Journal
ANNUAL REVIEW OF PUBLIC HEALTH, VOL 33
Volume 33, Issue -, Pages 357-+Publisher
ANNUAL REVIEWS
DOI: 10.1146/annurev-publhealth-031210-101222
Keywords
complex systems; system dynamics; network analysis; agent-based modeling; computer models; simulation
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Funding
- NATIONAL CENTER FOR RESEARCH RESOURCES [KL2RR024994, UL1RR024992] Funding Source: NIH RePORTER
- NCRR NIH HHS [KL2RR024994, KL2 RR024994, UL1 RR024992, UL1RR024992] Funding Source: Medline
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Complex systems abound in public health. Complex systems are made up of heterogeneous elements that interact with one another, have emergent properties that are not explained by understanding the individual elements of the system, persist over time, and adapt to changing circumstances. Public health is starting to use results from systems science studies to shape practice and policy, for example in preparing for global pandemics. However, systems science study designs and analytic methods remain underutilized and are not widely featured in public health curricula or training. In this review we present an argument for the utility of systems science methods in public health, introduce three important systems science methods ( system dynamics, network analysis, and agent-based modeling), and provide three case studies in which these methods have been used to answer important public health science questions in the areas of infectious disease, tobacco control, and obesity.
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