Preprint
en Inglés
| PREPRINT-MEDRXIV | ID: ppmedrxiv-21249432
Accurate knowledge of accurate levels of prior population exposure has critical ramifications for preparedness plans of subsequent SARS-CoV-2epidemic waves and vaccine prioritization strategies. Serological studies can be used to estimate levels of past exposure and thus position populations in their epidemic timeline. To circumvent biases introduced by decaying antibody titers over time, population exposure estimation methods should account for seroreversion, to reflect that changes in seroprevalencemeasures over time are the net effect of increases due to recent transmission and decreases due to antibody waning. Here, we present a new method that combines multiple datasets (serology, mortality, and virus positivity ratios) to estimate seroreversion time and infection fatality ratios and simultaneously infer populationexposure levels. The results indicate that the average time to seroreversion is six months, and that true exposure may be more than double the current seroprevalence levels reported for several regions of England.