Guest post by Brian,
Introduction
A detailed analysis of the University of Manitoba’s recent model prepared on behalf of the Canadian Government illustrates exaggerated and incalculable conclusions. These explicitly theoretical projections, which have little evidence to support them, set an unrealistic foundation of what is considered a success or not with regards to Dr. Tam’s policies. In this case, the models that are used to predict the effects of Sars-Cov-2 adapts a completely unrealistic and unattainable worst-case scenario. Essentially any result, and every result possible, will be hailed as a resounding success – which is disingenuous. The virus would not come close to manifesting the chaos projected, even among a society with the loosest of policies. Fortunately, there are examples as many countries had their own approach in fighting the virus.
The basics of the SEIR model are rudimentary – though filled with several bells and whistles that create the sense of false precision. This commentary will go through these one at a time. I find it important to note the modelling is unrealistic, serves to spread unwarranted fear in the Canadian population, and a breach of the trust placed in the Government of Canada by all Canadian citizens.
Comments on the Canadian Health Ministries Latest Sars-Cov-2 Projections
Introduction
A detailed analysis of the University of Manitoba’s recent model prepared on behalf of the Canadian Government illustrates exaggerated and incalculable conclusions. These explicitly theoretical projections, which have little evidence to support them, set an unrealistic foundation of what is considered a success or not with regards to Dr. Tam’s policies. In this case, the models that are used to predict the effects of Sars-Cov-2 adapts a completely unrealistic and unattainable worst-case scenario. Essentially any result, and every result possible, will be hailed as a resounding success – which is disingenuous. The virus would not come close to manifesting the chaos projected, even among a society with the loosest of policies. Fortunately, there are examples as many countries had their own approach in fighting the virus.
The basics of the SEIR model are rudimentary – though filled with several bells and whistles that create the sense of false precision. This commentary will go through these one at a time. I find it important to note the modelling is unrealistic, serves to spread unwarranted fear in the Canadian population, and a breach of the trust placed in the Government of Canada by all Canadian citizens.
Canada’s COVID-19 Modeling
Fatality and Nursing Homes
Over 80% of all Sars-Cov-2 deaths in Canada are from Long term Care (“LTC”) and nursing home facilities[ii]. The inhabitants of these facilities are the oldest and weakest among the population. In fact, only wealthy populations have extensive LTC communities which are mainly in Europe and North America. Over 50% of Sars-Cov-2 fatality in the US and Europe are from these facilities[iii][iv].
The spread in these facilities is nosocomial. Meaning, not random population spread but a contagious virus dropped into a closed environment that then rips through the residents and staff[v],[vi]. These were all belatedly protected and we tragically saw the results of this inaction. Random spread can have no relationship to LTC spread if proper policy and funding is in place. It is important to note that the Canadian government modelers openly reference non-random influenza spread from a 2017 paper, but do not account for this in their modeling. This is completely inconsistent.
Having said that, any model that does not account separately for LTC spread and LTC fatality is simply a failure in illustrating the complete picture of the virus. The single largest source of risk and fatality not being broken out means this Canadian model has no ability to properly project fatality.
“Conclusions. Our study revealed a highly structured contact and movement patterns within the LTCF. Accounting for this structure—instead of assuming randomness—in decision analytic methods can result in substantially different predictions.” (https://doi.org/10.1177/0272989X17708564)
Infectious Fatality Rate (“IFR”)
IFR is simply defined as one risk of dying if infected and is not to be confused with Case Fatality Rate (“CFR”) which divides fatality by confirmed cases. CFR is an irrelevant statistic unless testing rate is relatively constant. The CFR misrepresents the danger of the virus. Incidentally, a corollary is new case counts that do not predict new fatality which sounds like a paradox but is statistically true. Unfortunately, the media is obsessed with case counts, but they are the least valuable statistic in describing the state of spread currently available, including the danger of the virus.
