... and one WILL tow it:
Fellow physicians, academics and journalists called out Dr. Kulvinder Kaur Gill on social media last summer for peddling what they alleged was anti-scientific misinformation and conspiracy theory.
At least one of her tweets was removed by Twitter, and complaints were filed to Ontario’s medical regulator. Those recently resulted in cautions for “irresponsible” and “indefensible” behaviour that could endanger public health.
But then the dialogue took a different turn.
Gill filed a $6.8-million libel suit in December against 23 of the detractors – including a former president of the Ontario Medical Association (OMA) – claiming they had maliciously sullied her reputation.
I must say that Dr. Gill (whose CPSO can be seen here) has quite the intestinal fortitude to mount such a challenge, one put out by an entire body of "experts" whose models and breathless assertions have kept an entire globe under house arrest and under great fear of catching something that a global octopus spread and will not account for.
I do not claim expertise in this field but even as a layman I know that contradicting one's self, not discovering the source of something and repeating the same failed actions over and over can't be productive.
Here I will leave a series of articles from various sources and on, as an adult, can deduce whether the Ontario Medical Association is hasty and unfair in its move against Dr. Gill or if it is correct in stamping out what is false information. If it is the former, then one must conclude that those who call themselves experts gave done a great disservice in not only not stopping this virus but in keeping a culture of misinformation alive, particularly by silencing, in Soviet-style, a colleague (as the Chinese have done) and creating a generation that distrusts science and those who study it. If it is the latter, then the Ontario Medical Association will have stopped an incompetent in their ranks.
See here:
The pro-lockdown evidence is shockingly thin, and based largely on comparing real-world outcomes against dire computer-generated forecasts derived from empirically untested models, and then merely positing that stringencies and “nonpharmaceutical interventions” account for the difference between the fictionalized vs. the real outcome. The anti-lockdown studies, on the other hand, are evidence-based, robust, and thorough, grappling with the data we have (with all its flaws) and looking at the results in light of controls on the population. ...
1. “A country level analysis measuring the impact of government actions, country preparedness and socioeconomic factors on COVID-19 mortality and related health outcomes” by Rabail Chaudhry, George Dranitsaris, Talha Mubashir, Justyna Bartoszko, Sheila Riazi. EClinicalMedicine 25 (2020) 100464. “[F]ull lockdowns and wide-spread COVID-19 testing were not associated with reductions in the number of critical cases or overall mortality.”
2. “Was Germany’s Corona Lockdown Necessary?” by Christof Kuhbandner, Stefan Homburg, Harald Walach, Stefan Hockertz. Advance: Sage Preprint, June 23, 2020. “Official data from Germany’s RKI agency suggest strongly that the spread of the coronavirus in Germany receded autonomously, before any interventions became effective. Several reasons for such an autonomous decline have been suggested. One is that differences in host susceptibility and behavior can result in herd immunity at a relatively low prevalence level. Accounting for individual variation in susceptibility or exposure to the coronavirus yields a maximum of 17% to 20% of the population that needs to be infected to reach herd immunity, an estimate that is empirically supported by the cohort of the Diamond Princess cruise ship. Another reason is that seasonality may also play an important role in dissipation.”
3. “Estimation of the current development of the SARS-CoV-2 epidemic in Germany” by Matthias an der Heiden, Osamah Hamouda. Robert Koch-Institut, April 22, 2020. “In general, however, not all infected people develop symptoms, not all those who develop symptoms go to a doctor’s office, not all who go to the doctor are tested and not all who test positive are also recorded in a data collection system. In addition, there is a certain amount of time between all these individual steps, so that no survey system, no matter how good, can make a statement about the current infection process without additional assumptions and calculations.”
4. Did COVID-19 infections decline before UK lockdown? by Simon N. Wood. Cornell University pre-print, August 8, 2020. “A Bayesian inverse problem approach applied to UK data on COVID-19 deaths and the disease duration distribution suggests that infections were in decline before full UK lockdown (24 March 2020), and that infections in Sweden started to decline only a day or two later. An analysis of UK data using the model of Flaxman et al. (2020, Nature 584) gives the same result under relaxation of its prior assumptions on R.”
5. “Comment on Flaxman et al. (2020): The illusory effects of non-pharmaceutical interventions on COVID-19 in Europe” by Stefan Homburg and Christof Kuhbandner. June 17, 2020. Advance, Sage Pre-Print. “In a recent article, Flaxman et al. allege that non-pharmaceutical interventions imposed by 11 European countries saved millions of lives. We show that their methods involve circular reasoning. The purported effects are pure artefacts, which contradict the data. Moreover, we demonstrate that the United Kingdom’s lockdown was both superfluous and ineffective.”
