DOI QR코드

DOI QR Code

Confidence intervals for the COVID-19 neutralizing antibody retention rate in the Korean population

  • Apio, Catherine (Interdisplinary Program in Bioinformatics, Department of Statistics, Seoul National University) ;
  • Kamruzzaman, Md. (Department of Statistics, Seoul National University) ;
  • Park, Taesung (Interdisplinary Program in Bioinformatics, Department of Statistics, Seoul National University)
  • 투고 : 2020.09.19
  • 심사 : 2020.09.22
  • 발행 : 2020.09.30

초록

The coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become a global pandemic. No specific therapeutic agents or vaccines for COVID-19 are available, though several antiviral drugs, are under investigation as treatment agents for COVID-19. The use of convalescent plasma transfusion that contain neutralizing antibodies for COVID-19 has become the major focus. This requires mass screening of populations for these antibodies. While several countries started reporting population based antibody rate, its simple point estimate may be misinterpreted without proper estimation of standard error and confidence intervals. In this paper, we review the importance of antibody studies and present the 95% confidence intervals COVID-19 antibody rate for the Korean population using two recently performed antibody tests in Korea. Due to the sparsity of data, the estimation of confidence interval is a big challenge. Thus, we consider several confidence intervals using Asymptotic, Exact and Bayesian estimation methods. In this article, we found that the Wald method gives the narrowest interval among all Asymptotic methods whereas mid p-value gives the narrowest among all Exact methods and Jeffrey's method gives the narrowest from Bayesian method. The most conservative 95% confidence interval estimation shows that as of 00:00 on September 15, 2020, at least 32,602 people were infected but not confirmed in Korea.

키워드

과제정보

The authors thank Dr. Asaph Young Chun, Ph.D., Director-General, Statistics Research Institute Statistics, Korea for his extremely helpful comments.

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