ModelSEIR: Susceptible Exposed Infected Recovered model (SEIR)

In epiworldR: Fast Agent-Based Epi Models

Susceptible Exposed Infected Recovered model (SEIR)

Description

Susceptible Exposed Infected Recovered model (SEIR)

Usage

ModelSEIR(name, prevalence, transmission_rate, incubation_days, recovery_rate)

Arguments

name	String. Name of the virus.
prevalence	Double. Initial proportion of individuals with the virus.
transmission_rate	Numeric scalar between 0 and 1. Virus's rate of infection.
incubation_days	Numeric scalar greater than 0. Average number of incubation days.
recovery_rate	Numeric scalar between 0 and 1. Rate of recovery_rate from virus.

Details

The initial_states function allows the user to set the initial state of the model. The user must provide a vector of proportions indicating the following values: (1) Proportion of non-infected agents who are removed, and (2) Proportion of exposed agents to be set as infected.

Value

• The ModelSEIRfunction returns a model of class epiworld_model.

See Also

epiworld-methods

Other Models: ModelDiffNet(), ModelMeaslesQuarantine(), ModelSEIRCONN(), ModelSEIRD(), ModelSEIRDCONN(), ModelSEIRMixing(), ModelSIR(), ModelSIRCONN(), ModelSIRD(), ModelSIRDCONN(), ModelSIRLogit(), ModelSIRMixing(), ModelSIS(), ModelSISD(), ModelSURV(), epiworld-data

Examples

model_seir <- ModelSEIR(name = "COVID-19", prevalence = 0.01,
  transmission_rate = 0.9, recovery_rate = 0.1, incubation_days = 4)

# Adding a small world population
agents_smallworld(
  model_seir,
  n = 1000,
  k = 5,
  d = FALSE,
  p = .01
)

# Running and printing
run(model_seir, ndays = 100, seed = 1912)
model_seir

plot(model_seir, main = "SEIR Model")

epiworldR documentation built on June 8, 2025, 1:48 p.m.