Using a simple $SI$ infection model, I uncover the

overall dynamics of the system and how they depend on the incidence

function. I consider both an epidemic and endemic perspective of the

model, but in both cases, three classes of incidence

functions are identified.

In the epidemic form,

power incidences, where the infective portion $I^p$ has $p\in(0,1)$,

cause unconditional host extinction,

homogeneous incidences have host extinction for certain parameter constellations and

host survival for others, and upper density-dependent incidences

never cause host extinction. The case of non-extinction in upper

density-dependent

incidences extends to the case where a latent period is included.

Using data from experiments with rhanavirus and salamanders,

maximum likelihood estimates are applied to the data.

With these estimates,

I generate the corrected Akaike information criteria, which

reward a low likelihood and punish the use of more parameters.

This generates the Akaike weight, which is used to fit

parameters to the data, and determine which incidence functions

fit the data the best.

From an endemic perspective, I observe

that power incidences cause initial condition dependent host extinction for

some parameter constellations and global stability for others,

homogeneous incidences have host extinction for certain parameter constellations and

host survival for others, and upper density-dependent incidences

never cause host extinction.

The dynamics when the incidence function is homogeneous are deeply explored.

I expand the endemic considerations in the homogeneous case

by adding a predator into the model.

Using persistence theory, I show the conditions for the persistence of each of the

predator, prey, and parasite species. Potential dynamics of the system include parasite mediated

persistence of the predator, survival of the ecosystem at high initial predator levels and

ecosystem collapse at low initial predator levels, persistence of all three species, and much more.