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

Background Serological surveys have been the gold standard to estimate the numbers of SARS-CoV-2 infections, epidemic dynamics, and disease severity. Serological assays have decaying sensitivity with time that can bias their results, but there is a lack of guidelines to account for this phenomenon for SARS-CoV-2. Aim Our goal is to assess the sensitivity decay of seroassays for detecting SARS-CoV-2 infections, the dependence of this decay on assay characteristics, and to provide a simple method to correct for this phenomenon. Methods We 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). Results Of 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 considerably from manufacturer specifications after 6 months. Conclusions Seroassay 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. Our analysis can guide the design and interpretation of serosurveys for SARS-CoV-2 and other pathogens, and quantify systematic biases in the existing serology literature.