IFR varies by age and this is universal to all countries[vii]. All Canadian Government models[viii] have used an IFR of 1.2% – or 15x the true non-LTC Sars-Cov-2 risk, despite very strong evidence in March that its was 0.1% – 0.35%, or, near the flu. Even the CDC when adjusted for asymptomatic infection has IFR 0.1%-0.35% inclusive of LTC fatality. Recently Alberta concluded its antibody study. Based on the results alone, the IFR in Alberta at the time as ~0.35%, however 75% of those fatalities were LTC[ix]. Non-LTC IFR is 0.08% – which is 50% less risky than the common influenza[x].
For the general population, the Canadian Government models intended to dictate health policy say the virus is 17X more deadly than reality – which is misleading and instills an unwarranted fear in Canadian citizens.
Canadian Government Estimates (per million) of Hospitalisations, ICUs, and Fatalities vs Alberta Serology Based Actual Percentages (Ex-LTC)
A true predictive model would break out IFR by age and separately break out LTC fatality[xi]. The LTC break out is important – an Ontario government study concluded an LTC resident was 13x more likely to die than the same age non-LTC resident.
Serology studies in Africa and India – with poor health care relative to Canada show IFR’s 0.005% – 0.06%. These younger populations with no LTC community have virtually no risk to dying despite little access to treatment.
No Canadian government model has performed this basic and necessary inclusion – which causes the modelling to be inaccurate and overstates the severity of the virus.
R0 Assumptions
R0 and R(t) are measurements on rate of viral spread. R0 is the rate of spread assuming no existing interactions with Sars-Cov-2, while R(t) which goes down over time adjusted R(0) for infected, recovered and dead.
The newest model uses R0 of 2.9, 3.3 and 3.7. These are results from old studies in hyperdense China. Side note, Canadian modeling only references old Chinese studies (dated) and the Imperial College/Neal Ferguson study (model failure) while excluding newer and more accurate studies. Models are a tool that require accurate inputs to accurately assess risk. The use of inaccurate inputs leads to inaccurate outputs.[xii],[xiii],[xiv].
Canadian R0, given our lower density (hence lower transmissible interactions) is about 2.0 nationally while early in the spread. There is tremendous supporting documentation/evidence of this, and it is unclear why the Government would only allow a lower bound almost 50% higher than actual and an upper bound almost 100% more.
The misuse of the R0 variable is another main driver – like the similar failed Imperial College model before it – the new Canadian model does not replicate spread in places like Florida or Sweden. It dramatically overestimates real life outcomes and should be compared against reality before providing outcomes to the public that cannot possibly happen under any scenario.
I’ll revisit R0 when discussing heterogeneity below.
Infectious period
There are multiple studies that the maximum infectious period of Sars-Cov-2 is about 8 days (known since early March)[xv]. The average time an infected person can infect another is about 4 days with a maximum of 8. The Canadian government model assumes an average of 10 days – which does not align with observable data. There is no science behind this assumption but has the effect of magnifying model spread and generating unnecessary fear.
Heterogeneity of Spread, Herd Immunity and the Function of T-cells
Herd Immunity Threshold (“HIT”) is defined as the point at which spread can only decay lower i.e. R(t) < 1 permanently[xvi]. Using basic math, HIT is reached when 1-1/R0 of the population is infected. If R0 is 2.0 – then 50% is HIT, if its 3.3 then ~70% need to be infected. But this isn’t true in the real world.
The main (and inaccurate) assumption is that everyone mixes perfectly – a concept called homogeneity. Using an analogy, the Canadian model assumes a bartender at a popular restaurant in downtown Toronto interacts with others the same about in a week as a person living alone in a cabin in the Yukon. The variation in interactions is called heterogeneity – uneven mixing. Uneven mixing lowers HIT. A lot. To assume mixing is equal across all people in Canada is the absolute worst-case scenario mathematically possible.
