Your Dr Fao Chi is a quack. I posted the fact February of last year. Pay attention. I posted in March 2020 that he was funding gain of function research. He was still lying about it this summer.
In point of fact, that is an estimate, not a confirmed count. A few years ago we had a flu with 80,000 deaths. A half year later, that had to be revised down to 61,000 deaths because the estimates had been way too high in the process of the flu season.
Nope. Not a "few aberrations" a year ago here in Colorado, they had to change from counting people deadbwith covid to only people dead from covid after several MEs caught them counting people that should not be counted (one was a dude dead of acute alcoh poisoning with alcohol levels many times the LETHAL limit). When they did the numbers dropped by TWENTY FIVE PERCENT. That's an enormous overcoat. Most other states have not made this change.
This analysis is right out of this report in the Coloradan. It is a good example of how a story can be carefully edited to make it sound worse than it is. First of all, the article was from May, 2020 - very early in the pandemic. Systems were still being developed for gathering and reporting covid deaths. But here is what the original article said:
So the number was corrected, and the current number of 668K reflects the correction done a long time ago.
It is the best estimate we have, and we don't need to know the exact number to understand the seriousness of the pandemic. The high number of deaths is confirmed by other data, such as the overall lifespan and the smallest growing in population in at least 120 years.
Because of the seriousness of the covid, the statistics have been tracked more carefully than they tracked the flu. But all this quibbling about precision in the numbers is just to distract from the fact that even if the numbers were off by 50%, it would still be serious enough to warrant all the attention it is getting.
If you didn't care you would not be so adamant about saying negative things about the vaccine. Those actions speak louder than your protestations to the contrary.
...cherry-picked facts that are not supported by the other articles I cited.
Cherry-picked data can be factual, and still imply conclusions that are not supported by other data. Excluding any data that is not supportive of ones view is that opposite of what a scientist should do. A scientists should actively seek out data contrary data and evaluate it. That's what I do. I come to places like this to get a sense of what contrary theories there are out there and evaluate those theories in light of other data. Sometimes it leads to a reconsideration of my own view, and sometimes I can reconcile that contrary data with what I have already seen. But to just ignore contrary data is the definition of cherry-picking.
This is good advice, but it also means not to exclude data that is contrary to what you believe. Also I would advise people to watch out for appeals to arrogance. For example, when you see a posting that cites an academic or technical paper from a professional journal, and then invites you to conclude what the poster wants you to conclude from it, consider the possibility that fully understanding that paper may be beyond your current training and expertise. When faced with the choice between agreeing with the poster's analysis of the technical article, or admitting that you are not qualified to understand it, the temptation is to give in to your arrogance and refuse to believe that you might not be qualified for understanding that paper. This is why such ploys are often successful. This is the basis behind the children's story, "The Emperor's New Clothes." In that story, the con artist appeals to the arrogance of the emperor and all his advisors to keep them from admitting that they just don't see what others are seemingly able to see. Finally it takes a small child with no pretense of superiority to defend to recognize and admit that the emperor does not have any clothes on. So don't be tricked by con artists who lull you into thinking you must be stupid if you cannot understand a technical journal. If you are not a professional in the field for which the journal was written, just admit to yourself that you may not have the specialized training needed to critically review the paper, and defer to those who do have that skill. That is why you seldom see misinformation based on publications made for the general population because it is easier to bamboozle people with faulty analyses of articles they cannot evaluate.
"This is good advice, but it also means not to exclude data that is contrary to what you believe."
If you read my posting in full you would know that I already to consider contrary data.
Once again we see the appeal to arrogance. The arrogant believe they are just as good as epidemiologists in critically reading and understanding a technical paper on vaccines. The less arrogant will look to trusted people to explain it to them.
Yes, those I trust and who are smarter than me about disease told me it would be good get vaccinated.
The vaccine has not been out long enough to make any final judgement about long term harmful benefits. All scientists are not as pure as the wind driven snow.
They are a lot purer that the sources you seem to prefer.
Ah we watch you lower yourself to insults.
When the left is low on substance, they result to insults.
And besides I have not referred to any source. I mostly ask questions and report observations, which one is not supposed to to to Big Brother.
'trusted people' like who? The epidemiologists who haven't had a clue this entire pandemic?
Do you have some better epidemiologists in mind? If so, tell me who they are.
No trusted people ever said that.
"Assuming the conclusion" fallacy, otherwise known as begging the question.
So you do not object to epidemiologists that you rely on being called clueless.