Last week, my colleague Mariano Lizarraga Fernandez pointed me to the Washington post simulation of COVID-19 and we thought it would be interesting to implement something similar using MathWorks products.
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):
Let's see how I put that together.
Extending the Curling Simulator
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 I published some time ago.
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.
To begin, let's look at the top level.
and here is what the Stateflow chart looks like:
Here is how it all works:
- Inside Stateflow, the Simulink State integrates the motion of the agents
- At every time step, we call a MATLAB function to detect if an agent hit one of the border walls. If one agent did, we invert the sign of its velocity in the wall direction and re-initialize the Integrator block in the Simulink State with this updated velocity.
- At every time step, we call a MATLAB Function to detect if two agents get into contact. If they did, we compute the new velocities using a Simulink Function and reset the Integrator block in the Simulink State.
- When that happens, we call a Stateflow Graphical function to determine if the infection gets propagated. To keep track of who is infected, we use a global Data Store
- If we determine that a new agent has been infected, the Stateflow chart calls a Simulink Function that generates a SimEvents Entity
- This entity is sent to a an Entity Server for a fixed amount of time to recover.
- Once the recovery time is over, the Entity Server exit action calls a Simulink Function that updates the global data store accordingly.
Here is a different result where I reduced the initial speed of the agents. It's interesting to see the impact on the propagation:
Now it's your turn
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