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

The CLIMPACTS synthesis report: An assessment of the effects of climate change and variation in New Zealand using the CLIMPACTS system

In the late 1980s, New Zealand undertook the first national assessment of climate change and its possible impacts on the country.The landmark report, reflecting the judgement of scores of national experts, called for greater efforts in building the national research capacity in order to better quantify the range of impacts that could occur in New Zealand from climate change and variability. In response, the collaborative CLIMPACTS Programme was established to provide this capacity. Ten years on from the first national assessment, the present synthesis offers some results from, as well as a demonstration of, the capacity developed by the CLIMPACTS Programme. The purpose of the present document is to provide a summary report from the CLIMPACTS Programme on climate change and its effects on New Zealand.The chapters and their contents are not comprehensive. Rather, they are focused on a specific set of questions, which conform to the particular expertise of the CLIMPACTS Programme members and which employ a limited set of the wide range of tools available within the CLIMPACTS Model. Other important areas such as forests, indigenous ecosystems and pests and diseases are not yet covered

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