There are various ways to model heterogeneity, but Dr. Tam’s group explicitly ignores its existence in a government model intended to guide policy[xvii]. They have decided to model only the worst case. Heterogeneity lowers R0 over time as highly interactive individuals spread the virus early and then become blockers – slowing the spread and lowering R0 and R(t). This is one large factor why Sweden[xviii] and other places have reached HIT when looking at their spread at far, far lower levels than this misguided Canadian model.
Heterogeneity is easily evidenced and can be partially quantified by the far higher spread in cities vs rural settings all over the world[xix],[xx]. Not accounting for these concepts – which are easily incorporated – is a breach of trust to Canadian citizens relying on knowledgeable health experts to provide accurate information.
Another related factor is T-cell immunity, a growing and popular area of research. It is not without contestation that Sars-Cov-2 is NOT “novel”; i.e. no one has existing defenses[xxi],[xxii],[xxiii].
- In February (Singapore), Sars-Cov-1 patients showed 100% immunity to Sars-Cov-2 despite being infected 17 years ago.
- We know that common cold coronavirus is cross reactive to Sars-Cov-2 initiating a T-cell response and destroying the virus[xxiv].
- T-cell protection does not create IgG antibodies (what antibody tests measure), but IgG antibodies create long term T-cell protection in at least 83% of cases. Antibody decay translates to long term immunity[xxv],[xxvi].
- T-cell protected persons get the virus but almost always fight it off. They show positive on PCR test but not antibody tests. Studies show on average 1.8x as PCR positive but antibody negative – meaning the virus has spread possibly 1.8x more than antibody tests alone imply. This translates into lower IFR; meaning the virus is even far less deadly than the flu.
The new government model does not even bother to address to existence of T-cell immunity despite its widespread acceptance in the medical community – which further compounds the inaccuracy of the model used to derive policy.
Conclusion
These new model outcomes have no basis in reality and should not be used for policy planning. Better and more accurate models do exist, but it is unclear why the Canadian government does not use them. This new model is beyond worst case – it is an impossibility like the models before it. It is intended only as a counterfactual. Furthermore, it has been paid for by Canadian taxpayers, who’s trust has been which depend on accurate information. Although I would prefer it were not true, I believe the model is being used purely as a preplanned counterfactual defense to Dr. Tam and her group’s expensive and mostly ineffective policy actions.
The most likely outcome in Canada assuming no lockdown is 10-15% antibody spread or 18-28% true spread including T-cells and about 4,000-8,000 non-LTC residents fatalities from Sars-Cov-2 (government estimate in April – 300,000). It is unclear that any interventions beyond full lockdowns have any material effect to slow viral spread; and full lockdown have tremendous cost. In fact, it’s very debatable that lockdowns have any net positive effect on fatality. The idea of ‘better safe than sorry’ policies undertaken not just by Canada, but other countries, are starting to show irreparable damage to citizens. This could be due to damage to the economic livelihoods of the citizenry, increases in mental illness, drug abuse, child abuse, incremental global famine, child development, etc[xxvii]. This is largely due to poor information communication, lack of education on the subject matter, and a lack of putting statistics into real world context. This only instills fear which can illicit irrational, sometimes dangerous behavior by citizens. I need not get into examples of what fear and irrational behavior can do within a society historically as there are countless amounts of them[xxviii]. To put it into graphical context, Franklin Templeton put out a survey to gauge fear of death from Sars-Cov-2 among all age groups.
Is this rational thought? Is this how we want people to live their daily lives? Between the ages of 18-64, there are a great many other things that have a higher chance of causing death outside of Sars-Cov-2. Not to mention people who are already struggling hard with mental illness. Many people who struggle with addiction depend so much on having structure, going to school/job, having hobby’s, meeting with friends etc. Video conferencing does very little for those who struggle with addiction. By enforcing isolationist policies, the biggest support of having ‘normality’ in their daily lives is eliminated and thus take a part in destroying the foundation of any form of happiness. What if they also have families, what if the person they depend on for their livelihood is the one that struggles with addiction? There are an estimated 2 million people who subscribe to Alcoholics Anonymous[xxix], and these are those who admit that they have a problem. If even 10% of them completely lose control of their lives because of these ill-conceived policies, that’s 200,000 people minimum who have their livelihoods destroyed with very little means to recover.
