Quantifying The Transmission Dynamics Of Mrsa In The Community And Healthcare Settings In A Low-Prevalence Country

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA(2019)

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摘要
Methicillin-resistant Staphylococcus aureus (MRSA) is a primarily nosocomial pathogen that, in recent years, has increasingly spread to the general population. The rising prevalence of MRSA in the community implies more frequent introductions in healthcare settings that could jeopardize the effectiveness of infection-control procedures. To investigate the epidemiological dynamics of MRSA in a low-prevalence country, we developed an individual-based model (IBM) reproducing the population's sociodemography, explicitly representing households, hospitals, and nursing homes. The model was calibrated to surveillance data from the Norwegian national registry (2008-2015) and to published household prevalence data. We estimated an effective reproductive number of 0.68 (95% CI 0.47-0.90), suggesting that the observed rise in MRSA infections is not due to an ongoing epidemic but driven by more frequent acquisitions abroad. As a result of MRSA importations, an almost twofold increase in the prevalence of carriage was estimated over the study period, in 2015 reaching a value of 0.37% (0.25-0.54%) in the community and 1.11% (0.79-1.59%) in hospitalized patients. Household transmission accounted for half of new MRSA acquisitions, indicating this setting as a potential target for preventive strategies. However, nosocomial acquisition was still the primary source of symptomatic disease, which reinforces the importance of hospital-based transmission control. Although our results indicate little reason for concern about MRSA transmission in low-prevalence settings in the immediate future, the increases in importation and global circulation highlight the need for coordinated initiatives to reduce the spread of antibiotic resistance worldwide.
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关键词
methicillin-resistant Staphylococcus aureus, individual-based model, transmission dynamics, mathematical model, antibiotic resistance
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