Updated 15 Jun 2020
This is a part of the following NSF project:
ReCOVER: Accurate Predictions and Resource Allocation for COVID-19 Epidemic Response
PIs: Viktor K. Prasanna (firstname.lastname@example.org), Ajitesh Srivastava (email@example.com)
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
Ajitesh Srivastava (2023). ReCOVER (https://www.mathworks.com/matlabcentral/fileexchange/75281-recover), MATLAB Central File Exchange. Retrieved .
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Fixed a forecast lag
Added smoothing in forecasting. Also added possibility of detecting unreported cases
Improved hyperparameter search. Added pre-calculated hyper-parameters for various days in the past.
Added some comments