ModelSIRCONN

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ModelSIRCONN#

class epiworldpy.epimodels.ModelSIRCONN(self: epiworldpy._core.epimodels.ModelSIRCONN, name: str, n: SupportsInt | SupportsIndex, prevalence: SupportsFloat | SupportsIndex, contact_rate: SupportsFloat | SupportsIndex, transmission_rate: SupportsFloat | SupportsIndex, recovery_rate: SupportsFloat | SupportsIndex)#

Bases: Model

Susceptible-Infected-Recovered (SIR) model in a connected population.

States: Susceptible, Infected, Recovered.

Every agent can contact every other agent (a well-mixed population), so no network is needed: the model creates its n agents itself. This is equivalent to a compartmental model.

Examples

>>> from epiworldpy import epimodels
>>> covid = epimodels.ModelSIRCONN("COVID-19", n=10000, prevalence=0.01,
...                                contact_rate=5, transmission_rate=0.4,
...                                recovery_rate=0.95)
>>> covid.run(ndays=100, seed=1912)

Create a connected SIR model.

Parameters:

  • name (str) – Name of the virus.

  • n (int) – Number of agents.

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

  • contact_rate (float) – Average number of contacts per agent per day.

  • 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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