Emerg Infect Dis. 2021 Dec;27(12):3063-3072. doi: 10.3201/eid2712.204958.
Despite its critical role in containing outbreaks, the efficacy of contact tracing, measured as the sensitivity of case detection, remains an elusive metric. We estimated the sensitivity of contact tracing by applying unilist capture-recapture methods on data from the 2018-2020 outbreak of Ebola virus disease in the Democratic Republic of the Congo. To compute sensitivity, we applied different distributional assumptions to the zero-truncated count data to estimate the number of unobserved case-patients with any contacts and infected contacts. Geometric distributions were the best-fitting models. Our results indicate that contact tracing efforts identified almost all (n = 792, 99%) of case-patients with any contacts but only half (n = 207, 48%) of case-patients with infected contacts, suggesting that contact tracing efforts performed well at identifying contacts during the listing stage but performed poorly during the contact follow-up stage. We discuss extensions to our work and potential applications for the ongoing coronavirus pandemic.
尽管接触者追踪在控制疫情爆发方面起着关键作用，但作为病例检出灵敏度的衡量标准，其效果仍然难以捉摸。我们应用单列表捕获-再捕获方法，利用刚果民主共和国 2018-2020 年埃博拉病毒病疫情的数据来估计接触者追踪的灵敏度。为了计算灵敏度，我们对零截断计数数据应用了不同的分布假设，以估计任何接触者和感染接触者的未观察到的病例数。几何分布是最合适的模型。我们的研究结果表明，接触者追踪工作几乎发现了所有（n=792，99%）有任何接触者的病例，但只有一半（n=207，48%）有感染接触者的病例，这表明接触者追踪工作在列名阶段很好地识别了接触者，但在接触者随访阶段效果不佳。我们讨论了对我们工作的扩展以及对当前冠状病毒大流行的潜在应用。
