Inferring the effectiveness of government interventions against COVID-19-Reference-Cited by-同舟云学术

Inferring the effectiveness of government interventions against COVID-19

Published:2021-02-19 Issue:6531 Volume:371 Page:
ISSN:0036-8075
Container-title:Science
language:en
Short-container-title:Science

Author:

Brauner Jan M.¹²^ORCID,Mindermann Sören¹^ORCID,Sharma Mrinank²³⁴^ORCID,Johnston David⁵⁶^ORCID,Salvatier John⁶^ORCID,Gavenčiak Tomáš⁷^ORCID,Stephenson Anna B.⁸,Leech Gavin⁹^ORCID,Altman George¹⁰^ORCID,Mikulik Vladimir¹¹,Norman Alexander John¹²,Monrad Joshua Teperowski²¹³¹⁴^ORCID,Besiroglu Tamay¹⁵^ORCID,Ge Hong¹⁶^ORCID,Hartwick Meghan A.¹⁷^ORCID,Teh Yee Whye³^ORCID,Chindelevitch Leonid¹⁸¹⁹^ORCID,Gal Yarin¹,Kulveit Jan²^ORCID

Affiliation:

1. Oxford Applied and Theoretical Machine Learning (OATML) Group, Department of Computer Science, University of Oxford, Oxford, UK.

2. Future of Humanity Institute, University of Oxford, Oxford, UK.

3. Department of Statistics, University of Oxford, Oxford, UK.

4. Department of Engineering Science, University of Oxford, Oxford, UK.

5. College of Engineering and Computer Science, Australian National University, Canberra, Australia.

6. Quantified Uncertainty Research Institute, San Francisco, CA, USA.

7. Independent scholar, Prague, Czech Republic.

8. Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA.

9. School of Computer Science, University of Bristol, Bristol, UK.

10. School of Medical Sciences, University of Manchester, Manchester, UK.

11. Independent scholar, London, UK.

12. Mathematical, Physical and Life Sciences (MPLS) Doctoral Training Centre, University of Oxford, Oxford, UK.

13. Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, UK.

14. Department of Health Policy, London School of Economics and Political Science, London, UK.

15. Faculty of Economics, University of Cambridge, Cambridge, UK.

16. Engineering Department, University of Cambridge, Cambridge, UK.

17. Tufts Initiative for the Forecasting and Modeling of Infectious Diseases, Tufts University, Boston, MA, USA.

18. Medical Research Council (MRC) Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK.

19. Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, UK.

Abstract

How to hold down transmission Early in 2020, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission was curbed in many countries by imposing combinations of nonpharmaceutical interventions. Sufficient data on transmission have now accumulated to discern the effectiveness of individual interventions. Brauner et al. amassed and curated data from 41 countries as input to a model to identify the individual nonpharmaceutical interventions that were the most effective at curtailing transmission during the early pandemic. Limiting gatherings to fewer than 10 people, closing high-exposure businesses, and closing schools and universities were each more effective than stay-at-home orders, which were of modest effect in slowing transmission. Science , this issue p. eabd9338

Funder

Engineering and Physical Sciences Research Council

Cancer Research UK

UK Medical Research Council

Community Jameel

Berkeley Existential Risk Initiative

Deepmind

UK Foreign, Commonwealth & Development Office

EDCTP2 Programme

Publisher

American Association for the Advancement of Science (AAAS)

Subject