Title: Group Testing under Superspreading Dynamics Show Chinese title

Title: 超级传播动态下的群组检测

Abstract: Testing is recommended for all close contacts of confirmed COVID-19 patients. However, existing group testing methods are oblivious to the circumstances of contagion provided by contact tracing. Here, we build upon a well-known semi-adaptive pool testing method, Dorfman's method with imperfect tests, and derive a simple group testing method based on dynamic programming that is specifically designed to use the information provided by contact tracing. Experiments using a variety of reproduction numbers and dispersion levels, including those estimated in the context of the COVID-19 pandemic, show that the pools found using our method result in a significantly lower number of tests than those found using standard Dorfman's method, especially when the number of contacts of an infected individual is small. Moreover, our results show that our method can be more beneficial when the secondary infections are highly overdispersed. Show Chinese abstract

Abstract: 建议对所有新型冠状病毒病确诊病例的密切接触者进行检测。然而，现有的分组检测方法忽视了接触者追踪提供的感染情况信息。在这里，我们在已知的半自适应池化检测方法——多尔夫曼的不完美检测方法的基础上，通过动态规划推导出了一种专门利用接触者追踪提供信息的简单分组检测方法。使用包括新冠疫情背景下估计值在内的各种繁殖数和分散水平的实验表明，与标准多尔夫曼方法相比，我们方法所发现的检测池导致的检测次数显著减少，尤其是在感染个体的接触人数较少的情况下。此外，我们的结果显示，当次级感染高度分散时，我们的方法可以带来更大的益处。