INTRODUCTION Clostridium difficile infection (CDI) is currently the most important cause of hospital acquired diarrhoea in the UK. In 2007 there were over 50,392 reports of CDI in patients over the age of 65 years to the Health Protection Agency 1. In response to dramatic increases in CDI reports and associated mortality; the UK Department of Health has made the reduction of cases of CDI a national priority. Currently very little is known about community acquired CDI and how to best approach any community based initiatives. AIM This study aims to use the technique of geographical mapping to identify clusters of CDI in the community, in order to identify administrative areas for targeted intervention. METHODS & RESULTS We included all C. difficile test results from the Boroughs of Brent and Harrow during the 2008 calendar year. Postcodes and geographic co- ordinates were obtained for all patients, GP surgeries and test requestors. During this period 5,610 specimens from 3,112 patients were received in the laboratory. 265 specimens from 185 patients tested positive for C.difficile toxin. 52% of patients testing positive for C.difficile were female and 48% male. The mean age of females testing positive for C.difficile was 75 years and 73 years for males. Using geographical mapping and statistical software (MapInfo Professional and Stata) we created a scatter plot based on patients' addresses in order to identify hot spots. The surgeries and the site of requestors were also ranked according to the number of both diarrhoeal cases and C difficile cases. The distribution of diarrhoeal cases by postcode identified only 6 geographic locations with 8 or more patients – on average 1.3 (range ) cases per postcode per year. We were then able to identify 174 postcode areas with C. difficile cases. They had on average 1.06 cases (range 1 - 3) per postcode area. Just 9 areas had 2 or more positive C.difficile cases. However, using the GP surgeries as geographic indicators showed that 434 surgeries accounted for 3032 diarrhoeal cases (mean 7.0, range 1 – 110). Eleven (2.5%) surgeries with 50 cases or more counted for 762 (25%). The 177 C. difficile cases were distributed over 92 surgeries (mean 1.9, range 1- 9). Eight (8.7%) surgeries with five or more cases each accounted for 50 (28%) cases. It was not possible to demonstrate a geographic correlation between diarrhoeal diseases and C. difficile infections. CONCLUSIONS Geographical mapping is a useful tool for identification of administrative hot spots in order to instigate health service improvement. The study found that approaching selected surgeries will reach the greatest number of diarrhoeal cases. REFERENCES 1. Department of Health and Health Protection Agency (2009). Clostridium Difficile Infection: How to deal with the problem, January Available on the Department of Health Website at: Electron micrograph courtesy of Annie Cavanagh/Wellcome Images. Figure 1. Map of positive C.difficile cases in Harrow and Brent