Susceptible Exposed Infected Recovered model (SEIR)
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.
Value
The
ModelSEIRfunction returns a 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(),
ModelMeaslesMixing(),
ModelMeaslesMixingRiskQuarantine(),
ModelMeaslesSchool(),
ModelSEIRCONN(),
ModelSEIRD(),
ModelSEIRDCONN(),
ModelSEIRMixing(),
ModelSEIRMixingQuarantine(),
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.
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")
