Sandra Kulon

Remote sensing and Geographical Information Systems (GIS) were used to analyze the spatial distribution of West Nile (WN) virus in the City of Toronto. More specifically, this study explored the relationships between vegetation, land use, mosquito counts, and WN virus activity in 2003. Using a statistical t-test, the amount qf vegetation, measured by the Normalized Difference Vegetation Index (NDVI), adjacent to mosquito traps that tested positive for WN virus was comp~ed to the amount of vegetation found adjacent to mosquito traps that tested negative for WN virus. An identical test was also used to explore the influence NDVI had on dead birds that tested positive and negative for WN virus throughout the city. The results demonstrated that NDVI offered no significant explanation towards the spatial distribution of WN virus activity (represented by mosquitoes and birds) throughout the city.

The relationship between mosquito counts and WN virus infected mosquito traps was also examined using a statistical test. Using a Mann-Whitney test, the number of mosquitoes collected from traps that tested positive for WN virus was compared with the number of mosquitoes collected from traps that tested negative. The results of this study demonstrated that mosquito counts did not significandy influence the distribution of WN virus activity throughout the city .

Finally, the influence of land use on mosquito counts was examined in this study using statistical plots. The locations of the mosquito traps were explored as a means to predict the distribution of mosquito counts throughout Toronto. Due to an unevenly distributed sampling plan, the results from this particular test were inconclusive and further research was suggested.