  In this paper, we estimate the seroprevalence against COVID-19 by country and
derive the seroprevalence over the world. To estimate seroprevalence, we use
serological surveys (also called the serosurveys) conducted within each
country. When the serosurveys are incorporated to estimate world
seroprevalence, there are two issues. First, there are countries in which a
serological survey has not been conducted. Second, the sample collection dates
differ from country to country. We attempt to tackle these problems using the
vaccination data, confirmed cases data, and national statistics. We construct
Bayesian models to estimate the numbers of people who have antibodies produced
by infection or vaccination separately. For the number of people with
antibodies due to infection, we develop a hierarchical model for combining the
information included in both confirmed cases data and national statistics. At
the same time, we propose regression models to estimate missing values in the
vaccination data. As of 31st of July 2021, using the proposed methods, we
obtain the 95% credible interval of the world seroprevalence as [38.6%, 59.2%].

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