den Boon, Saskia; Jit, Mark; Brisson, Marc; Medley, Graham; Beutels, Philippe; White, Richard; Flasche, Stefan; Hollingsworth, T Déirdre; Garske, Tini; Pitzer, Virginia E; +5 more... Hoogendoorn, Martine; Geffen, Oliver; Clark, Andrew; Kim, Jane; Hutubessy, Raymond; (2019) Guidelines for multi-model comparisons of the impact of infectious disease interventions. BMC medicine, 17 (1). 163-. ISSN 1741-7015 DOI: https://doi.org/10.1186/s12916-019-1403-9
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Abstract
BACKGROUND: Despite the increasing popularity of multi-model comparison studies and their ability to inform policy recommendations, clear guidance on how to conduct multi-model comparisons is not available. Herein, we present guidelines to provide a structured approach to comparisons of multiple models of interventions against infectious diseases. The primary target audience for these guidelines are researchers carrying out model comparison studies and policy-makers using model comparison studies to inform policy decisions. METHODS: The consensus process used for the development of the guidelines included a systematic review of existing model comparison studies on effectiveness and cost-effectiveness of vaccination, a 2-day meeting and guideline development workshop during which mathematical modellers from different disease areas critically discussed and debated the guideline content and wording, and several rounds of comments on sequential versions of the guidelines by all authors. RESULTS: The guidelines provide principles for multi-model comparisons, with specific practice statements on what modellers should do for six domains. The guidelines provide explanation and elaboration of the principles and practice statements as well as some examples to illustrate these. The principles are (1) the policy and research question - the model comparison should address a relevant, clearly defined policy question; (2) model identification and selection - the identification and selection of models for inclusion in the model comparison should be transparent and minimise selection bias; (3) harmonisation - standardisation of input data and outputs should be determined by the research question and value of the effort needed for this step; (4) exploring variability - between- and within-model variability and uncertainty should be explored; (5) presenting and pooling results - results should be presented in an appropriate way to support decision-making; and (6) interpretation - results should be interpreted to inform the policy question. CONCLUSION: These guidelines should help researchers plan, conduct and report model comparisons of infectious diseases and related interventions in a systematic and structured manner for the purpose of supporting health policy decisions. Adherence to these guidelines will contribute to greater consistency and objectivity in the approach and methods used in multi-model comparisons, and as such improve the quality of modelled evidence for policy.
Item Type | Article |
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Faculty and Department |
Faculty of Epidemiology and Population Health > Dept of Infectious Disease Epidemiology & Dynamics (2023-) Faculty of Public Health and Policy > Dept of Global Health and Development Faculty of Public Health and Policy > Dept of Health Services Research and Policy |
Research Centre |
TB Modelling Group Centre for the Mathematical Modelling of Infectious Diseases |
PubMed ID | 31422772 |
Elements ID | 135861 |