Title: "Application of GIS and Statistical Modelling for Dengue Fever Surveillance in Delhi, India"

DOI: 10.15224/978-1-63248-114-6-17
Page(s): 26 - 30


In recent years, Geographic Information System (GIS) has become popular in the field of epidemiology for the identification of unusual spatial patterns of disease occurrences and monitoring. Over the years, global burden of Dengue Fever has increased drastically. According to WHO (Global Environmental Change, Geneva) report, there is a strong indication of inter-annual variability and link between meteorological factors and infectious diseases such as Dengue Fever and many other vector-borne diseases. Recently, researchers have demonstrated the importance of determining the impact of various meteorological factors on the propagation of the infectious diseases and such impacts will be more pronounced in a climate change scenario. To control the spread of any infectious disease, it is crucial to identify areas with higher disease risk. The present work is aimed at using GIS techniques such as Point Density method and Empirical Bayesian Kriging method to produce optimal spatial distribution and prediction of Dengue cases in Delhi using historical Dengue Fever case counts and their geographic locations. Poisson regression method has been used to determine the association of Dengue Fever incidences with selected meteorological parameters such as relative humidity, mean temperature and mean wind speed. The outcomes of this study proved that Dengue Fever occurrences are not random. Also, the regression results revealed that there is a significant relationship between meteorological parameters and Dengue Fever incidences. Thus, providing strong evidence that climatic characteristics are playing an important role in the transmission of Dengue Fever in Delhi in addition other important causative factors.