Granted, masks, basic social distancing, hand washing all may have an effect, but they appear to be less effective than we have been led to believe by the Canadian government. Most spread can be explained be reasonable heterogeneity models and T-cell immunity
The single best NPI the Canadian government can do is to open borders with no restriction to herd immune countries (Sweden, US, India, Mexico, France, and Brazil among others). Canada will import lots of immune “blockers” and almost no live infections. These blockers will serve to reduce R0 and R(t) – a concept easily modeled. This single action is an order of magnitude more helpful in slowing spread permanently than masks, further lockdowns or even handwashing. It is permanent and has the effect of positive economic and social benefit (all other NPI’s are varying degrees of negative).
We should all implore Dr. Tam and our highly compensated health experts to incorporate widely available empirical evidence to provide projections that accurately represent the risk of Sars-Cov-2 to Canadians. Its very probable that the true outcome of such work will demonstrate the risk from Sars-Cov-2 was not and is not severe, outside of nursing homes. The work is also likely to show all the interventions, costs, and fear to slow its inevitable spread was not necessary. Yes, it would be a devasting blow to Dr. Tam and our government’s reputation, but the good of Canadians is what matters. The current model has no basis in reality and has constituted a breach of the trust placed in Dr. Tam by the Canadian citizenry.
I will reiterate, I prefer it were not true, but building such an obviously counterfactual model so Dr. Tam can later point to the outcomes being better than the model and say “see, I saved lives” seems to be the only point of the modelling exercise. This serves nothing but to instill unwarranted fear in the citizenry and provide a façade of competency in government policy.
Its disappointing that a knowledgeable individual such as Dr. Tam, whose expertise include infectious disease, would allow this model to be released.
End Notes (References):
[i] https://www.cbc.ca/news/politics/covid19-pandemic-modelling-tam-fall-peak-1.5686250
[ii] https://www.theglobeandmail.com/canada/article-new-data-show-canada-ranks-among-worlds-worst-for-ltc-deaths/
[iii] https://www.eurosurveillance.org/content/10.2807/1560-7917.ES.2020.25.22.2000956#html_fulltext
[iv] https://www.wsj.com/articles/coronavirus-deaths-in-u-s-nursing-long-term-care-facilities-top-50-000-11592306919
[v] http://www.imperial.ac.uk/mrc-global-infectious-disease-analysis/covid-19/report-13-europe-npi-impact/
[vi] https://doi.org/10.1177/0272989X17708564
[vii] https://www.cebm.net/covid-19/global-covid-19-case-fatality-rates/
[viii] https://www.canada.ca/en/public-health/services/reports-publications/canada-communicable-disease-report-ccdr/monthly-issue/2020-46/issue-6-june-4-2020/predictive-modelling-covid-19-canada.html
[ix] https://www.cbc.ca/news/canada/calgary/covid-19-deaths-long-term-care-cihi-1.5626821#:~:text=The%20analysis%20found%20537%20confirmed,per%20cent%20of%20total%20deaths.
