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Effect of non-pharmaceutical interventions to contain COVID-19 in China

Effect of non-pharmaceutical interventions to contain COVID-19 in China
Effect of non-pharmaceutical interventions to contain COVID-19 in China

On 11 March 2020, the World Health Organization (WHO) declared coronavirus disease 2019 (COVID-19) a pandemic 1. The strategies based on non-pharmaceutical interventions that were used to contain the outbreak in China appear to be effective 2, but quantitative research is still needed to assess the efficacy of non-pharmaceutical interventions and their timings 3. Here, using epidemiological data on COVID-19 and anonymized data on human movement 4,5, we develop a modelling framework that uses daily travel networks to simulate different outbreak and intervention scenarios across China. We estimate that there were a total of 114,325 cases of COVID-19 (interquartile range 76,776–164,576) in mainland China as of 29 February 2020. Without non-pharmaceutical interventions, we predict that the number of cases would have been 67-fold higher (interquartile range 44–94-fold) by 29 February 2020, and we find that the effectiveness of different interventions varied. We estimate that early detection and isolation of cases prevented more infections than did travel restrictions and contact reductions, but that a combination of non-pharmaceutical interventions achieved the strongest and most rapid effect. According to our model, the lifting of travel restrictions from 17 February 2020 does not lead to an increase in cases across China if social distancing interventions can be maintained, even at a limited level of an on average 25% reduction in contact between individuals that continues until late April. These findings improve our understanding of the effects of non-pharmaceutical interventions on COVID-19, and will inform response efforts across the world.

0028-0836
410-413
Lai, Shengjie
b57a5fe8-cfb6-4fa7-b414-a98bb891b001
Ruktanonchai, Nick
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Zhou, Liangcai
11c9d257-1256-4d56-86a6-d5e3d8fa9f79
Prosper, Olivia
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Luo, Wei
c76a8e31-38e7-47cb-bd13-670fc8ab036d
Floyd, Jessica
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Wesolowski, Amy
343b0df8-5a2f-46e2-9f1c-001d4adf7fb1
Santillana, Mauricio
3988a10d-f370-41aa-b4fe-df6b7ca0040b
Zhang, Chi
420acf73-d18f-49d7-941f-868ba2d772b9
Du, Xiangjun
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Yu, Hongjie
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Tatem, Andrew
6c6de104-a5f9-46e0-bb93-a1a7c980513e
Lai, Shengjie
b57a5fe8-cfb6-4fa7-b414-a98bb891b001
Ruktanonchai, Nick
fe68cb8d-3760-4955-99fa-47d43f86580a
Zhou, Liangcai
11c9d257-1256-4d56-86a6-d5e3d8fa9f79
Prosper, Olivia
5d82e9bd-8612-41b8-a266-444c6b98371b
Luo, Wei
c76a8e31-38e7-47cb-bd13-670fc8ab036d
Floyd, Jessica
b54620d7-9154-4807-a9a7-60d87001b0dc
Wesolowski, Amy
343b0df8-5a2f-46e2-9f1c-001d4adf7fb1
Santillana, Mauricio
3988a10d-f370-41aa-b4fe-df6b7ca0040b
Zhang, Chi
420acf73-d18f-49d7-941f-868ba2d772b9
Du, Xiangjun
20efe0ad-c516-44e1-9381-0539e00217d4
Yu, Hongjie
80d8f51d-a23c-468f-8ac9-7262d9b31b40
Tatem, Andrew
6c6de104-a5f9-46e0-bb93-a1a7c980513e

Lai, Shengjie, Ruktanonchai, Nick, Zhou, Liangcai, Prosper, Olivia, Luo, Wei, Floyd, Jessica, Wesolowski, Amy, Santillana, Mauricio, Zhang, Chi, Du, Xiangjun, Yu, Hongjie and Tatem, Andrew (2020) Effect of non-pharmaceutical interventions to contain COVID-19 in China. Nature, 585 (7825), 410-413. (doi:10.1038/s41586-020-2293-x).

Record type: Article

Abstract

On 11 March 2020, the World Health Organization (WHO) declared coronavirus disease 2019 (COVID-19) a pandemic 1. The strategies based on non-pharmaceutical interventions that were used to contain the outbreak in China appear to be effective 2, but quantitative research is still needed to assess the efficacy of non-pharmaceutical interventions and their timings 3. Here, using epidemiological data on COVID-19 and anonymized data on human movement 4,5, we develop a modelling framework that uses daily travel networks to simulate different outbreak and intervention scenarios across China. We estimate that there were a total of 114,325 cases of COVID-19 (interquartile range 76,776–164,576) in mainland China as of 29 February 2020. Without non-pharmaceutical interventions, we predict that the number of cases would have been 67-fold higher (interquartile range 44–94-fold) by 29 February 2020, and we find that the effectiveness of different interventions varied. We estimate that early detection and isolation of cases prevented more infections than did travel restrictions and contact reductions, but that a combination of non-pharmaceutical interventions achieved the strongest and most rapid effect. According to our model, the lifting of travel restrictions from 17 February 2020 does not lead to an increase in cases across China if social distancing interventions can be maintained, even at a limited level of an on average 25% reduction in contact between individuals that continues until late April. These findings improve our understanding of the effects of non-pharmaceutical interventions on COVID-19, and will inform response efforts across the world.

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Accepted/In Press date: 23 April 2020
e-pub ahead of print date: 4 May 2020
Published date: 17 September 2020

Identifiers

Local EPrints ID: 439847
URI: http://eprints.soton.ac.uk/id/eprint/439847
ISSN: 0028-0836
PURE UUID: 7fd08364-769a-4cb9-9a32-b4c03d3f3934
ORCID for Shengjie Lai: ORCID iD orcid.org/0000-0001-9781-8148
ORCID for Andrew Tatem: ORCID iD orcid.org/0000-0002-7270-941X

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Date deposited: 05 May 2020 16:31
Last modified: 18 Feb 2021 17:37

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Contributors

Author: Shengjie Lai ORCID iD
Author: Liangcai Zhou
Author: Olivia Prosper
Author: Wei Luo
Author: Jessica Floyd
Author: Amy Wesolowski
Author: Mauricio Santillana
Author: Chi Zhang
Author: Xiangjun Du
Author: Hongjie Yu
Author: Andrew Tatem ORCID iD

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