Temporal and spatial distribution of human cryptosporidiosis in the west of Ireland 2004-2007

<p>Abstract</p> <p>Background</p> <p>Cryptosporidiosis is increasingly recognised as a cause of gastrointestinal infection in Ireland and has been implicated in several outbreaks. This study aimed to investigate the spatial and temporal distribution of human cryptosporidiosis in the west of Ireland in order to identify high risk seasons and areas and to compare Classically Calculated (CC) and Empirical Bayesian (EB) incidence rates. Two spatial scales of analysis were used with a view to identifying the best one in assessing geographical patterns of infection. Global Moran's I and Local Moran's I tests of autocorrelation were used to test for evidence of global and local spatial clustering.</p> <p>Results</p> <p>There were statistically significant seasonal patterns of cryptosporidiosis with peaks in spring and an increasing temporal trend. Significant (p < 0.05) global spatial clustering was observed in CC rates at the Electoral Division (ED) level but not in EB rates at the same level. Despite variations in disease, ED level was found to provide the most accurate account of distribution of cryptosporidiosis in the West of Ireland but required spatial EB smoothing of cases. There were a number of areas identified with significant local clustering of cryptosporidiosis rates.</p> <p>Conclusion</p> <p>This study identified spatial and temporal patterns in cryptosporidiosis distribution. The study also showed benefit in performing spatial analyses at more than one spatial scale to assess geographical patterns in disease distribution and that smoothing of disease rates for mapping in small areas enhances visualisation of spatial patterns. These findings are relevant in guiding policy decisions on disease control strategies.</p

Investigation and management of an outbreak of Salmonella Typhimurium DT8 associated with duck eggs, Ireland 2009 to 2011.

Salmonella Typhimurium DT8 was a very rare cause of human illness in Ireland between 2000 and 2008, with only four human isolates from three patients being identified. Over a 19-month period between August 2009 and February 2011, 34 confirmed cases and one probable case of Salmonella Typhimurium DT8 were detected, all of which had an MLVA pattern 2-10-NA-12-212 or a closely related pattern. The epidemiological investigations strongly supported a linkbetween illness and exposure to duck eggs. Moreover, S. Typhimurium with an MLVA pattern indistinguishable (or closely related) to the isolates from human cases, was identified in 22 commercial and backyard duck flocks, twelve of which were linked with known human cases. A range of control measures were taken at farm level, and advice was provided to consumers on the hygienic handling and cooking of duck eggs. Although no definitive link was established with a concurrent duck egg-related outbreak of S. Typhimurium DT8 in the United Kingdom, it seems likely that the two events were related. It may be appropriate for other countries with a tradition of consuming duck eggs to consider the need for measures to reduce the risk of similar outbreaks

Temporal and spatial distribution of human cryptosporidiosis in the west of ireland 2004-2007

Background: Cryptosporidiosis is increasingly recognised as a cause of gastrointestinal infection in Ireland and has been implicated in several outbreaks. This study aimed to investigate the spatial and temporal distribution of human cryptosporidiosis in the west of Ireland in order to identify high risk seasons and areas and to compare Classically Calculated (CC) and Empirical Bayesian (EB) incidence rates. Two spatial scales of analysis were used with a view to identifying the best one in assessing geographical patterns of infection. Global Moran\u27s I and Local Moran\u27s I tests of autocorrelation were used to test for evidence of global and local spatial clustering. Results: There were statistically significant seasonal patterns of cryptosporidiosis with peaks in spring and an increasing temporal trend. Significant (p &amp;lt; 0.05) global spatial clustering was observed in CC rates at the Electoral Division (ED) level but not in EB rates at the same level. Despite variations in disease, ED level was found to provide the most accurate account of distribution of cryptosporidiosis in the West of Ireland but required spatial EB smoothing of cases. There were a number of areas identified with significant local clustering of cryptosporidiosis rates. Conclusion: This study identified spatial and temporal patterns in cryptosporidiosis distribution. The study also showed benefit in performing spatial analyses at more than one spatial scale to assess geographical patterns in disease distribution and that smoothing of disease rates for mapping in small areas enhances visualisation of spatial patterns. These findings are relevant in guiding policy decisions on disease control strategies