This study was performed in order to understand the effect of climatological variables on the malaria situation in the north-east region of India, which is prolonged by the disease. Time-series analysis of major climate parameters like rainfall, maximum temperature, minimum temperature, mean temperature, relative humidity, and soil moisture distributions is carried out, and their correlation with the malaria incidence is quantified state-wise, which is the unique part of the study. The correlation analysis reveals that malaria is significantly related with the maximum temperature and soil moisture in three out of eight states in NE India. To assess the climate variability, the inter-dependency between the meteorological parameters is obtained and the state wise correlation matrix for all states are reported. The analysis shows that maximum and mean temperature has highest positive correlation whereas minimum temperature and relative humidity has negative correlation. The climate-malaria relation is being carried out in the study region using the regression analysis and the results revealed that the regional climate has the most impact for the malaria incidence in the state of Arunachal Pradesh, Meghalaya, Tripura and Nagaland and in other states the impact is moderate. Analysis of variance modelling in the regions also indicates the degree of the fitment of both the data sets with the regression model and it is observed that the relation is also significant in the same 4 states. As a case study the impact of large scale oscillations like El Niño-Southern Oscillation on the malaria load is also assessed which can be a good indicator in the prediction of the climate and in turn the malaria incidences over the region.
Keywords: ANOVA; Correlation analysis; Malaria; North east India; Rainfall; Soil moisture; Temperature.
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