Developing WHO guidelines: Time to formally include evidence from mathematical modelling studies [version 2; referees: 2 approved]

Egger, Matthias; Johnson, Leigh; Althaus, Christian; Schöni, Anna; Salanti, Georgia; Low, Nicola; Norris, Susan L (2018). Developing WHO guidelines: Time to formally include evidence from mathematical modelling studies [version 2; referees: 2 approved]. F1000Research, 6, p. 1584. F1000 Research Ltd 10.12688/f1000research.12367.2

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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'.

Item Type:

Journal Article (Original Article)


04 Faculty of Medicine > Pre-clinic Human Medicine > Institute of Social and Preventive Medicine (ISPM)

UniBE Contributor:

Egger, Matthias, Althaus, Christian, Schöni, Anna, Salanti, Georgia, Low, Nicola


600 Technology > 610 Medicine & health
300 Social sciences, sociology & anthropology > 360 Social problems & social services




F1000 Research Ltd




Tanya Karrer

Date Deposited:

13 Sep 2018 11:33

Last Modified:

05 Dec 2022 15:17

Publisher DOI:


PubMed ID:


Uncontrolled Keywords:

GRADE World Health Organization guidelines mathematical modelling study quality




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