processes impacted by sleep deprivation. Moreover, the practice effect on the task was found to be independent of the TSD effect and minimized by a task pacing manipulation.
Collapse
Affiliation(s)
- Kimberly A Honn
- Sleep and Performance Research Center, Washington State University, Spokane, WA.,Elson S. Floyd College of Medicine, Washington State University, Spokane, WA
| | - T Halverson
- Cognitive Models and Agents Branch, Air Force Research Laboratory, Wright-Patterson Air Force Base, OH.,Aptima, Inc., Woburn, MA
| | - M L Jackson
- Sleep and Performance Research Center, Washington State University, Spokane, WA.,Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia
| | | | - V P Chavali
- Sleep and Performance Research Center, Washington State University, Spokane, WA.,University of Washington School of Medicine, Seattle, WA
| | - G Gunzelmann
- Cognitive Models and Agents Branch, Air Force Research Laboratory, Wright-Patterson Air Force Base, OH
| | - H P A Van Dongen
- Sleep and Performance Research Center, Washington State University, Spokane, WA.,Elson S. Floyd College of Medicine, Washington State University, Spokane, WA
| |
Collapse
|
35
|
Jackson ML, Hart GR, McCulloch DJ, Adler A, Brandstetter E, Fay K, Han P, Lacombe K, Lee J, Sibley TR, Nickerson DA, Rieder MJ, Starita L, Englund JA, Bedford T, Chu H, Famulare M. Effects of weather-related social distancing on city-scale transmission of respiratory viruses: a retrospective cohort study. BMC Infect Dis 2021; 21:335. [PMID: 33836685 PMCID: PMC8033554 DOI: 10.1186/s12879-021-06028-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2020] [Accepted: 03/31/2021] [Indexed: 02/13/2023] Open
Abstract
Background Unusually high snowfall in western Washington State in February 2019 led to widespread school and workplace closures. We assessed the impact of social distancing caused by this extreme weather event on the transmission of respiratory viruses. Methods Residual specimens from patients evaluated for acute respiratory illness at hospitals in the Seattle metropolitan area were screened for a panel of respiratory viruses. Transmission models were fit to each virus to estimate the magnitude reduction in transmission due to weather-related disruptions. Changes in contact rates and care-seeking were informed by data on local traffic volumes and hospital visits. Results Disruption in contact patterns reduced effective contact rates during the intervention period by 16 to 95%, and cumulative disease incidence through the remainder of the season by 3 to 9%. Incidence reductions were greatest for viruses that were peaking when the disruption occurred and least for viruses in an early epidemic phase. Conclusion High-intensity, short-duration social distancing measures may substantially reduce total incidence in a respiratory virus epidemic if implemented near the epidemic peak. For SARS-CoV-2, this suggests that, even when SARS-CoV-2 spread is out of control, implementing short-term disruptions can prevent COVID-19 deaths. Supplementary Information The online version contains supplementary material available at 10.1186/s12879-021-06028-4.
Collapse
Affiliation(s)
- Michael L Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA.
| | | | - Denise J McCulloch
- Department of Medicine, University of Washington School of Medicine, Seattle, WA, USA
| | - Amanda Adler
- Seattle Children's Research Institute, Seattle, WA, USA
| | | | - Kairsten Fay
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Peter Han
- Brotman Baty Institute for Precision Medicine, Seattle, WA, USA.,Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | | | - Jover Lee
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Thomas R Sibley
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Deborah A Nickerson
- Brotman Baty Institute for Precision Medicine, Seattle, WA, USA.,Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Mark J Rieder
- Brotman Baty Institute for Precision Medicine, Seattle, WA, USA
| | - Lea Starita
- Brotman Baty Institute for Precision Medicine, Seattle, WA, USA.,Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | | | - Trevor Bedford
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.,Brotman Baty Institute for Precision Medicine, Seattle, WA, USA.,Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Helen Chu
- Department of Medicine, University of Washington School of Medicine, Seattle, WA, USA.,Brotman Baty Institute for Precision Medicine, Seattle, WA, USA
| | | | | |
Collapse
|
36
|
Jackson ML, Ferdinands J, Nowalk MP, Zimmerman RK, Kieke B, Gaglani M, Murthy K, Petrie JG, Martin ET, Chung JR, Flannery B, Jackson LA. Differences between Frequentist and Bayesian inference in routine surveillance for influenza vaccine effectiveness: a test-negative case-control study. BMC Public Health 2021; 21:516. [PMID: 33726743 PMCID: PMC7968177 DOI: 10.1186/s12889-021-10543-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Accepted: 03/03/2021] [Indexed: 11/10/2022] Open
Abstract
Background Routine influenza vaccine effectiveness (VE) surveillance networks use frequentist methods to estimate VE. With data from more than a decade of VE surveillance from diverse global populations now available, using Bayesian methods to explicitly account for this knowledge may be beneficial. This study explores differences between Bayesian vs. frequentist inference in multiple seasons with varying VE. Methods We used data from the United States Influenza Vaccine Effectiveness (US Flu VE) Network. Ambulatory care patients with acute respiratory illness were enrolled during seasons of varying observed VE based on traditional frequentist methods. We estimated VE against A(H1N1)pdm in 2015/16, dominated by A(H1N1)pdm; against A(H3N2) in 2017/18, dominated by A(H3N2); and compared VE for live attenuated influenza vaccine (LAIV) vs. inactivated influenza vaccine (IIV) among children aged 2–17 years in 2013/14, also dominated by A(H1N1)pdm. VE was estimated using both frequentist and Bayesian methods using the test-negative design. For the Bayesian estimates, prior VE distributions were based on data from all published test-negative studies of the same influenza type/subtype available prior to the season of interest. Results Across the three seasons, 16,342 subjects were included in the analyses. For 2015/16, frequentist and Bayesian VE estimates were essentially identical (41% each). For 2017/18, frequentist and Bayesian estimates of VE against A(H3N2) viruses were also nearly identical (26% vs. 23%, respectively), even though the presence of apparent antigenic match could potentially have pulled Bayesian estimates upward. Precision of estimates was similar between methods in both seasons. Frequentist and Bayesian estimates diverged for children in 2013/14. Under the frequentist approach, LAIV effectiveness was 62 percentage points lower than IIV, while LAIV was only 27 percentage points lower than IIV under the Bayesian approach. Conclusion Bayesian estimates of influenza VE can differ from frequentist estimates to a clinically meaningful degree when VE diverges substantially from previous seasons. Supplementary Information The online version contains supplementary material available at 10.1186/s12889-021-10543-z.
