DSAIDE (version 0.9.6)

simulate_SIRSd_model_stochastic: SIRSd model

Description

A SIRSd model with 3 compartments. Processes are infection, recovery, births deaths and waning immunity.

Usage

simulate_SIRSd_model_stochastic(
  S = 1000,
  I = 1,
  R = 0,
  b = 0.002,
  g = 1,
  w = 1,
  n = 0,
  m = 0,
  tfinal = 100,
  rngseed = 123
)

Value

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.

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

w

: waning immunity rate : numeric

n

: birth rate : numeric

m

: death rate : numeric

tfinal

: Final time of simulation : numeric

rngseed

: set random number seed for reproducibility : numeric

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

Details

The model includes susceptible, infected, and recovered compartments. The processes which are modeled are infection, recovery, natural births and deaths and waning immunity.

This code was generated by the modelbuilder R package. The model is implemented as a set of stochastic equations using the adaptivetau package. The following R packages need to be loaded for the function to work: adpativetau

Examples

 
# To run the simulation with default parameters:  
result <- simulate_SIRSd_model_stochastic() 
# To choose values other than the standard one, specify them like this:  
result <- simulate_SIRSd_model_stochastic(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'])))