Multiple Linear Regression Model Of Visceral Leishmaniasis In Bihar, India




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Visceral Leishmaniasis (VL) is one of the world's worst parasitic killers, second only to Malaria, claiming nearly 500,000 lives each year. The disease attacks the spleen, liver, and bone marrow, and if left untreated is nearly always fatal. Whilst the disease is found all around the world, it is primarily prevalent in developing countries, in particular India. The most affected state in India is Bihar, where the disease is endemic. While other research has been conducted with emphasis on the effect of climate variables on the disease incidence rate, this analysis focuses on socio-economic variables such as literacy rate, housing structure, and working environment, to study their roles on the incidence rate. A Multiple linear regression model that includes these socio-economic factors as independent variables was initially developed and it explained 92% of the observed variance. The model was then reduced via stepwise regression and two models that explained 81% and 63% of the observed variance were used to help determine the most significant variables, such as housing and literacy rates. Modest comments are made on possible measures that could be taken to decrease the VL incidence rate, along with limitations of the model and suggestions for further research on this topic.