Clinical Characterisation of Lateral Flow Assays for Detection of COVID-19 Antibodies in a population (preprint)

ABSTRACT

Importance Serological assays can help diagnose and determine the rate of SARS-CoV-2 infections in a population. Objective: We characterized and compared 11 different lateral flow assays for their performance in diagnostic or epidemiological settings. Design, Setting, Participants: We used two cohorts to determine the speci- ficity (i) up to 350 blood donor samples from past influenza seasons and (ii) up to 110 samples which tested PCR negative for SARS-CoV-2 during the first wave of SARS-CoV-2 infections in Switzerland. The sensitivity was determined using up to 370 samples which tested PCR positive for SARS-CoV-2 during the same time and is representative for age distribution and severity. Main Outcome: We found a single test usable for epidemiological studies in the current low-prevalence setting, all other tests showed lacking sensitivity or specificity for a usage in either epidemiological or diagnostic setting. However, orthogonal testing by combining two tests without common cross-reactivities makes testing in a low-prevalence setting feasible. Results: Nine out of the eleven tests showed specificities below 99%, only five of eleven tests showed sensitivities comparable to established ELISAs, and only one ful- filled both criteria. Contrary to previous results from lab assays, five tests measured an IgM response in >80% of the samples. We found no common cross-reactivities, which allows orthogonal testing schemes for five tests of sufficient sensitivities. Conclusions and Relevance This study emphasizes the need for large and diverse negative cohorts when determining specificities, and for diverse and repre- sentative positive samples when determining sensitivities of lateral flow assays for SARS-CoV-2 infections. Failure to adhere to statistically relevant sample sizes or cohorts exclusively made up of hospitalised patients fails to accurately capture the performance of these assays in epidemiological settings. Our results allow a rational choice between tests for different use cases.