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Open Access 01-12-2023 | COVID-19 | Research

Correction of vaccine effectiveness derived from test-negative case–control studies

Author: Farrokh Habibzadeh

Published in: BMC Medical Research Methodology | Issue 1/2023

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Abstract

Background

Determining the vaccine effectiveness (VE) is an important part of studying every new vaccine. Test-negative case–control (TNCC) studies have recently been used to determine the VE. However, the estimated VE derived from a TNCC design depends on the test sensitivity and specificity. Herein, a method for correction of the value of VE derived from a TNCC study is presented.

Methods

An analytical method is presented to compute the corrected VE based on the sensitivity and specificity of the diagnostic test utilized. To show the application of the method proposed, a hypothetical TNCC study is presented. In this in silico study, 100 000 individuals referring to a healthcare system for COVID-19-like illness were tested with diagnostic tests with sensitivities of 0.6, 0.8, and 1.0, and specificities ranging from 0.85 to 1.00. A vaccination coverage of 60%, an attack rate of 0.05 for COVID-19 in unvaccinated group, and a true VE of 0.70, were assumed. In this simulation, a COVID-19-like illness with an attack rate of 0.30 could also affect all the studied population regardless of their vaccination status.

Results

The observed VE ranged from 0.11 (computed for a test sensitivity of 0.60 and specificity of 0.85) to 0.71 (computed for a test sensitivity and specificity of 1.0). The mean computed corrected VE derived from the proposed method was 0.71 (the standard deviation of 0.02).

Conclusions

The observed VE derived from TNCC studies can be corrected easily. An acceptable estimate for VE can be computed regardless of the diagnostic test sensitivity and specificity used in the study.
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Metadata
Title
Correction of vaccine effectiveness derived from test-negative case–control studies
Author
Farrokh Habibzadeh
Publication date
01-12-2023
Publisher
BioMed Central
Published in
BMC Medical Research Methodology / Issue 1/2023
Electronic ISSN: 1471-2288
DOI
https://doi.org/10.1186/s12874-023-01962-0

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