The measure of malaria incidence on the basis of stratification of the population under study with respect to host and environmental factors is essential to know about the impact of causative/predictive factors. Therefore, to develop a suitable model based on causative/predictive factors on malaria incidence is most important. Here, we developed polynomial regression model to trace the impact of environmental factors on incidence of malaria cases in Lakhimpur district of Assam. Here, LogSPR is considered as explained variables whereas population, maximum temperature, minimum temperature, humidity and average rainfall are considered as explanatory variables. However, lag values of LogSPR at lag one is also considered as one of the explanatory variables. The study reveals that variables minimum temperature, maximum temperature, average rainfall and population play an important role in predicting malaria incidence cases.
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