Collapse
Affiliation(s)
- Michael L Jackson
- Kaiser Permanente Washington Health Research Institute, 1730 Minor Ave, Suite 1600, Seattle, WA, 98101-1448, USA.
| | - Jill Ferdinands
- Centers for Disease Control and Prevention, Atlanta, GA, USA
| | | | | | - Burney Kieke
- Marshfield Clinic Research Institute, Marshfield, WI, USA
| | - Manjusha Gaglani
- Baylor Scott & White Health, Temple, TX, USA.,Texas A&M College of Medicine, Temple, TX, USA
| | | | - Joshua G Petrie
- University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Emily T Martin
- University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Jessie R Chung
- Centers for Disease Control and Prevention, Atlanta, GA, USA
| | | | - Lisa A Jackson
- Kaiser Permanente Washington Health Research Institute, 1730 Minor Ave, Suite 1600, Seattle, WA, 98101-1448, USA
| |
Collapse
|
37
|
Ahmed F, Kim S, Nowalk MP, King JP, VanWormer JJ, Gaglani M, Zimmerman RK, Bear T, Jackson ML, Jackson LA, Martin E, Cheng C, Flannery B, Chung JR, Uzicanin A. Paid Leave and Access to Telework as Work Attendance Determinants during Acute Respiratory Illness, United States, 2017-2018. Emerg Infect Dis 2021; 26. [PMID: 31855145 PMCID: PMC6924903 DOI: 10.3201/eid2601.190743] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023] Open
Abstract
We assessed determinants of work attendance during the first 3 days after onset of acute respiratory illness (ARI) among workers 19-64 years of age who had medically attended ARI or influenza during the 2017-2018 influenza season. The total number of days worked included days worked at the usual workplace and days teleworked. Access to paid leave was associated with fewer days worked overall and at the usual workplace during illness. Participants who indicated that employees were discouraged from coming to work with influenza-like symptoms were less likely to attend their usual workplace. Compared with workers without a telework option, those with telework access worked more days during illness overall, but there was no difference in days worked at the usual workplace. Both paid leave benefits and business practices that actively encourage employees to stay home while sick are necessary to reduce the transmission of ARI and influenza in workplaces.
Collapse
|
38
|
Wu MJ, Chung JR, Kim SS, Jackson ML, Jackson LA, Belongia EA, McLean HQ, Gaglani M, Reis M, Beeram M, Martin ET, Monto AS, Nowalk MP, Zimmerman R, Santibanez TA, Singleton JA, Patel M, Flannery B. Influenza vaccination coverage among persons seeking outpatient medical care for acute respiratory illness in five states in the United States, 2011-2012 through 2018-2019. Vaccine 2021; 39:1788-1796. [PMID: 33597114 DOI: 10.1016/j.vaccine.2021.01.065] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2020] [Revised: 01/21/2021] [Accepted: 01/26/2021] [Indexed: 01/01/2023]
Abstract
BACKGROUND In the United States (U.S.), annual influenza vaccination has been recommended for all persons aged ≥6 months with the Healthy People 2020 coverage target of 70%. However, vaccination coverage has remained around 42-49% during the past eight influenza seasons. We sought to quantify influenza vaccination coverage and factors associated with vaccination in persons seeking outpatient medical care for an acute respiratory illness (ARI). METHODS We enrolled outpatients aged ≥6 months with ARI from >50 U.S. clinics from 2011 to 2012 through 2018-2019 influenza seasons and tested for influenza with molecular assays. Vaccination status was based on documented receipt of the current season's influenza vaccine. We estimated vaccination coverage among influenza-negative study participants by study site, age, and season, and compared to state-level influenza coverage estimates in the general population based on annual immunization surveys. We used multivariable logistic regression to examine factors independently associated with receipt of influenza vaccines. RESULTS We enrolled 45,424 study participants with ARI who tested negative for influenza during the study period. Annual vaccination coverage among influenza-negative ARI patients and the general population in the participating states averaged 55% (range: 47-62%), and 52% (range: 46-54%), respectively. Among enrollees, coverage was highest among adults aged ≥65 years (82%; range, 80-85%) and lowest among adolescents aged 13-17 years (38%; range, 35-41%). Factors significantly associated with non-vaccination included non-White race, no college degree, exposure to cigarette smoke, absence of high-risk conditions, and not receiving prior season influenza vaccine. CONCLUSIONS Influenza vaccination coverage over eight seasons among outpatients with non-influenza respiratory illness was slightly higher than coverage in the general population but 15% lower than national targets. Increased efforts to promote vaccination especially in groups with lower coverage are warranted to attain optimal health benefits of influenza vaccine.
Collapse
Affiliation(s)
- Michael J Wu
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Jessie R Chung
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Sara S Kim
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Michael L Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, United States
| | - Lisa A Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, United States
| | | | - Huong Q McLean
- Marshfield Clinic Research Institute, Marshfield, WI, United States
| | - Manjusha Gaglani
- Baylor Scott and White Health, Texas A&M University College of Medicine, Temple, TX, United States
| | - Michael Reis
- Baylor Scott and White Health, Texas A&M University College of Medicine, Temple, TX, United States
| | - Madhava Beeram
- Baylor Scott and White Health, Texas A&M University College of Medicine, Temple, TX, United States
| | - Emily T Martin
- University of Michigan and Henry Ford Health System, Ann Arbor, MI, United States
| | - Arnold S Monto
- University of Michigan and Henry Ford Health System, Ann Arbor, MI, United States
| | - Mary Patricia Nowalk
- University of Pittsburgh Schools of the Health Sciences and UPMC, Pittsburgh, PA, United States
| | - Richard Zimmerman
- University of Pittsburgh Schools of the Health Sciences and UPMC, Pittsburgh, PA, United States
| | - Tammy A Santibanez
- Immunization Services Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - James A Singleton
- Immunization Services Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Manish Patel
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, United States.
