An inaugural forum on epidemiological modeling for public health stakeholders in Arizona

Front Public Health. 2024 May 31:12:1357908. doi: 10.3389/fpubh.2024.1357908. eCollection 2024.

Abstract

Epidemiological models-which help us understand and forecast the spread of infectious disease-can be valuable tools for public health. However, barriers exist that can make it difficult to employ epidemiological models routinely within the repertoire of public health planning. These barriers include technical challenges associated with constructing the models, challenges in obtaining appropriate data for model parameterization, and problems with clear communication of modeling outputs and uncertainty. To learn about the unique barriers and opportunities within the state of Arizona, we gathered a diverse set of 48 public health stakeholders for a day-and-a-half forum. Our research group was motivated specifically by our work building software for public health-relevant modeling and by our earnest desire to collaborate closely with stakeholders to ensure that our software tools are practical and useful in the face of evolving public health needs. Here we outline the planning and structure of the forum, and we highlight as a case study some of the lessons learned from breakout discussions. While unique barriers exist for implementing modeling for public health, there is also keen interest in doing so across diverse sectors of State and Local government, although issues of equal and fair access to modeling knowledge and technologies remain key issues for future development. We found this forum to be useful for building relationships and informing our software development, and we plan to continue such meetings annually to create a continual feedback loop between academic molders and public health practitioners.

Keywords: collective knowledge building; infectious disease epidemiology; predictive modeling; public health; stakeholder engagement.

MeSH terms

  • Arizona / epidemiology
  • Humans
  • Models, Theoretical
  • Public Health*
  • Software
  • Stakeholder Participation

Grants and funding

The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. Research reported in this publication was supported by the National Institute of Allergy and Infectious Diseases of the National Institutes of Health under award number R01AI168144, and by the Southwest Health Equity Research Collaborative at Northern Arizona University (U54MD012388), which was sponsored by the National Institute on Minority Health and Health Disparities (NIMHD).