[x] https://calgaryherald.com/news/local-news/about-36000-albertans-had-covid-19-by-mid-may-new-serology-testing-suggests
[xi] https://www.medrxiv.org/content/10.1101/2020.05.13.20101253v3
[xii] https://www.imperial.ac.uk/media/imperial-college/medicine/sph/ide/gida-fellowships/imperial-college-covid19-npi-modelling-16-03-2020.pdf
[xiii] https://doi.org/10.1503/cmaj.200476
[xiv] https://doi.org/10.1016/S1473-3099(20)30243-7
[xv] https://www.acpjournals.org/doi/10.7326/M20-0504
[xvi] https://www.medrxiv.org/content/10.1101/2020.06.26.20140814v2
[xvii] https://globalnews.ca/news/7249803/coronavirus-vaccine-restrictions-theresa-tam/
[xviii] https://www.biorxiv.org/content/10.1101/2020.06.29.174888v1.full.pdf
[xix] https://www.medrxiv.org/content/10.1101/2020.04.27.20081893v3
[xx] https://www.medrxiv.org/content/10.1101/2020.07.15.20154294v1
[xxi] https://www.nature.com/articles/s41586-020-2550-z
[xxii] https://www.biorxiv.org/content/10.1101/2020.05.26.115832v1
[xxiii] https://science.sciencemag.org/content/early/2020/08/04/science.abd3871
[xxiv] https://www.livescience.com/common-cold-coronaviruses-t-cells-covid-19-immunity.html
[xxv] https://science.sciencemag.org/content/early/2020/08/04/science.abd3871
[xxvi] https://www.nature.com/articles/s41586-020-2598-9
[xxvii] https://www.medrxiv.org/content/10.1101/2020.08.12.20173302v1
[xxviii] https://www.franklintempletonnordic.com/investor/article?contentPath=html/ftthinks/common/cio-views/on-my-mind-they-blinded-us-from-science.html
[xxix] https://www.aa.org/pages/en_US/aa-around-the-world
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https://www.aier.org/article/governments-are-faking-it-and-copying-each-other/
Richard and any other late lurkers,
Gateway Pundit has a new article about how China used thousands of bogus Twitter accounts to influence politicians and nations to adopt the lockdown strategy they used in Wuhan!
There is a Twitter thread where these accounts can be seen criticizing those advocating against lockdowns and praising those who fell for the scam! They started in Italy and then took on critics in the US, UK, Europe and Australia. This whole plandemic appears to have been an opening salvo in China’s war against the rest of the world!
Twitter tried to delete the bogus accounts but was completely unable to deal with the volume the ChiComs employed for their disinformation campaign! Time to hold these criminals accountable!!
Brian,
Are you aware of Canadian population’s Vit. D deficiency and the connection between Covid and Vit D deficiency?
Statistic Canada has taken blood samples from a representative sample of Canadians and found that 32% of the Canadian population on the average are deficient in Vit. D. Below is a direct copy from the Stat. Can web site data on the Canadian population’s, Vit D deficiency.
40% of the Canadian population’s Vit D level is less than 20 ng/ml in the winter and only 25% in the summer.
32% of the Canadian population have an active Vit. D blood serum level that is less than 20 ng/ml (US units) or less than 50 nmol/L (EU units).
It has been shown that those Canadian citizens that have a Vit D blood serum level that is less than 20 ng/ml or 50 nmol/L have a 19 times greater chance of dying from covid or having serious organ.
This Vit D deficiency finding explains why there are twice as many US blacks and UK blacks dying from covid than US general population.
Vit. D enables our cells to access their copy of our DNA to build chemical producing modules. The chemical producing modules produce specialized chemicals to protect the cells, repair the cells, and maintain the cells.
The percentage of our cells that get these chemical producing modules has been shown based on the cancer studies to be depend on the level of active Vit. D in our blood stream.
So the internal cells of a person with a blood serum level that is less than 20 ng/ml would have less of the evolutionary developed chemical modules.
This Vit D ‘theory’ explains why the death rate for flu changes seasonally. In the summer less of the population is Vit. D deficient.
https://emerginnova.com/patterns-of-covid19-mortality-and-vitamin-d-an-indonesian-study/
Patterns of COVID-19 Mortality and Vitamin D: An Indonesian Study
Vitamin D Insufficient Patients 12.55 times more likely to die, blood serum 25(OH)D level from 21 to 29 ng/ml
Vitamin D Deficient Patients 19.12 times more likely to die, Vitamin D blood serum level less than 20 ng/ml
Vitamin D ‘normal’ for this study is 25(0H)D above 30 ng/ml.
Canadians: Statistics Canada
Highlights
• Just over two-thirds of Canadians (68%) had blood concentrations of vitamin D over 50 nmol/L (above 20 ng/ml)—a level that is sufficient for healthy bones for most people. About 32% of Canadians were below the cut-off.
