@shavixmir saidOf course it does.
Nope. It is not.
I’ve repeated this 10 times or more: the death rate has squat diddley to do with the measures being taken.
Decreasing viral load in the environment through masks or avoiding large gatherings causes the average infection to be caused by a lower viral load, decreasing median severity of infection.
Decreasing the number of infections in a given time decreases the pressure on the healthcare system, allowing better case for those who get sick.
I hardly need to point out that increasing funding of R&D for treatments creates better treatments.
Of course the death rate is influenced by measures taken.
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The post that was quoted here has been removedYou're conflating case fatality rate with infection fatality rate. Not every case is diagnosed. In fact, it's unanimously agreed that most cases are not.
The CFR was up near 5% in April; it's now down under 2.7%, which likely means that it's been ~1% or less if you isolated that past few months.
While 0.1% may be a bit optimistic, that the current here-and-now IFR is ~0.2% seems a reasonable guesstimate.
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The post that was quoted here has been removedSure, deaths are undercounted, but by percentage points. Estimates vary, but I haven't seen anything higher than maybe 30%.
On the other hand, by most accounts, at most 1 in 3 or 1 in 4 infections are diagnosed today. In the Spring, it was probably more like 1 in 20. Some more controversial estimates (like the Stanford study) pegged it at more like 1 in 80.
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@shavixmir saidLooks like I have to step that back.
Nope. It is not.
I’ve repeated this 10 times or more: the death rate has squat diddley to do with the measures being taken.
Both viruses are most deadly for the elderly. The flu kills .83% of infected people above age 65, whereas the coronavirus's death rate is 10.4% for infected people from age 65 to 74, 20.8% for the 75-84 group, and 30.1% for people over 85.
Carry on!
@sh76 saidAnd those early estimates were wildly inaccurate as I showed you many times using reliable data. Early figures were more like 8:1, which not so coincidentally is about what you get by comparing the July serology study I already referenced to official case data.
Sure, deaths are undercounted, but by percentage points. Estimates vary, but I haven't seen anything higher than maybe 30%.
On the other hand, by most accounts, at most 1 in 3 or 1 in 4 infections are diagnosed today. In the Spring, it was probably more like 1 in 20. Some more controversial estimates (like the Stanford study) pegged it at more like 1 in 80.
You have constantly erred in under estimating the IFR and overestimating the number of untested cases.
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@sh76 saidYes. But it’s not the death rate which is influencing measures.
Of course it does.
Decreasing viral load in the environment through masks or avoiding large gatherings causes the average infection to be caused by a lower viral load, decreasing median severity of infection.
Decreasing the number of infections in a given time decreases the pressure on the healthcare system, allowing better case for those who get sick.
I hardly need to ...[text shortened]... r treatments creates better treatments.
Of course the death rate is influenced by measures taken.
Learn to FFing read.
I’m pretty much tired of the lot of you. It’s like talking to a broken record player of moronity.
Edit:
I’m sorry. I shouldn’t have written that in that way.
It’s just so breathtakingly naieve, that to have to argue it is like argueing with flat earthers.
At a certain point you just want to give up, but can’t handle misinformation and misinterpretation at the same time.
Ugh.
@no1marauder saidThe studies you've relied on were those focused on the places that got hit hardest and did the most testing (typically, New York and some areas in Spain), showing the highest IFRs and the lowest case undercounts in the world at that time. These areas with very high population density and strained healthcare systems had worse outcomes than places that did flatten the curve (whether by action or by happenstance of geography).
And those early estimates were wildly inaccurate as I showed you many times using reliable data. Early figures were more like 8:1, which not so coincidentally is about what you get by comparing the July serology study I already referenced to official case data.
You have constantly erred in under estimating the IFR and overestimating the number of untested cases.
Studies from other regions show much lower IFRs and much more dramatic case undercounts.
I really don't have time now, but one day if I get around to it I'll marshal the studies I've relied on and we can go tit for tat on them.
@sh76 saidWe already did.
The studies you've relied on were those focused on the places that got hit hardest and did the most testing (typically, New York and some areas in Spain), showing the highest IFRs and the lowest case undercounts in the world at that time. These areas with very high population density and strained healthcare systems had worse outcomes than places that did flatten the curve (wheth ...[text shortened]... day if I get around to it I'll marshal the studies I've relied on and we can go tit for tat on them.
The July serology study is just more proof that the studies I relied on were right and the "studies" you relied on were wrong.
-Removed-"It's just like the flu" has been a right wing talking point for a long time but as I already pointed out:
". In the last six flu seasons, the CDC’s reported number of actual confirmed flu deaths—that is, counting flu deaths the way we are currently counting deaths from the coronavirus—has ranged from 3,448 to 15,620, which far lower than the numbers commonly repeated by public officials and even public health experts."
https://blogs.scientificamerican.com/observations/comparing-covid-19-deaths-to-flu-deaths-is-like-comparing-apples-to-oranges/
@no1marauder saidI don't know what studies you're referring to, but serology studies underestimate infection prevalence anyway, as not everybody infected needs to develop antibodies to fight off COVID (there is certainly at least some level of cross-immunity from antibodies developed to fight off other coronaviruses) and (especially) because antibody levels seem to fade after as little as six weeks in some people.
We already did.
The July serology study is just more proof that the studies I relied on were right and the "studies" you relied on were wrong.