4.8 Article

Inferring the effectiveness of government interventions against COVID-19

期刊

SCIENCE
卷 371, 期 6531, 页码 802-+

出版社

AMER ASSOC ADVANCEMENT SCIENCE
DOI: 10.1126/science.abd9338

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资金

  1. EPSRC Centre for Doctoral Training in Autonomous Intelligent Machines and Systems [EP/S024050/1]
  2. Cancer Research UK
  3. Oxford University
  4. DeepMind
  5. UKRI Centre for Doctoral Training in Interactive Artificial Intelligence [EP/S022937/1]
  6. MRC Centre for Global Infectious Disease Analysis [MR/R015600/1]
  7. U. K. Medical Research Council (MRC)
  8. U.K. Foreign, Commonwealth and Development Office (FCDO), under the MRC/FCDO
  9. Berkeley Existential Risk Initiative
  10. EPSRC [EP/S022937/1] Funding Source: UKRI

向作者/读者索取更多资源

Research has found that closing educational institutions, limiting gathering sizes, and closing face-to-face businesses are effective nonpharmaceutical interventions in controlling the COVID-19 pandemic, while the additional effect of stay-at-home orders is relatively small.
Governments are attempting to control the COVID-19 pandemic with nonpharmaceutical interventions (NPIs). However, the effectiveness of different NPIs at reducing transmission is poorly understood. We gathered chronological data on the implementation of NPIs for several European and non-European countries between January and the end of May 2020. We estimated the effectiveness of these NPIs, which range from limiting gathering sizes and closing businesses or educational institutions to stay-at-home orders. To do so, we used a Bayesian hierarchical model that links NPI implementation dates to national case and death counts and supported the results with extensive empirical validation. Closing all educational institutions, limiting gatherings to 10 people or less, and closing face-to-face businesses each reduced transmission considerably. The additional effect of stay-at-home orders was comparatively small.

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