Hospital-associated Clostridium difficile infection and reservoirs within the hospital environment.

BACKGROUND: Clostridium difficile infection (CDI) is a leading cause of hospital-associated infections. Antibiotic stewardship, environmental disinfection, and reduction of transmission via health care workers are the major modes of CDI prevention within hospitals. METHODS: The aim of this study was to evaluate the role of the environment in the spread of CDI within hospital rooms. Bed tracing of positive-CDI inpatients was performed to detect the strength of association to specific rooms. Environmental cultures were conducted to identify adequacy of environmental C difficile (CD) spores. Whole-genome sequencing was performed to evaluate the degree of CD relatedness. RESULTS: Bed tracing performed for 211 CDI patients showed a limited list of high-burden rooms. Environmental cultures for surfaces disinfected with a sporicidal agent were almost entirely negative, whereas the floors were positive for CDI in 15% of the studied patient rooms. Whole-genome sequencing did not detect any close genetic relatedness. CONCLUSIONS: Unlike in an outbreak setting, bed tracing did not yield conclusive results of room reservoirs. The C diff Banana Broth culture was inexpensive, sensitive, and easy to incubate under aerobic conditions. Sporicidal disinfectants were effective in eliminating CD from the environment. CD spores were found on floors and hard-to-clean surfaces.

Disparities in the incidence of community-acquired Clostridioides difficile infection: An area-based assessment of the role of social determinants in Bernalillo County, New Mexico.

BACKGROUND: Community-associated Clostridioides difficile infections (CA-CDIs) share many risk factors with health care-associated cases, although the role of socioeconomic factors is poorly understood. This study estimates the influence of several census tract-level measures of socioeconomic status on CA-CDI incidence rates. METHODS: CA-CDI case data from the New Mexico Emerging Infections Program were analyzed using quasi-Poisson regression modeling. Geocoded cases were assigned census tract-level socioeconomic measures to explore racial, ethnic and socioeconomic disparities in CA-CDI incidence. RESULTS: Regression modeling identified census tract-level socioeconomic measures as well as individual and medical measures that together accounted for 57% of the variance in CA-CDI rates. At the census tract level, socioeconomic factors associated with an increase in CA-CDI incidence included a high percentage of individuals lacking health insurance and a low percentage of individuals with low educational attainment. A subanalysis that included racial and ethnic designation revealed that ethnicity had no significant effect, but compared to white race, other races were significantly more likely to acquire CA-CDI. CONCLUSIONS: Although this work reveals the role of certain socioeconomic and race and ethnicity risk factors in the incidence of CA-CDI, it also underscores the complex relationships that exist between socioeconomic status and access to health care.