{"id":9405,"date":"2020-03-23T13:12:17","date_gmt":"2020-03-23T18:12:17","guid":{"rendered":"https:\/\/blogs.mathworks.com\/simulink\/?p=9405"},"modified":"2020-10-14T14:36:20","modified_gmt":"2020-10-14T18:36:20","slug":"covid-19-simulating-exponential-spread-in-simulink","status":"publish","type":"post","link":"https:\/\/blogs.mathworks.com\/simulink\/2020\/03\/23\/covid-19-simulating-exponential-spread-in-simulink\/","title":{"rendered":"COVID-19: Simulating exponential spread in Simulink"},"content":{"rendered":"

Update (10\/14\/2020): <\/strong>The GitHub repository now contains a MATLAB App to simulate the model and visualize the results. We compiled the app as a MATLAB Web App<\/a> and host it in the cloud using the MATLAB Web App Server<\/a>.<\/em><\/p>\n

Last week, my colleague Mariano Lizarraga Fernandez pointed me to the Washington post simulation of COVID-19<\/a> and we thought it would be interesting to implement something similar using MathWorks products.<\/p>\n

Now that Cleve<\/a> published a MATLAB-based simulator<\/a>, it's time to for us to publish our simulation implemented using Simulink, Stateflow and SimEvents.<\/p>\n

Here is what the results looks like for a random set of 50 \"agents\" (green is before infection, red is infected and blue is recovered):<\/p>\n

\"Covid<\/p>\n

Let's see how I put that together.<\/p>\n

Extending the Curling Simulator<\/strong><\/p>\n

The first thing that crossed my mind when thinking about how I would implement this simulation is that I could probably reuse some of the algorithm I put together for the curling simulator<\/a> I published some time ago.<\/p>\n

With the dynamics of the stones bouncing against each other already implemented, I added bouncing against a boundary box and a logic to keep track of the infection propagation.<\/p>\n

To begin, let's look at the top level.<\/p>\n

\"Covid<\/p>\n

and here is what the Stateflow chart looks like:<\/p>\n

\"Covid<\/p>\n

The Details<\/strong><\/p>\n

Here is how it all works:<\/p>\n