An epidemic is spreading fast from airport to airport (not really). Scientists have been trying to create a map of the spread to study and prevent. They have been attempting to find the day that each airport hosted an infected individual. Still, they suspect that their measurements are imprecise. How can they denoise their data?
To have fun I decided to simulate this scenario. One interesting dataset I stumbled upon is the global flight network, depicting 2980 airports and their flight interconnections. The network comprises of a giant component covering the major world airports – if it wasn’t so, flying would be much more cumbersome. Network check! How about the epidemic? Well, studying the spread of diseases is a well established scientific topic both mathematically and numerically. To simulate my epidemic, I opted to use the simple (-istic) SIR model, standing for Suspected Infected Recovered. The results are shown below.