Showing posts with label infection fatality rate. Show all posts
Showing posts with label infection fatality rate. Show all posts

Monday, July 12, 2021

Covid-19 and the Corruption of Science, State Directed Medical Terror, and Media Censorship

By Eshani M. King

Dear Editor

The British Medical Journal, November 13, 2020 (Reproduced without permission): Congratulations on your editorial highlighting the depressing levels of “corruption” taking place in the name of “beating the pandemic”. Scrutiny certainly deserves to be directed towards conflicts of interest within members of SAGE and scientific/medical advisors as examined by Dr Zoe Harcombe PhD, a Cambridge mathematics/economics graduate[1,2]. Aided by mainstream media and censorship by tech giants, this group controls the scientific narrative on which Government action has been based, even when the “science” relied upon is at complete odds with the views of many other world-class scientists.

Suppression of science and lack of open debate has impinged enormously on three issues of fundamental significance. Firstly, public fear of Covid has been elevated to levels that are completely out of proportion to the actual danger. A recent peer-reviewed paper by one of the world’s most cited and respected scientist, Professor John Ioannidis of Stanford University, quotes an infection fatality rate (IFR) for Covid of 0.00-0.57% (0.05% for under 70s), far lower than originally feared and no different to severe flu [3]. This paper is published on WHO’s own Bulletin but ignored by UK mainstream media.

Secondly, although deaths are currently running at normal levels, fear is being driven by inflation of Covid “cases” caused by inappropriate use of the Polymerase Chain Reaction (PCR) test [4-7]. This test is hypersensitive and highly susceptible to contamination, particularly when not processed with utmost rigour by properly trained staff. Case inflation also occurs from use of excessive number of rounds of amplification cycles (termed CT) which amplifies non-infectious viral fragments and cross-reacting nucleotides from non-Covid coronaviruses/other respiratory viruses. These become mis-labelled as Covid. Even Dr Fauci confirms that a positive result using CT above 34 is invalid (Twitter thread, Jeff Nelson @vegsource 30 October 2020) but in the UK CTs may go up to 45, as confirmed by Professor Carl Heneghan of Oxford University’s Center for Evidence-Based Medicine: (House of Commons Science & Tech Committee, 17 Sep, 2020 YouTube.) An obvious improvement is to immediately halt any use of CTs above 34 and ensure that for CTs between 25 and 34, two consecutive positive results are required before confirming a case as Covid positive.

According to Professor Brookes, a Health Data Scientist from the University of Leicester, the UK’s official data shows no excess deaths due to respiratory infections this season (talkRadio, 'The number of people dying today is the same as it would be any other year', 17 November 2020 YouTube). Instead, excess total deaths have been driven by lack of treatment due to hospital closure/lockdowns and have occurred mostly at home. Whilst there is no question that the first wave of Covid, a then novel virus, was lethal to many, there is no sound evidence of any second wave.

The third and possibly the most consequential suppression of science relates to the narrative that people do not develop immunity following a Covid infection. We know that immunity to SARS-CoV-1 is very durable, persisting for at least 12-17 years [8-10]. Immunologists know that immunity to SARS-Cov-2 is no different. This is confirmed by many eminent scientists including Beda M Stadler, the former Director of the Institute for Immunology at the University of Bern and Professor Emeritus (Ivor Cummins, Ep91 Emeritus Professor of Immunology...Reveals Crucial Viral Immunity Reality, 28 July 2020, YouTube), and Sucharit Bhakdi, former Chair of Medical Microbiology at the University of Mainz [11]. The human population has encountered and co-existed with myriad coronaviruses throughout evolution. Most of us therefore have cross-reacting T-cells, B cells and antibodies derived from encounters with cold coronaviruses that can recognise SARS-CoV-2 [12-14], in the same way that people “immunised” with cowpox became less susceptible to serious illness from smallpox - as Edward Jenner discovered in 1796. This is why we do not generally die from cold coronaviruses and precisely why so many of us were not susceptible to falling severely ill from Covid earlier this year. Even the chance of passing Covid to your spouse at the height of the pandemic was as low as 17%! [15 ].

In line with expectations, mediators of robust long-term immune memory, memory B and T-cells have both been firmly established to be produced following even a mild a Covid infection [17,18]. Pouncing on a handful of examples of apparent second Covid infections is irresponsible of the media but suits the false [18] narrative that falling antibody levels lead to loss of immunity. The evidence that immunity lasts is all around us - if this were not so we would see as many people dying of and falling seriously ill with Covid now as we did in March/April, including doctors and nurses.

