The effect of human mobility and control measures on the COVID-19 epidemic in China

Moritz U. G. Kraemer(Boston University), Chia-Hung Yang(Northeastern University), Bernardo Gutiérrez(University of Oxford), Chieh‐Hsi Wu(University of Southampton), Brennan Klein(Northeastern University), David M. Pigott(Institute for Health Metrics and Evaluation), open COVID-19 data working group(University of Oxford), Louis du Plessis(University of Oxford), Nuno R. Faria(Harvard University), Ruoran Li(Harvard University), William P. Hanage(Boston University), John S. Brownstein(Boston University), Maylis Layan(Northeastern University), Alessandro Vespignani(Northeastern University), Huaiyu Tian(Beijing Normal University), Christopher Dye(Centre National de la Recherche Scientifique), Simon Cauchemez(Centre National de la Recherche Scientifique), Oliver G. Pybus(Northeastern University), Samuel V. Scarpino(Northeastern University)
medRxiv
March 6, 2020
Cited by 362Open Access
Full Text

Abstract

The ongoing COVID-19 outbreak has expanded rapidly throughout China. Major behavioral, clinical, and state interventions are underway currently to mitigate the epidemic and prevent the persistence of the virus in human populations in China and worldwide. It remains unclear how these unprecedented interventions, including travel restrictions, have affected COVID-19 spread in China. We use real-time mobility data from Wuhan and detailed case data including travel history to elucidate the role of case importation on transmission in cities across China and ascertain the impact of control measures. Early on, the spatial distribution of COVID-19 cases in China was well explained by human mobility data. Following the implementation of control measures, this correlation dropped and growth rates became negative in most locations, although shifts in the demographics of reported cases are still indicative of local chains of transmission outside Wuhan. This study shows that the drastic control measures implemented in China have substantially mitigated the spread of COVID-19.


Related Papers

No related papers found

Powered by citation graph analysis