Fauci and Walensky Bow To Science (Finally)

The reason I believe they admit these two facts that conservatives have been saying for over a year is that [coupled with the shorter isolation time-period] the Biden Administration is trying to make the cyclical spread of Covid (which moves just like the flu) in the blue states not seem as bad as when Florida had it. So the press bemoaned Florida and DeSantis when they had a supposed 25% of the nations cases. (See CLASH DAILY for newest statement conservatives have known since the beginning) Well, New York has almost 30% now. (See PJ-MEDIA for comparison). So bowing to keeping the economy going and not continually piss people off is the rational, which should have been the thinking to begin with (DAILY WIRE | NEW YORK POST). We know Fauci lies, and in fact, Hugh Hewitt points this out well in his challenge to Dr. Fauci retiring from his debacle [since HIV days] (100% FED-UP). Indeed, why can’t Dr. Fauci stop lying? (RED STATE)

This “Faucism” applies to adults as well… work injuries, appendix issues, etc.

SEE ALSO

  • (Recent) Fauci Now Says Hospitals Are ‘Overcounting’ COVID-19 Cases In Children Because They Automatically Get Tested. Sound Familiar? (DAILY WIRE)
  • (May 2021) Hospitals are OVERCOUNTING Children Admitted For Covid: Nearly Half Of Kids Recorded As Needing Inpatient Treatment For Virus Were Likely There For Something Else (And Just Happened To Test Positive), Study Suggests (DAILY MAIL)
  • (May 2021) COVID-19 Hospitalizations Among Children Likely Overcounted, Researchers Find (STANFORD)

NOT JUST CHILDREN w/COVID:

 

A Facebook “Covid Meme” Examined (“Experts vs Dummies”)

This is something I saw pop up on my FB in slow traffic yesterday and I thought it worthy of a “quick” retort.

A couple things going on here. First, no one I listen to or have read (other than the kooky “Alex Jones fringe,” has said it’s “not dangerous.” For instance, I myself argue it is as dangerous as the 1957-1958 and the 1968-1969 outbreaks — when the numbers are tampered down with the CDC’s change to how death certificates are written:

SOME EXAMPLES TO SUPPORT THE CONTENTION

  • Last month Alameda County, Calif., reduced its Covid death toll by 25% after state public-health officials insisted that deaths be attributed to Covid only if the virus was a direct or contributing factor. — Dr. Makary is a professor at the Johns Hopkins School of Medicine, Bloomberg School of Public Health and Carey Business School. (Wall Street Journal)
    1. Alameda County has changed the way it calculates deaths from the COVID-19 pandemic, resulting in a 25% drop this weekend. The official total fell from 1,634 to 1,223 on Friday after the county changed its methodology to align with narrower guidelines used by California and U.S. health agencies. According to a news release from the Alameda County Health Care Services Agency, the new number includes only people who “died as a direct result of COVID-19, or had the virus as a contributing cause of death as well as people for whom COVID-19 could not be ruled out as a cause of death.” (San Francisco Chronicle)

(FLASHBACK VIA RPT) And as states are going over death certificates, they are dropping by at least 25% in deaths by Covid-19. And some independent groups are helping “catch” the inflated number, like Pennsylvania’s “Wolf administration was caught this week adding up to 269 fake deaths to the state totals on Tuesday” (CITADELPOLITICS). Or this short example (PJ-MEDIA)

  • On Thursday, the Washington State Department of Health (DOH) confirmed a report by the Freedom Foundation that they have included those who tested positive for COVID-19 but died of other causes, including gunshot injuries, in their coronavirus death totals. This calls into serious question the state’s calculations of residents who have actually died of the CCP pandemic.
  • Last week, after it was reported that, like Washington, Colorado was counting deaths of all COVID-19 positive persons regardless of cause (which had resulted in the inclusion of deaths from alcohol poisoning), the Colorado Department of Health and Environment began to differentiate between deaths “among people with COVID-19” and “deaths due to COVID-19.”

Just one more of the many examples I could share is the New York Times getting 40% wrong of their “died from Covid-19 under 30-years old” front page news story. Mmmm, no, they didn’t die of Covid.

