Md. Ahsanul Islam

The rapid development and deployment of COVID-19 vaccines have been pivotal in the global battle against the pandemic. However, vaccine acceptance remains a critical determinant of their effectiveness. While numerous studies have explored factors influencing vaccine acceptance, there is a notable dearth of research regarding preferences and willingness to pay (WTP) among individuals with chronic diseases (ChD) who are at heightened risk of severe COVID-19 outcomes. This study addresses this gap by investigating COVID-19 vaccine preferences and WTP among individuals with and without chronic diseases.

Accurate forecasting of time series, specifically in meteorological context, is critical for informed decision-making in agriculture, disaster management and so on. In Bangladesh, seasonal monsoons and erratic weather patterns pose significant challenges to traditional time series models. This study investigates whether deep learning methods can offer tangible improvements over statistical approaches for univariate multi-step forecasting of rainfall, temperature, and ultraviolet radiation at three climatically diverse locations: Chattogram, Dhaka, and Sylhet in Bangladesh.