Quote:
Originally Posted by Hugh
It’s more like (imho) if you wander across a busy A-road with your eyes tight shut, you’d probably get run over,
It’s "possibility" versus "probability" - it’s possible you won’t get hit, but it’s probable you will...
They’re saying if we don’t take the appropriate measures, it’s probable the infection figures will escalate rapidly, based on the information we have at this time - it’s possible they won’t (but unlikely).
Basic Risk Assessment, Management, and Mitigation.
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You’re confusing Risk Assessment and Management with "complete guesswork" - they’re completely different...
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I had a quick look at the SAGE website to see how they generate their predictions and it looks like they use a number of datasets and two models (
linky)
Any modelling is dependent on the likelihood that the incoming data is right and the accuracy of the model. Of course, it only with the benefit of knowledge over time that you will know if the data is correct and only by running your model with previous data that you know your model is correct. The models are constantly being refined but there's always a chance that the model and reality don't match. The big question is by how much.
Using the word 'If' in the statements is scientifically correct as you can never be certain. However, if you run enough different models and datasets and they all point in the same direction, then the qualitative prediction that things are going a certain direction becomes more likely to be correct, the only difference between models is by how much.
See climate change, economic predictions for Brexit,
etc. *runs*