> For example, people in the contemporary control group weren’t tested for COVID-19, so it’s possible that some of them actually had mild infections.
How doesn't this completely invalidate the title? If we aren't actually comparing between a group that provably did not have COVID and one that did, we can't possibly draw any conclusions about the effect of having COVID compared to not having it at all.
> What's the issue with simply reversing that metric to show many people are COVID negative?
There are three groups. Positive, negative, and untested. The untested group is the biggest, and you can't call them COVID negative, because there's really no reason. They're not (yet) either positive or negative.
> Consider the countries like Japan that do not actually have excess mortality despite COVID-19. Suppose they just stopped testing for it. You would not be able to tell the difference.
That assumes that testing-dependent interventions (whether contact tracing and quarantines of the exposed, appropriate treatment of systematic infections, etc.) have nothing to do with the absence of excess deaths.
> Could it have something to do with being locked up for the last 6 months or worry about ones future career maybe?
So you're saying the study is so shoddy that they didn't have a control group of people who went through the same lockdowns but didn't get COVID? Otherwise, your comment doesn't make sense.
> They subtract COVID deaths from excess deaths to get the baseline, forgetting that COVID deaths were counted somewhat liberally, and some percentage of non-COVID deaths were counted as COVID deaths if someone was infected close to their time of death.
If COVID deaths were counted liberaly and even after subtracting those inflated numbers you still have excess deaths, then that only further underlines their point that these excess deaths are not COVID-related.
Just because you think the criteria for counting COVID deaths were wrong doesn't make every conclusion based on those numbers incorrect.
> we have real data showing that there are long term effects from getting full blown COVID.
As in, 90% (probably more because asymptomatic people are never tested) of people actually have no symptoms at all and seem to go along fine with it? Or are you talking about something else?
> We can't say for certain that the sample is an exact representation of the general population.
I actually think we can say for certain this is NOT a good representation of the general population. The general population has not been living in close quarters with multiple COVID positive people.
> every person with the flu was labeled as having “Covid”
I got a cold a few weeks ago. Got tested, it wasn't Covid. Where mental gymnastics are needed is in ignoring hospitalization and excess mortality statistics.
> because that's the amount of people who don't show symptoms anyway.
I don't think this is accurate. A large majority of people show no or relatively mild symptoms comparable to a seasonal flu or cold, yes, but that's not the same thing as no symptoms at all for a large majority.
> So, your not arguing that people didn't die from Covid19, just that you think those people weren't expected to live for much longer? The implication being we shouldn't care so much because someone died only a year earlier?
I don't think this is what they're saying. I think the point is that those people's actual times of death weren't far enough from their expected times of death given their preexisting conditions to be able to confidently say that they died of Covid, rather than just having died with it. In other words, that there's a good chance they would have died at the exact same time even without Covid.
>there are still ~6x the number of viruses out there causing colds
The variety of viruses is totally irrelevant to the original question of what are one's odds of having COVID based on having cold symptoms. The only piece of information that matters for that are the aggregate numbers and aggregate numbers from previous years are misleading.
> The variety of viruses is totally irrelevant to the original question of what are one's odds of having COVID based on having cold symptoms. The only piece of information that matters for that are the aggregate numbers and aggregate numbers from previous years are misleading.
It is an essential factor, unless you make the (implausible) assumption that we have essentially eliminated all other respiratory viruses except for SARS-CoV2.
> Otherwise healthy people have died from COVID-19.
I never said they didn't. In fact, I directly acknowledge the healthy cases:
>> To have died of COVID, you had to be on death's door already, or so statistically unlucky as to make your suffering a rounding error.
Sorry if this was too much of a value judgment for you, but I do not consider any respiratory illness with a less than 0.5% death rate to be something which we need to bring the world to a halt over. I do not think that these unlikely deaths, nor the even more unlikely "asymptomatic spread" purportedly part of this virus's nature, can be used as evidence to the contrary without some actual analysis on your part.
>more than 11 million, there have been 13,164 cases throughout the entire pandemic, and 264 deaths
Given covid has proved really infectious but often mild, those numbers just say they have terrible testing. Probably more like 50%+ of the population have had it but not been diagnosed. In the UK they figure 70%+ and we have imperfect testing too.
Deaths are typically calculated as dying within 30 days of a positive test so no testing => no official covid deaths.
How doesn't this completely invalidate the title? If we aren't actually comparing between a group that provably did not have COVID and one that did, we can't possibly draw any conclusions about the effect of having COVID compared to not having it at all.
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