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A framework for considering the utility of models when facing tough decisions in public health: a guideline for policy-makers.
Thompson, Jason; McClure, Roderick; Scott, Nick; Hellard, Margaret; Abeysuriya, Romesh; Vidanaarachchi, Rajith; Thwaites, John; Lazarus, Jeffrey V; Lavis, John; Michie, Susan; Bullen, Chris; Prokopenko, Mikhail; Chang, Sheryl L; Cliff, Oliver M; Zachreson, Cameron; Blakely, Antony; Wilson, Tim; Ouakrim, Driss Ait; Sundararajan, Vijay.
  • Thompson J; Transport, Health and Urban Designed (THUD) Research Laboratory, Melbourne School of Design, The University of Melbourne, Melbourne, Australia. jason.thompson@unimelb.edu.au.
  • McClure R; Centre for Human Factors and Sociotechnical Systems, The University of the Sunshine Coast, Sippy Downs, Australia. jason.thompson@unimelb.edu.au.
  • Scott N; University Department of Rural Health, Faculty of Dentistry, Medicine and Health Sciences, The University of Melbourne, Melbourne, Australia. jason.thompson@unimelb.edu.au.
  • Hellard M; Faculty of Medicine and Health, University of New England, Armidale, Australia.
  • Abeysuriya R; Burnet Institute, Melbourne, Australia.
  • Vidanaarachchi R; Monash University, Melbourne, Australia.
  • Thwaites J; Burnet Institute, Melbourne, Australia.
  • Lazarus JV; Burnet Institute, Melbourne, Australia.
  • Lavis J; Monash University, Melbourne, Australia.
  • Michie S; Transport, Health and Urban Designed (THUD) Research Laboratory, Melbourne School of Design, The University of Melbourne, Melbourne, Australia.
  • Bullen C; Centre for Human Factors and Sociotechnical Systems, The University of the Sunshine Coast, Sippy Downs, Australia.
  • Prokopenko M; Monash University, Melbourne, Australia.
  • Chang SL; Barcelona Institute for Global Health (ISGlobal), Hospital Clinic, University of Barcelona, Barcelona, Spain.
  • Cliff OM; McMaster Health Forum, McMaster University, Hamilton, ON, Canada.
  • Zachreson C; Department of Health Research Methods, Evidence and Impact, Faculty of Health Sciences, McMaster University, Hamilton, ON, Canada.
  • Blakely A; Centre for Behaviour Change, University College London, London, United Kingdom.
  • Wilson T; National Institute for Health Innovation, The University of Auckland, Auckland, New Zealand.
  • Ouakrim DA; Centre for Complex Systems, The University of Sydney, Camperdown, Australia.
  • Sundararajan V; Sydney Institute for Infectious Diseases, The University of Sydney, Camperdown, Australia.
Health Res Policy Syst ; 20(1): 107, 2022 Oct 08.
Article in English | MEDLINE | ID: covidwho-2064815
ABSTRACT
The COVID-19 pandemic has brought the combined disciplines of public health, infectious disease and policy modelling squarely into the spotlight. Never before have decisions regarding public health measures and their impacts been such a topic of international deliberation, from the level of individuals and communities through to global leaders. Nor have models-developed at rapid pace and often in the absence of complete information-ever been so central to the decision-making process. However, after nearly 3 years of experience with modelling, policy-makers need to be more confident about which models will be most helpful to support them when taking public health decisions, and modellers need to better understand the factors that will lead to successful model adoption and utilization. We present a three-stage framework for achieving these ends.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Public Health / COVID-19 Limits: Humans Language: English Journal: Health Res Policy Syst Year: 2022 Document Type: Article Affiliation country: S12961-022-00902-6

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Public Health / COVID-19 Limits: Humans Language: English Journal: Health Res Policy Syst Year: 2022 Document Type: Article Affiliation country: S12961-022-00902-6