Optimising COVID-19 Episode Identification Using Serology and PCR/Rapid Antigen Testing: Insights from the BRACE Trial
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Background
Accurately identifying COVID-19 episodes was crucial during the early pandemic for evaluating interventions. Results from diagnostic tools like PCR, rapid antigen test (RAT), and serology are affected by factors such as timing of tests and vaccination status. The BRACE trial, which investigated the impact of BCG vaccination on COVID-19 prevalence among healthcare workers, developed a comprehensive algorithm integrating these diagnostic tools for illness episode classification.
Methods
In the BRACE trial, 3988 participants reported 5512 febrile/respiratory illness episodes and provided longitudinal blood samples over one year. SARS-CoV-2 diagnosis relied on a three-component algorithm: (1) a serology algorithm assessing anti-SARS-CoV-2 nucleocapsid antibody seroconversion, (2) a PCR/RAT algorithm, and (3) an episode interpretation algorithm combining serology and PCR/RAT results to categorise episodes as COVID-19, Not COVID-19, or Missing. The component algorithms also accounted for vaccination status and timing of testing relative to symptom onset to refine episode classifications.
Findings
Of 5512 illness episodes, 890 (16%) were classified as COVID-19, 3852 (70%) as not COVID-19, and 770 (14%) as missing. Compared to relying solely on PCR/RAT results, integrating serology in the algorithm reduced the proportion of missing classifications by more than half. Among the COVID-19 episodes, 89% were identified by positive PCR/RAT results, and the remaining 11% (with missing or negative PCR/RAT tests) were identified by serology. Discordance between PCR/RAT and serology occurred in 12.8% of episodes.
Interpretation
An algorithm integrating PCR/RAT and serology results in the context of test timing and vaccine status enabled the accurate identification of COVID-19 episodes and minimised the number of episodes that would otherwise have been classified as missing.
