Modeling the transmission of community-associated methicillin-resistant Staphylococcus aureus: a dynamic agent-based simulation
- Argonne National Lab. (ANL), Argonne, IL (United States). Decision and Information Sciences Division; Univ. of Chicago, IL (United States). Computation Inst.
- Argonne National Lab. (ANL), Argonne, IL (United States). Decision and Information Sciences Division
- Univ. of Colorado, Boulder, CO (United States). Applied Mathematics
- The Ohio State Univ., Columbus, OH (United States). Psychology
- Univ. of Chicago, IL (United States). Dept. of Medicine; Univ. of Chicago, IL (United States). Health Studies
- Univ. of Chicago, IL (United States). Pediatrics
- Univ. of Chicago, IL (United States). Health Studies
- Univ. of Chicago, IL (United States).Sociology
- Harbor-UCLA Medical Center, Torrance, CA (United States). Division of Infectious Diseases
Background: Methicillin-resistant Staphylococcus aureus (MRSA) has been a deadly pathogen in healthcare settings since the 1960s, but MRSA epidemiology changed since 1990 with new genetically distinct strain types circulating among previously healthy people outside healthcare settings. Community-associated (CA) MRSA strains primarily cause skin and soft tissue infections, but may also cause life-threatening invasive infections. First seen in Australia and the U.S., it is a growing problem around the world. The U.S. has had the most widespread CA-MRSA epidemic, with strain type USA300 causing the great majority of infections. Individuals with either asymptomatic colonization or infection may transmit CA-MRSA to others, largely by skin-to-skin contact. Control measures have focused on hospital transmission. Limited public health education has focused on care for skin infections. Methods: We developed a fine-grained agent-based model for Chicago to identify where to target interventions to reduce CA-MRSA transmission. An agent-based model allows us to represent heterogeneity in population behavior, locations and contact patterns that are highly relevant for CA-MRSA transmission and control. Drawing on nationally representative survey data, the model represents variation in sociodemographics, locations, behaviors, and physical contact patterns. Transmission probabilities are based on a comprehensive literature review. Results: Over multiple 10-year runs with one-hour ticks, our model generates temporal and geographic trends in CA-MRSA incidence similar to Chicago from 2001 to 2010. On average, a majority of transmission events occurred in households, and colonized rather than infected agents were the source of the great majority (over 95%) of transmission events. The key findings are that infected people are not the primary source of spread. Rather, the far greater number of colonized individuals must be targeted to reduce transmission. Conclusions: Our findings suggest that current paradigms in MRSA control in the United States cannot be very effective in reducing the incidence of CA-MRSA infections. Furthermore, the control measures that have focused on hospitals are unlikely to have much population-wide impact on CA-MRSA rates. New strategies need to be developed, as the incidence of CA-MRSA is likely to continue to grow around the world.
- Research Organization:
- Argonne National Laboratory (ANL), Argonne, IL (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), Biological and Environmental Research (BER). Biological Systems Science Division
- Grant/Contract Number:
- AC02-06CH11357
- OSTI ID:
- 1626581
- Journal Information:
- Journal of Translational Medicine, Vol. 12, Issue 1; ISSN 1479-5876
- Publisher:
- BioMed CentralCopyright Statement
- Country of Publication:
- United States
- Language:
- English
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