  • This Sunday morning, The New York Times has devoted their front page to the nearly 100,000 U.S. victims of COVID-19. The text-only cover lists 1,000 names and excerpts from the obituaries of people who have succumbed to the dreaded virus. The only problem with this lovely memorial is that at least one of the victims did not appear to have died from the coronavirus and his was only the sixth name on the list. [….] But others were quick to point out that Haynes was only the sixth name on the list. One replied, “He was one out of 5 under 30 on the list. Another in that group had a condition that doctors told him he would not live to 18. Did not test positive for COVID but still ruled a COVID death. That’s 40% of the under 30 age bracket.” (Red State)

[….]

APRIL 8TH (2020):

APRIL 19 (2020):

So, I am saying as an example, that a good portion of the deaths being attributed to Covid are not in fact Covid deaths.

The CDC has introduced a new ICD code, “to accurately capture mortality data for Coronavirus Disease 2019 (COVID-19) on death certificates.”

(Note: ICD stands for International Statistical Classification of Diseases and Related Health Problems. It is a medical classification list by the World Health Organization (WHO).)

The new ICD code for Coronavirus Disease 2019 (COVID-19) is U07.1. The CDC email says that the WHO has added a second code, U07.2, for instances “where a laboratory confirmation is inconclusive or not available. Because laboratory test results are not typically reported on death certificates in the U.S., National Center for Health Statistics (NCHS) is not planning to implement U07.2 for mortality statistics.”

The problem with the new codes is that it may result in an inflated number of coronavirus deaths….

(RED STATE)

And this is what I [for example] have argued. Do these changes made in April of 2020 impact previous outbreaks? Would this change also increase the 1957-1958 and the1968-1969 outbreaks? I think so.

A couple more examples to support the contention

(Story about a May 2020 death cert)

…. Jack Dake, an Oklahoma man who lived an admirable life as a veteran, a lifelong blue-collar worker and a loving dad, died on May 6 after contracting COVID-19.

There’s just one problem with his cause of death, his family says: Jack Dake did not die from the coronavirus.

The man barely had any symptoms, his family told The Oklahoman, and he died after a long battle with Alzheimer’s disease.

But, the family insists, that didn’t stop a coroner from labeling Dake as a coronavirus statistic on his death certificate on May 14.

Dake’s son, Jack Dake Jr., told the newspaper that his father’s death had absolutely nothing to do with the pandemic.

“Alzheimer’s was the cause of death, and COVID-19 was not even a contributing condition,” Dake Jr. told The Oklahoman. “Yet it’s recorded as the only cause of death.”

Dake apparently contracted the coronavirus at an Oklahoma City assisted living center and tested positive on April 17.

[….]

But the elder Dake was in one of the final stages of his battle with Alzheimer’s and had quit eating and drinking, which is common for end-stage sufferers of the degenerative brain disease.

Dake Jr. also said his father was never again tested for the coronavirus, but the family did request that he be put on hospice care, as he was not eating and was dehydrated.

Dake was listed as being terminal with COVID-19 by hospice workers, and when he died 20 days after testing positive, his death was recorded as one of the state’s coronavirus fatalities.

[….]

According to USA Today,  a provision in the Coronavirus Aid, Relieve and Economic Securities Act provides a “20% premium or add on” to Medicare reimbursements to health care facilities. (More information about that provision from the American Hospital Association.)

(WESTERN JOURNAL)

  • The Montezuma County Coroner’s Office is disputing the state’s claim of a third fatal case of the coronavirus in Cortez, saying the person died of alcohol poisoning. County Coroner George Deavers said the person tested positive for COVID-19, but an investigation by him and the pathologist determined the cause of death was ethanol toxicity. The person’s blood-alcohol content was 0.55, or almost seven times the legal driving limit of 0.08 in Colorado, Deavers said. A BAC of 0.3 is considered lethal. (DURANGO HERALD)
  • CBS 12 News examined medical examiner’s reports on COVID-19 deaths and found eight examples where a person was listed as a coronavirus death but had actually died from something else. This includes a 60-year-old man who died from a gunshot wound to the head, a 90-year-old who fell and broke a hip, and a 77-year-old who died of Parkinson’s disease. (CBS)
  • A woman is left with “no peace” after her father’s death certificate stated he died of the coronavirus despite previously testing negative and an MRI test showing he suffered multiple strokes. Jay Smith died on July 12 in San Antonio, Texas, after an MRI showed brain damage from enduring multiple strokes. Kayla Smith, however, said last week that her father’s death certificate listed him as a coronavirus victim. “They put him as COVID. He didn’t have COVID. He had a stroke,” she said. “The MRI showed that he had multiple strokes in the brain, and also he had a blood clot. Those multiple strokes caused so much damage in his brain that it caused damage in his body.” Jay Smith was first taken to the hospital on July 6, where he tested negative for the coronavirus and was transferred to a non-COVID floor on July 7, according to local outlet KATU. (WASHINGTON EXAMINER)

I have argued from the very get-go [or pointed to] stuff like: that (a) the PCR “cycle test” was too high, (b) that deaths attributed to Covid shouldn’t have been (here as well) that (c) the numbers of unknown – asymptomatic – cases lower the infection percentages/rates, i.e., the Infection Fatality rate, Etc., Etc.

