This repository contains complementary material to a paper published in Computación y Sistemas (CYS):
A computational approach to find SEIR model parameters that best explain infected and recovered time series for SARS-CoV 2.
The main entry point for the experimental results and source code is the Jupyter Notebook: COVID-SCENARIOS.iphnb
. From this, we can find the following sub-structure:
- Folder
data
contains a.json
file with COVID timeseries of several countries downloaded from https://covid19.who.int. - Folder
dnn_opt_seir
which is a modified clone of the library dnn_opt used for the optimization of SEIR model parameters.