[kasra85]

With regards to the need for flattening even more, I totally agree. But I think you are under the impression that the y axis in this model can simulate the real world. That's not the case. This is a "super simplified model" to show the effect of simple changes - relative to other scenarios, not necessary being an absolute measure.

The close circle size is the family/close friend size. In actual scientific models, this is a decimal value to represent the average of the community, but in this model, I kept it as a whole number to simplify my calculations. If I get a chance, I'll improve this further.

Anything that falls into more than 150 days is way beyond any sane model can predict. Cutting the "Random Contact" to 1 greatly drops the rate for at least 150 days - this is exactly the point of this model on showing how important it is to reduce social interactions.

[gus_massa]

I just noticed that the simulation does not have a field for the total size of the population. The initial state is 5 sick people in a population of 5000.

The initial grow is exponential until the logistic part of the curve kicks in. The current grow is something like 25% daily, so a x10 in the population is a delay of the peak of 3 days or something like that. It would be more days if we flatten the curve. (With the initial values in your simulation, the peak is at 60 days. For a big city with 1 million people, the delay is like 2 weeks.)

It's clear that this is a very simplified model, but they are useful to get a feeling of how the parameters affect the epidemy.