Some questions I ask myself when reading random posts with grand and important claims on any subject:
Where is this from? Who originally wrote it? Is this text’s origin really a random Facebook post, from a pseudonymous author with a cartoon profile picture and no claim of any serious credentials in the subject at hand? (Whether epidemiology or anything else)
Regardless of the merits of the text’s post (which I do not claim to be able to judge) all evidence has to be analysed for context as well as content. Simple “common sense” claims (with a couple of big words to impress non-epidemiologists like me) are made to debunk the models: where is the evidence rather than rhetoric, even some basic citations, and/or examples of or links to counter-modelling? The post doesn’t even link to the original model files from Imperial that they’re claiming to critique.
It’s perfectly _possible_ that the claims made in this Facebook post are correct, but it doesn’t mean anyone should take this post (and its conclusions) remotely seriously without asking some very robust questions of it.
Where is this from? Who originally wrote it? Is this text’s origin really a random Facebook post, from a pseudonymous author with a cartoon profile picture and no claim of any serious credentials in the subject at hand? (Whether epidemiology or anything else)
Regardless of the merits of the text’s post (which I do not claim to be able to judge) all evidence has to be analysed for context as well as content. Simple “common sense” claims (with a couple of big words to impress non-epidemiologists like me) are made to debunk the models: where is the evidence rather than rhetoric, even some basic citations, and/or examples of or links to counter-modelling? The post doesn’t even link to the original model files from Imperial that they’re claiming to critique.
It’s perfectly _possible_ that the claims made in this Facebook post are correct, but it doesn’t mean anyone should take this post (and its conclusions) remotely seriously without asking some very robust questions of it.