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Estimating protection afforded by prior infection in preventing reinfection: applying the test-negative study design.
- Source :
- American Journal of Epidemiology; Jun2024, Vol. 193 Issue 6, p883-897, 15p
- Publication Year :
- 2024
-
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. [ABSTRACT FROM AUTHOR]
- Subjects :
- 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
Subjects
Details
- Language :
- English
- ISSN :
- 00029262
- Volume :
- 193
- Issue :
- 6
- Database :
- Complementary Index
- Journal :
- American Journal of Epidemiology
- Publication Type :
- Academic Journal
- Accession number :
- 177681362
- Full Text :
- https://doi.org/10.1093/aje/kwad239