# Issue

*This Content is from Stack Overflow. Question asked by Sprawk48 *

I’m currently working on a two-host epidemiological SI model. That is, a compartmental model with no recovery compartment.

I’m still relatively new to R, but am developing a decent understanding after mostly using MATLAB. However, the thing I am having issues with finding any helpful resources on is how to vary two different input parameters so I can examine them and maybe even 3-D plot these variables or phase plot them to see if the population dies off.

So, more specifically I want to produce results when varying mu between 0 and 1, and alpha between 0 and 1, I could just “plug and play” but I want to be able to show a more dynamic result and think it would be handy to have as a tool in my wheel-house.

Anyway, here is the code I have so far:

```
# Here we will load the required packages for the assignment
library(deSolve)
library(ggplot2)
# Here we the two-host (male & female) SI model
KModel <- function(time, state, params){
with(as.list(c(state, params)),{
N <- SF+IF+SM+IM
dSF <- r*(SF+alpha*IF)-r*N*SF-BFM*(SF*IM)/N
dIF <- (BFM*(SF*IM)/N)-r*N*IF-mu*IF
dSM <- r*(SF+alpha*IF)-r*N*SM-BMF*(SM*IF)/N
dIM <- (BMF*(SM*IF)/N)-r*N*IM-mu*IM
return(list(c(dSF, dIF, dSM, dIM)))
})
}
```

```
# here are the initial parameters
r = 0.2
BFM = 1.2
BMF = 1
mu = 0
alpha = 0
params<-c(r,BFM,BMF,mu,alpha)
initial_state<-c(SF=0.49 ,IF=0.01, SM=0.49,IM=0.01)
times<-0:60
```

```
# Here we use ode() to numerically solve the system
out1<-ode(y=initial_state, times=times, func=KModel, parms=params, method="ode23")
out<-as.data.frame(out1)
plot(out1)
```

So, I think I have a pretty good “skeleton” for solving any single solution for a compartmental model, however Like I mentioned I’d like to be able to vary two of the parameters to examine specific scenarios.

Thanks!

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