Modeling the spread of community-associated MRSA

Authors:
Charles M. Macal;Michael J. North;Nicholson Collier;Vanja M. Dukic;Diane S. Lauderdale;Michael Z. David;Robert S. Daum;Philip Shumm;Robert S. Daum;James A. Evans;Jocelyn R. Wilder;Duane T. Wegener
Affiliations:
Argonne National Laboratory, Argonne, IL and University of Chicago, Chicago, IL;Argonne National Laboratory, Argonne, IL and University of Chicago, Chicago, IL;Argonne National Laboratory, Argonne, IL and University of Chicago, Chicago, IL;University of Colorado - Boulder, Boulder, CO;University of Chicago, Chicago, IL;University of Chicago, Chicago, IL;University of Chicago, Chicago, IL;University of Chicago, Chicago, IL;University of Chicago, Chicago, IL;University of Chicago, Chicago, IL;University of Chicago, Chicago, IL;Ohio State University, Columbus, OH
Venue:
Proceedings of the Winter Simulation Conference
Year:
2012

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Abstract

Community-associated methicillin-resistant Staphylococcus aureus (CA-MRSA) are strains of the bacterium S. aureus that are responsible for skin and soft tissue, blood, bone, and other infections that can be life threatening. CA-MRSA strains are resistant to standard antibiotics related to penicillins and have a high prevalence in the general community, as well as in healthcare facilities. CA-MRSA presents novel challenges for computational epidemiological modeling compared to other commonly modeled diseases. CA-MRSA challenges include modeling activities and contact processes of individuals in which direct skin contact can be an important infection pathway, estimating disease transmission parameters based on limited data, and representing behavioral responses of individuals to the disease and healthcare interventions. We are developing a fine-grained agent-based model of CA-MRSA for the Chicago metropolitan area. This paper describes how we are modeling CA-MRSA disease processes based on variants of standard epidemiological models and individual agent-based approaches.