Publication

Back to overview

Developing WHO guidelines: Time to formally include evidence from mathematical modelling studies

Type of publication Peer-reviewed
Publikationsform Original article (peer-reviewed)
Author Egger Matthias, Johnson Leigh, Althaus Christian, Schöni Anna, Salanti Georgia, Low Nicola, Norris Susan L.,
Project Forschungspauschale Forschungsratspräsident SNF
Show all

Original article (peer-reviewed)

Journal F1000Research
Volume (Issue) 6
Page(s) 1584 - 1584
Title of proceedings F1000Research
DOI 10.12688/f1000research

Open Access

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’.
-