That's really cool - thanks.
Improvements ? How much time do you have :-)
1. Visual display of contagion zone while running.
2. Recovery. After being infected for some length of time, an individual
stops being infectious; either it dies, and becomes a static black dot,
or recovers and becomes a white dot again. Probably different times for
each of those to happen. And obviously a control for the likelihood of
recovery vs death.
3. Probabilistic infection. Rather than always infect another which
comes within reach, make that a probability of infection.
4. Viral load. Make the probability as above follow a bell curve over
time, as the individual becomes more infected, then recovers.
5. Simulate superspreader events. Maybe introduce short-term "gravity"
that attracts individuals within a range together - and hence if one is
already infected they infects lots of others.
And I could go on almost forever :-)
Thinking of features is orders of magnitude easier and quicker than
implementing them :-)
Thanks again,
Alex.
On 29/12/2021 03:37, Roger Guay via use-livecode wrote:
I just uploaded a stack called “Infection" to Sample Stacks which might be a
little fun (in a scary way) for some of you. It’s a Monte Carlo simulation wherein a
number of individuals randomly moving about in an enclosed space, are infected by a
single randomly infected individual. I welcome any feedback that might lead to more
accuracy in or improvement to this model.
Cheers,
Roger
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