Identification of the potential effect of climate change on Dengue epidemic using spatial analysis in Chachoengasao province, Thailand
Somwang Kurusarttra1, Kanchana Nakhapakorn1 and Pattamaporn Kittiyapong2
1Industrial Ecology and Environment Program, Faculty of Environment and Resource Studies, Mahidol University, Nakhon
Pathom 73170, Thailand
2Center for Vectors and Vector-borne Diseases and Department of Biology, Faculty of Science, Mahidol University, Rama 6
Road, Bangkok, 10400, Thailand;
Dengue is a mosquito-borne viral infection causing a constant and serious risk to most tropical regions. As the countries become more developed and environmental transformed from rural to urban, the human population inexorable growth will change global patterns of the disease and mortality. Furthermore, changes in climate pattern phenomenon are thought to be a major contributing factor. Our aim was to indentify the potential effects of climate change on human
health, and in particular, on the incidence of vector-borne diseases. We studied among 11 districts both rural and urban sites in Chachoengsao province, Thailand from 1999 to 2007. Geographic
Information Systems (GIS) has been used to links between georeferenced factors including medical records, demographic data, and climatic data. Using multivariate regression analysis and spatialtemporal modelling, four classes of risk categories have been identified. The nearest neighbourhood method has been allowed to generate a spatial risk map. Dengue incidences in case numbers were significantly associated with climatic variables. The two most significant ones were mean minimum 2-weekly temperatures at t-1 (n = 2530, r2 = 0.245, P = 0.001) and total 2-weekly rainfall during t-2 (n = 2530, r2 = 0.137, P = 0.001). All variables, when entered into the same regression model by stepwise method, together evaluated 66.1% of the total variation in case numbers. At a small temporal scale, we assumed that the changes of land use/cover would not change much. However the predicted regression model implied that dengue epidemics were likely to associate with urbanization and industrialization. Not only they are a suitable ecological niche of denguemosquitoes in term of breeding sites and living habitats, but also urban and industrial increasing effected on the global warming directly. In summary, this research makes advances in dengue
research using GIS spatial analysis for planning prevention and control programs.