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SIR model

Usage

ModelSIR(name, prevalence, transmission_rate, 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.

recovery_rate

Numeric scalar between 0 and 1. Rate of recovery_rate from virus.

Value

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.

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)