SIR model estimation on COVID-19 cases dataset. There is a blog post describing the detail of the SIR model and COVID-19 cases dataset.
All dependencies are resolved by Pipenv
$ poetry install
$ poetry run python solver.py
Option to run
usage: solver.py [-h] [--countries COUNTRY_CSV] [--download-data]
[--start-date START_DATE] [--prediction-days PREDICT_RANGE]
[--S_0 S_0] [--I_0 I_0] [--R_0 R_0]
optional arguments:
-h, --help show this help message and exit
--countries COUNTRY_CSV
Countries on CSV format. It must exact match the data
names or you will get out of bonds error.
--download-data Download fresh data and then run
--start-date START_DATE
Start date on MM/DD/YY format ... I know ...It
defaults to first data available 1/22/20
--prediction-days PREDICT_RANGE
Days to predict with the model. Defaults to 150
--S_0 S_0 S_0. Defaults to 100000
--I_0 I_0 I_0. Defaults to 2
--R_0 R_0 R_0. Defaults to 0
The data used by this simulation is available in: