Mobile Phone-Based Population Flow Data for the COVID-19 Outbreak in Mainland China

Author:

Lu Xin12ORCID,Tan Jing34,Cao Ziqiang1,Xiong Yiquan3,Qin Shuo1,Wang Tong1ORCID,Liu Chunrong3,Huang Shiyao3,Zhang Wei5,Marczak Laurie B.6,Hay Simon I.6ORCID,Thabane Lehana4,Guyatt Gordon H.4,Sun Xin3ORCID

Affiliation:

1. College of Systems Engineering, National University of Defense Technology, Changsha, China

2. Department of Global Public Health, Karolinska Institute, Stockholm, Sweden

3. Chinese Evidence-Based Medicine Center, West China Hospital, Sichuan University, Chengdu, China

4. Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Canada

5. West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China

6. Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA

Abstract

Background. Human migration is one of the driving forces for amplifying localized infectious disease outbreaks into widespread epidemics. During the outbreak of COVID-19 in China, the travels of the population from Wuhan have furthered the spread of the virus as the period coincided with the world’s largest population movement to celebrate the Chinese New Year. Methods. We have collected and made public an anonymous and aggregated mobility dataset extracted from mobile phones at the national level, describing the outflows of population travel from Wuhan. We evaluated the correlation between population movements and the virus spread by the dates when the number of diagnosed cases was documented. Results. From Jan 1 to Jan 22 of 2020, a total of 20.2 million movements of at-risk population occurred from Wuhan to other regions in China. A large proportion of these movements occurred within Hubei province (84.5%), and a substantial increase of travels was observed even before the beginning of the official Chinese Spring Festival Travel. The outbound flows from Wuhan before the lockdown were found strongly correlated with the number of diagnosed cases in the destination cities (log-transformed). Conclusions. The regions with the highest volume of receiving at-risk populations were identified. The movements of the at-risk population were strongly associated with the virus spread. These results together with province-by-province reports have been provided to governmental authorities to aid policy decisions at both the state and provincial levels. We believe that the effort in making this data available is extremely important for COVID-19 modelling and prediction.

Funder

West China Hospital 1.3.5 Project for Disciplines of Excellence

Publisher

American Association for the Advancement of Science (AAAS)

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