Abstract
Accurate knowledge of prior population exposure has critical ramifications for preparedness plans for future SARS-CoV-2 epidemic 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 the decay in antibody titers over time, methods for estimating population exposure should account for seroreversion, to reflect that changes in seroprevalence measures 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 (IFR) and simultaneously infer population exposure levels. The results indicate that the average time to seroreversion is around six months, IFR is 0.54% to 1.3%, and true exposure may be more than double the current seroprevalence levels reported for several regions of England.
Highlights
The COVID-19 pandemic has inflicted devastating effects on global populations and economies [1]
It is challenging to determine the true proportion of the population that has been previously exposed to SARS-CoV-2
After seroconverting, infected individuals remain seropositive for about 176 days on average (95% credible intervals (CrI): 159–197 days) (Tables 1 and S1, S1 Fig)
Summary
The COVID-19 pandemic has inflicted devastating effects on global populations and economies [1]. The scientific and public health communities turned to serological surveys as a means to position populations along their expected epidemic timeline and provide valuable insights into COVID-19 lethality [3,4]. Those prospects were frustrated by apparent rapid declines in antibody levels following infection [5,6,7]. Performing T cell assays at scale is technically challenging and expensive, which justified the decision to conduct a series of serology surveys (some of which are still underway) in many locations globally to provide a better understanding of the extent of viral spread among populations [10]
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