Stochastic COVID-19 Simulation on Networks

Copyright: 2020, Gerrit Großmann, Group of Modeling and Simulation at Saarland University

Version: 0.1 (Please note that this is proof-of-concept code in a very early development stage.)

Caveat lector: This is an academic model, do not use academic models as a basis for political decision-making.

Overview

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Stochastic (Monte-Carlo) simulation of the of Covid-19 pandemic (of the SARS-CoV-2 virus) on complex networks (contact graphs). The model falls under the general class of a SEIR compartment models.
The model is a stochastic interpretation of a Covid-19 model based on the work of Dr. Alison Hill.

Installation

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With:

pip install -r requirements.txt

Example Usage

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With

python simulation.py

Output

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Dataframe as .csv file and corrsponding lineplot. Animations can be created with the visualization function.