Research
Geographical and temporal distribution of human giardiasis in Ontario, Canada
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* Corresponding author: Agricola Odoi aodoi@uoguelph.ca
1 Department of Population Medicine, University of Guelph, Guelph, Ontario, Canada, N1G 2W1
2 Université de Montreal, CP 5000, St-Hyacinthe, Québec, Canada
3 Department of Mathematics and Statistics, University of Guelph, Guelph, Ontario, Canada
4 Ministry of Health and Long-Term Care, Ontario, Canada
5 Division of Enteric, Foodborne and Waterborne Diseases, Population and Public Health Branch, Health Canada
International Journal of Health Geographics 2003, 2:5 doi:10.1186/1476-072X-2-5
Published: 11 August 2003Abstract
Background
Giardia is the most frequently identified intestinal parasite in North America. Although information on geographical distribution of giardiasis is critical in identifying communities at high risk, little has been done in this area. Therefore, the objective of this study was to investigate the geographical and temporal distribution of human giardiasis in Ontario in order to identify possible high risk areas and seasons. Two spatial scales of analyses and two disease measures were used with a view to identifying the best of each in assessing geographical patterns of giardiasis in Ontario. Global Moran's I and Moran Local Indicators of Spatial Associations were used to test for evidence of global and local spatial clustering, respectively.
Results
There were seasonal patterns with summer peaks and a significant (P < 0.001) decreasing temporal trend. Significant (P < 0.05) global spatial clustering of high rates was observed at the Census Sub-division spatial scale but not at the Census Division scale. The Census Sub-division scale was a better scale of analyses but required spatial empirical Bayesian smoothing of the rates. A number of areas with significant local clustering of giardiasis rates were identified.
Conclusions
The study identified spatial and temporal patterns in giardiasis distribution. This information is important in guiding decisions on disease control strategies. The study also showed that there is 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 visualization of spatial patterns.