Dynamics of SARS-CoV-2 seroassay sensitivity: a systematic review and modeling study

ABSTRACT

BackgroundSerological surveys have been the gold standard to estimate the numbers of SARS-CoV-2 infections, epidemic dynamics, and disease severity throughout the pandemic. Serological assays are known to have decaying sensitivity with time that can strongly bias their results, but there is a lack of guidelines to account for this phenomenon. AimAssess the sensitivity decay of seroassays for detecting infections, its dependence on assay characteristics, and provide a simple tool to correct for this phenomenon. MethodsWe performed a systematic review and meta-analysis of SARS-CoV-2 serology studies. We included studies testing previously diagnosed individuals, without any SARS-CoV-2 vaccines, and excluded studies of cohorts highly unrepresentative of the general population (e.g. hospitalised patients). ResultsOf the 488 screened studies, 76 studies reporting on 50 different seroassays were included in the analysis. Sensitivity decay depends strongly on the antigen and the analytic technique used by the assay, with average sensitivities ranging between 26% and 98% at 6 months after infection, depending on assay characteristics. We find that a third of the included assays depart significantly from manufacturer specifications after 6 months. ConclusionsSeroassay sensitivity decay depends on assay characteristics, and for some types of assays it can make manufacturer specifications highly unreliable. We provide a tool to correct for this phenomenon, and to assess the risk of decay for a given assay. This can be used to design better serosurveys, and quantify systematic biases in the existing serology literature.