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Discussion thread V - COVID-19 (new coronavirus)

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so, is it allowed here to speculate about the numbers and probable szenarios ?
"No one knows" for sure, but we still have probability estimates,
some outcomes are more likely. We must do our best to reasonably estimate
the risk
 
the main problem is - if it were so easy (vitamin D) they should already have figured that out.
and we would have heard more about it
(makes sense ?)
 
C : how to explain the higher CFR in Australia in wave 2 and the lower CFR in Europe,USA in wave 2
(compared to wave 2)

D : immunity may wane after 4 months (could also explain why we get a 2nd COVID-wave after 4 months -- if immunity plays a role despite only <10% infected)
how many % are infected in seasonal flu-waves ? 10% ? still it goes down. And immunity wanes , recently it has been recommended to get 2 shots per season for the elderly, Nov+Feb or such
 
I would add to this that it would be nice to keep a thread on known factors in the numbers reported. I only suggest this as an option to help in the future analysis of data, which will be looked at some point (also it is easier to document real time the questions/details on what made up those numbers, rather than dig thru past posts/articles). I think this could also be helpful in the determining of risks for the community.
 
Interesting. I wish they would see how the lack of information fuels distrust of scientists and Drs. I have seen recently some folks have managed to get this data, unfortunately it makes the testing look even worse when they show a CT of 45 vs. a <35. Many are now questioning the positives being posted for this very reason (are we chasing a ghost or non issue or is there a true concern still in play?). I see this also adding a variable to the data analysis of the increasing positive curves that are now not showing an correlating increasing death curve. I'm sure you have seen many of the theories such as the virus has changed/mutated(the term the media uses) to being less deadly, etc. to account for the shift in the curve. I see the test being a huge variable in this data.
 
That is the problem. The factors are both known and unknown. It is a mess. There is no standard method. It is basically comparing apples, oranges, and watermelons. There are several countries where the numbers are just totally ridiculous.
 
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