| | - Brendan Flannery
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, United States
| |
Collapse
|
39
|
Li X, Mukandavire C, Cucunubá ZM, Echeverria Londono S, Abbas K, Clapham HE, Jit M, Johnson HL, Papadopoulos T, Vynnycky E, Brisson M, Carter ED, Clark A, de Villiers MJ, Eilertson K, Ferrari MJ, Gamkrelidze I, Gaythorpe KAM, Grassly NC, Hallett TB, Hinsley W, Jackson ML, Jean K, Karachaliou A, Klepac P, Lessler J, Li X, Moore SM, Nayagam S, Nguyen DM, Razavi H, Razavi-Shearer D, Resch S, Sanderson C, Sweet S, Sy S, Tam Y, Tanvir H, Tran QM, Trotter CL, Truelove S, van Zandvoort K, Verguet S, Walker N, Winter A, Woodruff K, Ferguson NM, Garske T. Estimating the health impact of vaccination against ten pathogens in 98 low-income and middle-income countries from 2000 to 2030: a modelling study. Lancet 2021; 397:398-408. [PMID: 33516338 PMCID: PMC7846814 DOI: 10.1016/s0140-6736(20)32657-x] [Citation(s) in RCA: 104] [Impact Index Per Article: 34.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/26/2019] [Revised: 07/07/2020] [Accepted: 12/03/2020] [Indexed: 12/15/2022]
Abstract
BACKGROUND The past two decades have seen expansion of childhood vaccination programmes in low-income and middle-income countries (LMICs). We quantify the health impact of these programmes by estimating the deaths and disability-adjusted life-years (DALYs) averted by vaccination against ten pathogens in 98 LMICs between 2000 and 2030. METHODS 16 independent research groups provided model-based disease burden estimates under a range of vaccination coverage scenarios for ten pathogens: hepatitis B virus, Haemophilus influenzae type B, human papillomavirus, Japanese encephalitis, measles, Neisseria meningitidis serogroup A, Streptococcus pneumoniae, rotavirus, rubella, and yellow fever. Using standardised demographic data and vaccine coverage, the impact of vaccination programmes was determined by comparing model estimates from a no-vaccination counterfactual scenario with those from a reported and projected vaccination scenario. We present deaths and DALYs averted between 2000 and 2030 by calendar year and by annual birth cohort. FINDINGS We estimate that vaccination of the ten selected pathogens will have averted 69 million (95% credible interval 52-88) deaths between 2000 and 2030, of which 37 million (30-48) were averted between 2000 and 2019. From 2000 to 2019, this represents a 45% (36-58) reduction in deaths compared with the counterfactual scenario of no vaccination. Most of this impact is concentrated in a reduction in mortality among children younger than 5 years (57% reduction [52-66]), most notably from measles. Over the lifetime of birth cohorts born between 2000 and 2030, we predict that 120 million (93-150) deaths will be averted by vaccination, of which 58 million (39-76) are due to measles vaccination and 38 million (25-52) are due to hepatitis B vaccination. We estimate that increases in vaccine coverage and introductions of additional vaccines will result in a 72% (59-81) reduction in lifetime mortality in the 2019 birth cohort. INTERPRETATION Increases in vaccine coverage and the introduction of new vaccines into LMICs have had a major impact in reducing mortality. These public health gains are predicted to increase in coming decades if progress in increasing coverage is sustained. FUNDING Gavi, the Vaccine Alliance and the Bill & Melinda Gates Foundation.
Collapse
Affiliation(s)
- Xiang Li
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, UK
| | - Christinah Mukandavire
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, UK
| | - Zulma M Cucunubá
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, UK
| | - Susy Echeverria Londono
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, UK
| | - Kaja Abbas
- London School of Hygiene & Tropical Medicine
| | - Hannah E Clapham
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore; Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam; Nuffield Department of Medicine, Oxford University, Oxford, UK
| | - Mark Jit
- London School of Hygiene & Tropical Medicine; University of Hong Kong, Hong Kong Special Administrative Region, China; Public Health England, London, UK
| | | | - Timos Papadopoulos
- Public Health England, London, UK; University of Southampton, Southampton, UK
| | - Emilia Vynnycky
- London School of Hygiene & Tropical Medicine; Public Health England, London, UK
| | | | - Emily D Carter
- Department of International Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | | | - Margaret J de Villiers
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, UK
| | | | | | | | - Katy A M Gaythorpe
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, UK
| | - Nicholas C Grassly
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, UK
| | - Timothy B Hallett
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, UK
| | - Wes Hinsley
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, UK
| | | | - Kévin Jean
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, UK; Laboratoire MESuRS, Conservatoire National des Arts et Métiers, Paris, France; Unité PACRI, Institut Pasteur, Conservatoire National des Arts et Métiers, Paris, France
| | | | | | - Justin Lessler
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | | | - Sean M Moore
- Department of Biological Sciences, University of Notre Dame, Notre Dame, IN, USA
| | - Shevanthi Nayagam
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, UK; Section of Hepatology and Gastroenterology, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Duy Manh Nguyen
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam; School of Computing, Dublin City University, Dublin, Ireland
| | - Homie Razavi
- Center for Disease Analysis Foundation, Lafayette, CO, USA
| | | | - Stephen Resch
- Center for Health Decision Science, Harvard T H Chan School of Public Health, Harvard University, Cambridge, MA, USA
| | | | - Steven Sweet
- Center for Health Decision Science, Harvard T H Chan School of Public Health, Harvard University, Cambridge, MA, USA
| | - Stephen Sy
- Center for Health Decision Science, Harvard T H Chan School of Public Health, Harvard University, Cambridge, MA, USA
| | - Yvonne Tam
- Department of International Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Hira Tanvir
- London School of Hygiene & Tropical Medicine
| | - Quan Minh Tran
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam; Department of Biological Sciences, University of Notre Dame, Notre Dame, IN, USA
| | | | - Shaun Truelove
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | | | - Stéphane Verguet
- Department of Global Health and Population, Harvard T H Chan School of Public Health, Harvard University, Cambridge, MA, USA
| | - Neff Walker
- Department of International Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Amy Winter
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Kim Woodruff
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, UK
| | - Neil M Ferguson
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, UK.
| | - Tini Garske
- MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, UK
| |
Collapse
|
40
|
Jackson ML, Scott E, Kuypers J, Nalla AK, Roychoudury P, Chu HY. Epidemiology of Respiratory Syncytial Virus Across Five Influenza Seasons Among Adults and Children One Year of Age and Older-Washington State, 2011/2012-2015/2016. J Infect Dis 2021; 223:147-156. [PMID: 32556287 DOI: 10.1093/infdis/jiaa331] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Accepted: 06/12/2020] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Vaccines and novel prophylactics against respiratory syncytial virus (RSV) are in development. To provide a baseline for evaluating these interventions, we characterized the incidence and molecular epidemiology of RSV in persons aged ≥1 year. METHODS We identified patients with medically attended acute respiratory illness (MAARI) from the 2011/2012 through 2015/2016 influenza seasons among members of Kaiser Permanente Washington. We estimated the cumulative incidence of MAARI for laboratory-confirmed RSV or influenza infection. RESULTS Annual cohorts ranged from 82 266 to 162 633 individuals, 14% of whom were children aged 1 to 17 years. Cumulative incidence of RSV each season ranged from 14 per 1000 population (95% confidence interval [CI], 12-16) to 22 per 1000 (95% CI, 19-25). Incidence of RSV was greater than influenza in children aged 12-23 months and 2-4 years; incidence of influenza was greater in other age groups. Respiratory syncytial virus subtype A dominated in 2011/2012, 2012/2013, and 2015/2016, with ON1 being the most common genotype. Respiratory syncytial virus subtype B dominated in 2013/2014 and 2014/2015, primarily of the BA genotype. CONCLUSIONS The burden of RSV is comparable to that of influenza across the life course. These results provide a baseline for evaluating the impact of new RSV interventions on the epidemiology of RSV.
