Numerical Epidemics

As of April 2020, the main topic in the news is the Coronavirus pandemic, and expressions like basic reproduction number, superspreaders or the danger of exponential growth occur everywhere while the efficiency of various quarantine and other measures to spread contagion is discussed.

It's relatively clear how an epidemic in the ideal case develops - but... how does it really work? When some real world complications are present?

I started to write this software to find out why exponential growth was not seen anywhere in the world - despite the fact that the simple model makes it very hard to avoid. So obviously there are real-world effects which do - substantially - influence the spread of a disease.

With the simulation sofware below, you can start to study some of them in a qualitative way - what is the influence of restricting movement? What is the role of super-spreaders? How would a disease respond to vaccination or to a prior level of immunity in the population? So, you're no longer expected to take someone's pronouncements on face value, you can start simulating and understanding yourself.


The source code of the simulation is available under the GNU General Public License 2.0+ - in short, you may use, re-distribute and modify the software freely, but you are required to provide the source code and license any additions/changes also GPL if you re-distribute.

The tarball extracts into its own subfolder, the code is inside the src/ folder, the doc/ folder contains a manual, the config/ folder a few sample configuration files. A few tutorials on how to use the software are found below. There is no Linux executable provided.

Download Numerical Epidemics V0.4


Exponential Growth
Prior immunity
Containment measures
Disease strains
Vaccination campaigns

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Created by Thorsten Renk 2020-2021 - see the disclaimer, privacy statement and contact information.