Pfizer’s vaccination trial data provides further confirmation of the now low rates of prevalence. 94 participants were apparently infected based on PCR positive results (of unknown CT so we cannot be sure they are all genuinely Covid). The placebo group must comprise around 22,000, half the total trial number. This yields an infection rate of, at the very most, 0.4% and makes the chances of escaping infection greater than 99.6% during the trial period. The vaccine might well be 90% “effective” - although we are yet to learn exactly how this is measured - but the risk of contracting Covid in the first place is self-evidently low. The risk of both contracting and dying from Covid using an IFR of 0.57 (the worst case) was a mere 0.002% based on pessimistic assumptions. Of course, the elderly and other high-risk categories face greater risk, but it is still far less than it was early this year and it will continue to reduce as population immunity builds further.

Hijacking of science by vested interests has resulted in immeasurable harms to society. Lockdowns, meant to save lives but being pushed by narratives that have little basis in science, have themselves caused loss of life, livelihoods, dignity, and humanity. We need to ask how we have got to this sorry state. It seems that only the extrication of science from industry by introduction of independent sources of funding for scientific research institutions, perhaps by levying a brand-new tax on industry, will allow the nation’s best scientists an independent voice and put an end to the suppression of good science, together with the mistrust and conflict it generates.

References:

1. Dr Zoe Harcombe PhD. 9 November. SAGE conflicts of interest. https://www.zoeharcombe.com/2020/11/sage-conflicts-of-interest/
2. PM Hails “ herculean efforts” of life science companies to defeat coronavirus. 10 Downing Street Press Release. https://www.gov.uk/government/news/pm-hails-herculean-effort-of-life-sci...
3. John P A Ioannidis Infection fatality rate of COVID-1937 inferred from seroprevalence data. Publication: Bulletin of the World Health Organization; Type: Research Article ID: BLT.20.265892 Page 1. 14 October 2020 https://www.who.int/bulletin/online_first/BLT.20.265892.pdf
4. Elena Surkova, Vladyslav Nikolayevskyy, Francis Drobniewski. False positive Covid-19 results:hidden problems and costs. Lancet Respir Med 2020.September 29, 2020 https://doi.org/10.1016/S2213-2600(20)30453-7
5. Dr M Yeadon. Lies, damned lies and health statistics: the deadly danger of false positives. 20 September.
6. Dr Clare Craig FRC Path. How Covid Deaths Are Over-Counted. 27 October 2020. Updated 29 October 2020.
7. PCR positives: what do they mean? The Oxford Centre for Evidence-based Medicine, University of Oxford.23 September https://www.cebm.net/covid-19/pcr-positives-what-do-they-mean/
8. William J.Liuabc et al. T-cell immunity of SARS-CoV: Implications for vaccine development against MERS-CoV. Antiviral Research. Volume 137, January 2017, Pages 82-92 https://doi.org/10.1016/j.antiviral.2016.11.006
9. Le Bert N, Bertoletti A et al. SARS-CoV-2-specific T cell immunity in cases of COVID-19 and SARS, and uninfected controls. Nature. 2020 Aug;584(7821):457-462. doi: 10.1038/s41586-020-2550-z. Epub 2020 Jul 15. PMID: 32668444.
10. Guo, Z. Guo, C. Duan, Z. Chen, G. Wang, Y. Lu, M. Li, J. Lu. Long-Term Persistence of IgG Antibodies in SARS-CoV Infected Healthcare Workers. MedRxiv (2020) 2020.02.12.20021386 doi: https://doi.org/10.1101/2020.02.12.20021386 11. Dr Karina Reiss, Dr Sucharit Bhakdi. Book, Corona False Alarm? Facts and Figures. Pages 101-108.
12. Peter Doshi. Covid-19: Do many people have pre-existing immunity? 17 September 2020 BMJ 2020; 370 doi: https://doi.org/10.1136/bmj.m3563
13. E. King. Letter to BMJ: T-cells really are the superstars in fighting COVID-19 - but why are some of us so poor at making them? 21 Sep 2020 https://www.bmj.com/content/370/bmj.m3563/rr-6
14. Kevin W NG et al. Preexisting and de novo humoral immunity to SARs-CoV-2 in humans. 6 Nov 2020 DOI: 10.1126/science.abe1107
15. Frederik Plesner Lyngse et al. COVID-19 Transmission Within Danish Households: A Nationwide Study from Lockdown to Reopening. medRxiv 2020.09.09.20191239; doi: https://doi.org/10.1101/2020.09.09.20191239
16. Phuong Nguyen-Contant et al. S Protein-Reactive IgG and Memory B Cell Production after Human SARS-CoV-2 Infection Includes Broad Reactivity to the S2 Subunit. mBio Sep 2020, 11 (5) e01991-20; DOI:10.1128/mBio.01991-20
17. Isabel Schulien et al, Characterization of pre-existing and induced SARS-CoV-2-specific CD8+ T cells, Nature Medicine (2020). DOI: 10.1038/s41591-020-01143-2
18. Tyler J Ripperger, Deepta Bhattacharya et al. Orthogonal SARS-CoV-2 Serological Assays Enable Surveillance of Low Prevalence Communities and Reveal Durable Humoral Immunity. Immunity Volume 53, Issue 5, 17 November 2020, Pages 925-933.e4 https://doi.org/10.1016/j.immuni.2020.10.004

