Moritz U. G. Kraemer 1 , 2 , 3 , * , Chia-Hung Yang 4 , Bernardo Gutierrez 1 , 5 , Chieh-Hsi Wu 6 , Brennan Klein 4 , David M. Pigott 7 , Open COVID-19 Data Working Group †, Louis du Plessis 1 , Nuno R. Faria 1 , Ruoran Li 8 , William P. Hanage 8 , John S. Brownstein 2 , 3 , Maylis Layan 9 , 10 , Alessandro Vespignani 4 , 11 , Huaiyu Tian 12 , Christopher Dye 1 , Oliver G. Pybus 1 , 13 , * , Samuel V. Scarpino 4 , *
25 March 2020
The ongoing COVID-19 outbreak expanded rapidly throughout China. Major behavioral, clinical, and state interventions have been undertaken 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, 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 explained well 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 were still indicative of local chains of transmission outside Wuhan. This study shows that the drastic control measures implemented in China substantially mitigated the spread of COVID-19.