1
|
Hitchings MDT, Lewnard JA, Dean NE, Ko AI, Ranzani OT, Andrews JR, Cummings DAT. Use of Recently Vaccinated Individuals to Detect Bias in Test-Negative Case-Control Studies of COVID-19 Vaccine Effectiveness. Epidemiology 2022; 33:450-456. [PMID: 35384900 PMCID: PMC9148635 DOI: 10.1097/ede.0000000000001484] [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] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Accepted: 03/17/2022] [Indexed: 11/30/2022]
Abstract
Postauthorization observational studies play a key role in understanding COVID-19 vaccine effectiveness following the demonstration of efficacy in clinical trials. Although bias due to confounding, selection bias, and misclassification can be mitigated through careful study design, unmeasured confounding is likely to remain in these observational studies. Phase III trials of COVID-19 vaccines have shown that protection from vaccination does not occur immediately, meaning that COVID-19 risk should be similar in recently vaccinated and unvaccinated individuals, in the absence of confounding or other bias. Several studies have used the estimated effectiveness among recently vaccinated individuals as a negative control exposure to detect bias in vaccine effectiveness estimates. In this paper, we introduce a theoretical framework to describe the interpretation of such a bias indicator in test-negative studies, and outline strong assumptions that would allow vaccine effectiveness among recently vaccinated individuals to serve as a negative control exposure.
Collapse
Affiliation(s)
- Matt D. T. Hitchings
- From the Department of Biology, University of Florida, Gainesville, FL
- Emerging Pathogens Institute, University of Florida, Gainesville, FL
| | - Joseph A. Lewnard
- Division of Epidemiology, School of Public Health, University of California, Berkeley, Berkeley, CA
- Division of Infectious Diseases & Vaccinology, School of Public Health, University of California, Berkeley, Berkeley, CA
- Center for Computational Biology, College of Engineering, University of California, Berkeley, Berkeley, CA
| | - Natalie E. Dean
- Emerging Pathogens Institute, University of Florida, Gainesville, FL
- Department of Biostatistics, University of Florida, Gainesville, FL
| | - Albert I. Ko
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT
- Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, BA, Brazil
| | - Otavio T. Ranzani
- Barcelona Institute for Global Health, ISGlobal, Barcelona, Spain
- Pulmonary Division, Heart Institute (InCor), Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, Brazil
| | - Jason R. Andrews
- Division of Infectious Diseases and Geographic Medicine, Stanford University, Stanford, CA
| | - Derek A. T. Cummings
- From the Department of Biology, University of Florida, Gainesville, FL
- Emerging Pathogens Institute, University of Florida, Gainesville, FL
| |
Collapse
|
2
|
Hitchings MD, Ranzani OT, Lind ML, Dorion M, D’Agostini TL, de Paula RC, de Paula OFP, de Moura Villela EF, Torres MSS, de Oliveira SB, Schulz W, Almiron M, Said R, de Oliveira RD, da Silva PV, de Araújo WN, Gorinchteyn JC, Dean NE, Andrews JR, Cummings DA, Ko AI, Croda J. Change in COVID-19 risk over time following vaccination with CoronaVac: A testnegative case-control study. medRxiv 2021:2021.12.23.21268335. [PMID: 34988559 PMCID: PMC8728874 DOI: 10.1101/2021.12.23.21268335] [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] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
OBJECTIVE To estimate the change in odds of covid-19 over time following primary series completion of the inactivated whole virus vaccine, CoronaVac (Sinovac Biotech) in São Paulo state, Brazil. DESIGN Test negative case-control study. SETTING Community testing for covid-19 in São Paulo state, Brazil. PARTICIPANTS Adults aged 18-120 years who were residents of São Paulo state, without a previous laboratory-confirmed covid-19 infection, who received only two doses of CoronaVac, and underwent reverse transcription polymerase chain reaction (RT-PCR) testing for SARS-CoV-2 from 17 January to 30 September 2021. MAIN OUTCOME MEASURES RT-PCR-confirmed symptomatic covid-19 and associated hospital admissions and deaths. Cases were pair-matched to test-negative controls by age (in 5-year bands), municipality of residence, healthcare worker (HCW) status, and date of RT-PCR test (±3 days). Conditional logistic regression was adjusted for sex, number of covid-19-associated comorbidities, race, and previous acute respiratory infection. RESULTS From 137,820 eligible individuals, 37,929 cases with symptomatic covid-19 and 25,756 test-negative controls with covid-19 symptoms were formed into 37,929 matched pairs. Adjusted odds ratios of symptomatic covid-19 increased with time since series completion, and this increase was greater in younger individuals, and among HCWs compared to non-HCWs. Adjusted odds ratios of covid-19 hospitalisation or death were significantly increased from 98 days since series completion, compared to individuals vaccinated 14-41 days previously: 1.40 (95% confidence interval 1.09 to 1.79) from 98-125 days, 1.55 (1.16 to 2.07) from 126-153 days, 1.56 (1.12 to 2.18) from 154-181 days, and 2.12 (1.39-3.22) from 182 days. CONCLUSIONS In the general population of São Paulo state, Brazil, an increase in odds of moderate and severe covid-19 outcomes was observed over time following primary series completion with CoronaVac.