• Children aged 3 to 5 had the highest rates above the cut-off (89%), while the 20- to 39-year-olds had the lowest (59%).
• A minority of Canadians (34%) took a supplement containing vitamin D, but a larger percentage of those taking supplements were above the cut-off (85%), compared with non-supplement users (59%).
• About 40% of Canadians were below the cut-off in winter, compared with 25% in the summer.
• On average, females had a higher concentration of vitamin D in their blood than males.
Chart Showing US Vit D Units ng/ml Vs EU Units nmol/l (same thing measured active Vit. D in blood stream)
ng/ml nmol/l
100 250
90 225
80 200
70 175
60 150
50 125
40 100
30 75
20 50
10 25
0 0
•
It is amazing to me how CDC doesn’t strongly suggest people get sufficient vitamin D. We he endlessly about masks and social distancing but no talk on basic nutrition.
Correct!!!
Its out of my expertise but I have seen studies on Vitamin D and Vitamin D stimulation of T-cells. There was a study out of Singapore back in May that noted all serious infections had low Vitamin D levels for example. My background is on the maths and science side, not so much on biology. My comments won’t carry much weight I’m afraid.
Brian, I don’t know if you can address this question or not, but I was wondering what you made of the Lancet meta analysis of the efficacy of masks? I can’t understand it (as I am a lay person), but I was told that it was ‘the gold standard’ of studies and should lay to rest any doubts that masks can help stop the spread.
Of course, I know how they goofed up on HCQ. What I could tell from the study was that it relied heavily on data for MERS as wells as SARS covid. I also was unable to figure out how the masks and distancing were inter-related with the study…
I honestly want to wear a mask in situations where it would help. But I’ve seen so much misuse of masks. Also, I’d be happy to get covid and have it out of the way. The mask debate is as muddy as a crocodile infested river when you throw in a baby donkey…. argh.
The mask issue will continue to be debated. The Canadian “experts” blew it when they said masks were not necessary. They said it because the masks and other equipment was in short supply. So I really have no faith in experts by position of authority.
re Lancet: after their retraction of the HCQ study I will not even waste my time reading Lancet.
The data on masks is not very compelling. If they worked really well then every place with mask policy would see no meaningful spread increase – obviously this has happened in numerous places.
When spread is declining due to natural decay, you require a control group of unmasked areas at a similar point in the spread to compare. There is lots of data like this and its pretty clear masks have zero effect.
Additionally, the studies themselves are mixed at best but most skew little to no effect. Some even net negative (masks may not work and people take risks they normally wouldn’t while wearing). My view is unless you have a N95 mask and other PPE avoid symptomatic people (since thats who spread Covid). Wear one if you want but its very probably a waste of time.
@youyangu has several great threads
As of last week yu could not enter Walmart in our town without a mask. Now the pharmacies have followed suit. The level of fear is palpable. Of course any +’s will be blamed on the young and the non-conforming. Very divisive on top of the fear. I saw a silly chap out fishing alone in his little boat wearing a mask last week. And on top of this the govmint has just announced fines for parties in BC. Total lunacy.
YES!
The pretend experts in Canada never talk about Vitamin D and HCQ. So to me they are politically motivated and medically incompetent. When I mention this Vitamin D deficiency, I get weird looks and comments questioning my medical knowledge. I do not need the knowledge, I have already read the real facts. I sent a letter to our Minister of Health about Vitamin D. I got a standard reply plus a comment that too much Vitamin D is no good. How many people have died from an overdose of |D??? In addition I wonder what treatment is being given in Canada. I bet not HCQ.
Yale University epidemiologist, MD and Professor, recommends HCQ. Many front line doctors are recommending and prescribing it as well. In early stages, right when fever starts. We are being led to a false dichotomy: lock down until a vaccine. What if HCQ is the cure? Evidence is pointing that way.
https://www.newsweek.com/key-defeating-covid-19-already-exists-we-need-start-using-it-opinion-1519535
I totally agree with the recommendation that based on unbiased tests of the HCQ cocktail treatment, the early treatment HCQ cocktail treatment, is a lifesaver for those people who are severely Vit. D deficient and hence will suffer organ damage or death if they get covid and are not treated. See above.
