The use of mathematical modelling studies for evidence synthesis and guideline development: a glossary.

Abstract

Mathematical modelling studies are increasingly recognised as an important tool for evidence synthesis and to inform clinical and public health decision-making, particularly when data from systematic reviews of primary studies do not adequately answer a research question. However, systematic reviewers and guideline developers may struggle with using the results of modelling studies, due at least in part to the lack of a common understanding of concepts and terminology between evidence synthesis experts and mathematical modellers. The use of a common terminology for modelling studies across different clinical and epidemiological research fields that span infectious and non-communicable diseases will help systematic reviewers and guideline developers with the understanding, characterisation, comparison and use of mathematical modelling studies. This glossary explains key terms used in mathematical modelling studies that are particularly salient to evidence synthesis and knowledge translation in clinical medicine and public health.