Understanding Perspectives of Key Stakeholders in Planning, Producing and Applying Infectious Disease Models

Abstract

Background: ​Infectious disease outbreaks are amongst the most threatening of disasters, capable of affecting the health and economies of millions of people around the world in a single occurrence. Mathematical models are a tool that can be used to synthesize information from different disciplines into a comprehensive model, which can further be used to guide public health in making appropriate economic and social decisions. However, the integration of modelling within public health is not maximized. This study aims to explore perceptions of key stakeholders in planning, producing and applying infectious disease mathematical models in public health.

Methodology: ​Data was collected using semi-structured key informant interviews with key stakeholder groups (n=19), academic modellers (n=6), government modellers (n=5), government end-users (n=5) and professionals and practitioners who are end-users (n=4). Data was analyzed with thematic analysis with NVivo 11 (QSR International). A stakeholder analysis was used to map out the interrelatedness of key stakeholder issues, and a thematic analysis was used to abstract themes of collaboration between stakeholders, challenges with data and perceptions of predictive modelling.

Results and Conclusion:​ The findings of this study identify and organize important insights and recommendations required to optimize the utilization of infectious disease mathematical models in public health decision-making. The findings suggest that models that are most applicable to public health problems often go through iterative collaborations between end-users and modellers. The findings also suggest that there are growing challenges when it comes to the collection and interpretation of sources of infectious disease data and that mathematical models are valuable when used for understanding infectious disease outbreaks and/or interventions, rather than projecting the course of a specific outbreak. This study recommends actions be taken in education, practice and research to minimize the existing gap between mathematical models of infectious disease and their application for public health decision-making.