Georgia ChinCOVID Deaths

As of this writing, Georgia reports 2,642 ChinCOVID deaths. 1,182 of those were in long-term care facilities.

44.7%

I think we’ve identified the primary morbidity indicator. Jeez; Georgia wasn’t even one of the states that made the homicidal call to require nursing homes take in ChinCOVID patients. Having spoken to Georgia nurses who’ve worked in nursing homes over the years, I’m willing to place the blame on the administrators.

Amusingly, the Journal constipation, like other muddia outlets, is spinning the “surge” in “new” cases.

Georgia just reported 1,800 new COVID-19 cases on Saturday, the highest number the state has reported in a single day since the pandemic started.

 

The Georgia Department of Public Health on Saturday reported 1,800 new cases of COVID-19, bringing the statewide total to 63,809.

Not quite. GA DPH actually reported 89 new cases on Saturday (preliminary). The other 1,711 were old cases just now being reported. Judging by the changing graph, some of those cases may go back to as early as May 11. Not all the labs use electronic reporting, so there can be rather long lag times before DPH hears about cases; that’s why DPH calls the recent numbers “preliminary.” But implying that there were 1,800 new cases in a single day is much scarier.

If some of those “new” cases are as old as they appear, the folks could have recovered by the time they were reported. If you’ll look at DPH’s “Cumulative Cases” graph, you should note there is no huge surge; the cases were spread over so many days that the curve remains linear until it begins flattening out on June 18.

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Early ChinCOVID

I’ve thought for months that SARS-CoV-2 was already widespread long before the lockdowns began, making them destructively pointless. And I’ve collected a fair bit of data to support that, including a case in Washington in December. Well, here’s another data point.

Coronavirus was in northern Italy in December, officials reveal after studying wastewater
SARS-Cov-2 RNA (ribonucleic acid) was found in samples collected in Milan and Turin on Dec. 18, 2019, and in Bologna on Jan. 29, 2020.

Detectable levels of RNA in wastewater indicate a lot of infected people, not just one or two. Community transmission was in full swing in Milan by 12/18/2019.

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Yet Another Early-COVID Datapoint

I’ve thought that SARS-CoV-2 was circulating widely long before people realized it; among other things, thing making the lockdowns pointless. Barn doors, horses; you know the drill. I collected quite a few bits of data to support that hypothesis, including confirmed community spread in Washington state back in December 2019 (before China even announced it).

Now we have this Harvard study suggesting it was becoming widespread in China last summer.

The global COVID-19 pandemic was originally linked to a zoonotic spillover event in Wuhan’s Huanan Seafood Market in November or December of 2019. However, recent evidence suggests that the virus may have already been circulating at the time of the outbreak. Here we use previously validated data streams – satellite imagery of hospital parking lots and Baidu search queries of disease related terms – to investigate this possibility. We observe an upward trend in hospital traffic and search volume beginning in late Summer and early Fall 2019. While queries of the respiratory symptom “cough” show seasonal fluctuations coinciding with yearly influenza seasons, “diarrhea” is a more COVID-19 specific symptom and only shows an association with the current epidemic. The increase of both signals precede the documented start of the COVID-19 pandemic in December, highlighting the value of novel digital sources for surveillance of emerging pathogens.

It’s purely statistical, and doesn’t prove anything, and China denies it. Call it confirmation bias, but it is consistent with all the other things I found.

It would certainly explain why 5.9% of the tested population in Georgia is already positive for SARS-CoV-2 antibodies.

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IHME Model: Declining into utter bullshit

I’m now checking the IHME Georgia COVID-19 model just for giggles. These dishonest scumbuckets are getting further and further from reality. And I’m not even talking about their projections.

IHME currently claims that Georgia saw 965 confirmed infections on June 4, 2020. Confirmed; not model projection.

Georgia DPH says…

89

So from which stinking orifice did IHME pull an additional imaginary 876 cases? Cases that the state agency that gathers and reports this data doesn’t know about?

Just for scale, while IHME is claiming 965 cases that day, Georgia reports that its peak new cases day was April 20, with 950.

As for deaths, IHME is still holding deaths in reserve to falsely maintain a fake curve. IHME claims 2,084 had died by June 3, while the state says 2,159. While that might seem optimistic on IHME’s part, you have to remember that they’ll maliciously report the extra deaths on a later day to make it look like lots of people are still dying. For instance…

Daily deaths, June 3
IHME: 29
GA DPH (the source of the real data): 9

Georgia has not had 29 daily deaths since May 12. And it’s been dropping since. It was declining then.