6. Professor Ben Israel’s Analysis of virus transmission. April 16, 2020. “Some may claim that the decline in the number of additional patients every day is a result of the tight lockdown imposed by the government and health authorities. Examining the data of different countries around the world casts a heavy question mark on the above statement. It turns out that a similar pattern – rapid increase in infections that reaches a peak in the sixth week and declines from the eighth week – is common to all countries in which the disease was discovered, regardless of their response policies: some imposed a severe and immediate lockdown that included not only ‘social distancing’ and banning crowding, but also shutout of economy (like Israel); some ‘ignored’ the infection and continued almost a normal life (such as Taiwan, Korea or Sweden), and some initially adopted a lenient policy but soon reversed to a complete lockdown (such as Italy or the State of New York). Nonetheless, the data shows similar time constants amongst all these countries in regard to the initial rapid growth and the decline of the disease.”
**
Does the CDC really think that masks prevent the wearer from getting Covid, or from spreading it to others? The CDC admits that the scientific evidence is mixed, as their most recent report glosses over many unanswered scientific questions. But even if it were clear – or clear enough – as a scientific matter that masks properly used could reduce transmission, it is a leap to conclude that a governmental mandate to wear masks will do more good than harm, even as a strictly biological or epidemiological matter. Mask mandates may not be followed; masks worn as a result of a mandate may not be used properly; some mask practices like double masking can do harm, particularly to children; and even if a mask mandate results in some increased number of masks being worn and worn properly, the mandate and the associated publicity may reduce the public’s attention to other more effective safeguards, such as meticulous hygiene practices.
Thus, it is not surprising that the CDC’s own recent conclusion on the use of nonpharmaceutical measures such as face masks in pandemic influenza, warned that scientific “evidence from 14 randomized controlled trials of these measures did not support a substantial effect on transmission…” Moreover, in the WHO’s 2019 guidance document on nonpharmaceutical public health measures in a pandemic, they reported as to face masks that “there is no evidence that this is effective in reducing transmission…” Similarly, in the fine print to a recent double-blind, double-masking simulation the CDC stated that “The findings of these simulations [supporting mask usage] should neither be generalized to the effectiveness …nor interpreted as being representative of the effectiveness of these masks when worn in real-world settings.”
Just look at the data from Jonas F. Ludvigsson that is emerging from Sweden in children 16 years old and under when preschools and schools were kept open and there were no face masks though social distancing was fostered. The result was zero (0) deaths from COVID-19 in 1.95 million Swedish children across the study period. The number of infections was exceedingly low, the number of hospitalizations was exceedingly low, and there were no deaths in children with COVID-19, all this despite not wearing masks due to no schoolwide mask mandate.
**
Exactly two weeks later hydroxychloroquine was deemed the most highly rated treatment for the novel coronavirus in an international poll of more than 6,000 doctors.
Dr. Fauci was skeptical of hydroxychloroquine’s effectiveness in treating the novel coronavirus.
But he wasn’t so skeptical back in 2013.
In fact, Dr. Anthony Fauci CHEERED the use of hydroxychloroquine appeared effective “only in cells in lab dishes” in treatment of against MERS.
(Sidebar: this.)
**
The UK Government’s reporting system for COVID vaccine adverse reactions from the Medicines and Healthcare products Regulatory Agency released their latest report today, March 4, 2021.
The report covers data collected from December 9, 2020, through February 21, 2021, for the two experimental COVID vaccines currently in use in the U.K. from Pfizer and AstraZeneca.
They report a total of 460 deaths and 243,612 injuries.
