Bibliographic Details
| 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 |
| Source: |
American Journal of Epidemiology; Jun2024, Vol. 193 Issue 6, p883-897, 15p |
| Subject Terms: |
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 |
| Geographic Terms: |
QATAR |
| 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] |
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| Database: |
Complementary Index |
