Liu Jie, Hao Jingyu, Sun Yuyu, Shi Zhenwu
Northeast Forestry University, School of Civil Engineering, 26 Hexing Road, Harbin, China.
Cities. 2021 May;112:103138. doi: 10.1016/j.cities.2021.103138. Epub 2021 Feb 5.
Large-scale and diffuse population flow amplifies the localized COVID-19 outbreak into a widespread pandemic. Network analysis provides a new methodology to uncover the topology and evolution of the population flow and understand its influence on the early dynamics of COVID-19 transmission. In this paper, we simulated 42 transmission scenarios to show the distribution of the COVID-19 outbreak across China. We predicted some original (Guangzhou, Shanghai, Shenzhen) had higher total aggregate population outflows than Wuhan, indicating larger spread scopes and faster growth rates of COVID-19 outbreak. We built an importation risk model to identify some major cities (Dongguan and Foshan) with the highest total importation risk values and the highest standard deviations, indicating the core transmission chains (Dongguan-Shenzhen, Foshan-Guangzhou). We built the population flow networks to analyze their Spatio-temporal characteristics and identify the influential sub-groups and spreaders. By removing different influential spreaders, we identified Guangzhou can most influence the network's topological characteristics, and some major cities' degree centrality was significantly decreased. Our findings quantified the effectiveness of travel restrictions on delaying the epidemic growth and limiting the spread scope of COVID-19 in China, which helped better derive the geographical COVID-19 transmission related to population flow networks' structural features.
大规模且分散的人口流动将局部的新冠疫情爆发扩大为广泛的大流行。网络分析提供了一种新方法，用以揭示人口流动的拓扑结构和演变，并理解其对新冠病毒传播早期动态的影响。在本文中，我们模拟了42种传播情景，以展示新冠疫情在中国的分布情况。我们预测，一些初始城市（广州、上海、深圳）的总流出人口比武汉更多，这表明新冠疫情的传播范围更大、增长率更快。我们构建了输入风险模型，以识别总输入风险值最高且标准差最大的一些主要城市（东莞和佛山），这表明了核心传播链（东莞 - 深圳、佛山 - 广州）。我们构建了人口流动网络，以分析其时空特征，并识别有影响力的子群体和传播者。通过移除不同的有影响力的传播者，我们发现广州对网络拓扑特征的影响最大，一些主要城市的度中心性显著下降。我们的研究结果量化了旅行限制在中国延缓疫情增长和限制新冠病毒传播范围方面的有效性，这有助于更好地推导与人口流动网络结构特征相关的新冠病毒地理传播情况。
