论文标题
具有其他人口控制的测试阴性设计:一种实用方法,可以快速获取有关SARS-COV-2流行病的原因的信息
The test-negative design with additional population controls: a practical approach to rapidly obtain information on the causes of the SARS-CoV-2 epidemic
论文作者
论文摘要
在全球范围内,正在对有症状的人进行症状性感染。我们提出了两种类型的病例对照研究,可以在有症状的人的测试中共同进行。首先,测试阴性病例对照设计(TND)是最容易实施的。它仅要求从经过测试的症状人士那里收集有关Covid-19的潜在危险因素的信息。第二,标准的病例对照研究与人群对照,需要针对在测试设施中测试的每个人收集一个或多个人群控制的数据,以便可以将测试促阳性和测试阴性与人口对照进行比较。 TND将检测患有COVID-19(测试启动剂)与其他呼吸道感染(测试阴性)的有症状性人之间的危险因素差异。然而,TND不会鉴定出COVID-19和其他呼吸道感染的危险因素均具有相等大小的幅度。因此,我们讨论了如何添加人群控制以与测试启示和测试阴性相比,从而提供了另外两项病例对照研究。我们描述了人群对照组的两个选择:一个由伴随人员组成的测试设施,另一种是从现有的全国性医疗保健数据库中汲取的。我们还描述了人口控制的其他可能性。将TND与人口控制结合起来产生了三角剖分方法,该方法区分了Covid-19和其他呼吸道感染的风险因素的暴露,以及仅是Covid-19的风险因素的暴露。这种组合设计可以应用于未来的流行病,也可以研究非流行病的原因。
Testing of symptomatic persons for infection with SARS-CoV-2 is occurring worldwide. We propose two types of case-control studies that can be carried out jointly in test-settings for symptomatic persons. The first, the test-negative case-control design (TND) is the easiest to implement; it only demands collecting information about potential risk factors for COVID-19 from the tested symptomatic persons. The second, standard case-control studies with population controls, requires the collection of data on one or more population controls for each person who is tested in the test facilities, so that test-positives and test-negatives can each be compared with population controls. The TND will detect differences in risk factors between symptomatic persons who have COVID-19 (test-positives) and those who have other respiratory infections (test-negatives). However, risk factors with effect sizes of equal magnitude for both COVID-19 and other respiratory infections will not be identified by the TND. Therefore, we discuss how to add population controls to compare with the test-positives and the test-negatives, yielding two additional case-control studies. We describe two options for population control groups: one composed of accompanying persons to the test facilities, the other drawn from existing country-wide health care databases. We also describe other possibilities for population controls. Combining the TND with population controls yields a triangulation approach that distinguishes between exposures that are risk factors for both COVID-19 and other respiratory infections, and exposures that are risk factors for just COVID-19. This combined design can be applied to future epidemics, but also to study causes of non-epidemic disease.