ELECTION UPDATE 10-26-24

With ten days before the presidential election, the odds listed on Pinnacle.com, one of the world’s largest offshore betting sites, make Trump a 4-7 favorite to win the election, and Harris a 7-4 underdog.  Through most of September, Harris was favored.  Then, in late September and early October, the two were rated even.  Since then, Trump has slowly edged into favorite status.

 

         (I find the large international betting sites to be far more reliable than polls for predicting election results, though some polls are better than others.  With so many polls, it’s hard for a layman like me to distinguish the real polling efforts from the partisan ones designed to shape the results rather than report on them.  Also, even honest pollsters can be incompetent, so even if I were certain which polls were honest, I wouldn’t know which ones were done correctly.  Also, I find betting sites to be just plain more serious.  If they are wrong on the odds, a savvy bettor can take them for a lot of money, so it is safe to assume they at least want the truth and make genuine efforts to figure out what it is.)

 

         In other words, Trump appears likely to win this election.

 

         Because of that, and because of Harris’s steady drift downward, I have been expecting the Democrats to do something different, to change their strategy somehow.

 

         It’s not easy, of course.  Just as Trump is Trump, Harris and Walz are Harris and Walz, and the nature of the candidates are largely baked into the campaigns.  Nevertheless, though no major changes are possible, it is always possible to tweak the campaign slightly, even at this late date.  And I’ve been expecting the Democrats to do that.

 

         For one thing, I think it has been apparent for some time that the physical image of Kamala Harris does her no good.  The earth-tone pantsuits she wears on every occasion effectively turn her into the “Black Hillary,” and that comparison does not help her.  Her handlers have succeeded in getting her to stifle the annoying laugh (something Hillary never did), and that has helped somewhat, but the reminders of Hillary in Kamala’s wardrobe are unmistakable.

 

         Instead, they have apparently decided to double-down on the Trump-is-Hitler theme.  General John Kelly, who was Trump’s Chief of Staff in the White House in 2019, now reports that Trump once said he wished he had some of Hitler’s generals because they were so loyal and obedient.  These are the guys who repeatedly tried to murder Hitler, by the way, but I guess Trump is not expected to know any history.  Also, among students of military history, the German military command was never admired for their unthinking obedience, but rather for their independence and resourcefulness.  But I guess Trump is not expected to know that either.

 

         In any event, the Trump-is-Hitler theme won’t work.  It hasn’t worked and the Democrats have been throwing it at him since 2016.  If this is the best they can come up with to turn the tide, the Democrats may be cooked.  The evidence from polls and betting sites is increasing that Trump will get more votes than Harris in every swing state and may even win non-swing states like Virginia.  The desperation revealed in the return to the Trump-is-Hitler message tends to convince me the Democrats may be out of vote-getting strategies.

 

         Which doesn’t mean Trump will be our next President.

 

         The war over electoral fraud and cheating in the swing states is happening behind the scenes, it is waged differently from state to state, and almost nothing is being reported publicly about it.  Therefore, while I can tell you Trump will get more actual votes than Harris in Georgia and Michigan and Pennsylvania, I have no prediction to make on who will be declared the winner of those states on November 5 or December 2 or January 1 or whenever.

 

         The seven swing states are Arizona, Georgia, Michigan, Nevada, North Carolina, Pennsylvania and Wisconsin.  All except North Carolina ultimately went to Biden in 2020, but none of the Biden states had a declared victor on election night.

 

        As in 2020, the key metric for predicting shenanigans will be the date on which victory is declared for Trump or Harris, either by election officials or a major news organization.  If a state is “called” on November 5, the date of the election, there will likely be little controversy about it.  But once the sun comes up on November 6 with no official results, I personally will suspect the necessary Democratic ballots are being found in order to flip the result to Harris, because that is what happened four years ago.  The earliest any of these swing states were called was three days after the election.  Nevada was not decided until November 24th, with a ruling from the state’s Supreme Court.  And that seems to be what is happening again.

 

          Election officials in Pennsylvania, Michigan, Wisconsin, Arizona and Nevada have already announced that they do not expect to be able to call a winner in the presidential race on election night.  Arizona reports that its Maricopa County will not have results until ten to thirteen days after the election.  (A tip to my betting public:  you can get better than 2-1 on Kamala winning Arizona.  Grab it.) 

 

           The one swing state I know something about is Pennsylvania, and I have no confidence the vote and the counting will be fair.  In fact, like last time, I’m convinced the Democrats in Philadelphia and Delaware County and in a few other places are already working to deliver sufficient fraudulent ballots to win Pennsylvania for Harris.  The Republicans have spent enormous amounts of time and money and effort in very publicly and noisily battling for honest counting on November 5 and beyond, but most of their work has focused on things (like proper dating and sealing of mail-in ballots) that will make no difference.

Copyright2024MichaelKubacki        

PANDEMIC OF THE UNVACCINATED

         

        Back in mid-2021, after the mRNA vaccines had been approved for emergency use, the authorities (including the pharma companies), presented a number of arguments to boost acceptance of these products.  One was the claim that unvaccinated people in hospitals were more likely to die of COVID than vaccinated patients.  A friend recently asked me about this argument, and this was my response. 

         The claim that COVID deaths in hospitals were more likely to be unvaccinated people than vaccinated ones is no longer being made by anybody who has looked at what happened.  Even the pharma companies that are still pushing RNA vaccines seem to have abandoned this bogus claim.

