This model allows for the simulation of 2 IDs in a single host

simulate_multipathogen_ode(
  S = 1000,
  I1 = 1,
  I2 = 0,
  I12 = 0,
  b1 = 0.001,
  b2 = 0,
  b12 = 0,
  g1 = 1,
  g2 = 1,
  g12 = 1,
  a = 0,
  tmax = 120
)

Arguments

S

: initial number of susceptible hosts : numeric

I1

: initial number of hosts infected with type 1 : numeric

I2

: initial number of hosts infected with type 2 : numeric

I12

: initial number of double infected hosts : numeric

b1

: rate at which type 1 infected hosts transmit : numeric

b2

: rate at which type 2 infected hosts transmit : numeric

b12

: rate at which double infected hosts transmit : numeric

g1

: the rate at which infected type 1 hosts recover : numeric

g2

: the rate at which infected type 2 hosts recover : numeric

g12

: the rate at which double infected hosts recover : numeric

a

: fraction of type 1 infections produced by double infected hosts : numeric

tmax

: maximum simulation time, units of months : numeric

Value

This function returns the simulation result as obtained from a call to the deSolve ode solver.

Details

A compartmental ID model with several states/compartments is simulated as a set of ordinary differential equations. The function returns the output from the odesolver as a matrix, with one column per compartment/variable. The first column is time.

Warning

This function does not perform any error checking. So if you try to do something nonsensical (e.g. any negative values or fractions > 1), the code will likely abort with an error message.

References

See e.g. Keeling and Rohani 2008 for SIR models and the documentation for the deSolve package for details on ODE solvers

See also

The UI of the Shiny app 'Multi-Pathogen Dynamics', which is part of this package, contains more details on the model

Examples

# To run the simulation with default parameters just call the function: result <- simulate_multipathogen_ode() # To choose parameter values other than the standard one, specify them like such: result <- simulate_multipathogen_ode(S = 100, I2 = 10, tmax = 100, b1 = 2.5) # You should then use the simulation result returned from the function, like this: plot(result$ts[,"time"],result$ts[,"I1"], xlab="Time",ylab="Number Infected Type 1",type="l")