COVID-19 Deaths Plummet: Media & Governments Exacerbating Hype on Increased Case Numbers to Keep the Fear Going – WFFJ-TV News –

July 17, 2020


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COVID-19 Deaths Plummet


Media & Governments Exacerbating Hype on Increased Case Numbers to Keep the Fear Going


By:  David Deschesne

Fort Fairfield Journal, July 15, 2020


   Death rates for the dreaded and over-hyped theatrical media superstar virus, COVID-19 have been declining continuously over the past two months.  With an average death rate of 2,421 per day in mid-April (which may itself be inflated due to over-counting mandates by the CDC), the death rate has dropped nearly 75% by the first week of July.  However, amidst all this good news, the mainstream theatrical news media - and governments, alike - have shifted the public’s attention to an ambiguous increase in “positive” COVID-19 cases.  While there has been a slight increase in reported positive cases in the U.S. overall, a wide angle view shows how all the hype over those new cases is unnecessarily hyperbolic - unless, of course, the establishment wants to continue the COVID-19 hysteria in the general public.

   In the opening salvo of the virus around 60,000 to 100,000 COVID-19 tests were being processed daily in the U.S., compared to over 600,000 tests per day by July - a six to ten times increase in total tests administered (see blue bars in chart) and peaking to over 822,000 total tests in a single day on July 10.  By capturing a wider sample base, there will obviously be more total positive cases for a virus that has ubiquitous spread throughout the country by now.  But that increased sample size shouldn’t necessarily be construed as a gigantic “spike” in new infections, as the media and state governments are attempting to sell to the public.  In fact, the recent “spike” was a less than  three percent rise in daily positive cases from the low point in mid-June.  

   In order to bring the daily testing numbers with differing sample sizes on par with each other, they should be converted into Positive Cases per 1,000 tests.  This way, a smaller sample set taken at the beginning of the pandemic can be more objectively judged and compared against a much larger sample set taken several months later.  When adjusted to Positive cases per 1,000 overall tests, it has been found that the so-called “spike” is nothing more than a small pebble in the middle of a moderately bumpy road (see yellow line near bottom of the chart).

   Looking at Positive case numbers without adjusting for the total sample size can be a bit misleading.  For example, on March 27 there were 19,043 positive cases of COVID-19 identified in the U.S. on that day.  Nearly a month later, on April 26, that day logged 27,412 positive cases of COVID-19.  That does look like an increase in daily cases, until you consider the sample size. 

   On March 27, the 19,043 positive cases came from a total sample size of 103,461 tests processed on that day.  The April 26 positive case number of 27,412 came from double the sample size - or 206,550 total tests reported out on that day.  So, adjusting the positive cases to per 1,000 people tested, March 27 had 184 Positive Cases per Thousand (PC/T) while April 26 had actually dropped to 133 PC/T.  By failing to adjust positive cases to the thousand people tested, the media and governments are able to create the illusion of COVID-19 case increases with steadily and precipitously increasing sample sizes.  Taken in their proper context as positive cases per thousand, however, it can be shown that positive cases have dropped substantially since the outbreak in the U.S. began.

   In the middle of March, with around 17,000 to 45,000 COVID-19 tests administered, the PC/T averaged around 174 per day.  That number increased slightly to 181 by the end of March and peaked to 211 in the first week of April.  The daily average PC/T then began a steady decline by the week to 191; 144; 116; 90; 64; 56; 53; 45 and finally bottoming out to a daily average of 44 Positive Cases per Thousand by the middle week of June.  There has been a slight up-tick in that daily average since then - the so-called “spike” as illustrated by the media - to 51; 68 and 75 PC/T by the first week of July.  While it is a slight increase from the 44 PC/T trough of mid-June, 75 PC/T is still a 64% decline from the peak in positive cases during the first week of April.  But, there may be some reasonable explanations for this increase that have nothing to do with new infections of the virus.

   For example, there are reports from some patients in Arizona that when they are counted as COVID-19 positive they are told to come back in fourteen days to be retested.  If they test positive again - and they probably will even if they recover, because the dead virus RNA articles may still be in them - that second test is counted as another positive case.  When asked why they’re double counting the same person as two or more cases, one nurse explained, “we are counting positive tests, not individuals.”   Also, nationwide, if a person tests positive, then goes for a second opinion and gets another test at another testing facility that also comes out positive, that gets counted as two positive tests even though it was for the same person.   This purposeful skewing of the numbers isn’t just happening in the U.S., it’s going on worldwide.