Collapse
Affiliation(s)
- Matt D.T. Hitchings
- Department of Biostatistics, College of Public Health & Health Professions, University of Florida, Gainesville, FL, USA
| | - Otavio T. Ranzani
- Barcelona Institute for Global Health, ISGlobal, Barcelona, Spain
- Pulmonary Division, Heart Institute (InCor), Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, São Paulo, SP, Brazil
| | - Margaret L. Lind
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
| | - Murilo Dorion
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
| | | | | | | | | | | | | | - Wade Schulz
- Department of Laboratory Medicine, Yale University School of Medicine, New Haven, CT, USA
| | - Maria Almiron
- Pan American Health Organization, Brasília, DF, Brazil
| | - Rodrigo Said
- Pan American Health Organization, Brasília, DF, Brazil
| | | | | | - Wildo Navegantes de Araújo
- Pan American Health Organization, Brasília, DF, Brazil
- Universidade de Brasília, Brasília, DF, Brazil
- National Institute for Science and Technology for Health Technology Assessment, Porto Alegre, RS, Brazil
| | | | - Natalie E. Dean
- Department of Biostatistics & Bioinformatics, Rollins School of Public Health, Emory University
| | - Jason R. Andrews
- Division of Infectious Diseases and Geographic Medicine, Stanford University, Stanford, CA, USA
| | - Derek A.T. Cummings
- Department of Biology, University of Florida, Gainesville, FL, USA
- Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA
| | - Albert I. Ko
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
- Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, BA, Brazil
| | - Julio Croda
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
- Universidade Federal de Mato Grosso do Sul - UFMS, Campo Grande, MS, Brazil
- Fiocruz Mato Grosso do Sul, Fundação Oswaldo Cruz, Campo Grande, MS, Brazil
| |
Collapse
|
3
|
Hitchings MDT, Ranzani OT, Torres MSS, de Oliveira SB, Almiron M, Said R, Borg R, Schulz WL, de Oliveira RD, da Silva PV, de Castro DB, Sampaio VS, de Albuquerque BC, Ramos TCA, Fraxe SHH, da Costa CF, Naveca FG, Siqueira AM, de Araújo WN, Andrews JR, Cummings DAT, Ko AI, Croda J. Effectiveness of CoronaVac among healthcare workers in the setting of high SARS-CoV-2 Gamma variant transmission in Manaus, Brazil: A test-negative case-control study. ACTA ACUST UNITED AC 2021;:100025. [PMID: 34386791 DOI: 10.1016/j.lana.2021.100025] [Citation(s) in RCA: 72] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Revised: 07/03/2021] [Accepted: 07/06/2021] [Indexed: 12/21/2022]
Abstract
Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant, Gamma, emerged in the city of Manaus in late 2020 during a large resurgence of coronavirus disease (COVID-19), and has spread throughout Brazil. The effectiveness of vaccines in settings with widespread Gamma variant transmission has not been reported. Methods We performed a matched test-negative case-control study to estimate the effectiveness of an inactivated vaccine, CoronaVac, in healthcare workers (HCWs) in Manaus, where the Gamma variant accounted for 86% of genotyped SARS-CoV-2 samples at the peak of its epidemic. We performed an early analysis of effectiveness following administration of at least one vaccine dose and an analysis of effectiveness of the two-dose schedule. The primary outcome was symptomatic SARS-CoV-2 infection. Findings For the early at-least-one-dose and two-dose analyses the study population was, respectively, 53,176 and 53,153 HCWs residing in Manaus and aged 18 years or older, with complete information on age, residence, and vaccination status. Among 53,153 HCWs eligible for the two-dose analysis, 47,170 (89%) received at least one dose of CoronaVac and 2,656 individuals (5%) underwent RT-PCR testing from 19 January, 2021 to 13 April, 2021. Of 3,195 RT-PCR tests, 885 (28%) were positive. 