Related: 


Meantime, Google censors pandemic science that fails to support the terror narrative. Thus for example a search for the Youtube video by Professor Sucharit Bhakdi, M.D. explaining the evidence of almost universal pre-existent immunity to Covid-19 yields the message: 
This video has been removed for violating youtube's community guidelines.
This followed by a link inviting one to "Learn more," which prompted the person to whom I had sent the video link to remark:
I love the irony of exhorting me to learn more while preventing me from doing so.

But let us give thanks where thanks is due: To the unsung heroes who clear the piles of dead bodies from the streets each night. 

Saturday, February 6, 2021

India Achieves Covid Herd Immunity With Mortality of One in Five Thousand

 India, is reported to have achieved Covid herd immunity, with about half the population, or just under seven hundred million people, having Covid19-specific antibodies. That means India is essentially finished with Covid as a national disaster. 

Covid deaths recorded in India total 155,000, indicating a Covid19 infection fatality rate of around one in 5000.  That is around one tenth of the rates reported in Europe and North America. That difference reflects, at least in part, the steep age-dependence of Covid mortality and a difference in population age profile. India has fewer than 6% of its population aged over 60 versus around 26% in Europe and North America. 

In addition, the European and North American infection fatality rates are undoubtedly greatly exaggerated due to underestimation of the infection rate, which is based on reported cases, not population-wide antibody surveys.  

The inference is clear: The Western states have totally mishandled the epidemic. The virus should have been allowed to spread among the young and resilient, while the elderly should have been given every means to isolate themselves — if they so chose. And it should be emphasized that isolation of the elderly should have been entirely voluntary. At the age of 75 plus, why should one not take a 10% risk of dying a year or two prematurely due to Covid, rather than being locked up for much, or perhaps all, of the rest of one's life?

What the response of the Western nations to Covid19 demonstrates is either remarkably poor judgement in government, or a conspiracy to undermine Western economies and crush the spirit of the people. 

Related:

Zero Covid is a mirage

How Phony Coronavirus “Fear Videos” Were Used as Psychological Weapons to Bring America to Her Knees

Sunday, October 25, 2020

Scared of Covid19: Here's the Risk It'll Kill Ya

 The CDC reports that, in America, the age-dependent infection fatality rates for Covid19 are:

Age             Risk of death

0    - 19       0.00003 or one in 33,333
20  - 49       0.0002, or one in 5,000
50  - 69       0.005, or one in 200
70 +            0.06, or one in 18

Or looking at that in a more positive way, Covid19 survival rates are:

Age                  Survival rate

0   - 19 Years    99.997%
20 - 49 Years    99.98%
50 - 69 Years    99.5%
70 - 80 Years    94.6%

And that's if you're infected. But thus far, probably no more than about one in ten of the world's population has been infected, so if effective vaccines materialize, you'll likely never be infected. 

And for comparison, here are all ages risk of death due to some other causes:

Cancer:                          one in     562
heart disease:                 one in     520
Respiratory disease:      one in    2104
Motor vehicle accident: one in   5243

So what those numbers show is that it would make as much sense to shutter much of the economy to protect under-50's from motor vehicle accidents as to protect them from covid-19. Yet no one in the right mind would suggest doing anything so idiotic. So why do we do something so idiotic because of Covid19? Explanations invited.

Related:
Medical Express:
over 80% of COVID-19 patients have vitamin D deficiency
DM:
anti-lockdown protests sweeps across Europe

Friday, September 18, 2020

Dealing With Covid19: A Conversation with Stanford University Professor, John Ioannidis, America's Most Distinguished Epidemiologist

 By SAURABH JHA, MD

The COVID-19 pandemic has been a testing time for the already testy academic discourse. Decisions have had to be made with partial information. Information has come in drizzles, showers and downpours. The velocity with which new information has arrived has outstripped our ability to make sense of it. On top of that, the science has been politicized in a polarized country with a polarizing president at its helm.

