Abstract
most deaths worldwide including in Bangladesh. Since 1964, Bangladesh has experienced the sporadic occurrence of dengue until 2000 when the first epidemic of dengue was reported in the capital city, Dhaka. Since then, the disease has shown an annual occurrence in all major cities of the country. The state-of-the-art methodologies, eg, machine learning approaches, are now being used in many countries for early predicting or forecasting dengue cases. In this chapter, we propose machine learning algorithms for the early prediction of dengue cases in Bangladesh. We collect and preprocess meteorological data of Dhaka city to fit the machine learning models. In this work, we propose a weighted average ensemble technique of five machine learning methodologies for predicting the number of dengue cases per month from meteorological data. The proposed approach produced promising results in predicting the dengue cases for our testing data samples, which shows great potential for employing machine learning algorithms successfully for early dengue incident prediction in various cities of Bangladesh. We hope that our methodology can contribute to further research on predicting dengue incidents in Bangladesh using meteorological data.