Theoretical Framework for Retrospective Studies of the Effectiveness of SARS-CoV-2 Vaccines
Open accessPublished version of a preprint
Abstract
Observational studies of the effectiveness of vaccines to prevent COVID-19 are needed to inform real-world use. Such studies are now underway amid the ongoing rollout of SARS-CoV-2 vaccines globally. Although traditional case-control and test-negative design studies feature prominently among strategies used to assess vaccine effectiveness, such studies may encounter important threats to validity. Here, we review the theoretical basis for estimation of vaccine direct effects under traditional case-control and test-negative design frameworks, addressing specific natural history parameters of SARS-CoV-2 infection and COVID-19 relevant to these designs. Bias may be introduced by misclassification of cases and controls, particularly when clinical case criteria include common, nonspecific indicators of COVID-19. When using diagnostic assays with high analytical sensitivity for SARS-CoV-2 detection, individuals testing positive may be counted as cases even if their symptoms are due to other causes. The traditional case-control design may be particularly prone to confounding due to associations of vaccination with healthcare-seeking behavior or risk of infection. The test-negative design reduces but may not eliminate this confounding, for instance, if individuals who receive vaccination seek care or testing for less-severe illness. These circumstances indicate the two study designs cannot be applied naively to datasets gathered through public health surveillance or administrative sou…
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The observational nature of the study may have limited consideration of the difference in risks of infection between vaccinated and unvaccinated individuals.
“Nonetheless, the study also bears some limitations inherent to its observational nature, which may have limited our consideration of the difference in the risks of infection between vaccinated and unvaccinated individuals [36].”
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Self-citation
- Authors
- Lewnard, J. A., Patel, M. M., Jewell, N. P., Verani, J. R., Kobayashi, M., Tenforde, M. W., Dean, N. E., Cowling, B. J., & Lopman, B. A.
- Affiliations
- University of California, Berkeley (US)
- Centers for Disease Control and Prevention (US)
- London School of Hygiene & Tropical Medicine (GB)
- University of Florida (US)
- University of Hong Kong (HK)
- Emory University (US)
- Corresponding author
- Lewnard, Joseph A.
- ORCID
- Venue
- Epidemiology
- Published
- 2021-05-13
- Volume
- 32
- Issue
- 4
- Pages
- 508-517
- ISSN
- 1044-3983 (ISSN-L)
- PMC
- PMC8168935
- OpenAlex
- W3161135492
- Cited by
- 103
- References
- 5
- Citations by year
- 2026: 5 · 2025: 14 · 2024: 13 · 2023: 19 · 2022: 32 · 2021: 20
- FWCI
- 2.46
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Locations
- Epidemiology (publishedVersion)
- medRxiv (acceptedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- LSHTM Research Online (London School of Hygiene and Tropical Medicine) (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- Pfizer
- National Institute of Allergy and Infectious Diseases (R01AI139761, R01AI148127)
- Topics
- Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
- Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Keywords
- COVID-19 vaccines, COVID-19 vaccine effectiveness, case-control study, test-negative design, confounding, diagnostic sensitivity, health-seeking behavior, public health surveillance data, administrative data
- MeSH terms
- COVID-19, SARS-CoV-2, COVID-19 Vaccines, Humans, Retrospective Studies, Vaccines
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