A simple agent-based model of viral infections inspired by current news about COVID-19. Healthy and sick agents interact in a two-dimensional world. How many will survive? Model code available at: github.com/DaveAckley/SPLATTh...
Interesting and informative. Mr. Ackley inadvertently demonstrates The need for another critical human intervention to reduce the spread of infection: he touches his nose and face at least 20 times during this video.
Nice and informative demonstration of the effects and especially the goal of prevention measures. Even if it might not be accurate considering covid19 it shows that every small change in behaviour can have a big impact overall!
Can you model in that people change their behaviour only when the treat becomes visible to them? For example, today I realized that I probably only going to start wearing a mask when I see at least 10% of other people wear a mask.
Could add like 'Masked' types and work on rules for how they are created and how others react to them. Hard part is trying to keep it relatively simple.
Fantastic work! The whole presentation was brilliant and to end with the R-not was the icing on the cake. Keep these videos coming, there's a lot to learn from them. Thank you!
Flattening the curve is good, but inversely, you are also _elongating_ the curve by doing so. Even in your simulation where almost every single person became infected at some point, it only halved the deaths. So if that flattened curve were twice as long (if it were more realistic), there would have been no difference in deaths. Moreover, it's possible to have _more deaths_ from a flatter curve. Great video!
