论文标题
SARS-COV-2抗体的世界血清阳性估计
Estimation of World Seroprevalence of SARS-CoV-2 antibodies
论文作者
论文摘要
在本文中，我们估计了国家对Covid-19的血清阳性，并获得了世界各地的血清阳性。为了估计血清阳性，我们使用每个国家内进行的血清学调查（也称为血清神父）。当纳入血清犬以估计世界血清阳性时，有两个问题。首先，有一些国家没有进行血清学调查。其次，样本收集日期因国家 /地区而异。我们尝试使用疫苗接种数据，确认的病例数据和国家统计数据来解决这些问题。我们构建贝叶斯模型，以估计分别感染或疫苗接种产生抗体的人的数量。对于由于感染而引起的抗体的人数，我们开发了一个分层模型，用于结合确认案例数据和国家统计数据中的信息。同时，我们提出了回归模型，以估计疫苗接种数据中的缺失值。截至2021年7月31日，使用拟议的方法，我们获得了世界血清阳性的95％可靠间隔，为[38.6％，59.2％]。
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%].
