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by savara 2235 days ago
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.

1 comments

I have another view really. Which is reading a paper analyzing pandemic overshoot. The authors covered a half dozen models. From very simple ones built on a simple differential equations to complex ones that factored in network effects. My take away is actual models[1] in this space tend to be robust.

The Imperial College Model is a complex model designed to answer subtle questions about the spread and containment of an epidemic. But there is nothing subtle about COVID19. The model predicts catastrophe unless you turn all the knobs to contain it to 11 and do it now.

The model is validated by real experience. Italy, New York both blew up. And elsewhere half hearted measures merely slowed the virus down, not stop it.

The true the deniers can't escape is. If what's been thrown at the pandemic is unnecessary. Then if so, why hasn't the pandemic just collapsed?

[1] As opposed to models that fit a prior defined curve to data. Those are shit.

> The model is validated by real experience. Italy, New York both blew up.

Do you know where the first clusters in New York where?

Because in Northern Italy, and especially around Bergamo, hospitals and then nursing care homes turned into infection centers, and with the population there so skewed with the most vulnerable (along with imperfect knowledge on the pathology) it was easy for the virus to kill them.

In fact most of the initial clusters were in hospitals, and negligence turned Alzano Lombardo in a nice spreading place.

Would a model tuned on what we know now, taking into account different infection routes and places, work the same way? I don't know, but it is a question worth asking even if in the end the model proves to be absolutely correct.