Your browser doesn't support javascript.
Effect of non-pharmaceutical interventions to contain COVID-19 in China.
Lai, Shengjie; Ruktanonchai, Nick W; Zhou, Liangcai; Prosper, Olivia; Luo, Wei; Floyd, Jessica R; Wesolowski, Amy; Santillana, Mauricio; Zhang, Chi; Du, Xiangjun; Yu, Hongjie; Tatem, Andrew J.
  • Lai S; WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK. shengjie.lai@soton.ac.uk.
  • Ruktanonchai NW; School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China. shengjie.lai@soton.ac.uk.
  • Zhou L; WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK. nr1e14@soton.ac.uk.
  • Prosper O; Population Health Sciences, Virginia Tech, Blacksburg, VA, USA. nr1e14@soton.ac.uk.
  • Luo W; Wuhan Center for Disease Control and Prevention, Wuhan, China.
  • Floyd JR; Department of Mathematics, University of Tennessee, Knoxville, TN, USA.
  • Wesolowski A; Computational Health Informatics Program, Boston Children's Hospital, Boston, MA, USA.
  • Santillana M; Department of Pediatrics, Harvard Medical School, Boston, MA, USA.
  • Zhang C; WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK.
  • Du X; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
  • Yu H; Computational Health Informatics Program, Boston Children's Hospital, Boston, MA, USA.
  • Tatem AJ; Department of Pediatrics, Harvard Medical School, Boston, MA, USA.
Nature ; 585(7825): 410-413, 2020 09.
Article in English | MEDLINE | ID: covidwho-164593
ABSTRACT
On 11 March 2020, the World Health Organization (WHO) declared coronavirus disease 2019 (COVID-19) a pandemic1. The strategies based on non-pharmaceutical interventions that were used to contain the outbreak in China appear to be effective2, but quantitative research is still needed to assess the efficacy of non-pharmaceutical interventions and their timings3. Here, using epidemiological data on COVID-19 and anonymized data on human movement4,5, 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.
Subject(s)

Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Social Isolation / Travel / Quarantine / Hand Disinfection / Contact Tracing / Coronavirus Infections / Pandemics Type of study: Diagnostic study / Experimental Studies / Observational study / Prognostic study Limits: Humans Country/Region as subject: Asia Language: English Journal: Nature Year: 2020 Document Type: Article Affiliation country: S41586-020-2293-x

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Social Isolation / Travel / Quarantine / Hand Disinfection / Contact Tracing / Coronavirus Infections / Pandemics Type of study: Diagnostic study / Experimental Studies / Observational study / Prognostic study Limits: Humans Country/Region as subject: Asia Language: English Journal: Nature Year: 2020 Document Type: Article Affiliation country: S41586-020-2293-x