Collapse
Affiliation(s)
- Michael L Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington, USA
| | - Emily Scott
- University of Washington School of Medicine, Seattle, Washington, USA
| | - Jane Kuypers
- University of Washington School of Medicine, Seattle, Washington, USA
| | - Arun K Nalla
- University of Washington School of Medicine, Seattle, Washington, USA
| | | | - Helen Y Chu
- University of Washington School of Medicine, Seattle, Washington, USA
| |
Collapse
|
41
|
Rogers JH, Link AC, McCulloch D, Brandstetter E, Newman KL, Jackson ML, Hughes JP, Englund JA, Boeckh M, Sugg N, Ilcisin M, Sibley TR, Fay K, Lee J, Han P, Truong M, Richardson M, Nickerson DA, Starita LM, Bedford T, Chu HY. Characteristics of COVID-19 in Homeless Shelters : A Community-Based Surveillance Study. Ann Intern Med 2021; 174:42-49. [PMID: 32931328 PMCID: PMC7517131 DOI: 10.7326/m20-3799] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
BACKGROUND Homeless shelters are a high-risk setting for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission because of crowding and shared hygiene facilities. OBJECTIVE To investigate SARS-CoV-2 case counts across several adult and family homeless shelters in a major metropolitan area. DESIGN Cross-sectional, community-based surveillance study. (ClinicalTrials.gov: NCT04141917). SETTING 14 homeless shelters in King County, Washington. PARTICIPANTS A total of 1434 study encounters were done in shelter residents and staff, regardless of symptoms. INTERVENTION 2 strategies were used for SARS-CoV-2 testing: routine surveillance and contact tracing ("surge testing") events. MEASUREMENTS The primary outcome measure was test positivity rate of SARS-CoV-2 infection at shelters, determined by dividing the number of positive cases by the total number of participant encounters, regardless of symptoms. Sociodemographic, clinical, and virologic variables were assessed as correlates of viral positivity. RESULTS Among 1434 encounters, 29 (2% [95% CI, 1.4% to 2.9%]) cases of SARS-CoV-2 infection were detected across 5 shelters. Most (n = 21 [72.4%]) were detected during surge testing events rather than routine surveillance, and most (n = 21 [72.4% {CI, 52.8% to 87.3%}]) were asymptomatic at the time of sample collection. Persons who were positive for SARS-CoV-2 were more frequently aged 60 years or older than those without SARS-CoV-2 (44.8% vs. 15.9%). Eighty-six percent of persons with positive test results slept in a communal space rather than in a private or shared room. LIMITATION Selection bias due to voluntary participation and a relatively small case count. CONCLUSION Active surveillance and surge testing were used to detect multiple cases of asymptomatic and symptomatic SARS-CoV-2 infection in homeless shelters. The findings suggest an unmet need for routine viral testing outside of clinical settings for homeless populations. PRIMARY FUNDING SOURCE Gates Ventures.
Collapse
Affiliation(s)
- Julia H Rogers
- University of Washington, Seattle, Washington (J.H.R., A.C.L., D.M., E.B., K.L.N., J.P.H., N.S., M.R., D.A.N., H.Y.C.)
| | - Amy C Link
- University of Washington, Seattle, Washington (J.H.R., A.C.L., D.M., E.B., K.L.N., J.P.H., N.S., M.R., D.A.N., H.Y.C.)
| | - Denise McCulloch
- University of Washington, Seattle, Washington (J.H.R., A.C.L., D.M., E.B., K.L.N., J.P.H., N.S., M.R., D.A.N., H.Y.C.)
| | - Elisabeth Brandstetter
- University of Washington, Seattle, Washington (J.H.R., A.C.L., D.M., E.B., K.L.N., J.P.H., N.S., M.R., D.A.N., H.Y.C.)
| | - Kira L Newman
- University of Washington, Seattle, Washington (J.H.R., A.C.L., D.M., E.B., K.L.N., J.P.H., N.S., M.R., D.A.N., H.Y.C.)
| | - Michael L Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington (M.L.J.)
| | - James P Hughes
- University of Washington, Seattle, Washington (J.H.R., A.C.L., D.M., E.B., K.L.N., J.P.H., N.S., M.R., D.A.N., H.Y.C.)
| | - Janet A Englund
- Seattle Children's Research Institute, University of Washington, Seattle, Washington (J.A.E.)
| | - Michael Boeckh
- Fred Hutchinson Cancer Research Center, Seattle, Washington (M.B., M.I., T.R.S., K.F., J.L., T.B.)
| | - Nancy Sugg
- University of Washington, Seattle, Washington (J.H.R., A.C.L., D.M., E.B., K.L.N., J.P.H., N.S., M.R., D.A.N., H.Y.C.)
| | - Misja Ilcisin
- Fred Hutchinson Cancer Research Center, Seattle, Washington (M.B., M.I., T.R.S., K.F., J.L., T.B.)
| | - Thomas R Sibley
- Fred Hutchinson Cancer Research Center, Seattle, Washington (M.B., M.I., T.R.S., K.F., J.L., T.B.)
| | - Kairsten Fay
- Fred Hutchinson Cancer Research Center, Seattle, Washington (M.B., M.I., T.R.S., K.F., J.L., T.B.)
| | - Jover Lee
- Fred Hutchinson Cancer Research Center, Seattle, Washington (M.B., M.I., T.R.S., K.F., J.L., T.B.)
| | - Peter Han
- University of Washington and Brotman Baty Institute for Precision Medicine, Seattle, Washington (P.H., M.T., L.M.S.)
| | - Melissa Truong
- University of Washington and Brotman Baty Institute for Precision Medicine, Seattle, Washington (P.H., M.T., L.M.S.)
| | - Matthew Richardson
- University of Washington, Seattle, Washington (J.H.R., A.C.L., D.M., E.B., K.L.N., J.P.H., N.S., M.R., D.A.N., H.Y.C.)
| | - Deborah A Nickerson
- University of Washington, Seattle, Washington (J.H.R., A.C.L., D.M., E.B., K.L.N., J.P.H., N.S., M.R., D.A.N., H.Y.C.)