The IHME model is fraudulent. If it isn’t deliberate as I think, they need to show the source of their alleged data.

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Georgia: No Post-Lockdown COVID-19 Surge

As of 6/2/2020, 5:49:29 PM, Georgia has recorded 48,207 cases of COVID-19 positive tests. And the new cases graph is showing an impressive post-lockdown surge. So why does my post title say the opposite?

Because GA DPH is finally showing separate tallies for viral (active infection) and antibody (post-infection/recovered) tests. 5,395 of the positives were antibody tests. Antibody testing started after the lockdown ended. And that matters because…

To test positive for SARS-CoV-2 antibodies, one must be exposed to the virus, be infected enough to stimulate an immune response, begin producing the appropriate antibodies, and produce enough to be detectable. The entire process can take weeks. That means any positive antibody test represents someone who was infected before the lockdown ended. They’re simply reporting those as new, post-lockdown cases. But in reality, they have no idea when they really occurred (as opposed to finding out about them).

DPH is still graphing viral and antibody testing together. I wish the idiots would separate those out. But a SWAG at the numbers strongly suggests that nearly the entire post-lockdown bump was really antibody-positives.

There was no post-lockdown surge in new cases; it was a surge in reporting, as predicted. The lockdown was pointless from a public health perspective. Kemp locked down Georgia three months after community transmission had already started in the US (despite CDC claims that it was late-January/early-February).

Another interesting point about Georgia’s antibody testing: 5.9% of those tested were positive. Remember; those were people who’d never had any symptoms to speak of, or they would have had viral testing before. COVID-19 has spread across the entire state; viral testing showed cases in every county. Georgia’s population is 10,617,423. Extrapolating, it’s very likely 5.9% of the population would be antibody-positive.

626,428

Georgia has reported 2,102 COVID-19 deaths (never mind for now that we know that number is inflated). That gives us a COVID-19 mortality rate of 0.335%. One-third of one percent. One-tenth of the 3.4% WHO claimed. The vast majority of whom were elderly and/or infirm (and many of those wouldn’t have happened if some states hadn’t decided nursing homes full of the elderly and/or infirm were a good place to stick the infected). But the powers that-be-locked down the entire younger working and student population, crippling the economy for — hopefully only — years.

Here are some more numbers to play with: You’ve heard that over 108,000 have died of COVID-19 in the US. Do you know how many the CDC actually has ICD-10 coded as COVID-19?

86,495.

Yeah, the other 21,000 may have had (or once had) SARS-CoV-2, but that wasn’t what killed them. It was little things like murder, or surgical complications.

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COVID-19: January? TRY to keep up.

The CDC now says SARS-CoV-2 may have been spreading slowly in the US in late January.

The first U.S. cases of nontravel–related COVID-19 were confirmed on February 26 and 28, 2020, suggesting that community transmission was occurring by late February.

This is — among other reasons — is why I do not consider the CDC to be a good source for data. Aside from the fact that nation-wide outbreaks occurred that were too widespread and early to be consistent with a mere late January slow spread, we know that there were nontravel-related illnesses well before that.

  • Ohio: Yes, Ohio, far from Washington. Antibody testing found a case dating as early as January 7. Patients in five counties spread across the state.
  • Washington: Two days after Christmas last year; December 27. Nontravel. That’s when she went symptomatic. Exposure had to be a week or two before that, meaning it was spreading mid-December.

Yes, we know that SARS-CoV-2 was widespread in the US by late last year. Three months before the gov noticed, and decided to use it as an excuse for a totalitarian police state.

Do try to keep up, CDC. Here’s a collection of links to case studies indicating extensive — and mostly harmless — exposure long before the lockdowns.

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My COVID-19 prediction a month later

On April 23, I made a prediction: that Georgia would not see a post-lockdown surge in COVID-19 cases. You can follow that link for my full reasoning, but the short form is that I’d seen indicators that the virus was already widespread before the lockdown ever started.

By May 12, I saw some preliminary indicators that also seemed to support my view; to wit, we did not see a decline in the rate of daily infections which one would expect if the lockdown slowed exposures.

