Author Topic: COVID-19 Data Model Updated Daily  (Read 22710 times)

Beasho

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Re: COVID-19 Data Model Updated Daily
« Reply #300 on: May 27, 2020, 01:44:09 PM »
Deaths in the United States below 1,000 per day for the last 3 days running.  This is good news.

At one point I suggested that the susceptability to Covid-19 was a function of 1) Comorbidity 2) Age (maybe) and 3) Bad Luck Genes

This woman calculates item #3 to be equal to just 20%.  Doing calculations on the isolated US Roosevelt and the Diamond Princess cruise ship she suggests that the High R value of 2.4 could / can coexist with a NET R value of just 0.48 if 80% of the population is NOT susceptible or does NOT catch Covid-19 in the first place. 

Interesting theory.  If true the NET R = 0.48 means that Covid-19 will go extinct on its own.  That the people who were susceptible caught it and caught it quickly and now it has flashed through the dry underbrush like a quick burning forest fire. 

Good New - YES!  Wishful Thinking - YES!  But at least she supports the hypothesis with numbers.

https://youtu.be/sTFOsQfDFi8

2nd Picture shows declining worldwide deaths.  This is beyond a flattened curve it is declining.
« Last Edit: May 27, 2020, 01:59:47 PM by Beasho »

all~wet

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Re: COVID-19 Data Model Updated Daily
« Reply #301 on: May 27, 2020, 05:04:43 PM »
That is good news. Thanks for posting.

I wonder if the above is true- plus herd immunity will make the estimated 18 mo wait for vaccine somewhat of a moot point? Or at least the prospect of a second wave in the fall not critically severe. One can only hope.

Chan

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Re: COVID-19 Data Model Updated Daily
« Reply #302 on: May 27, 2020, 05:30:59 PM »
80% are resistant but there is no evidence to support that 80% are resistant?

Beasho

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Re: COVID-19 Data Model Updated Daily
« Reply #303 on: May 27, 2020, 07:58:37 PM »
80% are resistant but there is no evidence to support that 80% are resistant?

The evidence comes from the USS Roosevelt and the Cruise ship.  The theory is that there was no hiding from the virus.  The ships were perfect petri dishes and therefore everyone was assumed to be exposed. 

We have since heard about old people that have "just caught the disease sitting at home."  Makes almost no sense unless this thing does have a VERY high R factor (transmissability) but only to those susceptible.  Similar observation on Washington state where they had it long before people were distancing or wearing masks yet the virus didn't go bonkers.

Another example was the person who died on February 6th diagnosed with Corona virus (much later) in Santa Clara, California.  This person was the first to die by 3 weeks from the assumed first in Washington state.  Again the virus did not go crazy and California only went into Shelter in Place on March 17th. 

Chan

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Re: COVID-19 Data Model Updated Daily
« Reply #304 on: May 27, 2020, 10:36:12 PM »
80% asymptomatic (still infected and contagious) not resistant (immune), correct?

Beasho

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Re: COVID-19 Data Model Updated Daily
« Reply #305 on: May 28, 2020, 06:00:34 AM »
80% asymptomatic (still infected and contagious) not resistant (immune), correct?

I wrestle with the term "Asymptomatic."  If you were completely Asymptomatic then you show no signs of the virus.  But the virus requires you to EMIT the virus or it doesn't spread.  Maybe the emission comes through like breathing or singing.  Otherwise a completely Asymptomatic carrier would be death for the virus. 

What Anne Marie Knott is suggesting is 80% of people do not engage with the virus.  The  virus can not employ the person to make more virus.  Therefore yes they are immune, indifferent and the virus bounces like water off a ducks back.  They can't catch it, they can't spread it.  Biologically this would be because the organism, people, have seen this virus before and our immune system or most peoples doesn't allow Covid-19 to replicate.

