A mathematical model of Clostridium difficile transmission in medical wards and a cost-effectiveness analysis comparing different strategies for laboratory diagnosis and patient isolation

• Published in: PloS one 2017-02, Vol.12 (2), p.e0171327-e0171327
• Main Authors: Schechner, Vered, Carmeli, Yehuda, Leshno, Moshe
• Format: Article
• Language: English
• Subjects: Analysis; Antibiotics; Bacteria; Biology and Life Sciences; Clostridium difficile; Clostridium difficile - pathogenicity; Compartments; Cost analysis; Costs and Cost Analysis; Cross Infection - economics; Cross Infection - epidemiology; Cross Infection - transmission; Diagnosis; Diagnostic systems; Disease control; Disease Outbreaks - prevention & control; Enterocolitis, Pseudomembranous - economics; Enterocolitis, Pseudomembranous - epidemiology; Enterocolitis, Pseudomembranous - transmission; Epidemiology; Health care; Hospital units; Hospitalization; Hospitals; Humans; Infections; Intensive care; Internal medicine; Laboratories; Laboratory methods; Management; Mathematical analysis; Mathematical models; Medical diagnosis; Medicine and Health Sciences; Models, Theoretical; Patient isolation; Patient Isolation - economics; Patient Isolation - methods; Patient Isolation - statistics & numerical data; Patients; Research and Analysis Methods; Social Sciences; Staphylococcus infections; Strategy; Studies; Ultrasonic testing
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0171327

Clostridium difficile infection (CDI) is a common and potentially fatal healthcare-associated infection. Improving diagnostic tests and infection control measures may prevent transmission. We aimed to determine, in resource-limited settings, whether it is more effective and cost-effective to allocate resources to isolation or to diagnostics. We constructed a mathematical model of CDI transmission based on hospital data (9 medical wards, 350 beds) between March 2010 and February 2013. The model consisted of three compartments: susceptible patients, asymptomatic carriers and CDI patients. We used our model results to perform a cost-effectiveness analysis, comparing four strategies that were different combinations of 2 test methods (the two-step test and uniform PCR) and 2 infection control measures (contact isolation in multiple-bed rooms or single-bed rooms/cohorting). For each strategy, we calculated the annual cost (of CDI diagnosis and isolation) for a decrease of 1 in the average daily number of CDI patients; the strategy of the two-step test and contact isolation in multiple-bed rooms was the reference strategy. Our model showed that the average number of CDI patients increased exponentially as the transmission rate increased. Improving diagnosis by adopting uniform PCR assay reduced the average number of CDI cases per day per 350 beds from 9.4 to 8.5, while improving isolation by using single-bed rooms reduced the number to about 1; the latter was cost saving. CDI can be decreased by better isolation and more sensitive laboratory methods. From the hospital perspective, improving isolation is more cost-effective than improving diagnostics.