  The UK health department admitted that if a person had both nasal and saliva tests taken, and were positive, both tests were counted as separate positive cases for the same person.

   This whole exercise in numbers could be merely academic since the dominant testing platform is the PCR test which was hastily built and rushed into service with the US Food and Drug Administration suspending nearly all of its testing and verification procedures for allowing new tests to market.

    A positive PCR test doesn’t really have a whole lot of meaning.  While it may be able to identify if a person has the specific RNA gene sequence for COVID-19 in their body, it is unable to describe the actual viral load (how much of the virus is present) in a given person’s body, or how it may present in a given person’s own particular health situation. 

   Think of a PCR test like trying to determine if there is a dog in the woods by rapidly flying over it in an aircraft.  While you may be able to determine with some degree of accuracy whether there is a dog in the woods, you cannot with this testing procedure know the dog’s temperament, whether it’s hungry, if it is a stray or domesticated, or if it will bite you if you approach it.  That is the essence of the PCR test when it comes to COVID-19: it simply does not provide enough meaningful data to make serious decisions about a person’s health, or the economy-at-large.

   These untested, unverified for accuracy PCR tests have been the ongoing basis for shutting down the world economy under the guise of “slowing the spread” of COVID-19.  But how much spread was there, how bad is the virus presenting and by how much is it being slowed in shuttering the global economy.  That’s hard to say since politicians, not scientists, are in charge of setting the standards for how the data is collected and processed.

   The way a PCR test works is by taking a sample of potential virus particles too small to be detected by themselves and “amplifying” their numbers to a level the test kit can perceive.  This is accomplished by cyclically duplicating the RNA so the fluorescing molecules will give off enough light to be detected by the testing apparatus.  Think of it like an antenna amplifier being used to boost weak radio or TV signals.  However, the more you amplify the desired signal, the more you amplify the noise.  So, there is a necessary cutoff in amplification cycles in the PCR test.

   Some test manufacturers have a cut-off of 36 cycles before determining a negative; some go as high as 45.  There are dozens of subjective guidelines for determining a “positive” COVID-19 result and they vary across as many manufacturers.  It has also been pointed out by Professor Steven Bustin that the efficiency of converting the duplicate RNA strands in subsequent cycling is rarely better than 50%.

  The FDA has no established guidelines and there is no uniformity in what is essentially a wild-west, anything-goes form of testing protocol.  Again, these are the tests being used to count the “positive” infections for COVID-19 and are the primary driver of state and business shutdowns nationwide - and ultimately, worldwide.

   According to David Crowe’s research on the PCR tests, posted on, “If the process is efficient, a large number of cycles could detect as little as three molecules of [COVID-19] RNA.  If there are people who had such a small amount of virus in their body, causing no health problems, they would still test positive.  If there are only parts of viruses present, or defective virus particles, that are not infectious, they would still produce positive results.  The tests do not prove that pathogenic, replicable virus is present.”

   In this sense, the PCR test can be fooled into a positive designation by detecting fragments of COVID-19 RNA particles from a past infection where the person has already recovered.  The South Korea CDC discovered this problem in mid-April when they retested people who were known to have previously had COVID-19, then recovered and no longer had symptoms.  260 of those people retested “positive” for COVID-19.  This was due to the test still able to detect fragments of the destroyed coronavirus still in their body even though it was no longer viable, effective, or transmissible.

   This could help to explain why the asymptomatic rate (test positive for the virus, but never show any symptoms) is as high as 35% for COVID-19.  Some people may have had the infection in the past, recovered from it, then as part of routine hospital testing, now test positive for it but show no symptoms.  The test in these cases could simply be detecting the debilitated viral particles and not an actual, bona fide full-blown infection.  The PCR test is simply not designed to provide that level of detailed information.

      Relying on the PCR test to confirm actual infection of COVID-19 is fraught with squirreliness. Late last month, Professional U.S. golfer, Cameron Champ withdrew from the PGA Tour’s Traveler’s Championship after testing positive for COVID-19.  Five days later he tested negative three times and had no symptoms before or after the suspiciously positive test.

