Testing individuals for the presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the pathogen causing the coronavirus disease 2019 (COVID-19), is crucial for curtailing transmission chains. Moreover, rapidly testing many potentially infected individuals is often a limiting factor in controlling COVID-19 outbreaks. Hence, pooling strategies, wherein individuals are grouped and tested simultaneously, are employed. We present a novel pooling strategy that implements D-Optimal Pooling Experimental design (DOPE). DOPE defines optimal pooled tests as those maximizing the mutual information between data and infection states. We estimate said mutual information via Monte-Carlo sampling and employ a discrete optimization heuristic for maximizing it. DOPE outperforms common pooling strategies both in terms of lower error rates and fewer tests utilized. DOPE holds several additional advantages: it provides posterior distributions of the probability of infection, rather than only binary classification outcomes; it naturally incorporates prior information of infection probabilities and test error rates; and finally, it can be easily extended to include other, newly discovered information regarding COVID-19. Hence, we believe that implementation of Bayesian D-optimal experimental design holds a great promise for the efforts of combating COVID-19 and other future pandemics.
Robust estimation of SARS-CoV-2 epidemic in US counties
2019冠状病毒病在美国各县的爆发是异步的。减少COVID-19传播不仅需要州和联邦层面的保护措施，如社交距离和检测，还需要公众意识到县和社区层面的时间依赖性风险和反应。我们提出了一种稳健的方法来估计美国所有县的SARS-CoV-2的异质性进展，这些县的COVID-19相关死亡人数不少于2人，我们使用易感个体感染SARS-CoV-2的每日概率来量化SARS-CoV-2在社区中传播的风险。我们发现，截至2020年9月20日，通过$5\%$缩短SARS-CoV-2的感染期可以减少美国COVID-19相关死亡的约$39\%$（或$78$ K，$95\%$ CI：$[66$ K $, 89$ K $]$）。我们的研究结果还表明，通过缩短传染期来减少感染和死亡，对于有效繁殖数接近1的地区更为明显，这表明应将检测与其他缓解措施（如社交距离和戴口罩）一起使用，以降低传播率。我们的成果包括一个动态的县级地图，供地方官员确定最佳政策反应，并让公众更好地了解每天感染SARS-CoV-2的风险。
Risk Estimation of SARS-CoV-2 Transmission from Bluetooth Low Energy Measurements
Fraunhofer Heinrich Hertz Institute（弗劳恩霍夫海因里希·赫兹研究所）；Technische Universität Berlin（柏林工业大学）；Korea University（高丽大学）；Max Planck Institute for Informatics（马克斯·普朗克信息学研究所）
Sequentially estimating the dynamic contact angle of sessile saliva droplets in view of SARS-CoV-2
估计病毒感染的唾液液滴的接触角被认为是一个重要的研究领域，因为它提出了关于相应液滴的干燥时间的想法，进而提出了潜在流行病的增长。在本文中，我们扩展了Balusamy，Banerjee和Sahu [在SARS-CoV-2的背景下固着唾液滴的寿命，Int. J. Heat Mass Transf. 123，105178（2021）]提供的数据，其中使用新提出的半圆形包裹指数模型拟合接触角，并且建立了顺序的置信区间估计方法，其大大减少了关于数据收集的时间和成本。
