COVID19 CASES AND DEATHS

At-A-Glance…

Cases:

• There are many reports that testing is not accurate, and that PCR testing is not conclusive for disease, and may not be specific to this SARS-CoV-2 coronavirus.

• Positive tests are not necessarily “cases” or “infections”.

• There have been reports of “positive” tests on untested persons, and positive results on submitted blank tests.

• Asymptomatic people who test positive should not be called cases, especially given that PCR testing has so many false positive and negatives.

Deaths:

• Coronavirus deaths have been counted haphazardly and incorrectly.

• CDC changed the death certificate guidelines for COVID19.

• Dying WITH COVID19 is not the same as dying FROM COVID 19 but often those who die of other causes in the hospital (and even outside the hospital) but tested COVID19 positive are being labeled as COVID19 deaths. For example, a motorcycle fatality in Florida was counted as a COVID19 death.

• Death statistics are manipulated and miscounted in both directions (overcounting and undercounting), so what numbers – if any – are correct?

COVID19 case and death numbers are pushed out daily by media, but where is this daily push for other conditions – like heart disease – that kill far more people annually? We do not see daily reporting during the annual flu fear-mongering campaigns. Daily tallies hype the threat of COVID19 despite the extremely low CDC current estimates of the case fatality ratio for COVID19, at only 0.0065. https://bit.ly/3fAsyLt. 

1. Case Numbers: Do They Mean Anything?

Here are several reasons why the number of COVID19 “cases” reported is largely irrelevant. Hear Dr. Simone Gold explain why: https://bit.ly/2PGH0H3. These sloppy statistics with their misused and misreported information are featured in this article and discussed with Dr. Scott Atlas a Senior Fellow at the Hoover Institute: https://bit.ly/2XMRdX7

(1) Questionable Testing

As seen in earlier MAMM reports, there are a variety of different tests with varying accuracy and with many opportunities for error. Many experts, for example, challenge the use of and accuracy of PCR tests to diagnose COVID19.

Moreover, when the outbreak first started, a positive test locally was only considered presumptive until confirmed by CDC. Are all samples still sent to CDC for confirmation or are we now assuming that a positive test result from a state or local lab is a positive case without confirming? It appears that the latter is now true. https://bit.ly/31C6JWS. Positive and negative rates are also skewed by who gets tested. If you only test the sickest people with COVID19 symptoms, you likely get a higher case rate, and, likely, a higher mortality rate. Case numbers are also skewed by the number of people tested.

As the number of asymptomatic people being tested grows, the number of “positive” test results may also increase. https://bit.ly/3fIg4Bd Positive tests are being declared “cases,” but should we count these people who are not sick as “cases” of COVID only based on positive test results? Reporting of positive but asymptomatic cases feeds the fear that the pandemic is growing or that a second wave, worse than the first, will arrive (https://bit.ly/2F5L8yd), ignoring that these asymptomatic carriers are not even sick at all!

In addition to these challenges, let’s also consider the following errors in “case” reporting:

• Texas removed almost 3,500 cases which were never confirmed positive but counted anyway. https://washex.am/33zLreQ

• Ohio Governor Mike DeWine tested “positive” and two tests taken a few hours later were “negative.” What did one expert say about testing, “[expletive] always happens.” https://bit.ly/2PB512q

• Actress Alyssa Milano was apparently very ill several months ago but three COVID19 tests were negative. Recently she tested positive https://bit.ly/30LBA49. How do you, or should you, count what some refer to as “false negatives?” https://bit.ly/2DVBNZd COVID19 symptoms are varied and many are consistent with other illnesses as well. Presuming positivity in the face of negative testing also can skew reported cases.

The DeWine and Milano reports raise some interesting questions about case counting. What if you test negative but have COVID symptoms – are you presumed to be a case? How are multiple test results for an individual linked, even if tests were done at multiple sites? Are states systematically linking results for individuals who have to test multiple times? For example, what if a person tests twice, a week apart, and is positive each time – there is a chance, depending on where the person is being tested and the infrastructure collecting results, that this person is counted as two cases instead of one. What if a person is tested in more than one state? CDC even admits that there are no criteria to distinguish a new case from an existing case. https://bit.ly/31C6JWS

In Florida, many labs have been reporting inaccurate positive test rates – with many labs incorrectly reporting 100% or close to 100% positive rates. In at least two instances, labs were found to have inflated their positive rates by a factor of 10. https://bit.ly/3a9V31s Is Florida alone in this?

