Vivek Kumar

Spatio-temporal assessment and mapping of health risk due to climatic and non-climatic factors in Patna, India

Mosquitoes can transmit a number of diseases in humans. Malaria and dengue are among the most well documented and highly researched vector borne diseases that infect millions of people every year. Dengue is a mosquito borne infectious disease that has become a major healthcare concern. Every year around 390 million individuals are infected with the illness, resulting in half a million hospitalizations. The number of dengue cases has increased dramatically post 60s and dengue is now endemic in over 110 countries. Patna in India is highly affected and each year high number of dengue cases are registered in Patna. In absence of any vaccine against the dengue and no drug that targets dengue virus directly, it is critical to understand and develop the preventive mechanisms as a remedial alternative. This can be achieved by seeking reduced exposure and limiting mosquito population. Several factors that include climatic (temperature, precipitation, humidity), environmental conditions such as open water bodies, distance to water bodies and road, housing conditions etc. and socioeconomic conditions (education, income, disease awareness) have an influence on the occurrence and spread of the disease outbreak. The interaction of all such factors (climatic and non-climatic) with the spatial distribution of vector borne disease (dengue) is important to investigate for the mapping of hot spot areas at risk for disease outbreaks that will be used by the decision makers for targeted and timely interventions. The overall objective of this research is to develop a spatial composite health risk map for Dengue in Patna, India. Remote sensing data along with several other data, such as socio-economic, environmental and climatic data are used in this study. The identification and visualization of hot spot areas at risk on the map are performed using Multi criteria analysis in this study. In addition, different methodological approaches i.e., Time series trend analysis, multiple regression and spatial clustering techniques are used to meet each of the research objectives.