Year: 2020
Type: preprint
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.
Source: arXiv (Cornell University)
Authors: Yang, Tong, Sha, Long, Li, Justin, Hong, Pengyu
Institution: Association for Computing Machinery
Language: English
Subfield: Modeling and Simulation
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W3048837939