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.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Colizza V, Barthelemy M, Barrat A, Vespignani A (2007) Epidemic modeling in complex realities. CR Biologies 330:364–374
Hoffer L (2006) Junkie business: The evolution and operation of a heroin dealing network. Belmont, CA, Thompson Wadsworth
Hoffer L, Bobashev GV (in press, 2009) Researching a local heroin market as a complex adaptive system. American Journal of Community Psychology
Riley S (2007) Large-scale spatial-transmission models of infectious diseases. Science 316:1298–1301
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag US
About this paper
Cite this paper
Bobashev, G.V., Morris, R.J., Zule, W.A., Borshchev, A.V., Hoffer, L. (2009). The Use of Agent-based Modeling in Projecting Risk Factors into the Future. In: Social Computing and Behavioral Modeling. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-0056-2_8
Download citation
DOI: https://doi.org/10.1007/978-1-4419-0056-2_8
Published:
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4419-0055-5
Online ISBN: 978-1-4419-0056-2
eBook Packages: Computer ScienceComputer Science (R0)