Am J Epidemiol. 2021 Sep 1;190(9):1918-1927. doi: 10.1093/aje/kwab098.
Serological surveys can provide evidence of cases that were not previously detected, depict the spectrum of disease severity, and estimate the proportion of asymptomatic infections. To capture these parameters, survey sample sizes may need to be very large, especially when the overall infection rate is still low. Therefore, we propose the use of "snowball sampling" to enrich serological surveys by testing contacts of infected persons identified in the early stages of an outbreak. For future emerging pandemics, this observational study sampling design can answer many key questions, such as estimation of the asymptomatic proportion of all infected cases, the probability of a given clinical presentation for a seropositive individual, or the association between characteristics of either the host or the infection and seropositivity among contacts of index individuals. We provide examples, in the context of the coronavirus disease 2019 (COVID-19) pandemic, of studies and analysis methods that use a snowball sample and perform a simulation study that demonstrates scenarios where snowball sampling can answer these questions more efficiently than other sampling schemes. We hope such study designs can be applied to provide valuable information to slow the present pandemic as it enters its next stage and in early stages of future pandemics.
血清学调查可以提供先前未检测到的病例的证据,描述疾病严重程度的范围,并估计无症状感染的比例。为了捕捉这些参数,调查样本量可能需要非常大,特别是当总体感染率仍然较低时。因此,我们建议使用“滚雪球抽样”来丰富通过测试在疫情早期发现的感染者的接触者来进行的血清学调查。对于未来的新发大流行,这种观察性研究抽样设计可以回答许多关键问题,例如估计所有感染病例的无症状比例、给定临床症状出现的概率,或者宿主或感染的特征与索引个体接触者的血清阳性之间的关联。我们提供了一些示例,在 2019 年冠状病毒病(COVID-19)大流行的背景下,说明了使用滚雪球样本的研究和分析方法,并进行了模拟研究,证明了滚雪球抽样在回答这些问题方面比其他抽样方案更有效。我们希望这些研究设计可以应用于为减缓目前的大流行进入下一阶段和未来大流行的早期阶段提供有价值的信息。