(2)  “Positive” results when no one has been tested

According to anecdotal reports from trusted sources in healthcare, some practitioners – curious about the accuracy of tests – have submitted “blank” test “samples,” having never swabbed an actual patient. In many instances, the lab results of these “tests” are positive – is it a flaw in the test or are the test kits contaminated (as many of the earliest CDC kits were: https://wb.md/3agsU90)? How are false positives potentially skewing results?

Similarly, there are many reports of individuals receiving positive test results when they have never been tested. Some signed up to be tested and either missed the appointment or left after a long wait without being tested. Regardless of reason, a positive test result is false. This enlightening report by investigative journalist Ben Swann is worth watching: https://bit.ly/2DUbova

(3) Asymptomatic Carriers

What about the estimated number of asymptomatic individuals – those people who never even get sick? The CDC estimates 40% of those infected are asymptomatic (https://bit.ly/3fAsyLt), but a Stanford University antibody study suggests that the prevalence may be 50-85 times higher than the number of confirmed cases (https://bit.ly/30A0PGi). As we asked above – how are these people counted and how should they be counted?

2. How Are COVID Deaths Counted?

Death numbers are open to serious questions. The “cause of death” definitions are inconsistent. As described recently by two experts writing for the American Council on Science and Health and examining COVID19 mortality statistics, “…  the exemptions and redefinitions suggest that the numbers of deaths attributed to Coronavirus have been counted haphazardly and incorrectly.” https://bit.ly/3kG21jA

In an analysis recently published on the Children’s Health Defense website (https://bit.ly/33DRPlm), a different group of experts explain why COVID death numbers and how deaths are reported is troubling. A new way of counting COVID deaths was put in place, rather than using well-established guidelines. The results may be catastrophically over-inflating COVID19 deaths:

Had the CDC used the well-established and successful methodology for recording COVID-19 related fatalities, as it does for all other causes of death, the fatality counts would be significantly lower.

How much lower?

We may never know. However, when we base our estimates upon the comorbidity data being published by New York, Massachusetts, Georgia, Oklahoma, Utah, Pennsylvania and Iowa the data suggests that accurate fatality rates could drop by approximately 90.2%. https://bit.ly/33DRPlm.

Here is another deep dive into the COVID death statistics and how they can be manipulated: https://bit.ly/33MJooa One important confounding variable: dying from COVID19 vs. dying with COVID19.

In many instances, individuals who die from other causes but happen to have tested positive for COVID19 are being counted as COVID19 deaths, in both the US and elsewhere. https://bit.ly/31G6pWOCould there be cases where people die from COVID but another cause of death is listed – and how do you figure out which is which? https://bit.ly/3fIg4Bd  Here is a short but thoughtful analysis of mortality calculations in the U.S. and Italy from strategic risk consultant F. William Engdahl: https://bit.ly/2F80KRT

Here are just a few stories demonstrating issues with the “COVID19” deaths:

(1)  Texas removes 225 COVID19 deaths added due to an “automation error.” https://bit.ly/30yM4DL

(2)  Pennsylvania removes 200 COVID19 deaths because of questions about reporting process and accuracy of reporting https://fxn.ws/31wdxFa

(3)  In Florida, a motorcycle accident death was reported as a COVID19 death because the deceased was tested and his results were positive. https://bit.ly/33H3MH2

(4)   A man died in Minnesota with symptoms consistent with COVID19 but his test was negative. His family was told this likely was a “false negative.” https://bit.ly/2DVBNZd

3. Why Would Numbers Be Inflated?

While there are many theories (some labelled “conspiracy theories”) about inflated numbers of both cases and deaths, you needn’t go down a rabbit hole to see why these numbers could be exaggerated. One reason may be very simple: financial gains to hospitals for treating COVID patients versus patients with other conditions.

CDC director Robert Redfield admitted in Congressional testimony that there may be perverse financial incentives for hospitals to inflate the number of COVID cases. https://cs.pn/3krcLCf    Why are we trusting these numbers?

Similarly, Physician and Minnesota State Senator Scott Jensen spoke about financial gains for Medicare COVID admissions: $13,000 and, if vented, $39,000 (at 3:15 in this video:  https://fxn.ws/33IMQzS with confirmation here: https://bit.ly/33KJ4WF)) While not suggesting that hospitals are committing massive fraud, there are certainly incentives to look for COVID cases, even where COVID might not be the primary reason for admission.

As many have said (including Mark Twain), “There are three kinds of lies: lies, damned lies, and statistics.” The public needs to keep this in mind in thinking critically about what we are being told.

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