Doctors Against Borders (Lockdowns)

 

A person holds a sign during a Reopen New Jersey protest in Point Pleasant, N.J., on May 25, 2020. (Michael Loccisano/Getty Images)

Benjamin Turner, MD, MA, FRCSC, is a general surgeon who writes at Epoch Times  Another Doctor Argues Against Lockdown: It’s Time We Ended This Disastrous Policy.  Excerpts in italics with my bolds.

Add my name to the list of physicians who cannot stay silent any longer. The lockdowns must end. They must end immediately and in earnest, not a slow sinking into a morass of rules so complex, illogical, and destructive of privacy as to make lockdown look enjoyable.

In March, the argument for lockdowns was simple: SARS-CoV-2 is far more deadly and infectious than seasonal influenza. A drastic and legally enforced decrease in socialization will prevent the overwhelming of hospitals. The cost of these measures is not to be compared to the loss of even a single life. We now hear a supplementary argument: The death toll was less than projected, but it would have been catastrophic without lockdowns.

Every one of these claims is either questionable or outright false. But if even one point fails, so does the case for lockdowns.

1. SARS-CoV-2 does not have a higher mortality rate than seasonal influenza

Dr. Tedros Adhanom Ghebreyesus, director-general of the World Health Organization, said 3.4 percent of COVID-19 patients die, and far less than 1 percent of influenza patients. Dr. Anthony Fauci, leading member of the White House Coronavirus Task Force, estimated 1 percent fatality, “ten times more lethal than the seasonal flu.” But both had severely underestimated mild cases.

Early in any epidemic, mortality is estimated as the ratio of deaths to confirmed cases; this is the case fatality ratio (CFR). Later, we can compare deaths to all cases, including those who did not seek medical attention; this is the infection fatality ratio (IFR). Tedros’s 3.4 percent refers to the CFR. The flu’s 0.1 to 0.2 percent is an IFR. The two must not be confused.

Antibody studies invariably show prevalence more than 10 times the early estimates, and IFR lower by the same.

In a systematic review by Dr. John Ioannidis, professor of medicine and co-director of the Meta-Research Innovation Center at Stanford, 9 out of 12 studies gave an IFR of 0.16 percent or less. The highest was only 0.4 percent.

2. SARS-CoV-2 is more contagious than the flu in some countries, but not by much

Prof. Neil Ferguson, director of the MRC Centre for Global Infectious Disease Analysis at Imperial College London, and member of the UK’s Scientific Advisory Group for Emergencies, predicted up to 81 percent transmission of SARS-CoV-2. This has happened nowhere, regardless of lockdown.

The highest prevalence in Ioannidis’s review was 25.9 percent. For perspective, 15 percent of the U.S. population contracted influenza in 2017/18.

3. So far, COVID-19 mortality is similar to that of seasonal influenza

Though this could change, the comparison to influenza is presently valid. COVID-19 has killed many thousands, and severely strained some hospitals. But influenza does the same. Only two years ago, influenza forced hospitals in the United States, England, and Italy to cancel elective surgery and use surge capacity, including in tents.

As of May 29, Italy counted 33,229 COVID-19 deaths, 33 percent above 2016/17 flu deaths (24,981), but still below that year’s deaths from influenza-like illnesses in general (43,336).

At 83,142 (CDC provisional count), the United States is even with the 2017/18 flu season, estimated contemporaneously at 80,000. The UK reports 38,489 deaths, similar to the 2014/15 flu (34,300). Globally, COVID-19 is estimated at 372,000 deaths, and the flu at 291,000 to 646,000 annually.

In worse years, influenza wins, hands down. Both the 1957 and the 1968 flu killed between 1 million and 4 million. The 1968 flu killed 100,000 Americans in a population two thirds the present size, and younger; a modern equivalent would exceed 150,000.

4. Deaths may be badly overestimated

There’s good reason to doubt even the numbers above. Early in the pandemic, Prof. Dr. Sucharit Bhakdi, professor emeritus and former head of the Institute for Medical Microbiology and Hygiene at the Johannes Gutenberg University of Mainz in Germany, pointed out that governments were failing to distinguish between deaths “of” and merely “with” SARS-CoV-2.

Prof. Walter Ricciardi, scientific adviser to the Italian minister of health, reports that only 12 percent of Italian “COVID-19” deaths were directly caused by COVID-19. The CDC encourages logging COVID-19 only on suspicion, without lab evidence. On the day New York started this practice, they added 3,700 deaths, about 50 percent of the previous total. Some of these surely died of COVID-19, but since the clinical picture overlaps with COPD, heart failure, and non-pulmonary sepsis, surely many of them did not.