| | - Lea M Starita
- University of Washington and Brotman Baty Institute for Precision Medicine, Seattle, Washington (P.H., M.T., L.M.S.)
| | - Trevor Bedford
- Fred Hutchinson Cancer Research Center, Seattle, Washington (M.B., M.I., T.R.S., K.F., J.L., T.B.)
| | - Helen Y Chu
- University of Washington, Seattle, Washington (J.H.R., A.C.L., D.M., E.B., K.L.N., J.P.H., N.S., M.R., D.A.N., H.Y.C.)
| | | |
Collapse
|
42
|
Chung JR, Kim SS, Jackson ML, Jackson LA, Belongia EA, King JP, Zimmerman RK, Nowalk MP, Martin ET, Monto AS, Gaglani M, Smith ME, Patel M, Flannery B. Clinical Symptoms Among Ambulatory Patients Tested for SARS-CoV-2. Open Forum Infect Dis 2020; 8:ofaa576. [PMID: 33537361 PMCID: PMC7717425 DOI: 10.1093/ofid/ofaa576] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Accepted: 11/17/2020] [Indexed: 12/20/2022] Open
Abstract
We compared symptoms and characteristics of 4961 ambulatory patients with and without laboratory-confirmed severe acute respiratory syndrome coronavirus 2 infection. Findings indicate that clinical symptoms alone would be insufficient to distinguish between coronavirus disease 2019 and other respiratory infections (eg, influenza) and/or to evaluate the effects of preventive interventions (eg, vaccinations).
Collapse
Affiliation(s)
- Jessie R Chung
- Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Sara S Kim
- Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Michael L Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington, USA
| | - Lisa A Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington, USA
| | | | - Jennifer P King
- Marshfield Clinic Research Institute, Marshfield, Wisconsin, USA
| | | | | | | | | | - Manjusha Gaglani
- Texas A&M University College of Medicine, Baylor Scott & White Health, Temple, Texas, USA
| | - Michael E Smith
- Texas A&M University College of Medicine, Baylor Scott & White Health, Temple, Texas, USA
| | - Manish Patel
- Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Brendan Flannery
- Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| |
Collapse
|
43
|
Newman KL, Rogers JH, McCulloch D, Wilcox N, Englund JA, Boeckh M, Uyeki TM, Jackson ML, Starita L, Hughes JP, Chu HY. Point-of-care molecular testing and antiviral treatment of influenza in residents of homeless shelters in Seattle, WA: study protocol for a stepped-wedge cluster-randomized controlled trial. Trials 2020; 21:956. [PMID: 33228787 PMCID: PMC7682130 DOI: 10.1186/s13063-020-04871-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2020] [Accepted: 11/04/2020] [Indexed: 11/10/2022] Open
Abstract
Introduction Influenza is an important public health problem, but data on the impact of influenza among homeless shelter residents are limited. The primary aim of this study is to evaluate whether on-site testing and antiviral treatment of influenza in residents of homeless shelters reduces influenza spread in these settings. Methods and analysis This study is a stepped-wedge cluster-randomized trial of on-site testing and antiviral treatment for influenza in nine homeless shelter sites within the Seattle metropolitan area. Participants with acute respiratory illness (ARI), defined as two or more respiratory symptoms or new or worsening cough with onset in the prior 7 days, are eligible to enroll. Approximately 3200 individuals are estimated to participate from October to May across two influenza seasons. All sites will start enrollment in the control arm at the beginning of each season, with routine surveillance for ARI. Sites will be randomized at different timepoints to enter the intervention arm, with implementation of a test-and-treat strategy for individuals with two or fewer days of symptoms. Eligible individuals will be tested on-site with a point-of-care influenza test. If the influenza test is positive and symptom onset is within 48 h, participants will be administered antiviral treatment with baloxavir or oseltamivir depending upon age and comorbidities. Participants will complete a questionnaire on demographics and symptom duration and severity. The primary endpoint is the incidence of influenza in the intervention period compared to the control period, after adjusting for time trends. Trial registration ClinicalTrials.gov NCT04141917. Registered 28 October 2019. Trial sponsor: University of Washington. Supplementary information The online version contains supplementary material available at 10.1186/s13063-020-04871-5.
Collapse
Affiliation(s)
- Kira L Newman
- Division of Allergy and Infectious Diseases, University of Washington, UW Medicine at South Lake Union, Chu Lab Room E630, 750 Republican St., Seattle, WA, 98109, USA
| | - Julia H Rogers
- Division of Allergy and Infectious Diseases, University of Washington, UW Medicine at South Lake Union, Chu Lab Room E630, 750 Republican St., Seattle, WA, 98109, USA
| | - Denise McCulloch
- Division of Allergy and Infectious Diseases, University of Washington, UW Medicine at South Lake Union, Chu Lab Room E630, 750 Republican St., Seattle, WA, 98109, USA
| | - Naomi Wilcox
- Division of Allergy and Infectious Diseases, University of Washington, UW Medicine at South Lake Union, Chu Lab Room E630, 750 Republican St., Seattle, WA, 98109, USA
| | - Janet A Englund
- Division of Allergy and Infectious Diseases, University of Washington, UW Medicine at South Lake Union, Chu Lab Room E630, 750 Republican St., Seattle, WA, 98109, USA.,Seattle Children's Research Institute, Seattle, WA, USA
| | - Michael Boeckh
- Division of Allergy and Infectious Diseases, University of Washington, UW Medicine at South Lake Union, Chu Lab Room E630, 750 Republican St., Seattle, WA, 98109, USA.,Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Timothy M Uyeki
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | | | - Lea Starita
- Division of Allergy and Infectious Diseases, University of Washington, UW Medicine at South Lake Union, Chu Lab Room E630, 750 Republican St., Seattle, WA, 98109, USA
| | - James P Hughes
- Division of Allergy and Infectious Diseases, University of Washington, UW Medicine at South Lake Union, Chu Lab Room E630, 750 Republican St., Seattle, WA, 98109, USA
| | - Helen Y Chu
- Division of Allergy and Infectious Diseases, University of Washington, UW Medicine at South Lake Union, Chu Lab Room E630, 750 Republican St., Seattle, WA, 98109, USA.