Tom

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Re: COVID-19 Data Model Updated Daily
« Reply #306 on: May 28, 2020, 10:45:37 AM »
Coincidentally, I just finished reading another survey that coincides with the two talked about in the video.

In one cruise-ship coronavirus outbreak, more than 80% of people who tested positive for COVID-19 did not show any symptoms of the disease, according to a new paper published in the journal Thorax.

https://www.msn.com/en-us/news/us/up-to-80-of-covid-19-infections-are-asymptomatic-a-new-case-report-says/ar-BB14GB3y

Tom

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Re: COVID-19 Data Model Updated Daily
« Reply #307 on: May 28, 2020, 11:08:17 AM »

So here's what I'd like to know. If 80% are asymptomatic when exposed to CV19, what happens to the 20% that are symptomatic?

Some die, some get so sick they need ICU treatment but survive, and some get sick but recover fairly quickly without being really that sick. I'd like to know the percentage of the survivors that don't get that sick and what are they doing right.

The large portion of those that die have underlying conditions. In the US, 11% of the countryís cases have occurred in long-term care facilities and deaths related to Covid-19 in these facilities account for 43% of the countryís pandemic fatalities.

Beasho

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Re: COVID-19 Data Model Updated Daily
« Reply #308 on: May 28, 2020, 04:32:24 PM »
In one cruise-ship coronavirus outbreak, more than 80% of people who tested positive for COVID-19 did not show any symptoms of the disease, according to a new paper published in the journal Thorax.

https://www.msn.com/en-us/news/us/up-to-80-of-covid-19-infections-are-asymptomatic-a-new-case-report-says/ar-BB14GB3y

If you apply Ann Marie Knott's logic to the Cruise Ship she would assume 100% of people were exposed.  So the Symptomatic infection rate was 24 / 217 or just 11%.   Meaning 90%+ were asymptomatic to the point of NOT EVEN TESTING POSITIVE.   The sub-text supports this when 10 Cabin Mates have tested negative living with People that were Positive.   Was it a "False Negative" or a human that couldn't contract Corona Virus???  They just assumed it was a false negative because

"Their cabin mate had it so they must have it."  Was this a BAD ASSUMPTION?
« Last Edit: May 28, 2020, 05:14:29 PM by Beasho »

PonoBill

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Re: COVID-19 Data Model Updated Daily
« Reply #309 on: May 28, 2020, 05:30:57 PM »

"Their cabin mate had it so they must have it."  Was this a BAD ASSUMPTION?

I don't know if it's a bad assumption, but it certainly IS an assumption, and therefore the validity of the conclusions are based entirely on the validity of the assumption. And yes, it's probably nonsense.

A virus has to have a number of fortuitous things happen in order to successfully infect a cell. First, it has to make it from one human to another, carried in some protective environment. If it gets too dry, too hot, too cold, or just hangs around a bit too long it will die--to whatever degree something that isn't alive can die. Then it has to make it's way to a susceptible area, has to attach to the cell wall somehow, and then it has to get through the cell membrane. While this is happening it has to not trigger an immune response when there are too few infected cells to successfully overwhelm the defense. If you just get a few successful viruses taking over the reproductive machinery and cranking out copies, the immune system has time to react and kills the cells and viruses.

Remember that these are not living things, struggling to reproduce, trying different strategies to slip through defenses--they have all the directive power of ping pong balls. They can evolve quickly while they are infecting a large population, but only in the random sense of inaccurate copies being made that have some difference that doesn't make them incapable of reproducing. The most likely direction of mutation is toward less virulence since hosts dying is not a positive outcome for virus selection.

In other words, the stars need to align even if you're in a petri dish of an environment. 100 percent infection is kind of nonsensical. If you've ever played with actual Petri dishes full of agar nutrient, infecting them with bacteria, you see that even literally in a Petri dish infections are generally spotty--and there's nothing defending the agar or trying to kill the bacteria.

That's a long way to say that she doesn't know what she's writing about. What she's doing is just math, and the outcome is inherently based on the assumptions.

