So there is a general model. It covers all the cases, by not covering the cases. It is usually so general that you don’t see the real complexity of the underlying until you start trying to implement something real.

But as you burrow into the details what happens to the general model in Pathogens and People. Does the general model hold up. Is it a good enough to really simulate the underlying reality. The easy answer is yes and no. As you start digging down into the details you are stuck with so many decisions.

How deep do you dig into a population. You can look at the population as a whole and develop a frequency based approach to modeling the situation. Some fraction of the population is exposed and from this some part of the population becomes infected.

So at one level you see someone who is clear of infections and maybe not contagious.

Then you see someone who is infected and maybe a source for further contagion.

Are you interested in someone who may have been exposed and is not yet contagious, or may be contagious but not exhibiting symptoms.

Maybe the person died of the infection, but is no longer infectious. Is this important to the model?

Maybe the person died of the infection and is infectious.

The life cycle of the disease in exposed persons may be very important at some level, but might be ignored if you are modeling the spread of the a pathogen. But somewhere along the line someone has to get the frequencies to drive the model. How many people are exposed, how many people are infected and how many of those are infectious? There is a lot of investigation to get the frequencies correct. It will be different for each pathogen.

Epidemiology is a vast subject. I approach things a dumb programmer trying to model things I don’t understand. The more I look, the more questions I have.