| | | |
Collapse
|
44
|
Affiliation(s)
- Manish M Patel
- COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Michael L Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington
| | - Jill Ferdinands
- COVID-19 Response Team, Centers for Disease Control and Prevention, Atlanta, Georgia
| |
Collapse
|
45
|
Jackson ML. Low-impact social distancing interventions to mitigate local epidemics of SARS-CoV-2. Microbes Infect 2020; 22:611-616. [PMID: 32977019 PMCID: PMC7508051 DOI: 10.1016/j.micinf.2020.09.006] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Revised: 09/10/2020] [Accepted: 09/15/2020] [Indexed: 01/08/2023]
Abstract
Many jurisdictions implemented intensive social distancing to suppress SARS-CoV-2 transmission. The challenge now is to mitigate the ongoing COVID-19 epidemic without overburdening economic and social activities. An agent-based model simulated the population of King County, Washington. SARS-CoV-2 transmission probabilities were estimated by fitting simulated to observed hospital admissions. Interventions considered included encouraging telecommuting, reducing contacts to high-risk persons, and reductions to contacts outside of the home, among others. Removing all existing interventions would result in nearly 42,000 COVID-19 hospitalizations between June 2020 and January 2021, with peak hospital occupancy exceeding available beds 6-fold. Combining interventions is predicted to reduce total hospitalizations by 48% (95% CI, 47-49%), with peak COVID-19 hospital occupancy of 70% of total beds. Targeted school closures can further reduce the peak occupancy. Combining low-impact interventions may mitigate the course of the COVID-19 epidemic, keeping hospital burden within the capacity of the healthcare system.
Collapse
Affiliation(s)
- Michael L Jackson
- Kaiser Permanente Washington Health Research Institute, 1730 Minor Ave Suite 1600, Seattle, WA, USA.
| |
Collapse
|
46
|
Balasubramani GK, Choi WS, Nowalk MP, Zimmerman RK, Monto AS, Martin ET, Belongia EA, McLean HQ, Gaglani M, Murthy K, Jackson ML, Jackson LA, Chung JR, Spencer S, Fry AM, Patel M, Flannery B. Relative effectiveness of high dose versus standard dose influenza vaccines in older adult outpatients over four seasons, 2015-16 to 2018-19. Vaccine 2020; 38:6562-6569. [PMID: 32800465 DOI: 10.1016/j.vaccine.2020.08.011] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Revised: 07/28/2020] [Accepted: 08/03/2020] [Indexed: 12/31/2022]
Abstract
BACKGROUND New influenza vaccine formulations are designed to improve vaccine effectiveness and protect those most vulnerable to infection. High dose trivalent inactivated influenza vaccine (HD-IIV3), licensed for ages ≥65 years, produces greater antibody responses and efficacy in clinical trials, but post-licensure vaccine effectiveness (VE) compared to standard dose (SD-IIV3/4) vaccine remains an open question. METHODS Using a test-negative, case control design and propensity analyses to adjust for confounding, US Influenza VE Network data from the 2015-2016 through 2018-2019 seasons were analyzed to determine relative VE (rVE) between HD-IIV3 and SD-IIV3/4 among outpatients ≥65 years old presenting with acute respiratory illness. Influenza vaccination status was derived from electronic medical records and immunization registries. RESULTS Among 3861 enrollees, 2993 (78%) were vaccinated; 1573 (53%) received HD-IIV3 and 1420 (47%) received SD-IIV3/4. HD-IIV3 recipients differed from SD-IIV3/4 recipients by race, previous vaccination, number of outpatient visits in the previous year and timing of vaccination, and were balanced in the propensity model except the timing of vaccination. Compared with no vaccination, significant protection against any influenza A was observed from both HD-IIV3 (VE = 29%; 95%CI = 10%, 44%) and SD-IIV3/4 (VE = 24%; 95%CI = 5%, 39%); rVE = 18% (95%CI = 0%, 33%, SD as referent). When stratified by virus type, against A/H1N1, HD-IIV3 VE was 30% (95%CI = -7%, 54%), SD-IIV3/4 VE was 40% (95%CI = 10%, 61%), and rVE = -32%; (95%CI = -94%, 11%); Against A/H3N2, HD-IIV3 VE was 31% (95%CI = 9%, 47%), SD-IIV3/4 VE was 19% (95%CI = -5%, 37%), and rVE = 27%; (95% CI = 9%, 42%). CONCLUSIONS Among adults ≥65 years of age, recipients of standard and high dose influenza vaccines differed significantly in their characteristics. After adjusting for these differences, high dose vaccine offered more protection against A/H3N2 and borderline significant protection against all influenza A requiring outpatient care during the 2015-2018 influenza seasons.
Collapse
Affiliation(s)
- G K Balasubramani
- University of Pittsburgh, Schools of the Health Sciences and UPMC, Pittsburgh, PA, USA
| | - Won Suk Choi
- Division of Infectious Diseases, Department of Internal Medicine, Korea University College of Medicine, Korea University, Ansan Hospital, Seoul, Republic of Korea
| | - Mary Patricia Nowalk
- University of Pittsburgh, Schools of the Health Sciences and UPMC, Pittsburgh, PA, USA.
| | - Richard K Zimmerman
- University of Pittsburgh, Schools of the Health Sciences and UPMC, Pittsburgh, PA, USA
| | - Arnold S Monto
- University of Michigan, Ann Arbor MI and Henry Ford Health System, Detroit, MI, USA
| | - Emily T Martin
- University of Michigan, Ann Arbor MI and Henry Ford Health System, Detroit, MI, USA
| | | | - Huong Q McLean
- Marshfield Clinic Research Institute, Marshfield, WI, USA
| | - Manjusha Gaglani
- Baylor Scott and White Health, Texas A&M University Health Science Center, College of Medicine, Temple, TX, USA
| | - Kempapura Murthy
- Baylor Scott and White Health, Texas A&M University Health Science Center, College of Medicine, Temple, TX, USA
| | - Michael L Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Lisa A Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Jessie R Chung
- Centers for Disease Control and Prevention, Influenza Division, National Center for Immunization and Respiratory Diseases, Atlanta, GA, USA
| | - Sarah Spencer
- Centers for Disease Control and Prevention, Influenza Division, National Center for Immunization and Respiratory Diseases, Atlanta, GA, USA
| | - Alicia M Fry
- Centers for Disease Control and Prevention, Influenza Division, National Center for Immunization and Respiratory Diseases, Atlanta, GA, USA
| | - Manish Patel
- Centers for Disease Control and Prevention, Influenza Division, National Center for Immunization and Respiratory Diseases, Atlanta, GA, USA
| | - Brendan Flannery
- Centers for Disease Control and Prevention, Influenza Division, National Center for Immunization and Respiratory Diseases, Atlanta, GA, USA
| | | |
Collapse
|
47
|
Flannery B, Chung JR, Monto AS, Martin ET, Belongia EA, McLean HQ, Gaglani M, Murthy K, Zimmerman RK, Nowalk MP, Jackson ML, Jackson LA, Rolfes MA, Spencer S, Fry AM. Influenza Vaccine Effectiveness in the United States During the 2016-2017 Season. Clin Infect Dis 2020; 68:1798-1806. [PMID: 30204854 DOI: 10.1093/cid/ciy775] [Citation(s) in RCA: 82] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2018] [Accepted: 09/06/2018] [Indexed: 12/26/2022] Open
Abstract
BACKGROUND In recent influenza seasons, the effectiveness of inactivated influenza vaccines against circulating A(H3N2) virus has been lower than against A(H1N1)pdm09 and B viruses, even when circulating viruses remained antigenically similar to vaccine components. METHODS During the 2016-2017 influenza season, vaccine effectiveness (VE) across age groups and vaccine types was examined among outpatients with acute respiratory illness at 5 US sites using a test-negative design that compared the odds of vaccination among reverse transcription polymerase chain reaction-confirmed influenza positives and negatives. RESULTS Among 7083 enrollees, 1342 (19%) tested positive for influenza A(H3N2), 648 (9%) were positive for influenza B (including B/Yamagata, n = 577), and 5040 (71%) were influenza negative. Vaccine effectiveness was 40% (95% confidence interval [CI], 32% to 46%) against any influenza virus, 33% (95% CI, 23% to 41%) against influenza A(H3N2) viruses, and 53% (95% CI, 43% to 61%) against influenza B viruses. CONCLUSIONS The 2016-2017 influenza vaccines provided moderate protection against any influenza among outpatients but were less protective against influenza A(H3N2) viruses than B viruses. Approaches to improving effectiveness against A(H3N2) viruses are needed.
