Abstract About half of the world’s population is at risk from the vector borne diseases including dengue and malaria. World Health Organization (WHO) has ranked Dengue fever as the most important mosquito borne viral disease in the world. The main objective of this research work is to study the spatial distribution patterns of dengue disease in Rawalpindi using spatial clustering techniques to identify the hotspots and the possible risk factor for those hotspots. Dengue disease data was collected from District Health Office, Rawalpindi. The climate data including average temperature, rainfall and relative humidity was collected from Pakistan Meteorological Department, Islamabad. ArcGIS version 10.1 was used for spatial statistical analysis. The results of this study indicated that incidence level of dengue disease varies according to geographic location and climatic conditions, showing significant spatial autocorrelation. Hotspots were identified using Getis-OrdGi* statistic. Temporal variations of disease cases show significant positive association with the meteorological variables including rainfall, relative humidity and temperature. So, this study highlights the usefulness of GIS in the epidemiological studies.
Keywords Epidemiological studies, Spatial Distribution, Getis-OrdGi* Statistic, Spatial Autocorrelation.
| [Full Text: PDF] |