Infection Simulation

[Roger Guay]

Thanks for the many great ideas, Alex. They will keep me busy for a while.

Roger

> On Dec 29, 2021, at 6:23 AM, Alex Tweedly via use-livecode <use-livecode at lists.runrev.com> wrote:
> 
> 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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