Identification of novel risk factors for community-acquired Clostridium difficile infection using spatial statistics and geographic information system analyses.


BACKGROUND: The rate of community-acquired Clostridium difficile infection (CA-CDI) is increasing. While receipt of antibiotics remains an important risk factor for CDI, studies related to acquisition of C. difficile outside of hospitals are lacking. As a result, risk factors for exposure to C. difficile in community settings have been inadequately studied. MAIN OBJECTIVE: To identify novel environmental risk factors for CA-CDI. METHODS: We performed a population-based retrospective cohort study of patients with CA-CDI from 1/1/2007 through 12/31/2014 in a 10-county area in central North Carolina. 360 Census Tracts in these 10 counties were used as the demographic Geographic Information System (GIS) base-map. Longitude and latitude (X, Y) coordinates were generated from patient home addresses and overlaid to Census Tracts polygons using ArcGIS; ArcView was used to assess "hot-spots" or clusters of CA-CDI. We then constructed a mixed hierarchical model to identify environmental variables independently associated with increased rates of CA-CDI. RESULTS: A total of 1,895 unique patients met our criteria for CA-CDI. The mean patient age was 54.5 years; 62% were female and 70% were Caucasian. 402 (21%) patient addresses were located in "hot spots" or clusters of CA-CDI (p<0.001). "Hot spot" census tracts were scattered throughout the 10 counties. After adjusting for clustering and population density, age ≥ 60 years (p = 0.03), race (<0.001), proximity to a livestock farm (0.01), proximity to farming raw materials services (0.02), and proximity to a nursing home (0.04) were independently associated with increased rates of CA-CDI. CONCLUSIONS: Our study is the first to use spatial statistics and mixed models to identify important environmental risk factors for acquisition of C. difficile and adds to the growing evidence that farm practices may put patients at risk for important drug-resistant infections.






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Publication Info

Anderson, Deverick J, Leoncio Flavio Rojas, Shera Watson, Lauren P Knelson, Sohayla Pruitt, Sarah S Lewis, Rebekah W Moehring, Emily E Sickbert Bennett, et al. (2017). Identification of novel risk factors for community-acquired Clostridium difficile infection using spatial statistics and geographic information system analyses. PLoS One, 12(5). p. e0176285. 10.1371/journal.pone.0176285 Retrieved from

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Deverick John Anderson

Professor of Medicine

Hospital epidemiology, infection control, antibiotic stewardship, multidrug-resistant organisms, device-related infections, surgical site infections, catheter-associated bloodstream infections, cost of infections, infections in community hospitals


Sarah Stamps Lewis

Associate Professor of Medicine

Rebekah Moehring

Associate Professor of Medicine

Daniel John Sexton

Professor Emeritus of Medicine

During the past 8 years my research interests have changed from a focus on tick-borne disease and endocarditis to a primary focus on healthcare-associated infections (HAIs). Specifically, I have been interested in HAIs in community hospitals. Using prospective data collected as part of our surveillance activities in the Duke Infection Control Outreach Network (DICON), I and my colleagues have focused on these specific areas of research:

• The accuracy and reliability of surveillance definitions used to document and trend rates of HAIs
• Outcomes of HAIs (both financial and clinical) with particular emphasis on bloodstream and surgical site infections
• Trends in HAIs due to pathogens resistant to common antimicrobial agents
• Temporal and geographic variations in the occurrence of pathogens such as methicillin-resistant S. aureus, E coli and Klebsiella pneumonia
• The prevention and control of HAIs with particular emphasis on the potential role of the environment in the transmission of HAIs

As the principal investigator on one of the 5 national epicenter grants funded by the Centers for Disease control I, along with my co-investigators from the Duke and University of North Carolina Division of Infectious Disease, are involved in a 5-year prospective study of the potential benefit of enhanced cleaning methods (such as the use of ultraviolet light emitters) in the prevention of HAIs. This study involves 9 hospitals in North Carolina and Virginia and will include a trial of 4 different cleaning methods utilized sequentially but randomly in these study hospitals over a 28-month time period. Additionally the Duke Epicenter is also undertaking prospective trials investigating the utility and reliability of new (streamlined) definitions of ventilator-associated pneumonia.

Key words that characterize my work: surgical site infections and nosocomial infections.

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