top of page

TEAM

Climate-Based Forecasting of Dengue Epidemic Years: A Case Study of Bangladesh

Haridas Kumar Das, Abdullah Al Helal

clear.png

Dengue outbreaks have become a global concern, affecting many regions such as the Americas, Africa, the Middle East, Asia, and the Pacific Islands. Over the past two decades, there has been a notable rise in dengue cases worldwide, with significant impacts observed in countries like Brazil and Bangladesh. Moreover, in the United States, local transmission of dengue has been reported in a few states including Florida, Hawaii, Texas, Arizona, and California. Numerous studies have demonstrated the correlation between climate factors—such as temperature and rainfall—and the transmission of dengue, Zika, chikungunya, and yellow fever. Specifically, elevated temperatures have been linked to an increased dengue infection risk, while extreme rainfall events have shown to decrease this risk. In this project, we develop machine learning algorithms to analyze climate and epidemiological data in order to forecast dengue epidemic years, focusing on the analysis of Bangladesh.

Screen Shot 2022-06-03 at 11.31.35 AM.png
github URL
bottom of page