Research Article Volume 5 • Issue 3 441 Dengue out break Prediction Based on Artifcial Neural Networking Model using Climatic Parameters Biplab Ghosh 1 and Monika Soni 2 * Afliation: 1 Indian Institute of Technology, Guwahati, Assam-781039, India 2 Assam Don Bosco University, Tepesia, Assam-781027, India *Corresponding author: Monika Soni, Assistant Professor, Department of Biosciences, Assam Don Bosco University, Tepesia, Assam-781027, India Citation: Biplab Ghosh and Monika Soni. Dengue out break Prediction Based on Artifcial Neural Networking Model using Climatic Parameters. Archives of Internal Medicine Research 5 (2022): 441-446. Received: June 16, 2022 Accepted: July 04, 2022 Published: September 29, 2022 Keywords: Artifcial neural network; Nonlinear models; Meteorological parameters; Dengue; Aedes mosquito. Introduction Dengue fever is a vector-borne disease that is one of the most important public health riskscaused by the all four serotypes of dengue virus DENV-1, DENV-2, DENV-3 and DENV-4. Globally there are 100 to 400 million cases of infections annually in tropical and subtropical regions [1-3]. Aedes aegypti and Aedes albopictus mosquitoes are responsible for the diseases transmission [1,2,4]. As the Ae. Aegypti mosquitoes have adjusted to urban settings, the control and mitigation of the disease has become very difcult [5-7]. The epidemics of dengue fever in India have turn out to be more commonand have rapidly spread to new areaswhere dengue was not generallyin existence [8]. Ensuing epidemics have been reported in diferent parts of India, especially in urban settings [9].An important shift has been observed in the range of the dengue afected area where it is not constrained to urban areas only but has spread to rural expanses [10].The increase in the burden of dengue cases in Abstract Purpose: Dengue fever is a vector-borne tropical disease radically amplifedby 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 artifcial 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.