Fuzzy linear regression approach for modelling dengue disease transmission in Colombo

Abstract

Dengue fever is caused by the dengue virus and is primarily transmitted through the bites of Aedes mosquitoes. Dengue fever is a significant public health concern in Colombo, Sri Lanka, with recurring outbreaks affecting a large number of individuals. Understanding the factors influencing dengue transmission is crucial for effective disease control and prevention. This study aims to explore a fuzzy regression approach for modelling dengue disease transmission in Colombo. As fuzzy linear regression incorporates uncertainty and imprecision into the modelling process, it has an advantage over conventional regression techniques. A fuzzy linear regression model was developed using various climate predictors, such as rainfall, relative humidity, wind speed, and temperature. Among these Climate variables, relative humidity and rainfall, are found to play a crucial role in mosquito breeding and the subsequent spread of the dengue virus. The fuzzy linear regression model is used to assess the relationships between these predictors and dengue transmission rates in Colombo. The suggested fuzzy linear regression model's evaluation criteria were done using R2 , Root Mean Squared Error, and Mean Absolute Error values. This study provides insights into the relationship between climatic factors and dengue transmission in Colombo by utilizing the above regression model. Climate variables, such as relative humidity and rainfall, are found to play a crucial role in mosquito breeding and the subsequent spread of the dengue virus. The findings highlight the importance of considering climatic predictors when developing dengue prevention strategies, particularly in urban environments like Colombo.