Recalibrating the notion of modelling for policymaking during pandemics
(2022) In Epidemics 38. p.1-6- Abstract
COVID-19 disease models have aided policymakers in low-and middle-income countries (LMICs) with many critical decisions. Many challenges remain surrounding their use, from inappropriate model selection and adoption, inadequate and untimely reporting of evidence, to the lack of iterative stakeholder engagement in policy formulation and deliberation. These issues can contribute to the misuse of models and hinder effective policy implementation. Without guidance on how to address such challenges, the true potential of such models may not be realised. The COVID-19 Multi-Model Comparison Collaboration (CMCC) was formed to address this gap. CMCC is a global collaboration between decision-makers from LMICs, modellers and researchers, and... (More)
COVID-19 disease models have aided policymakers in low-and middle-income countries (LMICs) with many critical decisions. Many challenges remain surrounding their use, from inappropriate model selection and adoption, inadequate and untimely reporting of evidence, to the lack of iterative stakeholder engagement in policy formulation and deliberation. These issues can contribute to the misuse of models and hinder effective policy implementation. Without guidance on how to address such challenges, the true potential of such models may not be realised. The COVID-19 Multi-Model Comparison Collaboration (CMCC) was formed to address this gap. CMCC is a global collaboration between decision-makers from LMICs, modellers and researchers, and development partners. To understand the limitations of existing COVID-19 disease models (primarily from high income countries) and how they could be adequately support decision-making in LMICs, a desk review of modelling experience during the COVID-19 and past disease outbreaks, two online surveys, and regular online consultations were held among the collaborators. Three key recommendations from CMCC include: A ‘fitness-for-purpose’ flowchart, a tool that concurrently walks policymakers (or their advisors) and modellers through a model selection and development process. The flowchart is organised around the following: policy aims, modelling feasibility, model implementation, model reporting commitment. Holmdahl and Buckee (2020) A ‘reporting standards trajectory’, which includes three gradually increasing standard of reports, ‘minimum’, ‘acceptable’, and ‘ideal’, and seeks collaboration from funders, modellers, and decision-makers to enhance the quality of reports over time and accountability of researchers. Malla et al. (2018) A framework for “collaborative modelling for effective policy implementation and evaluation” which extends the definition of stakeholders to funders, ground-level implementers, public, and other researchers, and outlines how each can contribute to modelling. We advocate for standardisation of modelling processes and adoption of country-owned model through iterative stakeholder participation and discuss how they can enhance trust, accountability, and public ownership to decisions.
(Less)
- author
- publishing date
- 2022-03
- type
- Contribution to journal
- publication status
- published
- in
- Epidemics
- volume
- 38
- article number
- 100552
- pages
- 1 - 6
- publisher
- Elsevier
- external identifiers
-
- scopus:85125749487
- pmid:35259693
- ISSN
- 1755-4365
- DOI
- 10.1016/j.epidem.2022.100552
- language
- English
- LU publication?
- no
- additional info
- Publisher Copyright: © 2022 The Authors
- id
- cf460db8-8049-4516-8666-4295cca16337
- date added to LUP
- 2024-07-02 12:47:23
- date last changed
- 2025-07-17 00:54:40
@article{cf460db8-8049-4516-8666-4295cca16337,
abstract = {{<p>COVID-19 disease models have aided policymakers in low-and middle-income countries (LMICs) with many critical decisions. Many challenges remain surrounding their use, from inappropriate model selection and adoption, inadequate and untimely reporting of evidence, to the lack of iterative stakeholder engagement in policy formulation and deliberation. These issues can contribute to the misuse of models and hinder effective policy implementation. Without guidance on how to address such challenges, the true potential of such models may not be realised. The COVID-19 Multi-Model Comparison Collaboration (CMCC) was formed to address this gap. CMCC is a global collaboration between decision-makers from LMICs, modellers and researchers, and development partners. To understand the limitations of existing COVID-19 disease models (primarily from high income countries) and how they could be adequately support decision-making in LMICs, a desk review of modelling experience during the COVID-19 and past disease outbreaks, two online surveys, and regular online consultations were held among the collaborators. Three key recommendations from CMCC include: A ‘fitness-for-purpose’ flowchart, a tool that concurrently walks policymakers (or their advisors) and modellers through a model selection and development process. The flowchart is organised around the following: policy aims, modelling feasibility, model implementation, model reporting commitment. Holmdahl and Buckee (2020) A ‘reporting standards trajectory’, which includes three gradually increasing standard of reports, ‘minimum’, ‘acceptable’, and ‘ideal’, and seeks collaboration from funders, modellers, and decision-makers to enhance the quality of reports over time and accountability of researchers. Malla et al. (2018) A framework for “collaborative modelling for effective policy implementation and evaluation” which extends the definition of stakeholders to funders, ground-level implementers, public, and other researchers, and outlines how each can contribute to modelling. We advocate for standardisation of modelling processes and adoption of country-owned model through iterative stakeholder participation and discuss how they can enhance trust, accountability, and public ownership to decisions.</p>}},
author = {{Teerawattananon, Yot and KC, Sarin and Chi, Y. Ling and Dabak, Saudamini and Kazibwe, Joseph and Clapham, Hannah and Lopez Hernandez, Claudia and Leung, Gabriel M. and Sharifi, Hamid and Habtemariam, Mahlet and Blecher, Mark and Nishtar, Sania and Sarkar, Swarup and Wilson, David and Chalkidou, Kalipso and Gorgens, Marelize and Hutubessy, Raymond and Wibulpolprasert, Suwit}},
issn = {{1755-4365}},
language = {{eng}},
pages = {{1--6}},
publisher = {{Elsevier}},
series = {{Epidemics}},
title = {{Recalibrating the notion of modelling for policymaking during pandemics}},
url = {{http://dx.doi.org/10.1016/j.epidem.2022.100552}},
doi = {{10.1016/j.epidem.2022.100552}},
volume = {{38}},
year = {{2022}},
}