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Agent-based modeling of noncommunicable diseases: a systematic review
Roch A Nianogo1, Onyebuchi A Arah
1Roch A. Nianogo and Onyebuchi A. Arah are with the Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles (UCLA). Onyebuchi A. Arah is also with the Center for Health Policy Research, UCLA, and the California Center for Population Research, UCLA, as well as the Academic Medical Center, University of Amsterdam, The Netherlands.
None:
We reviewed the use of agent-based modeling (ABM), a systems science method, in understanding noncommunicable diseases (NCDs) and their public health risk factors. We systematically reviewed studies in PubMed, ScienceDirect, and Web of Sciences published from January 2003 to July 2014. We retrieved 22 relevant articles; each had an observational or interventional design. Physical activity and diet were the most-studied outcomes. Often, single agent types were modeled, and the environment was usually irrelevant to the studied outcome. Predictive validation and sensitivity analyses were most used to validate models. Although increasingly used to study NCDs, ABM remains underutilized and, where used, is suboptimally reported in public health studies. Its use in studying NCDs will benefit from clarified best practices and improved rigor to establish its usefulness and facilitate replication, interpretation, and application.
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