论文标题
感染风险评分：根据人接触确定感染传播的风险
Infection Risk Score: Identifying the risk of infection propagation based on human contact
论文作者
论文摘要
已经采用了广泛的方法来管理诸如Covid-19之类的全球大流行事件的传播，这些事件已获得了不同程度的成功。鉴于大规模的社会和经济影响加上大流行的时间跨度的增加，重要的是不仅要管理疾病的传播，而且还为加快恢复社会和经济生活的措施付出了额外的努力。因此，重要的是要确定带有高风险的情况，并在确定这种情况时尽早采取行动。尽管已经开发了大量的移动应用程序，但它们旨在获取可用于接触跟踪的信息，但不是估计社交情况的风险。在本文中，我们引入了感染风险评分，该评分估算了人类接触引起的感染风险。使用现实世界中的人类联系数据集，我们表明拟议的风险评分可以提供对人口风险水平的现实估计。我们还描述了如何在智能手机上实现拟议的感染风险评分。最后，我们确定可以利用风险评分的代表性用例，以最大程度地减少感染传播。
A wide range of approaches have been applied to manage the spread of global pandemic events such as COVID-19, which have met with varying degrees of success. Given the large-scale social and economic impact coupled with the increasing time span of the pandemic, it is important to not only manage the spread of the disease but also put extra efforts on measures that expedite resumption of social and economic life. It is therefore important to identify situations that carry high risk, and act early whenever such situations are identified. While a large number of mobile applications have been developed, they are aimed at obtaining information that can be used for contact tracing, but not at estimating the risk of social situations. In this paper, we introduce an infection risk score that provides an estimate of the infection risk arising from human contacts. Using a real-world human contact dataset, we show that the proposed risk score can provide a realistic estimate of the level of risk in the population. We also describe how the proposed infection risk score can be implemented on smartphones. Finally, we identify representative use cases that can leverage the risk score to minimize infection propagation.
