Interplay between population density and mobility in determining the spread of epidemics in cities
Interplay between population density and mobility in determining the spread of epidemics in cities
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DOI：
10.1038/s42005-021-00679-0
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发表时间：
2021-08-23
影响因子：
5.5
通讯作者：
Ghoshal, Gourab
中科院分区：
文献类型：
--
作者：
Hazarie, Surendra;Soriano-Panos, David;Ghoshal, Gourab
人口越来越多地聚集在人口密集的城市地区，加上连接这些中心的高效交通方式的存在，使城市特别容易受到流行病传播的影响。在这里，我们开发了一种数据驱动的方法，结合元人口建模，以捕捉人口密度，流动性和流行病传播之间的相互作用。我们研究了来自四大洲的163个城市，并报告了一个全球趋势，即在人口流动主要集中在高人口密度中心之间的城市中，由人类流动引起的流行病风险持续增加。我们将我们的框架应用于SARS-CoV-2在美国的传播，为观察到的城市间传播过程的异质性提供了一个合理的解释。基于这一见解，我们提出了现实的缓解策略（比封锁更不严重），基于修改城市的流动性。我们的研究结果表明，一个最优的控制策略涉及到一个不对称的政策，限制进入最脆弱的地区，但允许居民继续其通常的流动pattern.The流行病爆发在城市环境中的演变是众所周知的人口，结构和经济特征之间的相互作用。在这里，作者将联合收割机数据驱动的方法与元人口模型相结合，表明城市的流行病脆弱性取决于人流的形态，并提出如何修改城市的流动骨干，以最大限度地减少流行病的风险。
The increasing agglomeration of people in dense urban areas coupled with the existence of efficient modes of transportation connecting such centers, make cities particularly vulnerable to the spread of epidemics. Here we develop a data-driven approach combines with a meta-population modeling to capture the interplay between population density, mobility and epidemic spreading. We study 163 cities, chosen from four different continents, and report a global trend where the epidemic risk induced by human mobility increases consistently in those cities where mobility flows are predominantly between high population density centers. We apply our framework to the spread of SARS-CoV-2 in the United States, providing a plausible explanation for the observed heterogeneity in the spreading process across cities. Based on this insight, we propose realistic mitigation strategies (less severe than lockdowns), based on modifying the mobility in cities. Our results suggest that an optimal control strategy involves an asymmetric policy that restricts flows entering the most vulnerable areas but allowing residents to continue their usual mobility patterns.The evolution of epidemic outbreaks in urban settings is known to stem from the interplay between demographic, structural, and economical characteristics. Here, the authors combine a data driven approach with meta-population modelling to show that the epidemic vulnerability of cities hinges on the morphology of human flows, and propose how a city's mobility backbone could be modified to minimize the epidemic risk.