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

Matthias Egger1,2, Leigh Johnson2, Christian Althaus1

  • 1Institute of Social and Preventive Medicine (ISPM), University of Bern, Bern, 3012, Switzerland.

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Summary
This summary is machine-generated.

Mathematical modelling studies are crucial for World Health Organization (WHO) guidelines, especially for public health program evaluation. Recommendations are provided for systematically incorporating these studies, focusing on model credibility over risk of bias.

Keywords:
GRADEWorld Health Organizationguidelinesmathematical modellingstudy quality

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Area of Science:

  • Health policy
  • Mathematical modeling
  • Evidence synthesis

Background:

  • Mathematical modeling studies are increasingly relevant to World Health Organization (WHO) guideline development.
  • These studies are currently underutilized in formal evidence reviews for WHO guidelines.
  • A gap exists in standardized methods for incorporating modeling evidence into guideline processes.

Purpose of the Study:

  • To develop recommendations for integrating mathematical modeling study results into WHO guidelines.
  • To address the systematic identification and commissioning of relevant models.
  • To propose adaptations for including modeling evidence within the Grading of Recommendations Assessment, Development and Evaluation (GRADE) framework.

Main Methods:

  • Convened an expert consultation hosted by WHO.
  • Conducted a survey of modelers and users of modeling studies.
  • Performed literature reviews to inform recommendations.

Main Results:

  • Modeling studies should be routinely considered in WHO guideline development, particularly for evaluating public health programs and effectiveness.
  • A systematic and transparent approach is needed for identifying and commissioning models.
  • The GRADE framework can be adapted to include evidence from modeling studies.
  • Model credibility, encompassing conceptualization, structure, data, uncertainty, transparency, and validation, is a more appropriate assessment than 'risk of bias'.

Conclusions:

  • Formal inclusion of mathematical modeling studies in WHO guidelines is recommended.
  • A standardized, transparent approach to model assessment and integration is necessary.
  • The concept of 'credibility' offers a robust framework for evaluating modeling studies within guideline development.