If we were going to see a new, post-lockdown surge, I thought it would start to appear approximately two weeks later, based on a roughly 14 day incubation period. The lockdown was lifted on May 1. I waited a little more than two weeks to give the state’s data time to catch up with local reporting. How did I do?

From that, you might think that my prediction of no new uptick was a complete failure. But wait.

As of this writing, that data is useless for confirming or denying my prediction. Georgia went and made some changes.

First, after the lockdown ended the state began offering COVID-19 screening to anyone. Previously, it was only available for those displaying symptoms. Unless they can report whether post-lockdown positives were symptomatic or not, we don’t know if we’re seeing something other than what we would have if testing had always been available regardless of symptoms.

Second, and far more serious… that graph no longer reports just SARS-CoV-2 testing. It now includes post-lockdown antibody screening. That is, people who never even knew they “had” COVID-19, but had been exposed enough to develop an immune response. And since, not being sick, they don’t know what days the “cases” developed, they seem to be reporting an antibody positive on the day of the test. A person might have been exposed all the way back in January, but it’s reported as happening after the lockdown lifted.

The uptick could be asymptomatic cases we’d never have seen before, because the state wasn’t looking for asymptomatic cases before the reopening. It could be antibody positives. We don’t know how much of which.

The state now says they’ll separate viral and antibody positives and report them separately. Until that happens, my prediction remains untestable, damnit. But the deaths-per-day graph may be another proxy. As yet, that does not appear to show an uptick; the 7-day average curve still looks like a classic epidemic curve. The state also reports that COVID-19 hospitalizations are “down 34% since May 1st.”

Hopefully they’ll sort out that data soon.

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IHME Model May Not Be Fraud, Exactly, After All

I had a discussion with a reporter who had done a story claiming that there were 32 COVID-19 deaths, and 610 new cases, “in a span of 24 hours in Georgia.”

Since the Georgia COVID-19 Dashboard reported 2 new deaths and 6 new cases (as of 5/13/2020, 1:25:00 PM), I was a little curious where she got her numbers.

It turns out she was just looking at how much the “Confirmed COVID-19 Cases” and “Deaths” total numbers at the top of the page incremented, and apparently assumed all those cases happened in the previous 24 hours. I explained that the increment actually includes cases from different days. Due to delays in testing and reporting by counties and labs, it can be weeks before a case that popped up on 4/27 finally appears on the Dashboard. In fact, I picked 4/27, because yesterday that date did pick up some new cases, making the new peak day (previously the peak day was 4/20).

While older dates are fairly stable now, the numbers for the past two or three weeks can be fluid.

But then it hit me: I’ve called the IHME model fraudulent because they are clearly generating new peaks by lumping days worth of data together and reporting them as occurring on the same day… just like this reporter did.

The reporter is being sloppy, and gives the impression those cases/deaths occurred in that 24 hour period. That’s the kind of reporting that panicked the nation into an unwarranted house arrest. Great for clickbait, bad for informing people.

For IHME — if this is what they’re doing — it’s laziness and incompetence that’s totally irresponsible in an allegedly scientific endeavour.

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Elephant Repellent

Bob walked down the driveway on his way to check the mail, and was hit with a horrifically noxious odor. He glanced around for the dead whatever, and saw neighbor Tom with a garden sprayer carefully applying a repugnant something to his lawn.

“What the hell are you spraying, Tom?” he shouted. “That shit reeks!”

Tom straightened up, smiling. “It’s elephant repellent. Those suckers are hell on lawns.”

“Elephant repellent! Are you nuts? This is Georgia; we don’t have elephants except in zoos.”

Tom beamed proudly. “See? It works.”


I’m sure you’ve heard that, or some variant before. But now you’re living it.

IHME told us we all going to die if we didn’t “social distance” and go into house arrest. When the real world didn’t match the predictions (and never did), they said, “See? It works.”

Let’s take Georgia for example. DPH conveniently graphs cases for us.

This is what the statewide cases look like, and they’ve even overlaid the graph with lines indicating when large gatherings were banned and when we went into lockdown. If social distancing and lockdowns “worked” we would expect to see discontinuities in the trend line at those dates.

