Advancing Deep Learning for Supply Chain Optimization of COVID-19 Vaccination in Rural Communities

Abstract

Covid19 is a global pandemic that brought lots of disruptions in day-to-day life, affected economies, closed millions of businesses, and took a lot of precious lives. Along with social distancing and wearing masks, the effective way to eradicate the virus is to administer vaccines. To prevent the spread of disease and avoid deaths, it is essential to prioritize vaccine distribution. At the request of CDC, National Academies of Science, Engineering and Medicine published the Framework for fair distribution of COVID-19 Vaccine. This paper focuses on studying the rate of vaccination in urban and rural communities and identifying gaps in the Covid19 vaccine supply chain using data science. Demand forecasting using deep learning is proposed for planning vaccine allocation and distribution. Deep learning refers to multilayer neural networks that can learn extremely complex patterns using hidden layers between inputs and outputs. Long Short-Term Memory neural networks will be used to forecast vaccine demand.