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A Directed Graph Model of Ecological Alcohol Systems Incorporating Spatiotemporal Effects

In: Compstat 2008

Author

Listed:
  • Edward J. Wegman

    (University of Cambridge, Isaac Newton Institute for Mathematical Sciences
    George Mason University, Department of Computational and Data Sciences)

  • Yasmin H. Said

    (University of Cambridge, Isaac Newton Institute for Mathematical Sciences
    George Mason University, Department of Computational and Data Sciences)

Abstract

Users of alcohol are incorporated into a societal system, which for many purposes resembles an ecological system. We have previously modeled such systems using a directed graph with acute outcomes reflecting undesirable individual and societal outcomes. In this paper, we expand the model to a hybrid social network directed graph model for modeling the acute outcomes associated with alcohol use and abuse. We describe the approximate estimates of conditional probabilities based on available data. In the present model, we also approximate geospatial effects related to transportation as well as temporal effects. Acute outcomes include assault, murder, suicide, sexual assault, infection with STDs or HIV, domestic violence, child abuse, and DWI and alcohol related fatal crashes. The model is calibrated using demographic, crime, alcohol-related, and alcohol outlet data from Virginia and Fairfax County in Virginia. We propose proxy data and methods for capturing temporal and geospatial effects. The goal is to investigate methods for simultaneous suppression of multiple negative public health consequences. The model may be used as a public policy decision tool by adjusting conditional probabilities in order to investigate the effect of interventions.

Suggested Citation

  • Edward J. Wegman & Yasmin H. Said, 2008. "A Directed Graph Model of Ecological Alcohol Systems Incorporating Spatiotemporal Effects," Springer Books, in: Paula Brito (ed.), Compstat 2008, pages 179-190, Springer.
    • Handle: RePEc:spr:sprchp:978-3-7908-2084-3_15
    DOI: 10.1007/978-3-7908-2084-3_15
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