Forecasting The Incidence Of Neglected Tropical Diseases And Vector-Borne Diseases

Abstract

Dengue fever is a common vector-borne sickness in tropical regions, particularly in India, Bangladesh, and Pakistan. This disease, caused by mosquitoes, affects people of all ages in more than a hundred nations throughout the world. The research looks into real-time series forecasting and analysis, applying three regression models and developing a weighted average forecasting model for infectious diseases. From 2014 to 2017, the integrated diseases monitoring program of the Indian Government provided monthly statistics on dengue cases. The data was analyzed using three regression models: support vector regression, neural network, and linear regression, with performance indicators including mean absolute error (MAE), root mean square error (RMSE), and mean square error (MSE). The study found that the proposed weighted ensemble model outperformed, with an emphasis on its ability to minimize predicting mistakes. The fundamental goal of the study, forecasting error reduction, was met thanks to the weighted ensemble model’s higher performance. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.