5. The models triggering lockdown were grossly flawed

Around the world, Prof. Ferguson’s model was the most influential. It forecast as many as 2,200,000 dead in the United States and 510,000 in the UK. It was released without its supporting code, which should have disqualified it immediately. It assumed an IFR of 0.9 percent, more than twice the highest estimate discussed above. The highly modified code was released a month late, and severely criticized by numerous programmers, including a team from the University of Edinburgh.

Pro-lockdown scientists from the Uppsala University ran a Swedish model based on Ferguson’s, and predicted 80,000 to 90,000 deaths by mid-May under the present rules, and 20,000 to 30,000 under lockdown. Without any lockdown, Sweden had 3,800 deaths by mid-May, 20 times fewer than predicted. We didn’t avert Ferguson’s forecast; it was just worthless.

6. There is no evidence that lockdowns saved lives

Even if mortality increases well past a bad flu year, that still won’t make lockdowns the right solution. Oxford University’s Blavatnik School of Government maintains a graph of lockdown stringency and prevalence of COVID-19 in different countries, and there’s no correlation between the two.

Dr. Carl Heneghan, director of the Centre for Evidence-Based Medicine, and researchers at both Switzerland’s ETH Zurich and Germany’s Robert Koch Institute have all separately argued that the transmission rate was already decreasing before lockdowns.

Nobel laureate and Stanford professor of structural biology Dr. Michael Levitt has shown that transmission decays at similar rates regardless of lockdown. No wonder, then, that Sweden reached peak infection at the same speed as other countries, and, as of May 31, has a lower overall death rate per million (435) than the UK (567), France (441), Spain (580), Italy (553), and Belgium (817).

If lockdowns make no difference, much less will the half-lockdowns we’re now told to call “normal.”

7. Lockdowns have probably killed people, but the recession will kill more

The UK reports about 20,000 excess deaths outside hospital, not associated with COVID-19. Emergency treatment for heart attacks is down 40 percent in England, implying that enormous numbers of people are not being treated. But widespread poverty may prove more important yet.

Suicide, drug use, and violence all increase with unemployment. Heart disease is directly related to poverty. One shudders to think of the developing world, where the U.N. World Food Program estimates that 130 million more people will be pushed to the brink of starvation. That’s 300 times the number of COVID-19 deaths worldwide.

It’s time we ended this disastrous policy, so aptly described by Prof. Dr. Bhakdi as “collective suicide.” I beg my colleagues who agree with me to break your own silence. We are already late to do our duty.

Benjamin Turner, MD, MA, FRCSC, is a general surgeon working in Alberta, British Columbia, and the Yukon, Canada.

Canadians Much Safer June 1

Update at May 31, 2020
It took a lot of work, but I was able to produce something akin to the Dutch advice to their citizens.

The media and governmental reports focus on total accumulated numbers which are big enough to scare people to do as they are told.  In the absence of contextual comparisons, citizens have difficulty answering the main (perhaps only) question on their minds:  What are my chances of catching Covid19 and dying from it?  The map shows a lot of cases, and the chart looks like an hockey stick, going upward on a straight line. So why do I say canadians are safer than it looks like from such images?

First let’s look at daily numbers to see where we are in this process.  All the statistics come from Canada Public Health Coronavirus disease (COVID-19): Outbreak update.

By showing daily tests, new cases and reported deaths, we can see how the outbreak has built up, peaked and declined over the last 2.5 months.  The green line shows how testing grew to a sustained daily rate of 29,000, with a recent drop and recovery (all numbers are smoothed with 7 day averages ending with the stated date.) Note that the curve is now descending after peaking at 1800 on April 22, now down to 893 new cases per day.  This lower rate of infections is despite the highest rate of testing since the outbreak began. Deaths have also peaked at 177 on May 6, down to 104 May 30. (Reported deaths bumped upward yesterday due to a data transmission catchup in Quebec, explained below).  The percentage of people testing positive is down to 3%, and deaths are 0.42% of the tests administered.

But it matters greatly where in Canada you live.  In the map at the top, Quebec is the dark blue province leading the nation in both cases and deaths.  Quebec has always celebrated being a distinct society, but not in this way. Below is the same chart for the Quebec epidemic from the same dataset. The province has about 23% of the national population and does about 26% of the tests.  But Quebec contributes 56% of the cases and 64% of the deaths, as of yesterday.  Here how the outbreak has gone in La Belle Province.

The Quebec graph is more lumpy showing cases peaking May 1-9, including several days inflated by data catchups. Cases have dropped off recently, from 1100 May 7 down to 521 yesterday.  Deaths are also slowing, declining from 110 on May 7 to 71 May 30. Yesterday the reported deaths in Quebec jumped to 202 due to 165 previously unrecorded data, while the actual new deaths were 37 . The animation below shows the epidemic in Canada with and without Quebec statistics.

