Mainstreaming modeling and simulation to accelerate public health innovation.
Dynamic modeling and simulation are systems science tools that examine behaviors and outcomes resulting from interactions among multiple system components over time. Although there are excellent examples of their application, they have not been adopted as mainstream tools in population health planning and policymaking. Impediments to their use include the legacy and ease of use of statistical approaches that produce estimates with confidence intervals, the difficulty of multidisciplinary collaboration for modeling and simulation, systems scientists' inability to communicate effectively the added value of the tools, and low funding for population health systems science. Proposed remedies include aggregation of diverse data sets, systems science training for public health and other health professionals, changing research incentives toward collaboration, and increased funding for population health systems science projects.
Paul P. Maglio is with the School of Engineering, University of California, Merced, and IBM Research, Almaden, CA. Martin-J. Sepulveda is with Health Systems and Policy Research, IBM Research, Yorktown, NY. At the time of the study, Patricia L. Mabry was with the Office of Behavioral and Social Sciences Research, National Institutes of Health, Bethesda, MD and is now with the Office of Disease Prevention, National Institutes of Health, Rockville, MD. Patricia L. Mabry is also a guest editor for this theme issue.
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D003142:Communication; D003198:Computer Simulation; D003299:Cooperative Behavior; D015438:Health Behavior; D006285:Health Planning; D006801:Humans; D008962:Models, Theoretical; D009765:Obesity / Q000517:prevention & control; D011050:Policy Making; D011634:Public Health; D012107:Research Design; D013598:Systems Theory