Saying that people are asymptomatic is just a simplification--it means people who test positive but are not noticeably sick at some subjective level. It could simply be that the majority of the people who get infected simply get a small enough initial infection that their immune system responds effectively. It's fairly clear that healthcare people who get infected often have moderate to severe course of COVID. That could be simply a difference in the viral load. People with compromised immune systems can be infected with a small amount of virus and still have it become severe simply because their immune response is ineffective.

While you're looking at all this data, recognize that it's being manipulated constantly and inconsistently. There's reasonable evidence that contrary to the often-related story that deaths are being over-reported because hospitals make more money with COVID patients than pneumonia patients, in fact, the reporting criteria varies from state to state, and there's some convincing evidence that deaths are under-reported in the USA by as much as 30 percent.

In short, it's a fucking mess. I almost would say there's no one to blame for that, though every politician is busy pointing at someone else. We didn't know what we didn't know two months ago, and we are still feeling our way around. The Federal response has been horrifically bad, and Trump has demonstrated that he has the comprehension of a poorly raised toddler. But I have no idea what success would have looked like. And I haven't really heard anyone else sound like they know either.
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Beasho

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Re: COVID-19 Data Model Updated Daily
« Reply #310 on: May 28, 2020, 05:35:16 PM »
In one cruise-ship coronavirus outbreak, more than 80% of people who tested positive for COVID-19 did not show any symptoms of the disease, according to a new paper published in the journal Thorax.

https://www.msn.com/en-us/news/us/up-to-80-of-covid-19-infections-are-asymptomatic-a-new-case-report-says/ar-BB14GB3y

Applying Ann Marie Knott's logic to this additional cruise ship shows just 53% Resistance Rate.  This is significantly LOWER than the 80% of the other 2 ships but provides more evidence that there is a natural resistance.  Especially when Cabin Mates do NOT infect each other.

Natural Resistance defined as extremely Asymptomatic, Don't even register as having the disease or as Pono suggests above their body just chewed up the virus.  Natural resistance is clear when it doesn't kill children.  This means the organism has seen the virus or it's kin before.   
« Last Edit: May 28, 2020, 06:29:53 PM by Beasho »

Beasho

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Re: COVID-19 Data Model Updated Daily
« Reply #311 on: May 28, 2020, 05:50:07 PM »

"Their cabin mate had it so they must have it."  Was this a BAD ASSUMPTION?

Remember that these are not living things, struggling to reproduce, trying different strategies to slip through defenses--they have all the directive power of ping pong balls. They can evolve quickly while they are infecting a large population, but only in the random sense of inaccurate copies being made that have some difference that doesn't make them incapable of reproducing. The most likely direction of mutation is toward less virulence since hosts dying is not a positive outcome for virus selection.

In other words, the stars need to align even if you're in a petri dish of an environment. 100 percent infection is kind of nonsensical. If you've ever played with actual Petri dishes full of agar nutrient, infecting them with bacteria, you see that even literally in a Petri dish infections are generally spotty--and there's nothing defending the agar or trying to kill the bacteria.

That's a long way to say that she doesn't know what she's writing about. What she's doing is just math, and the outcome is inherently based on the assumptions.

Saying that people are asymptomatic is just a simplification--it means people who test positive but are not noticeably sick at some subjective level. It could simply be that the majority of the people who get infected simply get a small enough initial infection that their immune system responds effectively. . . .

Agreed! 

Where I will push back is to say that this IS an exercise in mathematics.  You have to start somewhere.  Without math nothing is quantified and it is just one person yelling louder than another. 

Biology, cells, DNA, viruses, organisms and just accumulations of matter "trying" to replicate.   Statistically some aggregations work better than others.  I remember the statistic (probably from Dawkins) that the favorable mutation rate is 1 / 1 billion.  Every other attempt erodes the chances of replication.  The vast majority of mutations likely make the virus extinct.  Someone once observed that we, our cells, may just be aggregated collections of formerly hostile things that eventually worked their way into our reproductive gamete and then became part of the team. 

