SimPHO: an ontology for simulation modeling of population health

  • Authors:

  • Anya Okhmatovskaia;David L. Buckeridge;Arash Shaban-Nejad;Andrew Sutcliffe;Philippe Finès;Jacek A. Kopec;Michael C. Wolfson

  • Affiliations:

  • McGill University, Montreal, QC, Canada;McGill University, Montreal, QC, Canada;McGill University, Montreal, QC, Canada;McGill University, Montreal, QC, Canada;Statistics Canada, Ottawa, ON, Canada;Arthritis Research Centre of Canada, Vancouver, BC, Canada;University of Ottawa, Ottawa, ON, Canada

  • Venue:
  • Proceedings of the Winter Simulation Conference
  • Year:
  • 2012

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Abstract

Simulation modeling of population health is being used increasingly for epidemiology research and public health policy-making. However, the impact of population health simulation models is inhibited by their complexity and the lack of established standards to describe these models. To address this issue, we are developing the Ontology for Simulation Modeling of Population Health (SimPHO) -- a formal, explicit, computer-readable approach to describing population health simulation models. SimPHO builds on previous work to classify and formally represent knowledge about simulation models, and incorporates the semantics of the epidemiology and public health domains. SimPHO will allow model developers to make explicit their assumptions, to describe their models in a formal, consistent and interoperable manner, and to facilitate model reuse and integration. To illustrate the use of SimPHO, we describe one software application driven by this ontology, an automated visualization tool for generating interactive web-based diagrams of population health simulation models.