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

Type Journal Article Author Moritz U. G. Kraemer Author Chia-Hung Yang Author Bernardo Gutierrez Author Chieh-Hsi Wu Author Brennan Klein Author David M. Pigott Author Open COVID-19 Data Working Group† Author Louis du Plessis Author Nuno R. Faria Author Ruoran Li Author William P. Hanage Author John S. Brownstein Author Maylis Layan Author Alessandro Vespignani Author Huaiyu Tian Author Christopher Dye Author Oliver G. Pybus Author Samuel V. Scarpino URL https://science.sciencemag.org/content/368/6490/493 Rights Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. http://www.sciencemag.org/about/science-licenses-journal-article-reuseThis is an article distributed under the terms of the Science Journals Default License. Series Research Article Volume 368 Issue 6490 Pages 493-497 Publication Science ISSN 0036-8075, 1095-9203 Date 25/03/2020 Extra Publisher: American Association for the Advancement of Science Section: Research Article PMID: 32213647 DOI 10.1126/science.abb4218 Library Catalog science.sciencemag.org Language en Abstract Tracing infection from mobility data What sort of measures are required to contain the spread of severe acute respiratory syndrome–coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19)? The rich data from the Open COVID-19 Data Working Group include the dates when people first reported symptoms, not just a positive test date. Using these data and real-time travel data from the internet services company Baidu, Kraemer et al. found that mobility statistics offered a precise record of the spread of SARS-CoV-2 among the cities of China at the start of 2020. The frequency of introductions from Wuhan were predictive of the size of the epidemic sparked in other provinces. However, once the virus had escaped Wuhan, strict local control measures such as social isolation and hygiene, rather than long-distance travel restrictions, played the largest part in controlling SARS-CoV-2 spread. Science, this issue p. 493 The ongoing coronavirus disease 2019 (COVID-19) outbreak expanded rapidly throughout China. Major behavioral, clinical, and state interventions were 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 used real-time mobility data from Wuhan and detailed case data including travel history to elucidate the role of case importation in transmission in cities across China and to ascertain the impact of control measures. Early on, the spatial distribution of COVID-19 cases in China was explained well by human mobility data. After 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 of Wuhan. This study shows that the drastic control measures implemented in China substantially mitigated the spread of COVID-19. Mobile phone data show that the spread of COVID-19 in China was driven by travel and mitigated substantially by local control measures. Mobile phone data show that the spread of COVID-19 in China was driven by travel and mitigated substantially by local control measures.