Collapse
Affiliation(s)
- Brendan Flannery
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Jessie R Chung
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Arnold S Monto
- University of Michigan School of Public Health, Ann Arbor
| | - Emily T Martin
- University of Michigan School of Public Health, Ann Arbor
| | | | | | - Manjusha Gaglani
- Baylor Scott and White Health, Temple.,Texas A&M University Health Science Center College of Medicine, Temple
| | | | | | | | | | - Lisa A Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle
| | - Melissa A Rolfes
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Sarah Spencer
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Alicia M Fry
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia
| | | |
Collapse
|
48
|
Havers FP, Chung JR, Belongia EA, McLean HQ, Gaglani M, Murthy K, Zimmerman RK, Nowalk MP, Jackson ML, Jackson LA, Monto AS, Petrie JG, Fry AM, Flannery B. Influenza Vaccine Effectiveness and Statin Use Among Adults in the United States, 2011-2017. Clin Infect Dis 2020; 68:1616-1622. [PMID: 30371753 DOI: 10.1093/cid/ciy780] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2018] [Accepted: 09/20/2018] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Statin medications have immunomodulatory effects. Several recent studies suggest that statins may reduce influenza vaccine response and reduce influenza vaccine effectiveness (VE). METHODS We compared influenza VE in statin users and nonusers aged ≥45 years enrolled in the US Vaccine Effectiveness Network study over 6 influenza seasons (2011-2012 through 2016-2017). All enrollees presented to outpatients clinics with acute respiratory illness and were tested for influenza. Information on vaccination status, medical history, and statin use at the time of vaccination were collected by medical and pharmacy records. Using a test-negative design, we estimated VE as (1 - OR) × 100, in which OR is the odds ratio for testing positive for influenza virus among vaccinated vs unvaccinated participants. RESULTS Among 11692 eligible participants, 3359 (30%) were statin users and 2806 (24%) tested positive for influenza virus infection; 78% of statin users and 60% of nonusers had received influenza vaccine. After adjusting for potential confounders, influenza VE was 36% (95% confidence interval [CI], 22%-47%) among statin users and 39% (95% CI, 32%-45%) among nonusers. We observed no significant modification of VE by statin use. VE against influenza A(H1N1)pdm09, A(H3N2), and B viruses were similar among statin users and nonusers. CONCLUSIONS In this large observational study, influenza VE against laboratory-confirmed influenza illness was not affected by current statin use among persons aged ≥45 years. Statin use did not modify the effect of vaccination on influenza when analyzed by type and subtype.
Collapse
Affiliation(s)
- Fiona P Havers
- Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Jessie R Chung
- Centers for Disease Control and Prevention, Atlanta, Georgia
| | | | | | - Manjusha Gaglani
- Baylor Scott and White Health.,Texas A&M University Health Science Center College of Medicine, Temple
| | | | | | | | | | - Lisa A Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle
| | - Arnold S Monto
- University of Michigan School of Public Health, Ann Arbor
| | | | - Alicia M Fry
- Centers for Disease Control and Prevention, Atlanta, Georgia
| | | |
Collapse
|
49
|
Thompson MG, Kwong JC, Regan AK, Katz MA, Drews SJ, Azziz-Baumgartner E, Klein NP, Chung H, Effler PV, Feldman BS, Simmonds K, Wyant BE, Dawood FS, Jackson ML, Fell DB, Levy A, Barda N, Svenson LW, Fink RV, Ball SW, Naleway A. Influenza Vaccine Effectiveness in Preventing Influenza-associated Hospitalizations During Pregnancy: A Multi-country Retrospective Test Negative Design Study, 2010-2016. Clin Infect Dis 2020; 68:1444-1453. [PMID: 30307490 DOI: 10.1093/cid/ciy737] [Citation(s) in RCA: 98] [Impact Index Per Article: 24.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2018] [Accepted: 10/05/2018] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND To date, no study has examined influenza vaccine effectiveness (IVE) against laboratory-confirmed influenza-associated hospitalizations during pregnancy. METHODS The Pregnancy Influenza Vaccine Effectiveness Network (PREVENT) consisted of public health or healthcare systems with integrated laboratory, medical, and vaccination records in Australia, Canada (Alberta and Ontario), Israel, and the United States (California, Oregon, and Washington). Sites identified pregnant women aged 18 through 50 years whose pregnancies overlapped with local influenza seasons from 2010 through 2016. Administrative data were used to identify hospitalizations with acute respiratory or febrile illness (ARFI) and clinician-ordered real-time reverse transcription polymerase chain reaction (rRT-PCR) testing for influenza viruses. Overall IVE was estimated using the test-negative design and adjusting for site, season, season timing, and high-risk medical conditions. RESULTS Among 19450 hospitalizations with an ARFI discharge diagnosis (across 25 site-specific study seasons), only 1030 (6%) of the pregnant women were tested for influenza viruses by rRT-PCR. Approximately half of these women had pneumonia or influenza discharge diagnoses (54%). Influenza A or B virus infections were detected in 598/1030 (58%) of the ARFI hospitalizations with influenza testing. Across sites and seasons, 13% of rRT-PCR-confirmed influenza-positive pregnant women were vaccinated compared with 22% of influenza-negative pregnant women; the adjusted overall IVE was 40% (95% confidence interval = 12%-59%) against influenza-associated hospitalization during pregnancy. CONCLUSION Between 2010 and 2016, influenza vaccines offered moderate protection against laboratory-confirmed influenza-associated hospitalizations during pregnancy, which may further inform the benefits of maternal influenza vaccination programs.
