Py-Pandemic

A pandemic simulator based on the SIR (Susceptible, Infectious, Recovered/Dead) compartmental model in epidemiology.

Currently supported features

• Population shuffling
• Obtain people in contact with an individual
• Scalable from communities to cities
• Support for travellers
• R0s based on social distancing parameters
• Recovery time based on health care parameters
• Contact tracing
• Hotspots

Dependencies

• NumPy

Example

To simulate a city of population 1000, create a City object. Currently the community size is fixed to 100.

blore = City("Bangalore", 1000, gdp=1e9, healthCare=1)

Before calling the updateCity() method make sure there's at least one infected person in each community of the city.

for _ in range(len(blore.Communities)):
        currentCommunity = blore.Communities[_]
        pZero = random.randint(0, currentCommunity.grid.size - 1)
        currentCommunity.people[pZero].state = 'I'

You can call updateCity() a few times until everyone reaches state R. Other helpful methods such as getNumInfected() and getNumSusceptible() let you track infectious and susceptible people respectively during each iteration.