Covid “Fudge Factor” – A map of Covid data corruption and approach that worked
maximumtruth.substack.com
Covid “Fudge Factor” – A map of Covid data corruption and approach that worked
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Re: Covid “Fudge Factor” – A map of Covid data corruption and approach that worked
#2Sweden, which didn't lock down, also in the green.
Re: Covid “Fudge Factor” – A map of Covid data corruption and approach that worked
#3I would prefer to see the maps by postal code or at least somehow shaded by relative population density. Showing a given country - again for me - feels deceiving. That is, it's a social virus and more or less localized. For example, poor urban areas fared worse than rich suburb ones.
I'm glad to see someone getting into the details. Finally. But I still think the inequities of the pandemic - at least in the USA - are lost when using a national average. We need to drill down further still. We need to ask, what if the poor fared as well as the middle and up? But also, flip it so we understand a true worst case scenario.
Re: Covid “Fudge Factor” – A map of Covid data corruption and approach that worked
#4It's interesting, I do have trouble using excess deaths and attributing it to covid though. I was in Honduras in the ultra poor mountain region in intibuca and the people there said the entire town got covid, but there was only one death. It's was a small town, but the area had well over 200 people. What did happen was that the government literally cut off access to the nearest city where people could get food, supplies, and medicine.and there are many life-threatening illnesses that can be addressed with cheap medication. In the major cities, they made it so one person could leave a household during a week to get supplies, but I have to think that lockdown and decreased access to healthcare and necessities had severe impacts, especially when populations are more active.
Re: Covid “Fudge Factor” – A map of Covid data corruption and approach that worked
#5Interesting analysis, though he mentions early on a huge issue with the analysis:
> It does come with one major caveat: Because it counts ALL deaths, it cannot on its own disentangle deaths caused by Covid itself, impacts from the lockdowns themselves, impacts from vaccines, or unrelated death trends.
Especially as time goes on, and we see the effects of missed cancer screenings, economic destruction, increased obesity, etc, excess mortality will be almost entirely a measure of side effects of the pandemic response.
Re: Covid “Fudge Factor” – A map of Covid data corruption and approach that worked
#6What a sad thing for my username to line up with...
Re: Covid “Fudge Factor” – A map of Covid data corruption and approach that worked
#7I'm not at all convinced excess deaths is a good measure of Covid-19 deaths.
Re: Covid “Fudge Factor” – A map of Covid data corruption and approach that worked
#8Averaging out people dying to "days lost per life"?
Re: Covid “Fudge Factor” – A map of Covid data corruption and approach that worked
#9It's interesting, I do have trouble using excess deaths and attributing it to covid though. I was in Honduras in the ultra poor mountain region in intibuca and the people there said the entire town got covid, but there was only one death. It's was a small town, but the area had well over 200 people. What did happen was that the government literally cut off access to the nearest city where people could get food, suppl…
I always thought that this was a feature of "excess death" analysis! It's the combined effect of the pandemic, not just the disease itself.
Re: Covid “Fudge Factor” – A map of Covid data corruption and approach that worked
#10What I know from the Netherlands, at least from the numbers of hospitalisations, is that for the longest time we counted the number of people that had covid while being treated in hospital. This in contrast with most countries that counted the number of people in hospital, because of covid.