Analytics-Empowered Framework and an LSTM Model to Promote Preparedness to Curb Pandemics

The COVID-19 pandemic has significantly impacted all the sectors, forcing the governments all around the globe to adopt strict measures like remote work, online learning, and social distancing. Many schools and institutions were unprepared for the swift transition, and challenges persist in controlling infection rates and stabilizing economies. This research proposes a data-driven intelligent system to predict the spread of infection and guide effective measures. Using data from the UAE National Emergency Crisis and Disaster Management Authority, the system aims to identify effective measures to prevent infection and mitigate the pandemic's impact. The focus is on developing a prediction model for forecasting decision elements, such as case numbers and mortality rates, to empower UAE crisis management with timely and intelligent responses. Using machine learning optimizes decision making and improves preparedness for future outbreaks. Learning from global experiences, the system aims to provide accurate predictions and recommendations, improving economic stability and societal well-being.