Literature DB >> 32511428

Age profile of susceptibility, mixing, and social distancing shape the dynamics of the novel coronavirus disease 2019 outbreak in China.

Juanjuan Zhang1, Maria Litvinova2, Yuxia Liang1, Yan Wang1, Wei Wang1, Shanlu Zhao3, Qianhui Wu1, Stefano Merler4, Cecile Viboud5, Alessandro Vespignani6,2, Marco Ajelli4, Hongjie Yu1.   

Abstract

Strict interventions were successful to control the novel coronavirus (COVID-19) outbreak in China. As transmission intensifies in other countries, the interplay between age, contact patterns, social distancing, susceptibility to infection and disease, and COVID-19 dynamics remains unclear. To answer these questions, we analyze contact surveys data for Wuhan and Shanghai before and during the outbreak and contact tracing information from Hunan Province. Daily contacts were reduced 7-9 fold during the COVID-19 social distancing period, with most interactions restricted to the household. Children 0-14 years were 59% (95% CI 7-82%) less susceptible than individuals 65 years and over. A transmission model calibrated against these data indicates that social distancing alone, as implemented in China during the outbreak, is sufficient to control COVID-19. While proactive school closures cannot interrupt transmission on their own, they reduce peak incidence by half and delay the epidemic. These findings can help guide global intervention policies.

Entities:  

Year:  2020        PMID: 32511428      PMCID: PMC7217069          DOI: 10.1101/2020.03.19.20039107

Source DB:  PubMed          Journal:  medRxiv


  8 in total

1.  Reactive school closure weakens the network of social interactions and reduces the spread of influenza.

Authors:  Maria Litvinova; Quan-Hui Liu; Evgeny S Kulikov; Marco Ajelli
Journal:  Proc Natl Acad Sci U S A       Date:  2019-06-17       Impact factor: 11.205

2.  A Systematic Review of Social Contact Surveys to Inform Transmission Models of Close-contact Infections.

Authors:  Thang Hoang; Pietro Coletti; Alessia Melegaro; Jacco Wallinga; Carlos G Grijalva; John W Edmunds; Philippe Beutels; Niel Hens
Journal:  Epidemiology       Date:  2019-09       Impact factor: 4.822

3.  Patterns of human social contact and contact with animals in Shanghai, China.

Authors:  Juanjuan Zhang; Petra Klepac; Jonathan M Read; Alicia Rosello; Xiling Wang; Shengjie Lai; Meng Li; Yujian Song; Qingzhen Wei; Hao Jiang; Juan Yang; Henry Lynn; Stefan Flasche; Mark Jit; Hongjie Yu
Journal:  Sci Rep       Date:  2019-10-22       Impact factor: 4.379

4.  Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study.

Authors:  Joseph T Wu; Kathy Leung; Gabriel M Leung
Journal:  Lancet       Date:  2020-01-31       Impact factor: 79.321

5.  The transmissibility of novel Coronavirus in the early stages of the 2019-20 outbreak in Wuhan: Exploring initial point-source exposure sizes and durations using scenario analysis.

Authors:  Sam Abbott; Joel Hellewell; James Munday; Sebastian Funk
Journal:  Wellcome Open Res       Date:  2020-02-03

6.  Social contacts and mixing patterns relevant to the spread of infectious diseases.

Authors:  Joël Mossong; Niel Hens; Mark Jit; Philippe Beutels; Kari Auranen; Rafael Mikolajczyk; Marco Massari; Stefania Salmaso; Gianpaolo Scalia Tomba; Jacco Wallinga; Janneke Heijne; Malgorzata Sadkowska-Todys; Magdalena Rosinska; W John Edmunds
Journal:  PLoS Med       Date:  2008-03-25       Impact factor: 11.069

7.  Projecting social contact matrices in 152 countries using contact surveys and demographic data.

Authors:  Kiesha Prem; Alex R Cook; Mark Jit
Journal:  PLoS Comput Biol       Date:  2017-09-12       Impact factor: 4.475

8.  COVID-19: what is next for public health?

Authors:  David L Heymann; Nahoko Shindo
Journal:  Lancet       Date:  2020-02-13       Impact factor: 79.321

  8 in total

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