ModelSIR

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ModelSIR#

class epiworldpy.epimodels.ModelSIR(self: epiworldpy._core.epimodels.ModelSIR, name: str, prevalence: SupportsFloat | SupportsIndex, transmission_rate: SupportsFloat | SupportsIndex, recovery_rate: SupportsFloat | SupportsIndex)#

Bases: Model

Susceptible-Infected-Recovered (SIR) model on a network.

States: Susceptible, Infected, Recovered.

The model has no agents until a population is added, for example with agents_smallworld().

Examples

>>> from epiworldpy import epimodels
>>> covid = epimodels.ModelSIR("COVID-19", prevalence=0.01,
...                            transmission_rate=0.9, recovery_rate=0.1)
>>> covid.agents_smallworld(n=1000, k=5, d=False, p=0.01)
>>> covid.run(ndays=100, seed=1912)

Create a SIR model.

Parameters:

  • name (str) – Name of the virus.

  • prevalence (float) – Initial proportion of agents with the virus.

  • transmission_rate (float) – Probability of transmission per contact, between 0 and 1.

  • recovery_rate (float) – Daily probability of recovery, between 0 and 1.

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