Modeling the transmission of community-associated methicillin-resistant Staphylococcus aureus: a dynamic agent-based...

Area of Science:

• Infectious Disease Epidemiology
• Computational Public Health

Background:

• Methicillin-resistant Staphylococcus aureus (MRSA) has evolved, with community-associated (CA) strains like USA300 causing infections outside healthcare settings.
• CA-MRSA primarily causes skin and soft tissue infections but can lead to invasive disease, posing a growing global health challenge.
• Current MRSA control strategies primarily focus on hospital transmission, with limited public health education on community spread.

Purpose of the Study:

• To develop a fine-grained agent-based model for Chicago to pinpoint optimal intervention targets for reducing CA-MRSA transmission.
• To understand the heterogeneity in population behavior, locations, and contact patterns relevant to CA-MRSA transmission and control.

Main Methods:

• An agent-based model was created using nationally representative survey data to simulate population sociodemographics, locations, behaviors, and contact patterns.
• Transmission probabilities were informed by a comprehensive literature review.
• The model generated temporal and geographic trends in CA-MRSA incidence over 10-year simulations.

Main Results:

• The majority of CA-MRSA transmission events occurred within households.
• Colonized individuals, rather than infected individuals, were the primary source of transmission, accounting for over 95% of events.
• Infected individuals are not the main drivers of CA-MRSA spread; interventions should target the larger population of colonized individuals.

Conclusions:

• Existing MRSA control paradigms in the U.S. are unlikely to effectively reduce CA-MRSA incidence.
• Hospital-focused control measures have minimal population-wide impact on CA-MRSA rates.
• New strategies are urgently needed to address the increasing global incidence of CA-MRSA infections.