ModelSEIRCONN

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ModelSEIRCONN#

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

Bases: Model

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

States: Susceptible, Exposed, 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.ModelSEIRCONN("COVID-19", n=10000, prevalence=0.01,
...                                 contact_rate=2, transmission_rate=0.5,
...                                 incubation_days=7, recovery_rate=0.3)
>>> covid.run(ndays=100, seed=1912)

Create a connected SEIR 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.

  • incubation_days (float) – Average number of days in the exposed state; greater than 0.

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

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