Apio Catherine, Kamruzzaman Md, Park Taesung
Interdisplinary Program in Bioinformatics, Department of Statistics, Seoul National University, Seoul 08826, Korea.
Department of Statistics, Seoul National University, Seoul 08826, Korea.
Genomics Inform. 2020 Sep;18(3):e31. doi: 10.5808/GI.2020.18.3.e31. Epub 2020 Sep 23.
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.
由严重急性呼吸综合征冠状病毒2(SARS-CoV-2)引起的2019冠状病毒病(COVID-19)已成为全球大流行疾病。目前尚无针对COVID-19的特效治疗药物或疫苗,不过有几种抗病毒药物正在作为COVID-19的治疗药物进行研究。使用含有针对COVID-19的中和抗体的康复期血浆输血已成为主要关注点。这需要对人群进行大规模抗体筛查。虽然有几个国家开始报告基于人群的抗体率,但如果没有对标准误差和置信区间进行适当估计,其简单的点估计可能会被误解。在本文中,我们回顾了抗体研究的重要性,并使用韩国最近进行的两项抗体检测,给出了韩国人群COVID-19抗体率的95%置信区间。由于数据稀少,置信区间的估计是一个巨大挑战。因此,我们使用渐近、精确和贝叶斯估计方法考虑了几种置信区间。在本文中,我们发现Wald方法在所有渐近方法中给出的区间最窄,而中p值在所有精确方法中给出的区间最窄,Jeffrey方法在贝叶斯方法中给出的区间最窄。最保守的95%置信区间估计表明,截至2020年9月15日00:00,韩国至少有32,602人感染但未确诊。