Collapse
Affiliation(s)
- Mark G Thompson
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Jeffrey C Kwong
- Institute for Clinical Evaluative Sciences.,Public Health Ontario.,Department of Family and Community Medicine, University of Toronto.,Dalla Lana School of Public Health, University of Toronto.,University Health Network, Toronto, Ontario, Canada
| | - Annette K Regan
- School of Public Health, Curtin University, Perth.,Wesfarmers Centre of Vaccines and Infectious Diseases, Telethon Kids Institute, Subiaco, Western Australia, Australia
| | - Mark A Katz
- Chief Physician's Office, Clalit Health Services, Clalit Research Institute, Tel Aviv.,School of Public Health, Medical School for International Health, Ben Gurion University, Bersheva, Israel.,University of Michigan School of Public Health, Ann Arbor
| | - Steven J Drews
- University of Alberta.,ProvLab Alberta, Edmonton, Canada
| | | | - Nicola P Klein
- Kaiser Permanente Vaccine Study Center, Kaiser Permanente Northern California, Oakland
| | | | - Paul V Effler
- Communicable Disease Control Directorate, Department of Health Western Australia, Perth, Australia
| | - Becca S Feldman
- Chief Physician's Office, Clalit Health Services, Clalit Research Institute, Tel Aviv
| | - Kimberley Simmonds
- Cumming School of Medicine, University of Calgary.,Alberta Health, Edmonton, Canada
| | | | - Fatimah S Dawood
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Michael L Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington
| | - Deshayne B Fell
- Institute for Clinical Evaluative Sciences.,School of Epidemiology and Public Health, University of Ottawa.,Children's Hospital of Eastern Ontario Research Institute, Ottawa, Canada
| | - Avram Levy
- Department of Microbiology, QEII Medical Centre, PathWest Laboratory Medicine, Nedlands, Western Australia, Australia
| | - Noam Barda
- Chief Physician's Office, Clalit Health Services, Clalit Research Institute, Tel Aviv
| | - Lawrence W Svenson
- Alberta Health, Edmonton, Canada.,Division of Preventive Medicine.,School of Public Health, University of Alberta, Edmonton.,Department of Community Health Sciences, University of Calgary, Alberta, Canada
| | | | | | - Allison Naleway
- Center for Health Research, Kaiser Permanente Northwest, Portland, Oregon
| | | |
Collapse
|
50
|
Chung JR, Flannery B, Gaglani M, Smith ME, Reis EC, Hickey RW, Jackson ML, Jackson LA, Belongia EA, McLean HQ, Martin ET, Segaloff HE, Kim SS, Patel MM. Patterns of Influenza Vaccination and Vaccine Effectiveness Among Young US Children Who Receive Outpatient Care for Acute Respiratory Tract Illness. JAMA Pediatr 2020; 174:705-713. [PMID: 32364599 PMCID: PMC7199168 DOI: 10.1001/jamapediatrics.2020.0372] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
IMPORTANCE The burden of influenza among young children is high, and influenza vaccination is the primary strategy to prevent the virus and its complications. Less is known about differences in clinical protection following 1 vs 2 doses of initial influenza vaccination. OBJECTIVES To describe patterns of influenza vaccination among young children who receive outpatient care for acute respiratory tract illness in the US and compare vaccine effectiveness (VE) against medically attended laboratory-confirmed influenza by number of influenza vaccine doses received. DESIGN This test-negative case-control study was conducted in outpatient clinics, including emergency departments, at 5 sites of the US Influenza Vaccine Effectiveness Network during the 2014-2015 through 2017-2018 influenza seasons. The present study was performed from November 5, 2014, to April 12, 2018, during periods of local influenza circulation. Children aged 6 months to 8 years with an acute respiratory tract illness with cough who presented for outpatient care within 7 days of illness onset were included. All children were tested using real-time, reverse-transcriptase polymerase chain reaction for influenza for research purposes. EXPOSURES Vaccination in the enrollment season with either 1 or 2 doses of inactivated influenza vaccine as documented from electronic medical records, including state immunization information systems. MAIN OUTCOMES AND MEASURES Medically attended acute respiratory tract infection with real-time, reverse-transcriptase polymerase chain reaction testing for influenza. RESULTS Of 7533 children, 3480 children (46%) were girls, 4687 children (62%) were non-Hispanic white, and 4871 children (65%) were younger than 5 years. A total of 3912 children (52%) were unvaccinated in the enrollment season, 2924 children (39%) were fully vaccinated, and 697 children (9%) were partially vaccinated. Adjusted VE against any influenza was 51% (95% CI, 44%-57%) among fully vaccinated children and 41% (95% CI, 25%-54%) among partially vaccinated children. Among 1519 vaccine-naive children aged 6 months to 2 years, the VE of 2 doses in the enrollment season was 53% (95% CI, 28%-70%), and the VE of 1 dose was 23% (95% CI, -11% to 47%); those who received 2 doses were less likely to test positive for influenza compared with children who received only 1 dose (adjusted odds ratio, 0.57; 95% CI, 0.35-0.93). CONCLUSIONS AND RELEVANCE Consistent with US influenza vaccine policy, receipt of the recommended number of doses resulted in higher VE than partial vaccination in 4 influenza seasons. Efforts to improve 2-dose coverage for previously unvaccinated children may reduce the burden of influenza in this population.
Collapse
Affiliation(s)
- Jessie R. Chung
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Brendan Flannery
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Manjusha Gaglani
- Texas A&M University Health Science Center College of Medicine, Temple,Baylor Scott & White Health Research Institute, Temple, Texas
| | | | - Evelyn C. Reis
- Department of Pediatrics, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Robert W. Hickey
- Department of Pediatric Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Michael L. Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington
| | - Lisa A. Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington
| | - Edward A. Belongia
- Center for Clinical Epidemiology & Population Health, Marshfield Clinic Research Institute, Marshfield, Wisconsin
| | - Huong Q. McLean
- Center for Clinical Epidemiology & Population Health, Marshfield Clinic Research Institute, Marshfield, Wisconsin
| | - Emily T. Martin
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor
| | - Hannah E. Segaloff
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor
| | - Sara S. Kim
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Manish M. Patel
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia
| |
Collapse
|