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

descriptionPublicationkeyboard_double_arrow_right Article , Preprint 06 Mar 2020 English HAL CCSD

Moritz U. G. Kraemer; Chia-Hung Yang; Bernardo Gutierrez; Chieh-Hsi Wu; Brennan Klein; David M. Pigott; Louis du Plessis; +10 Authors

doi: 10.1126/science.abb4218 , 10.1101/2020.03.02.20026708

pmid: 32213647 , 32511452

pmc: PMC7239080 , PMC7146642

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

- Summary
- Subjects
- References
  (40)
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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.

One sentence summary: The spread of COVID-19 in China was driven by human mobility early on and mitigated substantially by drastic control measures implemented since the end of January.

Countries

United Kingdom, United Kingdom, France

Related Organizations

University of Oxford
United Kingdom
Northwestern University
United States
Universidad San Francisco de Quito
Ecuador
University of Cambridge
United Kingdom
CNRS
France

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Subjects by Vocabulary

Microsoft Academic Graph classification: 2019-20 coronavirus outbreak China Environmental health Outbreak Geography Demographics Transmission (mechanics) law.invention law Epidemiological Monitoring Coronavirus disease 2019 (COVID-19) Psychological intervention Control (management) Socioeconomics

Keywords

[SDV] Life Sciences [q-bio], [SDV.MHEP] Life Sciences [q-bio]/Human health and pathology, Multidisciplinary, [SDV]Life Sciences [q-bio], [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology, Age Distribution, Betacoronavirus, COVID-19, China, Coronavirus Infections, Epidemiological Monitoring, Humans, Linear Models, Pandemics, Pneumonia, Viral, SARS-CoV-2, Sex Distribution, Spatial Analysis, Travel, Research Article, Research Articles, R-Articles, Ecology, Epidemiology, Coronavirus, Age Distribution, Betacoronavirus, COVID-19, China, Coronavirus Infections, Epidemiological Monitoring, Humans, Linear Models, Pandemics, Pneumonia, Viral, SARS-CoV-2, Sex Distribution, Spatial Analysis, Travel, Article

40 references, page 1 of 4

1. S. Chen, J. Yang, W. Yang, C. Wang, T. Baerninghausen, COVID-19 control in China during mass population movements at New Year. Lancet (2020), doi:10.1016/ S0140-6736(20)30421-9.

2. N. Zhu et al., A Novel Coronavirus from Patients with Pneumonia in China, 2019. N. Engl. J. Med., NEJMoa2001017 (2020).

3. H. Tian et al., medRxiv, in press, doi:10.1101/2020.01.30.20019844.

4. Z. Du et al., Risk for Transportation of 2019 Novel Coronavirus Disease from Wuhan to Other Cities in China. Emerg. Infect. Dis. 26 (2020), doi:10.3201/eid2605.200146.

5. J. T. Wu, K. Leung, G. M. Leung, Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study. Lancet. 6736 (2020), doi:10.1016/S0140-6736(20)30260-9.

6. S. Cauchemez et al., Middle East respiratory syndrome coronavirus: Quantification of the extent of the epidemic, surveillance biases, and transmissibility. Lancet Infect. Dis. 14, 50-56 (2014). [OpenAIRE]

7. J. Lessler et al., Incubation periods of acute respiratory viral infections: a systematic review. Lancet Infect. Dis. 9, 291-300 (2009). [OpenAIRE]

8. J. A. Backer, D. Klinkenberg, J. Wallinga, Incubation period of 2019 novel coronavirus (2019- nCoV) infections among travellers from Wuhan, China, 20-28 January 2020. Eurosurveillance. 25, 20-28 (2020). [OpenAIRE]

9. Q. Li et al., Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus-Infected Pneumonia. N. Engl. J. Med., 1-9 (2020).

10. World Health Organization (WHO), Coronavirus disease 2019 (COVID-19) Situation Report - 27 (2020) (available at https://www.who.int/docs/default-source/coronaviruse/situationreports/20200216-sitrep-27-covid-19.pdf?sfvrsn=78c0eb78_2).

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Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	2K
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Exceptional
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Substantial
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Exceptional

Usage byUsageCounts

visibility	views	13
download	downloads	38

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	2K
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Exceptional
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Substantial
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Exceptional