As the country awoke to an unprecedented economic lockdown in the middle of March, John Ioannidis, professor of epidemiology at Stanford University and one of the most cited physician scientists who practically invented “metaresearch”, questioned the lockdown and wondered if we might cause more harm than good in trying to control coronavirus. What would normally pass for skepticism in the midst of uncertainty of a novel virus became tinder in the social media outrage fire.

Ioannidis was likened to the discredited anti-vax doctor, Andrew Wakefield. His colleagues in epidemiology could barely contain their disgust, which ranged from visceral disappointment – the sort one feels when their gifted child has lost their way in college, to deep anger. He was accused of misunderstanding risk, misunderstanding statistics, and cherry picking data to prove his point.

The pushback was partly a testament to the stature of Ioannidis, whose skepticism could have weakened the resoluteness with which people complied with the lockdown. Some academics defended him, or rather defended the need for a contrarian voice like his. The conservative media lauded him.

In this pandemic, where we have learnt as much about ourselves as we have about the virus, understanding the pushback to Ioannidis is critical to understanding how academic discourse shapes public’s perception of public policy.

Saurabh Jha (SJ): On March 17th, at the start of the lockdown, you wrote in STAT News cautioning us against overreacting to COVID-19. You likened our response to an elephant accidentally jumping off a cliff because it was attacked by a house cat. The lockdown had just begun. What motivated you to write that editorial?

John P.A. Ioannidis (JPA): March seems a long time ago. I should explain my thinking in the early days of the COVID-19 pandemic. Like many, I saw a train approaching. Like many, I couldn’t sense the train’s precise size and speed. Many said we should be bracing for a calamity and in many ways I agreed. But I was concerned that we might inflict undue damage, what I’d call “iatrogenic harm”, controlling the pandemic.

To answer your question specifically, I wrote the piece because I felt that the touted fatality rate of COVID-19 of 3.4 % was inflated, but we had so limited data and so much uncertainty that infection fatality rate values as different as 0.05% and 1% were clearly still possible. I was pleading for better data on COVID-19 to make our response more precise and proportionate.

Read More

(With Thanks to Yusef for this link).


Related:
DigWithin:

Has COVID-19 Testing Made the Problem Worse?

(With Thanks to Anastasia for this link).

Malcolm Kendrick:
COVID – why terminology really, really matters

(With Thanks to Peripatetic Commenter for this link).

Saturday, September 12, 2020

Covid Lies to Keep You Terrorized

Absent strong public health measures, we would expect it to kill something like 0.5% to 1.0% of a nation’s population, and whether or not that’s a large number is a matter of personal opinion.

So declared Ron Unz, publisher of the Unz Review

That claim is far from the truth as the case of Sweden demonstrates. There, in the absence of "strong public health measures" there have been 5,846 reported Covid deaths, or about 0.06% of the population. That must be close to the final toll, as Covid deaths in Sweden peaked in March and are now at or close to zero.

Why would a scientifically literate person such as Ron Unz make such a false claim? Mere confusion, perhaps*.

One way in which Covid death rates have been greatly exaggerated has been to confuse, deliberately or otherwise, two measures of the death rate; namely, the "Case Fatality Rate" and the  "Infection Fatality Rate." 

The Covid19 Case Fatality Rate (CFR) is a measure of deaths among confirmed Covid19 cases, the latter being mainly cases of serious illness, which thus came to the attention of the medical profession and were identified as due to Covid19 by a more or less reliable diagnostic methods.

The Covid19 Infection Fatality Rate (IFR) is a measure of deaths among all those infected with Covid19, whether they were seriously ill or not, or whether they were ill at all. The IFR can only be determined if there is population-wide testing for past or present Covid19 infection, for example by means of a reliable serological test for Covid19 antibodies. 

Evidence currently available suggests that the the IFR is only about one tenth of the CFR. Therefore, to mistake the CFR for the IFR will result in an exaggeration of the actual IFR by a factor of around ten. 

But even a ten-fold error does not explain Ron Unz's claim that "absent strong public health measures" Covid19 will "kill something like 0.5% to 1.0% of a nation’s population." To explain that, assuming it is not a straight lie, one must assume that Ron Unz confuses the Infection Fatality Rate with the Population Fatality Rate (PFR). Such confusion assumes a Covid death rate among the population as a whole equal to the Covid death rate among those made sick by a confirmed Covid19 infection, which is nonsense.