But I digress.  My hat is off to people like Ann Marie Knott who's math at attempts to explain the balance between a high R (~ 2.4) and the fact that whole countries are not dying at a 6% rate (US Average) or 14% rate (Italian Average where they probably tested people right before they died).  The agenda being driven by 1) Politicians and 2) the Media is horrific.   I agree it is mostly BS but if you hunt through the turds there has to be some good corn somewhere.

PS: I did appreciate your statistic about the average lifespan of a person in a nursing home.  I would like to find a solid benchmark for that metric when ~ 40% of the deaths are coming from that environment.   
« Last Edit: May 28, 2020, 06:04:22 PM by Beasho »

PonoBill

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Re: COVID-19 Data Model Updated Daily
« Reply #312 on: May 28, 2020, 07:45:37 PM »
Okay, I watched the video. Not convincing--in fact it's a good demonstration of the difference between working to convince people that your idea is right, and taking a scientific approach to an idea (hypothesis). She leads right off with data selected to prove her points. She claims seasonal flu deaths are higher this year which demonstrates that social distancing is not a factor in reducing the R0 of COVID. It's a critical piece of her argument, because if the R0 of COVID has been reduced by the preventive measures then she simply has nothing to talk about.

A. It's not true, and B. Flu deaths are highly variable year to year. 2016-2017 was much worse than this year, and 2018-2019 was marginally worse. The actual number of flu deaths for 2020 won't be known for months, but the trend looks like less than 30,000. 2016-2017 was 65,000. 2018-2019 was 34,000. The year to year variation depends on which strain was dominant, how effective the vaccine was, and how many people got vaccinated.

The "cruise ship as a perfect petri dish" hypothesis I've already written about. Certainly, some useful data can be gleaned from those occurrences, but not if you start out with unsupported and untested assumptions. Note that in the case of the Argentinian cruise ship in the Thorax paper, 128 out of 217 people on board in close quarters with the infection spreading for a month tested positive. It's not feasible to calculate an R0 for that because contact was ubiquitous. And inferring that the people who did not get infected were "resistant" is just wishful thinking. Even super-shedders don't infect everyone around them, there are so many potential factors that it's almost random. But between 5 and 20% of Americans get the flu every year, and we take no special efforts to stop the spread of the flu other than vaccination, which is at about 40%. That low rate isn't some magical resistance. It's well known that getting the flu multiple years in a row is not only possible but common. The biggest concern about COVID vaccine is that it might not generate a lasting immunity. There's no evidence of a useful immunity to common colds, which are mainly coronavirus.

I do think that exposure to other coronaviruses may confer some kind of immunity even if it's not evident with colds. Young kids are certainly steeped in those. Any kid under ten always looks like a snot factory to me. There may well be a substantial immunity factor circulating in the general population, someday we'll probably know. But now it's just a guess.

Every factor she used in the video was edged to support her assertions. That's fine when you're lawyering, but not when you're analyzing, and certainly not when you're making claims that could affect public health.

Her presentation states upfront she is not an epidemiologist. In other words, her opinion is of no more value than my opinion.
« Last Edit: May 28, 2020, 08:34:05 PM by PonoBill »
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Bean

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Re: COVID-19 Data Model Updated Daily
« Reply #313 on: May 28, 2020, 08:03:39 PM »
And, itís dated 2018.  Complete lack of attention to detail.  Uff..

SUPJorge

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Re: COVID-19 Data Model Updated Daily
« Reply #314 on: May 29, 2020, 08:25:23 AM »
I watched the video yesterday, and saw many of the same flaws, and had many of the same reservations, that Pono has expressed. I write separately only to emphasize that I see it as tremendously lacking any scientific humility, and, indeed, reckless, for the good professor to extrapolate from these interesting observations such forceful recommendations that affect the public health.
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