Why do you have to make everything political and ruin an important thread? You do this every time. I wish we could get you banned from here. You never have anything important to add - just the same old one-sided nonsense.

There are many who do not find their finding valid for many legitimate reasons.

[Link: wonkette.com]

That website is about as objective as it gets. Congrats on a deep search for facts.

Who cares? Do enough searches and you can either confirm or diss anyone or anything.

They are seasoned doctors. They run seven health care facilities. You can disagree with their opinions but cannot disagree with their experience.

In the end you simply choose to believe what you want to believe, regardless of facts. It’s the nature of mankind.

I see your tongue in cheek but still nominate you for the funny boy statement of the week.

Yes, their personal experience can be disagreed with. The topic at hand is how best to deal with a pandemic caused by a virus with no known treatment or data supporting things like herd immunity. In that case, the experience of being a clinical physician is not as valuable as the experience of being a long-term research epidemiologist who specializes in infectious disease.

While it is true that the Internet has made it incredibly simple for someone to cherry pick data to support their pre-existing bias, that is the precise reason why scrutinizing the sources of that data becomes vitally important in the debate.

"Free Speech" has nothing to do with what you can or cannot pot on Private websites.

If you want to discuss Covid-19 and its effects on our industry, thats great, just keep it civil or the posts will be removed and/or the thread will be closed.

'The Seasoned Doctors' are Unqualified to make statistical assessments.

The video is no longer up, but I got the following statement from this source:

[Link: bakersfieldnow.com]

"In Kern County, we've tested, 5,213 people and we have 340 positive COVID cases. Well that's 6.5 percent of the population. Which would indicate a widespread viral infection similar to the flu," Dr. Erickson said. He continued, "So if you look at California, these numbers are from yesterday, we have 33,865 COVID cases out of a total of 280,900 total tested that's 12 percent of Californian's were positive for COVID."

Dr. Erickson went on to say that the initial projections for the illness showed millions cases of death and called them "woefully inaccurate." He said those results were not materializing.

"Well we have 39.5 million people, if we just take a basic calculation and extrapolate that out, that equates to about 4.7 million cases throughout the state of California. Which means this thing is widespread, that's the good news. We've seen 1,227 deaths in the state of California with a possible incidents or prevalence of 4.7 million. That means you have a 0.03 chance of dying from COVID-19 in the state of California," said Dr. Erickson.
There is statistical assessment is flat out wrong, misleading and frankly dangerous. Why do I know this? My minor in university was statistics. Does this make me a professional statistician, no it doesn't. Does it make me understand statistics better than the average person - yes. Does it make understand statistics better than these doctors, absolutely.

You can't take any sample and presume it represents a general population. That is statistics 101. The sample has to be completely random. The numbers generated from that then can be statistically analyzed and applied to a population with a certain degree of error. Taken a sample from the those who were tested because they displayed symptoms or they were contact with a positive person will be skewed and likely highly skewed to be to higher percentage in the sample than the general population. That is not a hard concept to understand and I have no idea why these Doctors would overlook this.

They go on to use this a basis for their argument that you quarantine the sick not healthy etc. This is dangerous. There are many cases of asymptomatic spread so 'healthy' people could unknowingly spreading the disease.

Statistical pandemic modelling should be left to the experts in that field. It is highly specialized field that most doctors will not be qualified to do regardless to their 'years in the field'.

So no, their data point from a statistical point of view is invalid. Doing some simple math extrapolation and suggesting the CFR for Covid is 0.03 is at best misleading and at its worst downright irresponsible and dangerous. I am not even going to get into the fact that he uses the current death total as basis for his percentage even though there are at least 40,000 active cases who have not had an outcome one way or the other.

If they had taken any statistical course in their undergraduate studies they should have known that postulating these numbers is wrong and misleading. Their real life experience in the field will certainly help them be better doctors but certainly didn't make them experts in statistics or qualified to make macro level recommendations to how a pandemic should be handled.

My statistics 101 teacher made a point that, in his opinion, most of the statistics quoted in medical research papers is seriously flawed for the reasons that you brought up. Another way of expressing this is "confirmation bias".

We could get a much better handle on things if we had proper testing and sampling.

