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Simulation modeling to enhance population health intervention research for chronic disease prevention

Authors
  • Tanuseputro, Peter1, 2, 3, 4
  • Arnason, Trevor5
  • Hennessy, Deirdre2
  • Smith, Brendan6, 7
  • Bennett, Carol3
  • Kopec, Jacek8
  • Pinto, Andrew D.6, 9, 10, 11
  • Perez, Richard3
  • Tuna, Meltem3
  • Manuel, Douglas1, 2, 3, 12
  • 1 Bruyère Research Institute, 43 Bruyère Street, Ottawa, ON, K1N 5C8, Canada , Ottawa (Canada)
  • 2 Ottawa Hospital Research Institute, Ottawa Hospital - Civic Campus, 1053 Carling Ave Box 693, 2-005 Admin Services Building, Ottawa, ON, K1Y 4E9, Canada , Ottawa (Canada)
  • 3 Institute for Clinical Evaluative Sciences, Civic Campus, Administrative Services Building, 1st Floor, 1053 Carling Avenue, Ottawa, ON, K1Y 4E9, Canada , Ottawa (Canada)
  • 4 University of Ottawa, Department of Medicine, Division of Palliative Care, Ottawa, Canada , Ottawa (Canada)
  • 5 Dalhousie University, Department of Community Health and Epidemiology, Halifax, NS, B3H 1V7, Canada , Halifax (Canada)
  • 6 University of Toronto, Dalla Lana School of Public Health, 155 College Street, Toronto, ON, M5T 3M7, Canada , Toronto (Canada)
  • 7 Public Health Ontario, 480 University Ave, Toronto, ON, M5G 1V2, Canada , Toronto (Canada)
  • 8 University of British Columbia, School of Population and Public Health, Milan Ilich Arthritis Research Centre, 5591 No. 3 Road, Richmond, BC, V6X 2C7, Canada , Richmond (Canada)
  • 9 St. Michael’s Hospital, Department of Family and Community Medicine, Toronto, Canada , Toronto (Canada)
  • 10 University of Toronto, Department of Family and Community Medicine, Faculty of Medicine, Toronto, Canada , Toronto (Canada)
  • 11 St. Michael’s Hospital, Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, Toronto, Canada , Toronto (Canada)
  • 12 University of Ottawa, Department of Family Medicine, Ottawa, K1H 8M5, Canada , Ottawa (Canada)
Type
Published Article
Journal
Canadian Journal of Public Health
Publisher
Springer International Publishing
Publication Date
Jul 23, 2018
Volume
110
Issue
1
Pages
52–57
Identifiers
DOI: 10.17269/s41997-018-0109-7
Source
Springer Nature
Keywords
License
Yellow

Abstract

Population Health Intervention Research (PHIR) is an expanding field that explores the health effects of population-level interventions conducted within and outside of the health sector. Simulation modeling—the use of mathematical models to predict health outcomes in populations given a set of specified inputs—is a useful, yet underutilized tool for PHIR. It can be employed at several phases of the research process: (1) planning and designing PHIR studies; (2) implementation; and (3) knowledge translation of findings across settings and populations. Using the example of community-wide, built environment interventions for the prevention of type 2 diabetes, we demonstrate how simulation models can be a powerful technique for chronic disease prevention research within PHIR. With increasingly available data on chronic disease risk factors and outcomes, the use of simulation modeling in PHIR for chronic disease prevention is anticipated to grow. There is a continued need to ensure models are appropriately validated and researchers should be cautious in their interpretation of model outputs given the uncertainties that are inherent with simulation modeling approaches. However, given the complexity of disease pathways and methodological challenges of PHIR studies, simulation models can be a valuable tool for researchers studying population interventions that hold the potential to improve health and reduce health inequities.

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