We don’t see the “expected” discontinuities. In fact, if you look closely, what you do see is:

  1. Once the epidemic kicked in we had a sharp rise until March 19.
  2. At March 20, we see the trend begin to slow slightly. That’s days before the large gathering ban.
  3. From March 20 to April 11 — that’s through the gathering ban (March 23) and the lockdown (April 2), the trend is darned near linear.

This is an “ideal” model of an epidemic, based on typical spread of any epidemic.

Does that look familiar? If the lockdown et al “worked,” our trend curve should have topped out early, then run more less flat for an extended period of time. Instead…

We peaked and declined just like any other epidemic.

There is a final test of whether the draconian measures “worked.” If the lockdown was making a noticeable difference, then approximately two weeks (SARS-CoV-2 incubation period runs around 3-14 days) after it ended in Georgia, we should see a significant uptick in new cases, as people “start” getting exposed again.

So far there’s no sign of a an uptick, but while it could have started showing, it probably won’t for a few more days. And then reporting will have to catch up.

As I’ve said before, I don’t think we’ll see the uptick, for the same reason we didn’t see the “expected” discontinuities is daily cases: COVID-19 was already widespread long before the “Oh my god, we’re all gonna die” reactions.” As the Diamond Princess and Roosevelt case studies showed, along with random COVID-19 virus and antigen testing, the disease is widespread, and almost no one knows they had it.

Our glorious leaders sold us elephant repellent.

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A Prediction: “Social Distancing” Was Pointless

Note on updates: As more supporting data for my theory comes in, I continue to update this post. You may wish to bookmark it so you have a convenient reference.

Last update 7/222/2020.


Or so I’ve been maintaining. I based that on the Diamond Princess case where 17.1% of the ship population tested positive, but more than half were asymptomatic. Only 7 people died, 1.1% of the cases.

Back when Worldometer was still reporting mild vs. serious/critical cases numbers, only about 5% were serious. (Added: They’re still reporting it on the world page: 3% “Serious or Critical”.)

On April 22, there were 717,008 active US cases, but only 58,173 hospitalizations (8.1% of active cases), and 15,341 in ICU (2.1%). For the vast majority of people it’s no big deal.* Apparently most of those who test positive are asymptomatic (see Diamond Princess) or have the equivalent of a mild cold.

I also noted how quickly known/tested cases were popping up well away from known, large COVID-19 clusters.

To me, all that implied that the virus was already widespread well before the first known cases. Before lockdowns started.

I have some data to support that, now that researchers are doing antibody testing (checking to see if a person was exposed and developed an immune reaction).

  • Massachusetts: 30% of people with no symptoms tested positive. Admittedly, it was a small sample: 200.
  • Santa Clara County, California: Between 2.5% and 4.2%. “These prevalence estimates represent a range between 48,000 and 81,000 people infected in Santa Clara County by early April, 50 (to) 85-fold more than the number of confirmed cases.” They sampled more than 3,000 people.
  • Los Angeles County: 4.1%, “suggesting the rate of infection may be 40 times higher than the number of confirmed cases.” 863 samples.
  • And then there’s New York state. They tested around 3,000 people in 19 counties. 13.9%.
  • Added, 4/26/2020: Miami-Dade: 6% test positive for antibodies; “about 165,000 estimated infections”.

Show of hands: Who believes that all those people went through the roughly 4-5 week process of contracting COVID-19, getting “sick” (asymptomatic or mild), developing antibodies, and got better all since lockdowns started? New York only locked down March 20.

I strongly suspect that the lockdowns did not even “flatten the curve.” They happened too late.

Fortunately, there’s a way to test whether or not I’m correct. Georgia’s Governor Kemp is lifting most lockdown restrictions effective tomorrow. If I am wrong, and the curve was flattened, then in about two weeks — call it May 8 — the state should see a large surge in new cases and hospitalizations. (The delay is the incubation period.)

If I am correct, then we may see a minor bump in a continuing downward trend. Watch here. You can ridicule me and say, “I toldja so,” or congratulate me, as the case may be.


Results: And the winner is… No one. Georgia changed testing and reporting methods, so you can no longer tell how many new daily cases there are.