         I remember the vaxxed death rate versus the unvaxxed death rate as part of the “pandemic of the unvaccinated” scare campaign.  This was when Biden and Walensky and Jimmy Kimmel and Rachel Maddow and all the news anchors were telling people that once you got the shot you would never get COVID, and that people like me should be fired from jobs and denied medical care and barred from restaurants and public transit.

 

         I don’t think there was ever a serious study on the death rate issue, and there was certainly nothing that was peer-reviewed.  The claims were mostly official-looking press releases from a hospital or a few hospitals, and they never withstood much scrutiny.  For one thing, the definition of “vaccinated” tended to differ among these varying reports.  Some of the “unvaccinated” COVID victims had actually been vaccinated but were not counted as vaccinated for a number of reasons (too recent, wrong vaccine, etc.).  It seemed clear early on that the death-rate argument was not based in any kind of science since the data supporting the various elements of it was so questionable.

 

         First, the largest number of COVID deaths occurred in 2020 when the virus was most lethal since it had not yet started to mutate.  Because there was not yet a vaccine, all those early deaths were among the unvaccinated.  Were all those people included in the so-called studies?  And if so, doesn’t that skew the results toward the unvaxxed-death side of the equation?

 

         But that’s a minor issue.  The real problem is that we have no idea how many people died of COVID from 2020 to 2023.  We are just now finding that out from studies of the official death data and studies of the autopsies done at the time and filed away without analysis.

 

         As you will recall, the practice was to declare that any death of a person with a “confirmed case” of COVID was a COVID death (in other words, caused by the virus), even if the person displayed no COVID symptoms, was 96 years old, and had congestive heart failure.  This was entirely driven by financial incentives from Medicare and the pharma companies.  Any death that could conceivably be called a COVID death was called a COVID death.

 

         There was almost nothing the public health authorities would not do to inflate the number of COVID deaths so pretty much everyone who died “with COVID” died “of COVID.”  One of the more famous instances occurred when a man who died in a motorcycle crash in Orlando Florida was listed as a COVID death.  A public health officer in Orange County, Dr. Raul Pino, justified the result, stating that one “could actually argue that it could have been the COVID-19 that caused him to crash.”

 

         Then there were the flu deaths, which are counted and reported every year by the CDC.  Here are the official flu death totals from 2018 to 2023:

 

2018-19               27,000

2019-20               25,000

2020-21                    700

2021-22                 4,900

2022-23               21,000

 

Are we really supposed to think old people stopped dying from the flu in the two flu seasons from 2020 to 2022?  Or could it be there were just as many flu deaths, but they were called COVID deaths instead because of the extra money attached?

 

         Now, years later, it will be impossible to unravel all the poor science and outright fraud that went into the designation of COVID deaths.  The only thing we really know is that there were not nearly as many COVID deaths as we were told there were.

 

         The problem of determining how many COVID deaths occurred in hospitals brings with it an additional set of difficulties.  This is because, during the pandemic, anyone admitted to a hospital was required to take a PCR test for COVID whether they showed any symptoms or not.  The hospitals then, following CDC and WHO guidelines, defined a “confirmed case” as a person with a positive test result.  No symptoms were ever required.  Once you were a “confirmed case,” you were a COVID case, and if you died, you were a COVID death.

 

         This was a fundamental error.

 

         The basic mathematical principle, which has been understood for decades, is that a diagnostic test like the PCR should never be used on a population where only a very small percentage of the test subjects have the disease.  In 2021, a letter from the FDA to healthcare providers explained the problem: “As disease prevalence decreases, the percent of test results that are false positives increase.”  But though warned not to test for a disease in a low-prevalence population, the CDC decided to do it anyway.

 

         Here’s the problem.  If 1% of the population tested has the disease, there will be one true positive in every 100 subjects.  So even if your test is 99% COVID-specific (i.e., accurate), it will judge 99 of your 100 subjects correctly and there will be one false positive.  This means that among your 100 people, the test will give you one true positive and one false positive.  Thus, if you test positive for COVID, there is only a 50-50 chance you actually have it.  It’s a coin flip, and the test is worthless, even though it is 99% accurate.

 

         But in fact, PCR tests were quite a bit less reliable than that.  First, the rate of active COVID infection at any one time among the general population was always less than 1% (it was actually about 0.5%).  This could mean there would be fewer than 1 true positive in every 100 hospital admissions.  But even if people entering the hospital were ten times as likely to have COVID as the general population, that would still mean only 5 out of 100 would be true COVID cases.

 

         The real problem is that PCR tests were never close to being as accurate as in the example above.  Instead of being 99% COVID-specific, the CDC found they were only about 70% COVID-specific, meaning they would produce 30% false positives.  If there were 5 true positives and 30 false positives in every 100 hospital admissions, the false positives would be 85% of the total. Whatever the actual numbers were, a large majority of the positive PCR results were false positives and most of the “confirmed cases” in hospitals did NOT have COVID.

 

         The stated justification for this universal testing protocol in hospital admissions was that it would reduce widespread outbreaks in hospitals, though it is hard to see how falsely identifying large numbers of patients as having COVID would have that effect.  But the clear result was there were an enormous number of patients who had no COVID symptoms and did not have COVID, but were deemed to be COVID cases.  And when they died, they became hospital COVID deaths.  Some of them were vaccinated and some of them were not, but none of them died of COVID.

 

         The sum total of all this bad science piled on top of itself is that nobody now has any realistic measure of how many COVID deaths there were in hospitals or anywhere else, or whether most of the people who died of COVID were vaccinated or not. 

Copyright2024MichaelKubacki