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Susceptible Exposed Infected Recovered model (SEIR)

Source: R/ModelSEIR.R
ModelSEIR.Rd

Susceptible Exposed Infected Recovered model (SEIR)

Usage

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

# S3 method for class 'epiworld_seir'
plot(x, main = get_name(x), ...)

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.

x

Object of class SEIR.

main

Title of the plot

...

Currently ignore.

Value

The plot function returns a plot of the SEIR model of class epiworld_model.

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.

See also

epiworld-methods

Other Models: ModelDiffNet(), 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)
#> _________________________________________________________________________
#> Running the model...
#> ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| done.
#>  done.
model_seir
#> ________________________________________________________________________________
#> Susceptible-Exposed-Infected-Removed (SEIR)
#> It features 1000 agents, 1 virus(es), and 0 tool(s).
#> The model has 4 states.
#> The final distribution is: 0 Susceptible, 0 Exposed, 0 Infected, and 1000 Removed.

plot(model_seir, main = "SEIR Model")