A basic SIR model with 3 compartments and infection and recovery processes
simulate_SIR_model_ode( S =1000, I =1, R =0, b =0.002, g =1, tstart =0, tfinal =100, dt =0.1)
Arguments
S: : starting value for Susceptible : numeric
I: : starting value for Infected : numeric
R: : starting value for Recovered : numeric
b: : infection rate : numeric
g: : recovery rate : numeric
tstart: : Start time of simulation : numeric
tfinal: : Final time of simulation : numeric
dt: : Time step : numeric
Returns
The function returns the output as a list. The time-series from the simulation is returned as a dataframe saved as list element ts. The ts dataframe has one column per compartment/variable. The first column is time.
Details
The model includes susceptible, infected, and recovered compartments. The two processes that are modeled are infection and recovery.
This code was generated by the modelbuilder R package. The model is implemented as a set of ordinary differential equations using the deSolve package. The following R packages need to be loaded for the function to work: deSolve.
Warning
This function does not perform any error checking. So if you try to do something nonsensical (e.g. have negative values for parameters), the code will likely abort with an error message.
Model Author
Andreas Handel
Model creation date
2020-09-01
Code Author
generated by the modelbuilder R package
Code creation date
2021-07-19
Examples
# To run the simulation with default parameters: result <- simulate_SIR_model_ode()# To choose values other than the standard one, specify them like this: result <- simulate_SIR_model_ode(S =2000,I =2,R =0)# You can display or further process the result, like this: plot(result$ts[,'time'],result$ts[,'S'],xlab='Time',ylab='Numbers',type='l')print(paste('Max number of S: ',max(result$ts[,'S'])))