Abstract
In this work, we developed a deep learning model-based approach to forecast
the spreading trend of SARS-CoV-2 in the United States. We implemented the
designed model using the United States to confirm cases and state demographic
data and achieved promising trend prediction results. The model incorporates
demographic information and epidemic time-series data through a Gated Recurrent
Unit structure. The identification of dominating demographic factors is
delivered in the end.