A framework for considering the utility of models when facing tough decisions in public health: a guideline for policy-makers
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..
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2022 |
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| Erschienen: |
2022 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:20 |
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| Enthalten in: |
Health research policy and systems - 20(2022), 1 vom: 08. Okt. |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Thompson, Jason [VerfasserIn] |
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| Links: |
Volltext [kostenfrei] |
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| Themen: |
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| Anmerkungen: |
© The Author(s) 2022 |
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| doi: |
10.1186/s12961-022-00902-6 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| 520 | |a 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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