Kiel Corkran, Majid Bani-Yaghoub, Gary Sutkin, Arash Arjmand, Susanna Paschal
{"title":"某城市社会保障医院耐甲氧西林金黄色葡萄球菌传播率的贝叶斯推断。","authors":"Kiel Corkran, Majid Bani-Yaghoub, Gary Sutkin, Arash Arjmand, Susanna Paschal","doi":"10.1016/j.jhin.2025.07.018","DOIUrl":null,"url":null,"abstract":"<p><p>Methicillin-resistant Staphylococcus aureus (MRSA) is a strain of Staphylococcus aureus that poses significant challenges for effective treatment and infection control within healthcare settings. Recent research suggests that the incidence of healthcare-associated MRSA (HA-MRSA) is higher among patients treated in safety-net hospitals when compared to other healthcare settings. This study aimed to identify HA-MRSA transmission patterns across various nursing units of a safety-net hospital. This study employed Bayesian inference to investigate the transmission patterns of HA-MRSA across multiple nursing units within a safety-net hospital. Using surveillance data from 2019 to 2023, a compartmental disease model was constructed and validated to estimate MRSA transmission rates and basic reproduction number () for each nursing unit. Posterior probability distributions for MRSA transmission, Isolation, and hospital discharge rates were computed using the Delayed Rejection Adaptive Metropolis (DRAM) Bayesian algorithm. Analysis of 187,040 patient records revealed that inpatient nursing units exhibited the highest MRSA transmission rates in three out of the five years studied. Notable transmission rates were observed in certain inpatient and progressive care units (0.55 per individual per month; 0.018 per individual per day) and the surgical ICU (0.44 per individual per month; 0.015 per individual per day). In contrast, the Nursery NICU and Medical ICU had the lowest transmission rates. Although MRSA transmission rates significantly declined across all units in 2021, these rates rebounded to pre-pandemic levels in subsequent years. Notably, outbreaks emerged in units such as ICUs and progressive care units that had not experienced prior MRSA outbreaks since 2019. While MRSA transmission significantly declined during the initial phase of the pandemic, the pathogen reestablished itself in later years. These findings highlight the persistent and evolving challenge of HA-MRSA transmission in safety-net hospital settings, where resource constraints and patient vulnerability may contribute to elevated transmission risks.</p>","PeriodicalId":54806,"journal":{"name":"Journal of Hospital Infection","volume":" ","pages":""},"PeriodicalIF":3.1000,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Bayesian Inference of Nosocomial Methicillin-resistant Staphylococcus aureus Transmission Rates in an Urban Safety-Net Hospital.\",\"authors\":\"Kiel Corkran, Majid Bani-Yaghoub, Gary Sutkin, Arash Arjmand, Susanna Paschal\",\"doi\":\"10.1016/j.jhin.2025.07.018\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Methicillin-resistant Staphylococcus aureus (MRSA) is a strain of Staphylococcus aureus that poses significant challenges for effective treatment and infection control within healthcare settings. Recent research suggests that the incidence of healthcare-associated MRSA (HA-MRSA) is higher among patients treated in safety-net hospitals when compared to other healthcare settings. This study aimed to identify HA-MRSA transmission patterns across various nursing units of a safety-net hospital. This study employed Bayesian inference to investigate the transmission patterns of HA-MRSA across multiple nursing units within a safety-net hospital. Using surveillance data from 2019 to 2023, a compartmental disease model was constructed and validated to estimate MRSA transmission rates and basic reproduction number () for each nursing unit. Posterior probability distributions for MRSA transmission, Isolation, and hospital discharge rates were computed using the Delayed Rejection Adaptive Metropolis (DRAM) Bayesian algorithm. Analysis of 187,040 patient records revealed that inpatient nursing units exhibited the highest MRSA transmission rates in three out of the five years studied. Notable transmission rates were observed in certain inpatient and progressive care units (0.55 per individual per month; 0.018 per individual per day) and the surgical ICU (0.44 per individual per month; 0.015 per individual per day). In contrast, the Nursery NICU and Medical ICU had the lowest transmission rates. Although MRSA transmission rates significantly declined across all units in 2021, these rates rebounded to pre-pandemic levels in subsequent years. Notably, outbreaks emerged in units such as ICUs and progressive care units that had not experienced prior MRSA outbreaks since 2019. While MRSA transmission significantly declined during the initial phase of the pandemic, the pathogen reestablished itself in later years. 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Bayesian Inference of Nosocomial Methicillin-resistant Staphylococcus aureus Transmission Rates in an Urban Safety-Net Hospital.
Methicillin-resistant Staphylococcus aureus (MRSA) is a strain of Staphylococcus aureus that poses significant challenges for effective treatment and infection control within healthcare settings. Recent research suggests that the incidence of healthcare-associated MRSA (HA-MRSA) is higher among patients treated in safety-net hospitals when compared to other healthcare settings. This study aimed to identify HA-MRSA transmission patterns across various nursing units of a safety-net hospital. This study employed Bayesian inference to investigate the transmission patterns of HA-MRSA across multiple nursing units within a safety-net hospital. Using surveillance data from 2019 to 2023, a compartmental disease model was constructed and validated to estimate MRSA transmission rates and basic reproduction number () for each nursing unit. Posterior probability distributions for MRSA transmission, Isolation, and hospital discharge rates were computed using the Delayed Rejection Adaptive Metropolis (DRAM) Bayesian algorithm. Analysis of 187,040 patient records revealed that inpatient nursing units exhibited the highest MRSA transmission rates in three out of the five years studied. Notable transmission rates were observed in certain inpatient and progressive care units (0.55 per individual per month; 0.018 per individual per day) and the surgical ICU (0.44 per individual per month; 0.015 per individual per day). In contrast, the Nursery NICU and Medical ICU had the lowest transmission rates. Although MRSA transmission rates significantly declined across all units in 2021, these rates rebounded to pre-pandemic levels in subsequent years. Notably, outbreaks emerged in units such as ICUs and progressive care units that had not experienced prior MRSA outbreaks since 2019. While MRSA transmission significantly declined during the initial phase of the pandemic, the pathogen reestablished itself in later years. These findings highlight the persistent and evolving challenge of HA-MRSA transmission in safety-net hospital settings, where resource constraints and patient vulnerability may contribute to elevated transmission risks.
期刊介绍:
The Journal of Hospital Infection is the editorially independent scientific publication of the Healthcare Infection Society. The aim of the Journal is to publish high quality research and information relating to infection prevention and control that is relevant to an international audience.
The Journal welcomes submissions that relate to all aspects of infection prevention and control in healthcare settings. This includes submissions that:
provide new insight into the epidemiology, surveillance, or prevention and control of healthcare-associated infections and antimicrobial resistance in healthcare settings;
provide new insight into cleaning, disinfection and decontamination;
provide new insight into the design of healthcare premises;
describe novel aspects of outbreaks of infection;
throw light on techniques for effective antimicrobial stewardship;
describe novel techniques (laboratory-based or point of care) for the detection of infection or antimicrobial resistance in the healthcare setting, particularly if these can be used to facilitate infection prevention and control;
improve understanding of the motivations of safe healthcare behaviour, or describe techniques for achieving behavioural and cultural change;
improve understanding of the use of IT systems in infection surveillance and prevention and control.