Dengue out break Prediction Based on Artificial Neural Networking Model using Climatic Parameters

Author(s): Biplab Ghosh and Monika Soni

Purpose Dengue fever is a vector-borne tropical disease radically amplifiedby 30 times in occurrence between 1960 and 2010. The upsurge is considered to be because of urbanization, population growth and climate change. Therefore, Meteorological parameters (temperature, precipitation and relative humidity) have impact on the occurrence and outbreaks of dengue fever. There are not many studies that enumerate the relationship between the dengue cases in a particular locality and the meteorological parameters.This study explores the relationship between the dengue cases and the meteorological parameters.In prevalent localities, it is essential to alleviate the outbreaks using modelling techniques for better disease control.

Materials and Methods An artificial neural network (ANN) model was developed for predicting the number of dengue cases by knowing the meteorological parameters.The model was trained with 7 years of dengue fever data of Kamrup and Lakhimpur district of Assam, India. The practicality of the model was corroborated using independent data set with satisfactory outcomes.

Result and conclusion It was apparent from the sensitivity analysis that precipitation is more sensitive to the number of dengue cases than other meteorological parameters. This model would assist dengue fever alleviation and control in the long run.

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