National Centre for Pharmacoeconomics, St James's Hospital, D08 HD53 Dublin, Ireland.
Department of Pharmacology and Therapeutics, Trinity College Dublin, D08 HD53 Dublin, Ireland.
Int J Environ Res Public Health. 2021 Apr 27;18(9):4640. doi: 10.3390/ijerph18094640.
SARS-CoV-2 continues to widely circulate in populations globally. Underdetection is acknowledged and is problematic when attempting to capture the true prevalence. Seroprevalence studies, where blood samples from a population sample are tested for SARS-CoV-2 antibodies that react to the SARS-CoV-2 virus, are a common method for estimating the proportion of people previously infected with the virus in a given population. However, obtaining reliable estimates from seroprevalence studies is challenging for a number of reasons, and the uncertainty in the results is often overlooked by scientists, policy makers, and the media. This paper reviews the methodological issues that arise in designing these studies, and the main sources of uncertainty that affect the results. We discuss the choice of study population, recruitment of subjects, uncertainty surrounding the accuracy of antibody tests, and the relationship between antibodies and infection over time. Understanding these issues can help the reader to interpret and critically evaluate the results of seroprevalence studies.
SARS-CoV-2 在全球人群中继续广泛传播。检测不足是公认的问题，在试图捕捉真实流行率时会产生问题。血清流行率研究是一种常见的方法，通过对人群样本中的血液样本进行 SARS-CoV-2 抗体检测，这些抗体可以与 SARS-CoV-2 病毒发生反应，从而估计在特定人群中先前感染该病毒的人数比例。然而，由于多种原因，从血清流行率研究中获得可靠的估计值具有挑战性，并且结果中的不确定性通常被科学家、政策制定者和媒体所忽视。本文综述了设计这些研究中出现的方法学问题，以及影响结果的主要不确定性来源。我们讨论了研究人群的选择、受试者的招募、抗体检测准确性的不确定性以及抗体与时间的关系。了解这些问题可以帮助读者解释和批判性地评估血清流行率研究的结果。
