Two contrasting approaches to predicting (guessing) the outcome of an epidemic are 1) projecting data from similar situations observed in the past; and 2) modelling from varying degrees of first principles. Models must match reality for any reasonable usefulness, but are often extremely sensitive to intitial (unknown) conditions and the slightest variation in input parameters.
Here are both approaches, in broad outline, to generate boundaries around expected outcome.
NB1: Code in R (requires population and death or case time series)
NB: My thesis “Mathematical modelling of inherent susceptibility to fatal diseases” has some relevance, but not to epidemic modelling.Continue reading Modelling an epidemic