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The Use of Agent-based Modeling in Projecting risk factors into the future

Abstract

Human behavior is dynamic, which means that it changes and adapts. Health sciences, however, often consider static risk factors measured once in a cross-sectional survey. Population or group outcomes are then linked to these static risk factors. In this paper, we show how the use of agent-based models allow one to consider risks in a dynamic sense, i.e., to estimate how risk factors affect future outcomes through behavior. We illustrate the issue of dynamic risks using the examples of the heroin market and HIV transmission on sexual and drug-using networks. We show how the social hierarchy among drug users impacts the order of injection and thus the probability of HIV-free survival. We also illustrate the role of street brokers in the functioning of the heroin market. Although the results do not have the same validity as the data obtained from a longitudinal study, they often provide good insight into underlying social mechanisms without the need for conducting expensive and often unfeasible longitudinal studies.

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