The other contention in the “meme” is that “no experts” agree with portions of the above. Just high-school dummies.

Here is an older post:


List of “Dummies”


Dennis Prager interviews the co-author of the Great Barrington Declaration, Jay Bhattacharya. Dr. Bhattacharya is a professor of medicine at Stanford University and a research associate at the National Bureau of Economic Research. He directs Stanford’s Center for Demography and Economics of Health and Aging. Bhattacharya’s research focuses on the health and well-being of populations, with a particular emphasis on the role of government programs, biomedical innovation, and economics. Most recently, Bhattacharya has focused his research on the epidemiology of COVID-19 and evaluation of the various policy responses to the epidemic. He is a co-author of the Great Barrington Declaration, a document proposing a relaxation of social controls that delay the spread of COVID-19.

A worthwhile interview.

Here are some of the signatories of Great Barrington Declaration:

  • Martin Kulldorff, professor of medicine at Harvard University, a biostatistician, and epidemiologist with expertise in detecting and monitoring infectious disease outbreaks and vaccine safety evaluations.
  • Sunetra Gupta, professor at Oxford University, an epidemiologist with expertise in immunology, vaccine development, and mathematical modeling of infectious diseases.
  • Jay Bhattacharya, professor at Stanford University Medical School, a physician, epidemiologist, health economist, and public health policy expert focusing on infectious diseases and vulnerable populations.
  • Alexander Walker, principal at World Health Information Science Consultants, former Chair of Epidemiology, Harvard TH Chan School of Public Health, USA
  • Andrius Kavaliunas, epidemiologist and assistant professor at Karolinska Institute, Sweden
  • Angus Dalgleish, oncologist, infectious disease expert and professor, St. George’s Hospital Medical School, University of London, England
  • Anthony J Brookes, professor of genetics, University of Leicester, England
  • Annie Janvier, professor of pediatrics and clinical ethics, Université de Montréal and Sainte-Justine University Medical Centre, Canada
  • Ariel Munitz, professor of clinical microbiology and immunology, Tel Aviv University, Israel
  • Boris Kotchoubey, Institute for Medical Psychology, University of Tübingen, Germany
  • Cody Meissner, professor of pediatrics, expert on vaccine development, efficacy, and safety. Tufts University School of Medicine, USA
  • David Katz, physician and president, True Health Initiative, and founder of the Yale University Prevention Research Center, USA
  • David Livermore, microbiologist, infectious disease epidemiologist and professor, University of East Anglia, England
  • Eitan Friedman, professor of medicine, Tel-Aviv University, Israel
  • Ellen Townsend, professor of psychology, head of the Self-Harm Research Group, University of Nottingham, England
  • Eyal Shahar, physician, epidemiologist and professor (emeritus) of public health, University of Arizona, USA
  • Florian Limbourg, physician and hypertension researcher, professor at Hannover Medical School, Germany
  • Gabriela Gomes, mathematician studying infectious disease epidemiology, professor, University of Strathclyde, Scotland
  • Gerhard Krönke, physician and professor of translational immunology, University of Erlangen-Nuremberg, Germany
  • Gesine Weckmann, professor of health education and prevention, Europäische Fachhochschule, Rostock, Germany
  • Günter Kampf, associate professor, Institute for Hygiene and Environmental Medicine, Greifswald University, Germany
  • Helen Colhoun, professor of medical informatics and epidemiology, and public health physician, University of Edinburgh, Scotland
  • Jonas Ludvigsson, pediatrician, epidemiologist and professor at Karolinska Institute and senior physician at Örebro University Hospital, Sweden
  • Karol Sikora, physician, oncologist, and professor of medicine at the University of Buckingham, England
  • Laura Lazzeroni, professor of psychiatry and behavioral sciences and of biomedical data science, Stanford University Medical School, USA
  • Lisa White, professor of modelling and epidemiology, Oxford University, England
  • Mario Recker, malaria researcher and associate professor, University of Exeter, England
  • Matthew Ratcliffe, professor of philosophy, specializing in philosophy of mental health, University of York, England
  • Matthew Strauss, critical care physician and assistant professor of medicine, Queen’s University, Canada
  • Michael Jackson, research fellow, School of Biological Sciences, University of Canterbury, New Zealand
  • Michael Levitt, biophysicist and professor of structural biology, Stanford University, USA.
  • Recipient of the 2013 Nobel Prize in Chemistry.
  • Mike Hulme, professor of human geography, University of Cambridge, England
  • Motti Gerlic, professor of clinical microbiology and immunology, Tel Aviv University, Israel
  • Partha P. Majumder, professor and founder of the National Institute of Biomedical Genomics, Kalyani, India
  • Paul McKeigue, physician, disease modeler and professor of epidemiology and public health, University of Edinburgh, Scotland
  • Rajiv Bhatia, physician, epidemiologist and public policy expert at the Veterans Administration, USA
  • Rodney Sturdivant, infectious disease scientist and associate professor of biostatistics, Baylor University, USA
  • Salmaan Keshavjee, professor of Global Health and Social Medicine at Harvard Medical School, USA
  • Simon Thornley, epidemiologist and biostatistician, University of Auckland, New Zealand
  • Simon Wood, biostatistician and professor, University of Edinburgh, Scotland
  • Stephen Bremner,professor of medical statistics, University of Sussex, England
  • Sylvia Fogel, autism provider and psychiatrist at Massachusetts General Hospital and instructor at Harvard Medical School, USA
  • Tom Nicholson, Associate in Research, Duke Center for International Development, Sanford School of Public Policy, Duke University, USA
  • Udi Qimron, professor of clinical microbiology and immunology, Tel Aviv University, Israel
  • Ulrike Kämmerer, professor and expert in virology, immunology and cell biology, University of Würzburg, Germany
  • Uri Gavish, biomedical consultant, Israel
  • Yaz Gulnur Muradoglu, professor of finance, director of the Behavioural Finance Working Group, Queen Mary University of London, England

