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About Toofarfromthesea

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  1. Equally important is adequate study of whether the dog will give false positives for people who had the infection but recovered. That was the problem with the S. Korean "re-infection" issue.
  2. Um, WHAT, is a pretty good write-up? Did you mean to include a link? I do that all the time. Email my cyber-security daughter about an article I've read that she would find interesting and then forget to paste the link.
  3. If you are going to cite an article it would be nice if you included a link so we could evaluate the source for ourselves. Because without that this is just blah blah blah with no details, no idea who is making the claim or why, what it is based on, etc. The very epitome of context-less "information" - besides either you or the article reporting something as fact which clearly is opinion, i.e., the motivations of the pharma companies. Even if vaccine trials bobble the stock price, something asserted but not demonstrated, trials are expensive to run, and the payoff is not running the running of the trials it is coming to market with an effective vaccine. A pharma company that is just going through the motions and wasting corporate assets to do what you or the article call 'show' trials for a short-term stock bump would be killed by their investors, most of whom are very sophisticated institutional money managers who have research departments who follow this kind of thing closely. So I'd love to have a link.
  4. Here is an optimistic report on something we have been discussing. There have been concerns about the possibility of getting reinfected after recovery - and the ominous implications that would have for both post-infection immunity and the likelihood of an effective vaccine. Turns out that the "re-infections" were actually false positives caused by the inability of the test to distinguish between live and dead versions of the genetic sequence being tested for. That is terrific news, if it holds up. https://www.livescience.com/coronavirus-reinfections-were-false-positives.html
  5. For the record, Gus doesn't fully understand how the forum software works and nothing shown in that "quote" from me was actually written by me. It is an easy mistake for a newby to make and I'm not upset at all of Gus, but I want the record clear.
  6. Not only was it over-simplified, it was made by the same agency, WHO, that told us in mid-January that there was no evidence of human to human transmission.
  7. Right, it was in the first paragraph and was highlighted in their tweet. But lower down in their article and completely missing from their tweet was the real truth, there is NOT ENOUGH evidence. No evidence is not the same as not enough evidence. And they got called on it and retracted the misleading tweet.
  8. In your own link, in the first paragraph they say the same thing they said in their tweet: "There is currently no evidence that people who have recovered from COVID-19 and have antibodies are protected from a second infection."
  9. REALLY? Nothing I have said is an opinion - I am citing facts. And providing links. On the specific point of the uselessness of a model that tells you in 30 days you will need a minimum of 185,000 beds when it turns out in retrospect that 2000 were enough. I understand having a margin of safety but that is ridiculous.
  10. Yup, I stood in a line like that back when I was a little kid (age 64, now). The vaccine was administered on sugar cubes, as I recall, although that might have been a different occasion, since my recollections are hazy. Whether people get the vaccine or not will depend, in part, on its level of effectiveness. If they are right and this virus mutates much slower than the flu virus we could have a vaccine with 80%+ effectiveness and I think most people will get it. If they are wrong about the mutation rate and the effective rate is more like the 50% effectiveness of the flu vaccine, many won't.
  11. Stop with the gobbledygook already. Nothing you are saying is remotely relevant to the points I am making. A ridiculous model which has been a prime motivator of resource misallocations is a part of the process that should be discarded. Wildly overestimating the problem does nothing to solve the problem - it becomes PART OF the problem. You can mouth all the platitudes you want but that doesn't make them relevant or helpful. The more you try to save face the deeper the hole you are digging.
  12. The actual quote of what WHO actually said was: ""There is currently no evidence that people who have recovered from #COVID19 and have antibodies are protected from a second infection."" But they quickly took it down, and replaced it with: "Earlier today we tweeted about a new WHO scientific brief on "immunity passports". The thread caused some concern & we would like to clarify: We expect that most people who are infected with #COVID19 will develop an antibody response that will provide some level of protection.' A very different kettle of fish. And a good reminder that if possible we should go to the actual source, rather than letting the MSM filter it for you. There is a big difference between a claim that there is "not enough" evidence and a claim that there is "no evidence". But you shouldn't believe me, either. Here is the Twitter thread: https://twitter.com/i/status/1254160937805926405 and if you scroll down about 4 tweets you'll see their own record of the original immunity passport thread, which they had deleted. Showing what they actually said, as I described above.
  13. Yes, but completely irrelevant to the point that the models give garbage results that being used to make decisions about resource allocations. Imagine the effort and anxiety when you are told you will need a minimum of 185,000 hospital beds within 30 days. And how much of that was wasted when it turned out that you only actually needed 2,000. And actually, the count of how many hospitalizations occurred is a far more definite number than things like infections, mortality, and recoveries. Added: certainly the number of hospitalizations during the subsequent 30 days will be different. But no rational person would use that model to predict how many.
  14. It has to do with how we measure life expectancy and average age at death. Actuarial science 101. OT warning When we casually talk about life expectancy we generally mean at birth, but then it changes every year of life. At every age there is a mortality risk of death, mortality rate, before reaching the next age. Life expectancy is based on a computation incorporating all of those mortality rates, from the age at which you are measuring it to the end of the mortality table (the table ends at an age where everyone is assumed to have died, frequently 120) It is a little easier to think of it as expected age at death, because each year that you dodge death, your expected age at death goes up. A 70 year old has a later expected age at death than a 19 year old because the 19 year old hasn't faced and dodged mortality for 51 years already like the 70 year old. Assuming that underlying mortality rates stay constant, IF the 19 year old survives to 70 THEN his expected age at death would be the same as a 70 year old's because he now IS a 70 year old. But a certain number of 19 year olds won't make 70. To oversimplify it a bit, the 19 year olds that make it to 70 will have the same average age at death as our hypothetical 70 year old, but the deaths between 19 and 69 reduce that average. The life expectancy for a 19 year old may be (making these numbers up, since I don't have a mortality table handy, but it could be computed exactly) 60, while the life expectancy for a 70 year old might be 11. Giving the 19 year old an expected age at death of 79 and the 70 year old an expected age at death of 81 (I'm using the word expected in the statistical sense of average). The 2 years difference represents all of the death risk the 19 year old was subject to and avoided while getting to 70. It is like a rachet. Each year you survive, you expected age at death rachets up, a bit. And all of this depends on choosing an appropriate mortality table. Constructing and choosing appropriate mortality tables is what actuaries do. In getting my certification as an actuary I had to learn how to construct a mortality table. And that is way more than you wanted to know, but let this be a lesson to you. Always be careful about asking for an explanation when there is an actuary turned mat teacher around. LOL Anyone whose read this far deserves an actuary joke. Do you know the difference between a legitimate actuary and a Mafia actuary? The legit actuary can tell you how many people will die. The Mafia actuary can tell you their names.
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