We'd really like to know if there is any significant heard immunity. We cannot measure this by testing only those who present with symptoms.

How do figure into the statistics the millions who have been exposed, have fought it off, and now have some immunity? They also are an invisible pool that would upset models, or am I missing something? They may have experienced the mildest of symptoms or no symptoms at all.

I would like to say let’s leave the modeling for statistical experts, but they are so far off base so often, that I have to ask why their data is more valid than anyone else’s?

As of last week we still are not sure one has immunity after getting the virus. Moreso, those that have little to no symptons still can pass the virus along. With all that the WORLD has done to mitigate the spreading of this virus the death toll keeps rising.

[Link: npr.org]

Well the truth is we are not sure of a lot of things. We seem to selectively be more sure about some things than others. The blood can be tested for signs that you have been exposed to it and have not come down with the virus. If it works like other viruses, there is more than a good chance that there is some immunity there.

Models are only good as the assumptions they are based on. Early on, Covid assumptions had to be very broad as the world knew little of its characteristics. It was doing best estimates based on other coronavirus characteristics. As the knowledge grows, the assumptions are better determined and the models get better.

'so far off base so often' - evidence, compared to what? Or is this just your perception / opinion.

The model most currently referenced (UofWash / IHME model) is getting more and more criticism for being inaccurate.

This newer model is more accurate:

https://covid19-projections.com/



[url=[Link: ibb.co]][img][/img][/url]

May 2 predictions (as stated on Apr 17 (Apr 12 for Michigan), all #'s from John Hopkins, used the above graph for the comparison)


NY - ~25,000 C19proj vs ~21,000 IHME | Actual - 24,796
Mich - ~4,000 C19proj vs ~1,900 IHME | Actual - 3,972
Italy - ~28,000 C19proj vs ~26,000 IHME | Actual - 28,558

C19proj is pretty spot on, where IHME is off especially with NY and Mich.



Currently, the C19proj USA projection is 163,789 deaths by Aug 4, 2020 (Range: 95-282k)

The IHME for the same date is 72,433.

Current death toll 67,954 with a range of deaths per day in the last week ~1,700 to ~2,500. The US will hit the IHME prediction with 3 or 4 days not Aug 4.

The modelers are like weathermen, whether they are right or wrong, whether they are close or miss by a mile, they still have their jobs tomorrow. Meanwhile, their inaccuracy still is taken as gospel and allows policy to be laid down for an entire nation. More data flows in that contradicts them? Just tweak the model. Right or wrong, near or far, it doesn’t seem to matter. The worst case is like a law has been passed as far as the country is concerned. They are the experts. Anyone else is not worth listening to. Anyone seeing things differently at ground level is not an expert and only needs a wonky website article to discredit them and all heads nod in agreement.

So this debate of course is only a debate. We won’t settle it here nor will we know the truth until a year from now or whenever. It’s worth talking about but will not get settled here.

Next question, do we just close down the working class until it’s safe? When is it safe? No one can say for sure until it is in the rear view mirror.

If we are lucky enough to be able to work or have a month or two nest egg, we can easily decide for the rest of the country how long they can’t work. I have lived long enough to believe that 75% of the world lives from paycheck to paycheck. The no work situation can’t go on.

If I want to get snarky, I could point out that at least the essentials are still open, abortion clinics, liquor stores, marijuana sellers. Politicians and prognosticators are still drawing salaries and getting rich off our tax dollars while telling us we cannot work. The state governors definitely know what is best for us. Wait, I shouldn’t be so snarky.

Projection - an estimate or forecast of a future situation or trend based on a study of present ones.

So we should do away with modelling because we don't like the projections it gives? There is documented range or amount of error in these forecasts. Governments have to decide what to do given the information it receives not the epidemiologists / statisticians. The IHME has been used to quote figures to the American public. I don't know what study(s) the US government used to determine their pandemic policies.

There is no easy alternatives in this situation, let more people go back to work = more people will ultimately die. Where that line should be drawn is very difficult to determine with imperfect data and many moving parts.

And that is the problem. You can get opinions to line up on either side of the debate, you can get data to support either side of the debate. In the end, no one will agree on what to do, other than we have just given the government unprecedented power over our daily lives that we will never get back.