Cole Butler
Department of Mathematics, North Carolina State University, Raleigh, NC
Jinjin Cheng
College of Science, Shanghai University, Shanghai, China
Lorena Correa
School of Mathematical and Computational Sciences, Yachay Tech University, Urcuquí, Ecuador
María R. Preciado-Rivas
Department of Applied Mathematics, University of Waterloo, Waterloo, Canada
Andrés Ríos-Gutiérrez
Departamento de Estadística, Universidad Nacional de Colombia, Bogotá, Colombia
César Montalvo
Simon A. Levin Mathematical Computational and Modeling Sciences Center, Arizona State University, Tempe, AZ
Christopher Kribs
Department of Mathematics, University of Texas at Arlington, Arlington, TX
Methicillin-resistant Staphylococcus aureus (MRSA) contributes greatly to the growing concern of antibiotic-resistant bacteria, especially given its stubborn persistence in healthcare settings. MRSA resists treatment and has colonized an estimated 2% of people worldwide. The CDC reports MRSA prevalence as high as 25–50% in countries like the U.K. and the U.S. Given its resistant nature—it evolves to compensate antibiotic treatment—controlling MRSA levels requires precautionary and defensive measures. This study examines the "search and isolation" approach, which seeks to isolate MRSA-positive patients in hospitals to decrease transmission. Although this strategy is straightforward, whom to screen may vary in practice. We compare screening at admission to screening at discharge, using a mathematical model whose simulations determine MRSA endemic levels in a hospital under either control measure. We found screening at discharge more effective in controlling MRSA endemicity, but at the cost of more isolated patients.
