基于手机大数据的中国人口迁徙模式及疫情影响研究

Measuring the impact of COVID-19 on China’s population migration with mobile phone data

新型冠状病毒感染的肺炎(COVID-19)可通过人员接触与流动迅速传播,因此研究人类迁徙和出行模式的变化对疫情防控至关重要.本文基于手机运营商2020年春运及疫情暴发前后连续两个月的全国地级市之间的人口流动数据,运用时序网络分析方法构建人口流动网络拓扑结构指标,并通过引入地理衰减因子提出Spatial-Louvain社团检测算法,研究平时、春运、疫情防控隔离和生产复工四阶段的人口迁徙模式的时空演化规律.研究发现:受各地疫情防控措施影响,武汉封城后全国城市间人口流量急剧下降,并持续至2月中旬.疫情期间人口流动网络结构呈现四阶段的时空演化模式;本文提出的空间网络社团检测算法比传统Louvain算法平均模块度值提高了14%;中国城市分布以经济交互和地理位置为基础,形成了以核心城市为中心,向周边辐射的城市群格局;疫情因素仅能在短暂时间内改变部分城市的城市群归属,当该因素消失或减弱后,城市群能迅速恢复原有格局.

Population migration is an essential medium for the spread of epidemic,which can accelerate localized outbreaks of disease into widespread epidemic.Large-scale population movements between different areas increase the risk of cross-infection and bring great challenges to epidemic prevention and control.As COVID-19 can spread rapidly through human-to-human transmission,understanding its migration patterns is essential to modeling its spreading and evaluating the efficiency of mitigation policies applied to COVID-19.Using nationwide mobile phone data to track population flows throughout China at prefecture-level,we use the temporal network analysis to compare topological metrics of population mobility network during two consecutive months between before and after the outbreak,i.e.January 1st to February 29th.To detect the regions which are closely connected with population movements,we propose a Spatial-Louvain algorithm through adapting a gravity attenuation factor.Moreover,our proposed algorithm achieves an improvement of 14%in modularity compared with the Louvain algorithm.Additionally,we divide the period into four stages,i.e.normal time,Chunyun migration,epidemic interventions,and recovery time,to describe the patterns of mobility network’s evolution.Through the above methods,we explore the evolution pattern and spatial mechanism of the population mobility from the perspective of spatiotemporal big data and acquire some meaningful findings.Firstly,we find that after the lockdown of Wuhan and effective epidemic interventions,a substantial reduction in mobility lasted until mid-February.Secondly,based on the economic interaction and geographic location,China has formed an urban agglomeration structure with core cities centering and radiating toward the surroundings.Thirdly,in the extreme cases,the dominant factor of population mobility in remote areas is geographic location rather than economy.Fourthly,the urban agglomeration structure of cities is robust so that when the epidemic weakens or disappears,the city clusters can quickly recover into their original patterns.