Priscilla Doran, Natsuka Hayashida, Kristen Joyner, Grace Moberg, Austin Kind, Matthew Senese, Brittany Stephenson, Cara Jill Sulyok
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引用次数: 0
Abstract
Clostridioides difficile, also known as C. difficile, is a prevalent cause of infectious diarrhea in United States healthcare facilities. Spread through the fecal-oral route and often through contact with spores on contaminated surfaces, C. difficile can cause severe diarrhea, stomach pain, and colitis. Most individuals can mount an effective immune response, but older populations, immunocompromised individuals, and those taking antibiotics have a higher risk of being colonized by C. difficile. While extensive research has been conducted in hospital-based settings to improve understanding of the transmission of this bacteria, few studies apply mathematical models in the context of long-term care facilities. This work introduced a mathematical model using a system of ordinary differential equations to represent C. difficile transmission dynamics in assisted living facilities, with their interactive nature and high risk factors. The equations included four resident classes (susceptible, colonized, diseased, and isolated) and three pathogen-carrying classes (high-traffic areas, low-traffic areas, and healthcare workers' hands) to simultaneously capture the movement between classes and track spore density on environmental reservoirs and healthcare workers' hands, including their contributions to disease spread. Parameter estimation using data from the Emerging Infections Program at the Centers for Disease Control and Prevention was completed and was followed by sensitivity analyses to quantify the impact of varying these parameters and their impact on incidence. Mitigation strategies, including frequent disinfection, increased healthcare worker hand hygiene compliance, a lower ratio between residents and healthcare workers, and increased resident screening had the greatest impact on reducing the incidence of C. difficile.
期刊介绍:
Mathematical Biosciences and Engineering (MBE) is an interdisciplinary Open Access journal promoting cutting-edge research, technology transfer and knowledge translation about complex data and information processing.
MBE publishes Research articles (long and original research); Communications (short and novel research); Expository papers; Technology Transfer and Knowledge Translation reports (description of new technologies and products); Announcements and Industrial Progress and News (announcements and even advertisement, including major conferences).