All models are wrong, but some are completely wrong – Royal Statistical Society Data Science Section
▻https://rssdss.design.blog/2020/03/31/all-models-are-wrong-but-some-are-completely-wrong
Last week the Financial Times published the headline ‘Coronavirus may have infected half of UK population’, reporting on a new mathematical model of COVID-19 epidemic progression. The model produced radically different results when the researchers changed the value of a parameter named ρ – the rate of severe disease amongst the infected. The FT chose to run with an inflammatory headline, assuming an extreme value of ρ that most researchers consider highly implausible.
Since its publication, hundreds of scientists have attacked the work, forcing the original authors to state publicly that they were not trying to make a forecast at all. But the damage had already been done: many other media organisations, such as the BBC, had already broadcast the headline [1].
Epidemiologists are making the same mistakes that the climate science community made a decade ago. A series of crises forced climatologists to learn painful lessons on how (not) to communicate with policy-makers and the public.
In 2010 the 4th IPCC report was attacked for containing a single error – a claim that the Himalayan glaciers would likely have completely melted by 2035 (‘Glacier Gate’). Climate denialists and recalcitrant nations such as Russia and Saudi Arabia seized on this error as a way to discredit the entire 3000 page report, which was otherwise irreproachable.
