Examining the population flow network in China and its implications for epidemic control based on Baidu migration data

Sheng Wei,Lei Wang

doi:10.1057/s41599-020-00633-5

Abstract

This paper examines the spatial pattern of the population flow network and its implications for containing epidemic spread in China. The hierarchical and spatial subnetwork structure of national population movement networks is analysed by using Baidu migration data before and during the Chinese Spring Festival. The results show that the population flow was mainly concentrated on the east side of the Hu Huanyong Line, a national east-west division of population density. Some local hot spots of migration were formed in various regions. Although there were a large number of migrants in eastern regions, they tended to concentrate in corresponding provincial capital cities and the population movement subnetworks were affected by provincial administrative divisions. The patterns identified are helpful for the provincial government to formulate population policies on epidemic control. The movement flow from Wuhan (the city where the covid-19 outbreak) to other cities is significantly and positively correlated with the number of confirmed cases in other Chinese cities (about 70% of the population was constituted through innerprovincial movement in Hubei). The results show that the population flow network has great significance for informing the containment of the epidemic spread in the early stage. It suggests the importance for the Chinese government to implement provincial and municipal lockdown measures to contain the epidemic spread. The paper indicates that spatial analysis of population flow network has practical implications for controlling epidemic outbreaks.

Highlights

The spatial pattern of population movements reflects the relationship between cities and constitutes important information in exploring the economic connections and traffic demands between cities (Shumway and Otterstrom, 2010; Gonzàlez et al, 2008; Ravenstein, 1884)
We find that the spatial distribution characteristics of Betweenness centrality (BC) are associated with those of Weighted degree centrality (WDC) in general
Discussions and conclusions Different from the census data, the Baidu migration data are the most updated source for analysing the spatial pattern of population flow, and the findings are relevant to evidence-based regional population policymaking in highly mobile societies (Ma et al, 2015)

Summary

Introduction

The spatial pattern of population movements reflects the relationship between cities and constitutes important information in exploring the economic connections and traffic demands between cities (Shumway and Otterstrom, 2010; Gonzàlez et al, 2008; Ravenstein, 1884). Examining spatial patterns of population flow requires the deployment of new methods for data collection in ongoing research (Shen, 2020). Many recent studies have researched population movement based on mobile phone data, which has the benefit of high accuracy and large sample size (Bengtsson et al, 2015). These studies have explored geographic borders of human mobility, individual human mobility patterns, travel behaviour, and the spatial structure of cities (Gariazzo and Pelliccioni, 2019; Lee et al, 2018; Picornell et al, 2015; Sagl et al, 2014; Louail et al, 2014; Rinzivillo et al, 2012). Geo-tagged social media data have been used to explore the characteristics of human mobility at a much finer temporary and spatial scale (Khan et al, 2020; Hawelka et al, 2014; Naaman et al, 2012; Kamath et al, 2012)

Objectives

Methods

Results

Conclusion