ReCOVER

- Country and US state-level forecasts for COVID-19 using heterogeneous infection rate model - Data-driven identification of unreported case

This is a part of the following NSF project:
ReCOVER: Accurate Predictions and Resource Allocation for COVID-19 Epidemic Response
PIs: Viktor K. Prasanna ([e-mail]), Ajitesh Srivastava ([e-mail])
University of Southern California

This repository contains some codes for our ongoing work on NSF-funded project on COVID-19 forecasting.
We use our own epidemic model called SI-kJalpha - Heterogeneous Infection Rate with Human Mobility.

For live script for forecasting, run: plot_gen.mlx
For detecting unreported cases use: daily_explore_unrep.mlx

Our relevant presentation: https://www.youtube.com/watch?v=ll6k8wlxOFo
Our paper on forecasting: https://arxiv.org/abs/2004.11372
Paper on detecting unreported cases: https://arxiv.org/abs/2006.02127