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Inferring the effectiveness of government interventions against COVID-19.

Jan Markus BraunerSören MindermannMrinank SharmaDavid JohnstonJohn SalvatierTomáš GavenčiakAnna B StephensonGavin LeechGeorge AltmanVladimir MikulikAlexander John NormanJoshua Teperowski MonradTamay BesirogluHong GeMeghan A HartwickYee Whye TehLeonid ChindelevitchYarin GalJan Kulveit
Published in: Science (New York, N.Y.) (2020)
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.
Keyphrases
  • randomized controlled trial
  • systematic review
  • quality improvement
  • primary care
  • healthcare
  • coronavirus disease
  • physical activity
  • sars cov
  • machine learning
  • big data
  • artificial intelligence