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A global assessment of the impact of school closure in reducing COVID-19 spread.
Wu, Joseph T; Mei, Shujiang; Luo, Sihui; Leung, Kathy; Liu, Di; Lv, Qiuying; Liu, Jian; Li, Yuan; Prem, Kiesha; Jit, Mark; Weng, Jianping; Feng, Tiejian; Zheng, Xueying; Leung, Gabriel M.
  • Wu JT; WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, People's Republic of China.
  • Mei S; Laboratory of Data Discovery for Health (D24H), Hong Kong Science Park, New Territories, Hong Kong SAR, People's Republic of China.
  • Luo S; Department of Communicable Diseases Control and Prevention, Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, People's Republic of China.
  • Leung K; The First Affiliated Hospital of USTC, Division of Life Science and Medicine, University of Science and Technology of China, Hefei, People's Republic of China.
  • Liu D; Clinical Research Hospital (Hefei) of Chinese Academy of Science, Hefei, People's Republic of China.
  • Lv Q; WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, People's Republic of China.
  • Liu J; Laboratory of Data Discovery for Health (D24H), Hong Kong Science Park, New Territories, Hong Kong SAR, People's Republic of China.
  • Li Y; WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, People's Republic of China.
  • Prem K; Laboratory of Data Discovery for Health (D24H), Hong Kong Science Park, New Territories, Hong Kong SAR, People's Republic of China.
  • Jit M; Department of Communicable Diseases Control and Prevention, Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, People's Republic of China.
  • Weng J; Anqing Hospital Affiliated to Anhui Medical University (Anqing Municipal Hospital), Anqing, People's Republic of China.
  • Feng T; Department of Communicable Diseases Control and Prevention, Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, People's Republic of China.
  • Zheng X; Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK.
  • Leung GM; WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, People's Republic of China.
Philos Trans A Math Phys Eng Sci ; 380(2214): 20210124, 2022 Jan 10.
Article en En | MEDLINE | ID: mdl-34802277
Prolonged school closure has been adopted worldwide to control COVID-19. Indeed, UN Educational, Scientific and Cultural Organization figures show that two-thirds of an academic year was lost on average worldwide due to COVID-19 school closures. Such pre-emptive implementation was predicated on the premise that school children are a core group for COVID-19 transmission. Using surveillance data from the Chinese cities of Shenzhen and Anqing together, we inferred that compared with the elderly aged 60 and over, children aged 18 and under and adults aged 19-59 were 75% and 32% less susceptible to infection, respectively. Using transmission models parametrized with synthetic contact matrices for 177 jurisdictions around the world, we showed that the lower susceptibility of school children substantially limited the effectiveness of school closure in reducing COVID-19 transmissibility. Our results, together with recent findings that clinical severity of COVID-19 in children is lower, suggest that school closure may not be ideal as a sustained, primary intervention for controlling COVID-19. This article is part of the theme issue 'Data science approach to infectious disease surveillance'.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: COVID-19 Tipo de estudio: Prognostic_studies Límite: Aged / Child / Humans / Middle aged Idioma: En Año: 2022 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: COVID-19 Tipo de estudio: Prognostic_studies Límite: Aged / Child / Humans / Middle aged Idioma: En Año: 2022 Tipo del documento: Article