A 2007 report from the Milken Institute estimated that the total impact of chronic disease on the US economy was $1.3 trillion annually (2). The high prevalence of chronic disease is also a substantial economic burden to the nation. By 2013, nearly half of the adult population in the United States had at least one chronic health condition, and approximately 70% of deaths were caused by chronic disease (1). Finally, we discuss future research directions of agent-based modeling applied to problems related to specific chronic health conditions.Īmericans are facing a growing burden of chronic disease that includes heart disease, stroke, diabetes, and obesity. We also identify barriers to adopting agent-based models to study chronic diseases. This article introduces agent-based modeling by providing a narrative review of agent-based models of chronic disease and identifying the characteristics of various chronic health conditions that must be taken into account to build effective clinical- and policy-relevant models. Agent-based modeling is a promising systems science approach that can model complex interactions and processes related to chronic health conditions, such as adaptive behaviors, feedback loops, and contextual effects.

As the US population ages, health care providers and policy makers urgently need decision models that provide systematic, credible prediction regarding the prevention and treatment of chronic diseases to improve population health management and medical decision-making.

The United States is experiencing an epidemic of chronic disease.

Examples of Agent-Based Models of Chronic Diseases.

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