ReCOVER

Version 2.01 (637 KB) by Ajitesh Srivastava
- Country and US state-level forecasts for COVID-19 using heterogeneous infection rate model - Data-driven identification of unreported case
5.0
(1)
83 Downloads
Updated 15 Jun 2020

View License

This is a part of the following NSF project:
ReCOVER: Accurate Predictions and Resource Allocation for COVID-19 Epidemic Response
PIs: Viktor K. Prasanna (prasanna@usc.edu), Ajitesh Srivastava (ajiteshs@usc.edu)
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

Cite As

Ajitesh Srivastava (2024). ReCOVER (https://www.mathworks.com/matlabcentral/fileexchange/75281-recover), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2020a
Compatible with any release
Platform Compatibility
Windows macOS Linux
Categories
Find more on Biological and Health Sciences in Help Center and MATLAB Answers

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

ReCOVER/scripts

ReCOVER/scripts

Version Published Release Notes
2.01

Fixed a forecast lag
2.0

Added smoothing in forecasting. Also added possibility of detecting unreported cases
1.1

Improved hyperparameter search. Added pre-calculated hyper-parameters for various days in the past.
Also added scripts to generate dynamic reproductive number
1.0.1

Added some comments
1.0.0