Abstract
Serological surveys, such as EPICOVID19 (), are important to monitor the evolution of COVID-19 in a population. In this letter, we discuss how to best estimate its prevalence. It is well known that the naive estimator of prevalence that consists of counting how many individuals tested positive ignores the possibility of test errors and may therefore substantially bias the conclusions. The often-used Rogan-Gladen estimator () is an alternative that provides corrected confidence intervals based on sensitivity/specificity values. However, this estimator [...]
Highlights
Serological surveys, such as EPICOVID19 (1), are important to monitor the evolution of COVID-19 in a population
We use the sensitivity/specificity values provided in the paper: 82.1% (69.6%–91.1%) and 100.0% (96.5%–100.0%), respectively
The Bayesian interval that takes this uncertainty (4) into account is much wider; it contains points that are consistent with very different stages of the evolution of the epidemic
Summary
Serological surveys, such as EPICOVID19 (1), are important to monitor the evolution of COVID-19 in a population. Since we do not have access to the exact numbers, we assume that among the 61,075 individuals in the survey, 3,054 (5%) tested positive on the point-of-care test.
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