The CDC Is Lowering The PCR Test Cycle Thresholds

UPDATE BELOW IS DATED MAY 4th (2021)

The CDC is lowering post-vaccine case detection PCR test cycle thresholds to 28. It was 36-40 before, which “found” 10x [CORRECTION BELOW] as many false positive cases.

The CDC is not a medical organization. It is a political one. This is them shouting that fact.

— J.P.

  • CORRECTION I was wrong. The sudden lowering of the PCR cycle threshold by the CDC lowers the sensitivity not by 10x but by 1000x. It’s exponential. — J.P.

(RPT) What does this mean? Well, this means there will be a dramatic drop in cases under Biden.

UPDATE

The Facts:

  • The CDC is and will be collecting samples from COVID tests of vaccinated individuals to try and determine if the virus can breakthrough the protection of the vaccine. In doing so the CDC has specified a cycle threshold for PCR tests.

Reflect On:

  • Why a cycle threshold suddenly? Why not one prior to the rollout of vaccines? How many false positives have we seen as a result of no prior cycle threshold? Will PCR tests of the unvaccinated have this new cycle threshold?

The CDC is requiring that clinical specimens for sequencing should have an RT-PCR Ct value ≤28 when conducting tests for vaccinated individuals. “Ct” refers to cycle threshold.

According to Public Health Ontario,

The cycle threshold (Ct) value is the actual number of cycles it takes for the PCR test to detect the virus. It indicates an estimate of how much virus was likely in the sample to start with – not the actual amount. If the virus is found in a low number of cycles (Ct value under 30), it means that the virus was easier to find in sample and that the sample started out with a large amount of the virus. Think about it like the zoom button on your computer, if you only have to zoom in a little (zoom at 110%), it means that item was big to start with. If you have to zoom a lot (zoom at 180%), it means that the item was small to start with.

Why This Is Important: It’s been difficult to find what PCR Ct value tests have been using during this pandemic, and it’s important because at a value at 35 or more for example, an individual is more likely to test “positive” when they are not infected and/or do not even have the ability to transmit. This is commonly known as a “false positive.”

(COLLECTIVE EVOLUTION)