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Comparison of screening for methicillin-resistant Staphylococcus aureus (MRSA) at hospital admission and discharge

Abstract: 

Methicillin-resistant Staphylococcus aureus (MRSA) is a significant contributor to the growing concern of antibiotic resistant bacteria, especially given its stubborn persistence in hospital and other health care facility settings. In combination with the general persistence of S. aureus (colloquially referred to as staph), MRSA presents an additional barrier to treatment and is now believed to have colonized two of every 100 people worldwide. According to the CDC, MRSA prevalence sits as high as 25-50% in countries such as the United Kingdom and the United States. Given the resistant nature of staph as well as its capability of evolving to compensate antibiotic treatment, controlling MRSA levels is more a matter of precautionary and defensive measures. The subject of the following research is the method of "search and isolation" which seeks to isolate MRSA positive patients in a hospital so as to decrease infection potential. Although this strategy of search and isolate is straightforward, the question of just whom to screen is of practical importance. We compare screening at admission to screening at discharge. To do this, we develop a mathematical model and use both stochastic and deterministic simulations to determine MRSA endemic levels in a hospital with either control measure implemented. The more successful control measure will better control endemic potential and proliferation of MRSA.

 

Year: 2018

Authors:

Cole Butler - Department of Mathematics and Statistics, University of Maine, United States

Jinjin Cheng - College of Science, Shanghai University, China

Lorena Correa - Escuela de Ciencias Matemáticas y Tecnología Informática, Universidad Yachay Tech, Ecuador

Maria Rosa Preciado - Escuela de Física y Nanotecnología, Universidad Yachay Tech, Ecuador

 Andrés Ríos - Departamento de Estadística, Universidad Nacional de Colombia, Colombia

Baltazar Espinoza - Simon A. Levin Mathematical Computational and Modeling Sciences Center, Arizona State University, United States

César Montalvo - Simon A. Levin Mathematical Computational and Modeling Sciences Center, Arizona State University, United States

Christopher Kribs - Departament of Mathematics, University of Texas at Arlington, United States

 

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