Economists and data scientists abuse models because they love playing with their toys. And politicians are happy to cherry pick and promote the models which suit their ends !
Here are their weaknesses.
First, the modelling exercise applies a common template to disparate situations. There is clearly great variation in the nature and scale of the infection in diufferent countries, and we can’t use a one-size-fits-all model to suit our convenience !
Second, the modelling exercises rely on filling in gaps in knowledge by inventing numbers, often in immense quantities.
Third, these exercises necessarily assume, almost always without justification, stationarity of the underlying processes
Fourth, in the absence of stationarity, these modelling exercises have no means of accounting for uncertainty and the unknown.
All of these bogus models have a common failing. They begin by considering how you would make a decision if you had complete and perfect knowledge of the world, now and in the future. But very few of the relevant data are known. The solution? Make them all up.
They only offer probabilities that disguised uncertainty , as opposed to actually providing you with more useful information.
Notes from the book, Radical Uncertainty by Mervyn King