In the third part, we demonstrate how to refine a model to include more priors and posteriors. We keep enriching the model (from part 1 and 2) by adding more nodes and building a practical case study. We show that prior information on demographics, age, job category or risk level can impact the chances of getting infected and eventually result in more cases. We also add posterior nodes on the severity and contagiousness of an infected person based on these priors and review how these eventually affect the overall cost of care. This simple yet informative scenario can be used by public health policymakers or healthcare insurance to establish the best vaccination strategies. We explore three vaccination strategies and evaluate their respective impact. This is the third of a three parts demo.