SIR model
Value
The
ModelSIR
function returns a model of class epiworld_model.
Details
The initial_states function allows the user to set the initial state of the model. In particular, the user can specify how many of the non-infected agents have been removed at the beginning of the simulation.
See also
epiworld-methods
Other Models:
ModelDiffNet()
,
ModelMeaslesQuarantine()
,
ModelSEIR()
,
ModelSEIRCONN()
,
ModelSEIRD()
,
ModelSEIRDCONN()
,
ModelSEIRMixing()
,
ModelSIRCONN()
,
ModelSIRD()
,
ModelSIRDCONN()
,
ModelSIRLogit()
,
ModelSIRMixing()
,
ModelSIS()
,
ModelSISD()
,
ModelSURV()
,
epiworld-data
Examples
model_sir <- ModelSIR(name = "COVID-19", prevalence = 0.01,
transmission_rate = 0.9, recovery_rate = 0.1)
# Adding a small world population
agents_smallworld(
model_sir,
n = 1000,
k = 5,
d = FALSE,
p = .01
)
# Running and printing
run(model_sir, ndays = 100, seed = 1912)
#> _________________________________________________________________________
#> Running the model...
#> |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
model_sir
#> ________________________________________________________________________________
#> Susceptible-Infected-Recovered (SIR)
#> It features 1000 agents, 1 virus(es), and 0 tool(s).
#> The model has 3 states.
#> The final distribution is: 0 Susceptible, 3 Infected, and 997 Recovered.
# Plotting
plot(model_sir)