Social Bubbles and Superspreaders: Source Identification for Contagion Processes on Hypertrees
Social Bubbles and Superspreaders: Source Identification for Contagion Processes on Hypertrees
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DOI：
10.1109/ssp49050.2021.9513748
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发表时间：
2020-10
期刊：
影响因子：
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通讯作者：
Sam Spencer;L. Varshney
中科院分区：
文献类型：
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作者：
Sam Spencer;L. Varshney
之前的工作表明，对于扩展星星网络上的传染病，存在一个简单的封闭形式表达式，可以高度准确地近似最大似然感染源。在这里，我们将这一结果推广到一类超树，虽然在结构上有点类似，但提供了更丰富的表示空间。这种方法可以用来估计零患者来源，即使感染是通过大型群体聚集而不是人与人之间的传播传播，以及当它通过相互关联的社会泡沫传播时，具有不同程度的重叠。在接触者追踪背景下，该估计器可用于识别本地爆发的来源，然后可用于向前追踪或进一步向后追踪。
Previous work shows that for contagions on extended star networks, there is a simple, closed-form expression for a highly accurate approximation to the maximum likelihood infection source. Here, we generalize that result to a class of hypertrees which, although somewhat structurally analogous, provides a much richer representation space. This approach can be used to estimate patient zero sources, even when the infection has been propagated via large group gatherings rather than person-to-person spread, and when it is spreading through interrelated social bubbles with varying degrees of overlap. In contact tracing contexts, this estimator may be used to identify the source of a local outbreak, which can then be used for forward tracing or further backward tracing.