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BMC Med. 2019 Aug 19;17(1):163. doi: 10.1186/s12916-019-1403-9.

Guidelines for multi-model comparisons of the impact of infectious disease interventions.

Author information

1
Department of Immunization, Vaccines and Biologicals, World Health Organization, Avenue Appia 20, CH-1211, Geneva 27, Switzerland.
2
Centre for Mathematical Modelling of Infectious Disease, London School of Hygiene and Tropical Medicine, London, UK.
3
Modelling and Economics Unit, Public Health England, London, UK.
4
School of Public Health, University of Hong Kong, Hong Kong, SAR, China.
5
Department of Social and Preventive Medicine, Université Laval, Quebec, Canada.
6
Centre for Health Economics Research & Modelling Infectious Diseases, Vaccine & Infectious Disease Institute, University of Antwerp, Antwerp, Belgium.
7
Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK.
8
TB Modelling Group, London School of Hygiene and Tropical Medicine, London, UK.
9
Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.
10
Faculty of Medicine, School of Public Health, Imperial College London, London, UK.
11
Department of Epidemiology of Microbial Diseases, Yale School of Public Health, Yale University, New Haven, CT, 06511, USA.
12
Institute for Medical Technology Assessment (iMTA), Erasmus University Rotterdam, Rotterdam, The Netherlands.
13
Department of Health Services Research and Policy, London School of Hygiene and Tropical Medicine, London, UK.
14
Department of Health Policy and Management, Harvard T. H. Chan School of Public Health, Boston, USA.
15
Department of Immunization, Vaccines and Biologicals, World Health Organization, Avenue Appia 20, CH-1211, Geneva 27, Switzerland. hutubessyr@who.int.

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.

KEYWORDS:

Cost-effectiveness; Decision-making; Harmonisation; Impact modelling; Infectious diseases; Interventions; Mathematical modelling; Model comparisons; Policy

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