Abstract
In this paper both deterministic and stochastic models are developed to explore the roles that antibiotic exposure and environmental contamination play in the spread of antibiotic-resistant bacteria, such as methicillin-resistant Staphylococcus aureus (MRSA), in hospitals. Uncolonized patients without or with antibiotic exposure, colonized patients without or with antibiotic exposure, uncontaminated or contaminated healthcare workers, and free-living bacteria are included in the models. Under the assumption that there is no admission of the colonized patients, the basic reproduction number R0 is calculated. It is shown that when R0 < 1, the infection-free equilibrium is globally asymptotically stable; when R0 > 1, the infection is uniformly persistent. Numerical simulations and sensitivity analysis show that environmental cleaning is a critical intervention, and hospitals should use antibiotics properly and as little as possible. The rapid and efficient treatment of colonized patients, especially those with antibiotic exposure, is key in controlling MRSA infections. Screening and isolating colonized patients at admission, and improving compliance with hand hygiene are also important control strategies.
Highlights
Nosocomial infections caused by antibiotic-resistant bacteria are a major threat to global public health today
Under the assumption that there is no admission of the colonized patients, the basic reproduction number R0 is calculated
We developed a comprehensive study of methicillin-resistant Staphylococcus aureus (MRSA) infections in hospitals, which includes crucial factors such as antibiotic exposure and environmental contamination
Summary
Nosocomial infections caused by antibiotic-resistant bacteria are a major threat to global public health today. We refer to survey papers of Bonten et al [30], Grundmann and Hellriegel [31], Temime et al [32], van Kleef et al [33] and the references cited therein on modeling antimicrobial resistance These studies showed quantitatively how infection control measures such as hand washing, cohorting, and antibiotic restriction affect nosocomial cross-transmission. In our previous studies (Wang et al [24] and Wang and Ruan [25]) on nosocomial infections of MRSA in the emergency ward and respiratory intensive care unit in Beijing Tongren Hospital, Beijing, China, data on HCW, volunteers, patients, and environmental contamination were obtained. Based on the data in [24, 25], in this article, we first develop a deterministic ordinary differential equations model (ODE) to investigate the combined effects of antibiotic exposure and environmental contamination on the transmission dynamics of MRSA in hospitals. Numerical simulations show that the average of multiple stochastic outputs aligns with the ODE output
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