This HCQ cocktail issue is a political atomic bomb issue. Politicians will run for cover rather than risk going to jail.
There is a point, when there is overwhelming real positive data…. …… when fake data to hide a highly effective treatment for covid, becomes a conspiracy to commit murder.
Where is the Bill Gates Foundation? Where are the other ‘charitable’ organization? Has the US become third world corrupt? Does no one care for the people?
“As professor of epidemiology at Yale School of Public Health, I have authored over 300 peer-reviewed publications and currently hold senior positions on the editorial boards of several leading journals.”
“…. In the midst of a crisis, I am fighting for a treatment that the data fully support but which, for reasons having nothing to do with a correct understanding of the science, has been pushed to the sidelines.”
“..As a result, tens of thousands of patients with COVID-19 are dying unnecessarily. Fortunately, the situation can be reversed easily and quickly.”
Since publication of my May 27 article, seven more studies have demonstrated similar benefit.
In a lengthy follow-up letter, also published by AJE, I discuss these seven studies and renew my call for the immediate early use of hydroxychloroquine in high-risk patients.
These seven studies include: an additional 400 high-risk patients treated by Dr. Vladimir Zelenko, with zero deaths;
four studies totaling almost 500 high-risk patients treated in nursing homes and clinics across the U.S., with no deaths;
a controlled trial of more than 700 high-risk patients in Brazil, with significantly reduced risk of hospitalization and two deaths among 334 patients treated with hydroxychloroquine;
and another study of 398 matched patients in France, also with significantly reduced hospitalization risk.
Since my letter was published, even more doctors have reported to me their completely successful use.
There are too many people in power who stand to make money from the “approved” treatment – Rams something or other.
Unfortunately, the established media in Canada is in on the misinformation. They publish daily articles about increased case numbers, but scrupulously omit the figures for hospitalization. The province of Manitoba has a population of 1.4 million, and there are seven (7) people in hospital with COVID-19 in Manitoba. Saskatchewan has a population of 1.2 million and there are five (5) people in hospital with COVID-19 in Saskatchewan. If the media would publish these figures it would immediately confound the notion that this is a serious health crisis. But they don’t. They speak of sharp increases in case numbers, with the implied threat that new case numbers must translate into more hospitalizations and death. Of course the increases in case numbers are in the young, so the hospitalization numbers won’t budge much.
But yeah, it’s crooked. Once the people in charge, including the ranking media have made a mistake (and the reactions to the pandemic have been large and harmful mistakes), their priority then becomes to deny anyone the right to say they have made any mistakes. Which means more suppression of commerce, and more fearmongering by the media.
Flash! Urgent read on Gateway Pundit!
China used THOUSANDS of bogus Twitter accounts to push for the lockdown strategy they used in Wuhan! Twitter thread shows these accounts pushing people all over the world to accept lockdowns as the best means of slowing the spread!
They started in Italy where the first big outbreak occurred; then worked on influencing experts in the US, UK, Europe and Australia! They even managed to get India, who is not an ally of China, to go along!
This is a major story as it shows the ChiComs were willing to destroy the world economy for their sole benefit! The only allies they had were the bought and paid for servants and sycophants that supported the lockdowns in other nations!
“HIT is reached when 1-1/R0 of the population is infected. If R0 is 2.0 – then 50% is HIT, if its 3.3 then ~70% need to be infected. But this isn’t true in the real world.” – Very true.
In fact Dr Levitt et al are showing that it hasn’t got past 20% in any country before dying out. “Pre-Immunity” is about 80% if that turns out to be correct.
