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Susceptible Exposed Infected Removed model (SEIR connected)

Source: R/ModelSEIRCONN.R
ModelSEIRCONN.Rd

The SEIR connected model implements a model where all agents are connected. This is equivalent to a compartmental model (wiki).

Usage

ModelSEIRCONN(
  name,
  n,
  prevalence,
  contact_rate,
  transmission_rate,
  incubation_days,
  recovery_rate
)

Arguments

name

String. Name of the virus.

n

Number of individuals in the population.

prevalence

Initial proportion of individuals with the virus.

contact_rate

Numeric scalar. Average number of contacts per step.

transmission_rate

Numeric scalar between 0 and 1. Probability of transmission.

incubation_days

Numeric scalar greater than 0. Average number of incubation days.

recovery_rate

Numeric scalar between 0 and 1. Probability of recovery_rate.

Value

See also

epiworld-methods

Other Models: ModelDiffNet(), ModelMeaslesMixing(), ModelMeaslesMixingRiskQuarantine(), ModelMeaslesSchool(), ModelSEIR(), ModelSEIRD(), ModelSEIRDCONN(), ModelSEIRMixing(), ModelSEIRMixingQuarantine(), ModelSIR(), ModelSIRCONN(), ModelSIRD(), ModelSIRDCONN(), ModelSIRLogit(), ModelSIRMixing(), ModelSIS(), ModelSISD(), ModelSURV(), epiworld-data

Examples

# An example with COVID-19
model_seirconn <- ModelSEIRCONN(
  name                = "COVID-19",
  prevalence          = 0.01,
  n                   = 10000,
  contact_rate        = 2,
  incubation_days     = 7,
  transmission_rate   = 0.5,
  recovery_rate       = 0.3
)

# Running and printing
run(model_seirconn, ndays = 100, seed = 1912)
#> _________________________________________________________________________
#> Running the model...
#> ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| done.
model_seirconn
#> ________________________________________________________________________________
#> Susceptible-Exposed-Infected-Removed (SEIR) (connected)
#> It features 10000 agents, 1 virus(es), and 0 tool(s).
#> The model has 4 states.
#> The final distribution is: 446 Susceptible, 4 Exposed, 3 Infected, and 9547 Recovered.

plot(model_seirconn)


# Adding the flu
flu <- virus("Flu", .9, 1 / 7, prevalence = 0.001, as_proportion = TRUE)
add_virus(model_seirconn, flu)

#' # Running and printing
run(model_seirconn, ndays = 100, seed = 1912)
#> _________________________________________________________________________
#> Running the model...
#> ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| done.
model_seirconn
#> ________________________________________________________________________________
#> Susceptible-Exposed-Infected-Removed (SEIR) (connected)
#> It features 10000 agents, 2 virus(es), and 0 tool(s).
#> The model has 4 states.
#> The final distribution is: 0 Susceptible, 0 Exposed, 0 Infected, and 10000 Recovered.

plot(model_seirconn)