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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
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]

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