This is a refactor of https://towardsdatascience.com/building-your-own-covid-19-epidemic-simple-model-using-python-e39788fbda55

Please refer to the original post for more information.

I am not the original author.

The refactor did not alter or change the order of operation stated in the original script.

Make sure to have a look at config.ini, it houses the parameters that will define the model. An important aspect to consider when starting is the Group Size and the Sample Size, they will dictate the resources and time needed for the simulation. I couldn't equate the exact time needed; there are many factors to consider. Processing power and memory are but a few. The default configuration took my i7-6700HQ CPU @ 2.60GHz 10 minutes to complete, however after testing with a Group Size=3000 & Sample Size=0.1 it took 40 mins to reach day 17.

Not all parameters in config.ini are considered. This is a work in progress.

[SampleDefaults]
xLimit = 30
yLimit = 30
dayLimit = 100
groupSize = 3000
sampleSize = 0.1
distance = 1.5
numberOfBeds = 3 #Not Used
logfile = corona.log

[Rates]
#https://www.worldometers.info/coronavirus/coronavirus-death-rate/
deathRate = 0.034
deathsDueToLackOfBeds = 0.05 # Not Used
#https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/index.html
hospitalizationRate = 0.5
#https://www.worldometers.info/coronavirus/coronavirus-death-rate/
deathRateForICU = 0.15

[Days]
daysUntilLimboDieDuetoLackOfBeds = 3 # Not Used
dayUnitlCuredIfPositive = 14
dayUnitlCuredIfInHospital = 25

Limbo is also not taken into account. The state was supposed to represent those who are extremely sick yet cannot be hospitalized due to lack of beds...this is also a work in progress

I would suggest removing the ion func for Group Sizes > 1500

Since the model is dictated by ratios and counts, altering the parameters without considering it's soundness will result in unlikely outcomes. Be mindful when specifying your parameters.