基于占领的目标传染病控制的网络界限
The Network Limits of Infectious Disease Control via Occupation-Based Targeting
摘要：
政策制定者通常采用非药物干预措施来控制流行病的规模和严重程度。在非药物干预措施中，旨在减少人与人之间的病原体传播的社会距离政策最近变得突出。尤其是，全球各地为应对COVID-19疫情而广泛实施的居家政策已证明对减缓疫情增长显著有效。然而，这种生硬的政策工具虽然有效，但会产生许多意想不到的后果，包括可能大幅降低经济生产力。在这里，我们开发的方法来调查的潜力，同时控制流行病的传播，同时也尽量减少经济干扰。我们这样做是通过将包含在城市环境中的职业和网络信息结合起来，这些信息通常被排除在典型的流行病控制政策设计之外。我们的方法的结果表明，在经济生产力和流行病控制方面的巨大收益可能是通过纳入和考虑职业接触网络的简单测量特征而获得的。然而，我们发现证据表明，更复杂，更隐私的侵犯，这个网络的措施并没有大幅提高性能。
英文摘要：
Policymakers commonly employ non-pharmaceutical interventions to manage the scale and severity of pandemics. Of non-pharmaceutical interventions, social distancing policies -- designed to reduce person-to-person pathogenic spread -- have risen to recent prominence. In particular, stay-at-home policies of the sort widely implemented around the globe in response to the COVID-19 pandemic have proven to be markedly effective at slowing pandemic growth. However, such blunt policy instruments, while effective, produce numerous unintended consequences, including potentially dramatic reductions in economic productivity. Here we develop methods to investigate the potential to simultaneously contain pandemic spread while also minimizing economic disruptions. We do so by incorporating both occupational and network information contained within an urban environment, information that is commonly excluded from typical pandemic control policy design. The results of our method suggest that large gains in both economic productivity and pandemic control might be had by the incorporation and consideration of simple-to-measure characteristics of the occupational contact network. However we find evidence that more sophisticated, and more privacy invasive, measures of this network do not drastically increase performance.
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