   In another example, reported Shawn Smith had tested positive for COVID-19 while being processed for surgery.  Four hours later, seeking a second opinion, he tested negative at a drive-thru testing center.

   With the dozens of testing kits available, with no real scientific evaluation for the validity and veracity of their results, many people are beginning to question the accuracy of these hastily-built test kits; some of which are portable, “instant result” setups which allegedly can provide a diagnosis while you wait.

   But, most tests are sent to laboratories to have their samples analyzed.  However, those labs are bottlenecking the results due to the overwhelming volume of samples presented to them on a daily basis.

   On March 31, 2020 The Atlantic reported how more than 57,400 Californians still had pending tests that hadn’t yet been processed.  That was way back in the early days of the pandemic when the U.S. was only conducting around 100,000 tests per day.  Fast forward to July - just three months later  with the U.S. now presenting over 600,000 tests per day to a system that couldn’t handle 100,000 tests per day.  The weak points will have to fail and quality control and accuracy will suffer under these extraordinary conditions.

   Considering this issue with the labs, some of the cases in the “spike” in COVID-19 cases may in fact be samples that are up to two weeks old, finally making their way through the lab analysis process, so we may be counting cases in this current “spike” that had actually occurred in mid-June; coincidentally when the positive COVID-19 case rate was at its lowest.  If we were able to reassign the positive tests to the dates they were actually taken, the so-called “spike” may have some of its numbers shifted backward in time to mid-June, thus leveling off the “spike” to a flat line on the graph.  Or, these people could just be double-counted.  But, this level of information is either not being kept track of, or is being deliberately discarded amidst a system that is wholly incapable of effectively, efficiently and accurately processing tests at the volume being asked of it.

   While the PCR test results continue to be ambiguous, bordering on meaningless, a much more objective measure of the disease’s efficacy can be measured in the daily death rate.

   Deaths attributed to COVID-19 have declined precipitously since their peak in mid-April. It’s possible that peak was attributed in part to the CDC guidelines redefining the parameters more loosely on how a death gets classified as COVID-19 - thus making the mid-April death rate peak to be much greater than it really was.  Texas recently adopted subjective methods of determining COVID-19 infections with no PCR test, or other scientific diagnosis required.  This has set up a scenario where they will be purposefully over-counting their cases and deaths as New York and New Jersey did earlier in the outbreak. This purposeful, artificial inflation of the cases is once again causing the data to be artificially skewed, for political reasons, higher than it would have been otherwise.

  Skewed numbers aside, there are several reasons that can be attributed to this decline to what appears to be a more normal, reasonable level.  They are:


- 1.)  Doctors are learning more about the disease and how to treat it.  Many drugs and techniques used in other disease treatments are being found to be effective at treating the symptoms of COVID-19 until the person’s body is able to recover from it;


- 2.) The virus is simply burning itself out.  Initially, the virus found a population of “easy targets” in the frail, elderly and immune compromised sector of the population.  As those victims succumbed to the virus, the available hosts left over were of better health and better able to defend against the virus. Thus, the virus is succumbing to the Law of Diminishing Returns; and


- 3.)  Doctors have started to count the deaths more objectively.  At the beginning of the viral outbreak in the U.S., the U.S. Centers for Disease Control was suggesting doctors count every death as a COVID-19 death if the person died for any reason at all, but at least tested positive for the viral particles in their body.  There was even a financial incentive by Medicare to provide additional money to hospitals who claimed to have COVID cases -  hospitals that were unable to make any money otherwise, due to shuttering all of their non-COVID services.  Perhaps doctors have started counting the COVID-19 deaths more accurately and objectively than they did initially.  (But, new guidelines in Texas are now skewing the death numbers higher, again, as more people are counted as COVID deaths than have actually succumbed directly to the virus, or even been tested for it.)

   It could be one, or a combination of these three possible reasons that explains the falling COVID-19 death rate in the U.S.  But, the most telling sign that the death rate isn’t as bad as originally touted is for the past two weeks the mainstream theatrical news media has dropped death rates almost entirely from its COVID-19 narrative and is now focusing solely on the ambiguous, subjective and potentially inaccurate “Positive Cases” being generated by a litany of untested and untried, inaccurate and inefficient COVID-19 test kits rushed to market on a whim with little testing, verification or oversight.


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