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- Title
Estimating protection afforded by prior infection in preventing reinfection: applying the test-negative study design.
- Authors
Ayoub, Houssein H; Tomy, Milan; Chemaitelly, Hiam; Altarawneh, Heba N; Coyle, Peter; Tang, Patrick; Hasan, Mohammad R; Kanaani, Zaina Al; Kuwari, Einas Al; Butt, Adeel A; Jeremijenko, Andrew; Kaleeckal, Anvar Hassan; Latif, Ali Nizar; Shaik, Riyazuddin Mohammad; Nasrallah, Gheyath K; Benslimane, Fatiha M; Khatib, Hebah A Al; Yassine, Hadi M; Kuwari, Mohamed G Al; Romaihi, Hamad Eid Al
- Abstract
The COVID-19 pandemic has highlighted the need to use infection testing databases to rapidly estimate effectiveness of prior infection in preventing reinfection (|$P{E}_S$|) by novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants. Mathematical modeling was used to demonstrate a theoretical foundation for applicability of the test-negative, case–control study design to derive |$P{E}_S$|. Apart from the very early phase of an epidemic, the difference between the test-negative estimate for |$P{E}_S$| and true value of |$P{E}_S$| was minimal and became negligible as the epidemic progressed. The test-negative design provided robust estimation of |$P{E}_S$| and its waning. Assuming that only 25% of prior infections are documented, misclassification of prior infection status underestimated |$P{E}_S$| , but the underestimate was considerable only when > 50% of the population was ever infected. Misclassification of latent infection, misclassification of current active infection, and scale-up of vaccination all resulted in negligible bias in estimated |$P{E}_S$|. The test-negative design was applied to national-level testing data in Qatar to estimate |$P{E}_S$| for SARS-CoV-2. |$P{E}_S$| against SARS-CoV-2 Alpha and Beta variants was estimated at 97.0% (95% CI, 93.6-98.6) and 85.5% (95% CI, 82.4-88.1), respectively. These estimates were validated using a cohort study design. The test-negative design offers a feasible, robust method to estimate protection from prior infection in preventing reinfection.
- Subjects
QATAR; INFECTION prevention; BIBLIOGRAPHIC databases; MATHEMATICS; RESEARCH funding; PILOT projects; INFECTION; TREATMENT effectiveness; DESCRIPTIVE statistics; COVID-19 vaccines; DIAGNOSTIC errors; REINFECTION; EXPERIMENTAL design; LONGITUDINAL method; PRE-exposure prophylaxis; MATHEMATICAL models; CASE-control method; RESEARCH methodology; THEORY; CONFIDENCE intervals; COVID-19 pandemic; SARS-CoV-2; EVALUATION
- Publication
American Journal of Epidemiology, 2024, Vol 193, Issue 6, p883
- ISSN
0002-9262
- Publication type
Article
- DOI
10.1093/aje/kwad239