This project will create an agent-based model of an urban population in order to understand factors that have contributed to the recent spread of Methicillin resistant Staphylococcus aureus (MRSA) and to evaluate how effective different control strategies may be. MRSA is an antibiotic-resistant bacterium that most commonly causes skin infections but can cause serious and fatal infections of any organ. During the past decade, MRSA has spread exponentially and is a serious public health threat. New strains of MRSA have rapidly evolved in the community, interacting with MRSA in the healthcare environment that first appeared almost 50 years ago.
Our model will represent behavioral features of the population and the health care system that affect infectious disease transmission and control, including access to care, social networks relevant for information transfer and individual variation in propensity to seek care. Our project brings together multidisciplinary expertise in infectious disease epidemiology, public health, agent-based modeling, high performance computing, Bayesian statistics, health economics and social psychology. Our model, scaling up in stages, will represent the population of the Chicago metropolitan area.
We will develop variables to represent innate individual MRSA risk, location-specific MRSA transmission probabilities, and contamination of fomites (inanimate objects on which MRSA is present). Using the model, we will test hypotheses about factors contributing to MRSA spread. We will determine which clinical, public health and institutional measures are likely to have the greatest impact on the epidemic.
The model will use Repast Simphony, a flexible open source agent-based modeling toolkit developed at Argonne.