Countering the Second Wave with Facts, not Misconceptions
By: Udi Qimron, Uri Gavish, Eyal Shahar, Michael Levitt
https://www.dropbox.com/s/72hi9jfcqfct1n9/Haaretz-20Jul20_ENGLISH%2012082020%20v3.pdf?dl=0
Why do we call it “social distancing” when it is physical? 6 ft. or 2 m. is a physical measurement; learned in 9th grade science class.
A mask, on the other hand, appears to be a social thing — makes those you encounter think you care about them. Learned in college that sociology is the study of group behavior.
Finally, about half of USA folks and likely 90% (I just made that number up) of Canadians are short of Vitamin D.
At least take a 2000 unit pill until you can get a test. Not because of this virus, but because your bodies need it. [ D3 and Zinc might help with this virus; and won’t hurt.]
This last is a useful thing I learned with Panic2020.
Yes, and the “experts” are not mentioning Vitamin D.
I note in today’s newspaper that the Canadian “expert” is warning is about misinformation about vaccines. I am impressed.
Covid virus transmission depends on the age profile of the population, the prevalence of co-morbidities like diabetes, population density and housing type, climate, weather, number of international travellers and their country of origin, use of public transport, take-up of voluntary control measures like physical distancing and hand washing, and government response including border controls, quarantine procedures, and the full range of treatment modalities. Modelling that lot is about as ridiculous as modelling the climate.
Brian,
In your article, you state:
“There are multiple studies that the maximum infectious period of Sars-Cov-2 is about 8 days (known since early March)[xv]. The average time an infected person can infect another is about 4 days with a maximum of 8. The Canadian government model assumes an average of 10 days – which does not align with observable data. There is no science behind this assumption but has the effect of magnifying model spread and generating unnecessary fear.”
Unfortunately, your reference [xv] discusses incubation period which is something completely different. From what I’ve heard, the infectious period is MUCH longer than 10 days and overlaps the asymptomatic period where the virus is still incubating in the individual.
You might want to check the terminology you are using and perhaps the conclusions drawn in this section.
There are a ton of studies on this topic; I only quoted the German because it was published early on. The CDC states from several studies its rare to see replication competent viral spread past 10 days. Not an average as the Canadian model uses. In August.
https://www.cdc.gov/coronavirus/2019-ncov/hcp/duration-isolation.html
“The likelihood of recovering replication-competent virus also declines after onset of symptoms. For patients with mild to moderate COVID-19, replication-competent virus has not been recovered after 10 days following symptom onset (CDC, unpublished data, 2020; Wölfel et al., 2020; Arons et al., 2020; Bullard et al., 2020; Lu et al., 2020; personal communication with Young et al., 2020; Korea CDC, 2020). Recovery of replication-competent virus between 10 and 20 days after symptom onset has been documented in some persons with severe COVID-19 that, in some cases, was complicated by immunocompromised state (van Kampen et al., 2020). However, in this series of patients, it was estimated that 88% and 95% of their specimens no longer yielded replication-competent virus after 10 and 15 days, respectively, following symptom onset.”
Here is another from Muge Cevik. No viable culture has be replicated after 9 days.
https://www.medrxiv.org/content/10.1101/2020.07.25.20162107v2.full.pdf
For some analysis of the age factor in COVID-19 deaths for the province of Ontario, see:
https://thopid.blogspot.com/2020/08/some-covid-19-analyses.html
The analysis shows that, between age 20 and 90+, the risk of death from COVID-19 doubles every 5.8 years older you are. Indeed, for those over 90 years old, fully 35% of those who contracted the disease died from it, at least according to the case numbers published by the province. This extreme trend over a wide age range should inform public policies for reopening as discussed on that page. But Ontario seems almost blind to the importance of age as a factor, other than giving lip service to those over 70.
Wanted to post this somewhere. Perhaps you or someone else on WUWT would investigate and write an article on this:
https://www.youtube.com/watch?v=2uzXHnUViro
Belgian study seems pretty convincing.
Maybe it can save some lives if it can get out into the larger populace and force the politicians to allow lives to be saved.