But perhaps Ron Unz's claim is a straight lie, which would be consistent with the fact that, when I pointed out the error on his Unz Review post, my comment was deleted.

______
* Cf. Ronald B. Brown, 2000, Public Health Lessons Learned from Biases in Coronavirus Mortality Overestimation.

Related:
Zero Hedge: "It's Like Using A Hammer To Kill A Fly" - Architect Of Sweden's COVID-19 Anti-Lockdown Strategy Finally Vindicated

Friday, May 22, 2020

Coronavirus Not As Deadly As Flu? Oops Did We Wrecked the Economy By Mistake?

Ross Clark

The Spectator, May 20, 2020: One of the great unknowns of the Covid-19 crisis is just how deadly the disease is. Much of the panic dates from the moment, in early March, when the World Health Organisation (WHO) published a mortality rate of 3.2 per cent – which turned out to be a crude ‘case fatality rate’ dividing the number of deaths by the number of recorded cases, ignoring the large number of cases which are asymptomatic or otherwise go unrecorded.

The Imperial College modelling, which has been so influential on the government, assumed an infection fatality rate (IFR) of 0.9 per cent. This was used to compute the infamous prediction that 250,000 Britons would die unless the government abandoned its mitigation strategy and adopted instead a policy of suppressing the virus through lockdown. Imperial later revised its estimate of the IFR down to 0.66 per cent – although the 16 March paper which predicted 250,000 deaths was not updated.

Epidemiology versus reality: Uppsala University model —predictions of Covid deaths in Sweden under various management scenarios including doing nothing (Lowermost line). Source
In the past few weeks, a slew of serological studies estimating the prevalence of infection in the general population has become available. This has allowed professor John Ioannidis of Stanford university to work out the IFR in 12 different locations.

They range between 0.02 per cent and 0.5 per cent – although Ioannidis has corrected those raw figures to take account of demographic balance and come up with estimates between 0.02 per cent and 0.4 per cent. The lowest estimates came from Kobe, Japan, found to have an IFR of 0.02 per cent and Oise in northern France, with an IFR of 0.04 per cent. The highest were in Geneva (a raw figure of 0.5 per cent) and Gangelt in Germany (0.28 per cent).

The usual caveats apply: most studies to detect the prevalence of the SARS-CoV-2 virus in the general population remain unpublished, and have not yet been peer-reviewed. Some are likely to be unrepresentative of the general population. The Oise study, in particular, was based on pupils, teachers and parents in a single high school which was known to be a hotspot on Covid-19 infection. At the other end of the table, Geneva has a relatively high age profile, which is likely to skew its death rate upwards.

But it is noticeable how all these estimates for IFR are markedly lower than the figures thrown about a couple of months ago, when it was widely asserted that Covid-19 was a whole magnitude worse than flu. Seasonal influenza is often quoted as having an IFR of 0.1 to 0.2 per cent. The Stanford study suggests that Covid-19 might not, after all, be more deadly than flu – although, as Ioannidis notes, the profile is very different: seasonal flu has a higher IFR in developing countries, where vaccination is rare, while Covid-19 has a higher death rate in the developed world, thanks in part of more elderly populations.

The Stanford study, however, does not include the largest antibody study to date: that involving a randomised sample of 70,000 Spanish residents, whose preliminary results were published by the Carlos III Institute of Health two weeks ago. That suggested that five per cent of the Spanish population had been infected with the virus. With 27,000 deaths in the country, that would convert to an IFR of 1.1 per cent.

     Related:    
DM: Lockdowns failed to alter the course of pandemic and are now destroying millions of livelihoods worldwide, JP Morgan study claims
Brandon Smith: The Economic "Reopening" Is A Fake Out
Israel Shamir: Corona conspiracies
Gilad Atzmon: Is this controlled demolition all over again
ZH: San Francisco area suicide rate exceeds Covid death toll
Trauma surgeon, Dr. deBoisblanc:
"We've never seen numbers like this, in such a short period of time," he said. "I mean we've seen a year's worth of suicide attempts in the last four weeks."
ZH: "Grandma Killer" Cuomo Sent 4,300 To Nursing Homes Despite Positive COVID-19 Tests
Dr.  Andrew Bostom: Covid19 Lethality: Unhysterical Data Are Emerging
Rutherford Inst: The Slippery Slope to Despotism: Paved with Lockdowns, Raids and Forced Vaccinations
Washington Times: 500 doctors tell Trump to end the coronavirus shutdown, say it will cause more deaths