More supporting data:

Added: One more data point; USS Theodore Roosevelt. The Navy tested 100% of the crew. A few tests are pending, but of the 4,938 completed:

  • 4,098 negative
  • 840 positive
  • 9 sailors had been hospitalized
  • 1 sailor in ICU
  • 1 death

17% tested positive (hey, like Diamond Princess), and 1% of the infected needed hospitalization. 0.1% died. Although I’ll note that active duty Navy personnel are younger and healthier, in general, than the large number of retirees (i.e.- more vulnerable due to age) on the Diamond Princess, so fewer deaths on the Roosevelt are unsurprising.

Added, 5/1/2020: New data point supporting my theory: No COVID-19 Spike from Wisconsin’s In-Person Voting

Added, 5/1/2020: And another. That’s out of 890 workers so far. More than 40% of the workforce at Tyson Foods pork-processing plant in Indiana has tested positive for coronavirus, NBC News reports.

Added, 5/16/2010: Yet another data point supporting my theory that SARS-CoV-2 was already widespread much earlier than has been generally recognized.

Antibody testing places earliest Ohio coronavirus case in early January
The earliest coronavirus cases in Ohio now date back to January, indicating COVID-19 might have been in the state and spreading here earlier than initially thought.

Six people have reported feeling ill in January – as early as Jan. 7 – according to Ohio Department of Health data released Sunday. Few details about the patients were available Monday.

That’s two weeks earlier than what had been believed to be the first US case on January 21, and more than eight weeks prior to what had been thought to be Ohio’s first case.

Data point, 5/28/2020: Half the population may already have significant resistance to COVID-19, even if not exposed. “Importantly, we detected SARS-CoV-2−reactive CD4 + T cells in ~40-60% of unexposed individuals, suggesting cross-reactive T cell recognition between circulating ‘common cold’ coronaviruses and SARS-CoV-2.”

This doesn’t surprise me a bit. SARS-CoV-2 is just another coronavirus. Corona viruses are responsible, along with rhinoviruses, for the common cold. This would go far in explaining why most people testing positive for COVID-19 are asymptomatic (or very mild cases), while a few go bad quickly. The ones that go bad may be in the half or so that don’t already have these T cells.

Data point, 5/28/2020: COVID-19 apparently in the US in December 2019: A woman got sick 2 days after Christmas (meaning she was exposed a week or two prior). Classic COVID-19 symptoms, but no one had even heard of it yet. She hadn’t traveled. Months later, a COVID-19 antibody test was positive. This indicates the virus was already spreading in the US in mid-December last year.

Added, 6/19/2020: And the hits just keep coming:
Coronavirus was in northern Italy in December, officials reveal after studying wastewater
SARS-Cov-2 RNA (ribonucleic acid) was found in samples collected in Milan and Turin on Dec. 18, 2019, and in Bologna on Jan. 29, 2020.

Added, 6/23/2020: More than 8.7 million Americans with COVID-19 went undiagnosed in March, study says

Now, new research says the number of COVID-19 cases in March may have been 80 times greater than what original estimates revealed, amounting to more than 8.7 million new cases in the U.S. that health officials and the public never knew existed.

The researchers blame testing issues, high false-negative rates and asymptomatic spreaders for the “under-counting of the true prevalence of SARS-CoV-2,” according to the study.

The only surprise to me is that it was that much more widespread than even I estimated back in March. Admittedly, I didn’t find out until later that we had December 2019 and early January 2020 cases, already spread across the country. I expect to learn of more as antibody testing expands, and more old waste water samples are tested.

Datapoint, 6/25/202: Worldometer reports 2,487,638 total US cases, but…

US health officials believe 20 million Americans have had the coronavirus
U.S. officials believe as many as 20 million Americans have contracted the coronavirus, suggesting millions had the virus and never knew it.
[…]
Twenty million infections would mean about 6% of the nation’s 331 million people have been infected, leaving a majority of the population still susceptible to the virus.

I think that estimate is way too low. In April, New York state antibody testing showed 13.9% positive; a rate more than twice as high as what the feds are claiming now, which would have extrapolated to 2,703,550 cases in that state alone, two months ago. About the same time a small Massachusetts study found 30%. Currently, Georgia — with a much lower known infection rate than those states — is running a mere 5.9%.

Datapoint, 7/22/2020: By April 1, New York City had over a half a million people with ChinCOVID antibodies. Statewide, they only knew of 85,050 cases.


* Yes, I know it’s really a big deal for that comparatively small number of vulnerable folks whose cases do go bad. Those vulnerable people should minimize human contact, just as they should in flu season. For the exact same reason.

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