  In $2020$, Korea Disease Control and Prevention Agency reported three rounds
of surveys on seroprevalence of severe acute respiratory syndrome coronavirus 2
(SARS-CoV-2) antibodies in South Korea. We analyze the seroprevalence surveys
using a Bayesian method with an informative prior distribution on the
seroprevalence parameter, and the sensitivity and specificity of the diagnostic
test. We construct the informative prior using the posterior distribution
obtained from the clinical evaluation data based on the plaque reduction
neutralization test. The constraint of the seroprevalence parameter induced
from the known confirmed coronavirus 2019 cases can be imposed naturally in the
proposed Bayesian model. We also prove that the confidence interval of the
seroprevalence parameter based on the Rao's test can be the empty set, while
the Bayesian method renders a reasonable interval estimator. As of the $30$th
of October $2020$, the $95\%$ credible interval of the estimated SARS-CoV-2
positive population does not exceed $307,448$, approximately $0.6\%$ of the
Korean population.