393 and 418 case-control pairs were selected for the early and two-dose analyses, respectively, matched on calendar time, age, and neighbourhood. Among those who had received both vaccine doses before the RT-PCR sample collection date, the average time from second dose to sample collection date was 14 days (IQR 7-24). In the early analysis, vaccination with at least one dose was associated with a 0.50-fold reduction (adjusted vaccine effectiveness (VE), 49.6%, 95% CI 11.3 to 71.4) in the odds of symptomatic SARS-CoV-2 infection during the period 14 days or more after receiving the first dose. However, we estimated low effectiveness (adjusted VE 36.8%, 95% CI -54.9 to 74.2) of the two-dose schedule against symptomatic SARS-CoV-2 infection during the period 14 days or more after receiving the second dose. A finding that vaccinated individuals were much more likely to be infected than unvaccinated individuals in the period 0-13 days after first dose (aOR 2.11, 95% CI 1.36-3.27) suggests that unmeasured confounding led to downward bias in the vaccine effectiveness estimate. Interpretation Evidence from this test-negative study of the effectiveness of CoronaVac was mixed, and likely affected by bias in this setting. Administration of at least one vaccine dose showed effectiveness against symptomatic SARS-CoV-2 infection in the setting of epidemic Gamma variant transmission. However, the low estimated effectiveness of the two-dose schedule underscores the need to maintain non-pharmaceutical interventions while vaccination campaigns with CoronaVac are being implemented. Funding Fundação Oswaldo Cruz (Fiocruz); Municipal Health Secretary of Manaus; Fundação de Vigilância em Saúde do Amazonas
Collapse
|
4
|
Martínez-Baz I, Navascués A, Casado I, Aguinaga A, Ezpeleta C, Castilla J. Remaining Effect of Influenza Vaccines Received in Prior Seasons. J Infect Dis 2020; 220:1136-1140. [PMID: 31107953 DOI: 10.1093/infdis/jiz266] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [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: 03/18/2019] [Accepted: 05/18/2019] [Indexed: 11/14/2022] Open
Abstract
This study evaluates the remaining effect of influenza vaccines received in the 5 prior seasons. During 7 influenza seasons, 8933 patients were enrolled and 47% were confirmed for influenza. Compared with unvaccinated individuals in the current and 5 prior seasons, vaccination was protective when the last dose had been received in the current season (40% [95% confidence interval {CI}, 32%-47%]), and 1 (42% [95% CI, 27%-54%]), 2-3 (35% [95% CI, 16%-49%]), or 4-5 seasons (31% [95% CI, 4%-51%]) prior. This effect lasted for fewer seasons in the elderly and in patients with chronic conditions. On average, several recent prior doses were as protective as current-season vaccination.
Collapse
Affiliation(s)
- Iván Martínez-Baz
- Instituto de Salud Pública de Navarra - IdiSNA, Pamplona.,Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid
| | - Ana Navascués
- Complejo Hospitalario de Navarra - IdiSNA, Pamplona, Spain
| | - Itziar Casado
- Instituto de Salud Pública de Navarra - IdiSNA, Pamplona.,Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid
| | | | | | - Jesús Castilla
- Instituto de Salud Pública de Navarra - IdiSNA, Pamplona.,Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid
| |
Collapse
|
5
|
Abstract
BACKGROUND The test-negative design is a variant of the case-control study being increasingly used to study influenza vaccine effectiveness (VE). In these studies, patients with influenza-like illness are tested for influenza. Vaccine coverage is compared between those testing positive versus those testing negative to estimate VE. OBJECTIVES We reviewed features in the design, analysis and reporting of 85 published test-negative studies. DATA SOURCES Studies were identified from PubMed, reference lists and email updates. Study eligibility: All studies using the test-negative design reporting end-of-season estimates were included. STUDY APPRAISAL Design features that may affect the validity and comparability of reported estimates were reviewed, including setting, study period, source population, case definition, exposure and outcome ascertainment and statistical model. RESULTS There was considerable variation in the analytic approach, with 68 unique statistical models identified among the studies. CONCLUSION Harmonization of analytic approaches may improve the potential for pooling VE estimates.
Collapse
Affiliation(s)
- Sheena G Sullivan
- WHO Collaborating Centre for Reference and Research on Influenza, Peter Doherty Institute for Infection and Immunity, 792 Elizabeth St, Melbourne VIC 3000, Australia
| | - Shuo Feng
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Benjamin J Cowling
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
| |
Collapse
|