In our previous sessions we have reviewed how compartmental models can be used to describe infectious diseases. We have also examined how to specify rates of transition, its relation with time distributions and the how we interpret simple modelling output. During this first practical we will first see how a simple cohort model is coded, and will also examine testing the basic assumptions of the model.
1. A simple cohort model
Remember the cohort model we have studied, where we start with an initial population of infected individuals and we allow a transition into recovery. Let us see what are the basic building blocks of that model.
1.1 Running the cohort model
We have coded a simple cohort model with compartments I and R, initial conditions for those staes and also have defined the transition parameter gamma to reflect recovery rate.
Now let’s run the model and see some output:
Task: Using the code above explore running the same model but now imagine a scenario where the mean infectious period in our cohort is 10 days instead of two days. Can you explain why the plot looks different?