Forecasting Dengue and Studying its Plausible Pandemy using Machine Learning

Abstract

India has witnessed an alarming increase in the number of dengue cases to the count of about 300 percent since 2009 as per the National Health Profile, 2018. Dengue is considered a serious threat not only in India but also is becoming a problem all over the world especially in tropical countries like Indonesia, India and Malaysia. Dengue cases were widespread during the onset and the duration of monsoon due to the collection of water creating breeding grounds for female aedes mosquitoes which are vectors for Flavivirus (Dengue virus). With the lack of appropriate infrastructure and methodology to identify vulnerable regions in India, the cases of dengue have been on the rise. This paper is an attempt to use machine learning and statistical models to predict dengue cases across India and identify the patterns between climatic factors, urbanization and number of cases reported for dengue. This includes the spread spectrum of dengue and also accounts as an AI based mitigative forecast model to alert the concerned authorities before the spread of the epidemic. This will enable the concerned authorities to gauge the situation and take appropriate steps to prevent the pandemy.