For the COVID-19 mRNA Pfizer- BioNTech vaccine analysis they report:
- 2033 Blood disorders including 1 death
- 1032 Cardiac disorders including 25 deaths
- 3 Congenital disorder
- 713 Ear disorders
- 10 Endocrine disorders
- 1242 Eye disorders
- 9360 Gastrointestinal disorders including 11 deaths
- 26,394 General disorders including 111 deaths
- 17 Hepatic disorders
- 466 Immune system disorders
- 1863 Infections including 33 deaths
- 393 Injuries including 1 death
- 965 Investigations
- 525 Metabolic disorders including 1 death
- 11,565 Muscle & tissue disorders
- 20 Neoplasms
- 16,107 Nervous system disorders including 14 deaths
- 29 Pregnancy conditions including 1 death
- 1235 Psychiatric disorders
- 187 Renal & urinary disorders
- 338 Reproductive & breast disorders
- 3575 Respiratory disorders including 12 deaths
- 6042 Skin disorders including 1 death
- 16 Social circumstances
- 45 Surgical & medical procedures
- 992 Vascular disorders including 1 death
Total reactions for the COVID-19 mRNA Pfizer- BioNTech vaccine: 212 deaths and 85,179 injuries
For the COVID-19 vaccine Oxford University/AstraZeneca analysis they report:
- 799 Blood disorders
- 1516 Cardiac disorders including 30 deaths
- 13 Congenital disorders
- 891 Ear disorders
- 24 Endocrine disorders
- 1613 Eye disorders
- 17,597 Gastrointestinal disorders including 5 deaths
- 56,377 General disorders including 146 deaths
- 22 Hepatic disorders
- 410 Immune system disorders
- 3016 Infections including 32 deaths
- 668 Injuries including 1 death
- 1878 Investigations
- 2057 Metabolic disorders including 2 deaths
- 19,241 Muscle & tissue disorders
- 13 Neoplasms including 1 death
- 34,656 Nervous system disorders including 14 deaths
- 19 Pregnancy conditions
- 2773 Psychiatric disorders
- 453 Renal & urinary disorders including 1 death
- 229 Reproductive & breast disorders
- 4059 Respiratory disorders including 10 deaths
- 7872 Skin disorders including 1 death
- 39 Social circumstances
- 117 Surgical & medical procedures including 1 death
- 1274 Vascular disorders including 1 death
Total reactions for the COVID-19 vaccine Oxford University/AstraZenec vaccine: 244 deaths and 157,637 injuries
For the COVID-19 vaccine brand unspecified analysis they report:
- 4 Blood disorders
- 2 Cardiac disorder including 1 death
- 9 Ear disorders
- 11 Eye disorders
- 79 Gastrointestinal disorders
- 289 General disorders including 1 death
- 1 Hepatic disorders
- 1 Immune system disorders
- 10 Infections including 1 death
- 5 Injuries including 1 death
- 11 Investigations
- 26 Metabolic disorders
- 77 Muscle & tissue disorders
- 177 Nervous system disorders
- 22 Psychiatric disorders
- 7 Renal & urinary
- 1 Reproductive & breast disorders
- 18 Respiratory disorders including 1 death
- 38 Skin disorders
- 1 Social circumstances
- 7 Vascular disorders
Total reactions for the COVID-19 vaccine brand unspecified vaccines: 4 deaths and 796 injuries
**
If someone who has tested positive for COVID-19 commits suicide, the Ontario Ministry of Health will record their cause of death as COVID-19.
As of Sunday, December 13, Public Health Ontario counted 140,181 cumulative cases of COVID-19, and 3,949 deaths.
“As a result of how data is recorded by health units into public health information databases, the ministry is not able to accurately separate how many people died directly because of COVID versus those who died with a COVID infection,” Ontario Ministry of Health Senior Communications Advisor Anna Miller said to True North in an email.
“A death that occurs in an active case of COVID-19 is counted as a COVID-19 death.”
**
Canadian government health officials were at a loss to explain why new federal modelling shows such a wild trajectory when they appeared at a House of Commons health committee hearing Friday.
Earlier in the day, Dr. Theresa Tam presented new modelling forecasting COVID-19 cases. The slide deck presents charts about how cases and deaths across Canada are significantly declining.
However, when it comes to forecasting for the future, Tam presented a graph that showed cases of COVID-19 immediately shooting up like a rocket ship in an almost vertical line.
It shows Canada going from its current count of around 2,300 cases per day to over 20,000 daily cases by the second week of March. The exact figure is unclear because the line shoots so high it exits the top of the graph.
The graph left infectious diseases experts scratching their heads. “What are the underlying assumptions?” Dr. Martha Fulford, an assistant professor at McMaster University and infectious diseases physician at Hamilton Health Sciences, told the Sun.
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“For me, a model is only as good as the data inputted and we need to know what the underlying assumptions and the data are. Why is their modelling so different from the modelling everywhere else?”
The Center for Disease Control in the U.S., for example, forecasts a decrease in cases over the same timeline as Dr. Tam’s graph shows the rocket ship-like trajectory.
**
One of Ontario’s top public health officials is facing criticism over remarks she made into a hot microphone, minutes before the beginning of a COVID-19 briefing at Queen’s Park on Monday.
A short 15-second video circulating on Twitter shows Associate Medical Officer of Health Dr. Barbara Yaffe unpacking some papers next to her colleague Dr. David Williams prior to the beginning of their twice-weekly briefing.
At one point before the briefing gets underway, Yaffe remarks “I don’t know why I bring all these papers. I never look at them. I just say whatever they write down for me.”
If the experts wish science to prevail in this never-ending pandemic, shouldn't they factor in the above and - oh, I don't know - start demanding certainty, especially with themselves?
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