Abstract
In recent years, the number of mathematical modelling studies has increased steeply. Many of the questions addressed in these studies are relevant to the development of World Health Organization (WHO) guidelines, but modelling studies are rarely formally included as part of the body of evidence. An expert consultation hosted by WHO, a survey of modellers and users of modelling studies, and literature reviews informed the development of recommendations on when and how to incorporate the results of modelling studies into WHO guidelines. In this article, we argue that modelling studies should routinely be considered in the process of developing WHO guidelines, but particularly in the evaluation of public health programmes, long-term effectiveness or comparative effectiveness. There should be a systematic and transparent approach to identifying relevant published models, and to commissioning new models. We believe that the inclusion of evidence from modelling studies into the Grading of Recommendations Assessment, Development and Evaluation (GRADE) process is possible and desirable, with relatively few adaptations. No single "one-size-fits-all" approach is appropriate to assess the quality of modelling studies. The concept of the 'credibility' of the model, which takes the conceptualization of the problem, model structure, input data, different dimensions of uncertainty, as well as transparency and validation into account, is more appropriate than 'risk of bias'.
Highlights
Mathematical models have a long history in public health[1]
World Health Organization (WHO) guidelines are developed using processes and methods that ensure the publication of high-quality recommendations, as outlined in the WHO Handbook for Guideline Development[2]
WHO uses the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach to rate the certainty of a body of evidence and to produce information that is used by guideline panels to formulate recommendations, based on the balance of benefits and harms and other considerations[3]
Summary
Any reports and responses or comments on the article can be found at the end of the article. Keywords World Health Organization, guidelines, mathematical modelling, study quality, GRADE. We have clarified and elaborated upon the distinctions between mathematical and statistical modelling and between a mathematical model and a mathematical modelling study. We use a broad definition of mathematical models which encompasses both descriptive and predictive aspects. We elaborate on the GRADE domain of risk of bias as part of the assessment of certainty of a body of evidence for important and critical outcomes. We feel that the concept of risk of bias is too narrow in the context of mathematical modelling studies and prefer to use “credibility” which encompasses by risk of bias of the input data, and conceptualization of the problem, model structure, other dimensions of uncertainty, transparency, and validation
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