But clearly everywhere else in Canada, people are much safer than those living in Quebec.  So what is going on?

To enlarge image, open in new tab.

The graph shows that people in Quebec are dying in group homes, the majority in CHSLD (long term medical care facilities) and also in PSR (private seniors’ residences).  The huge majority of Quebecers in other, more typical living arrangements have very little chance of dying from this disease. Not even prisoners are much at risk.

Of course the other dimension is years of age, since this disease has punished mostly people suffering from end-of-life frailties.  A previous post reported that the Netherlands parliament was provided with the type of guidance everyone wants to see.

For canadians, the most similar analysis is this one from the Daily Epidemiology Update: :

The table presents only those cases with a full clinical documentation, which included some 2194 deaths compared to the 5842 total reported.  The numbers show that under 60 years old, few adults and almost no children have anything to fear.

Update May 20, 2020

It is really quite difficult to find cases and deaths broken down by age groups.  For Canadian national statistics, I resorted to a report from Ontario to get the age distributions, since that province provides 69% of the cases outside of Quebec and 87% of the deaths.  Applying those proportions across Canada results in this table. For Canada as a whole nation:

Age  Risk of Test +  Risk of Death Population
per 1 CV death
<20 0.05% None NA
20-39 0.20% 0.000% 431817
40-59 0.25% 0.002% 42273
60-79 0.20% 0.020% 4984
80+ 0.76% 0.251% 398

In the worst case, if you are a Canadian aged more than 80 years, you have a 1 in 400 chance of dying from Covid19.  If you are 60 to 80 years old, your odds are 1 in 5000.  Younger than that, it’s only slightly higher than winning (or in this case, losing the lottery).

As noted above Quebec provides the bulk of cases and deaths in Canada, and also reports age distribution more precisely,  The numbers in the table below show risks for Quebecers.

Age  Risk of Test +  Risk of Death Population
per 1 CV death
0-9 yrs 0.13% 0 NA
10-19 yrs 0.21% 0 NA
20-29 yrs 0.50% 0.000% 289,647
30-39 0.51% 0.001% 152,009
40-49 years 0.63% 0.001% 73,342
50-59 years 0.53% 0.005% 21,087
60-69 years 0.37% 0.021% 4,778
70-79 years 0.52% 0.094% 1,069
80-89 1.78% 0.469% 213
90  + 5.19% 1.608% 62

While some of the risk factors are higher in the viral hotspot of Quebec, it is still the case that under 80 years of age, your chances of dying from Covid 19 are better than 1 in 1000, and much better the younger you are.

Mr. Trudeau, Take Down This Wall !

Epidemiology Journal: Use HCQ+AZ

Prestigious medical journal urges outpatient use of hydroxychloroquine regimen for COVID-19
Reported at Just The News.  Excerpts in italics with my bolds.

‘These medications need to be widely available and promoted immediately for physicians to prescribe,’ the American Journal of Epidemiology says.

A prestigious medical journal is criticizing news media coverage of hydroxychlorioquine in the battle against coronavirus, saying there is evidence the anti-malarial drug combined with the antibiotic azithromycin helps in the early stages of outpatient treatment.

“These medications need to be widely available and promoted immediately for physicians to prescribe,” the American Journal of Epidemiology reported in an article published this week that pushed back against claims the regimen has been dangerous or ineffective in all cases.

“Hydroxychloroquine plus azithromycin has been widely misrepresented in both clinical reports and public media, and outpatient trials results are not expected until September,” the journal noted, urging medical professionals and the public to recognize there are different stages of the disease that may require different treatments.

The article said the two candidate medications which have been widely reported – remdesivir and hydroxychloroquine plus azithromycin — need to be looked at differently.

“Remdesivir has shown mild effectiveness in hospitalized inpatients, but no trials have been registered in outpatients,” it said.

Meanwhile, the regimen with hydroxychloroquine has been the subject of five studies, including two controlled clinical trials, that “have demonstrated significant major outpatient treatment efficacy.”

The article noted that while there have been some instances of the drug regimen creating heart arrhythmias, the reactions are relatively small compared to those dying from COVID-19.

“Hydroxychloroquine+azithromycin has been used as standard-of-care in more than 300,000 older adults with multicomorbidities, with estimated proportion diagnosed with cardiac arrhythmias attributable to the medications 47/100,000 users, of which estimated mortality is <20%, 9/100,000 users, compared to the 10,000 Americans now dying each week.” the journal said.

The most compelling argument, the journal said, is how hydroxycholoroquine plus azithromycin reduces the rate of mortality.

Below are the percentages of doctors prescribing the hydroxychloroquine plus azithromycin regimen to COVID-19 patients across the globe:

72% in Spain;
49% in Italy;
41% in Brazil;
39% in Mexico;
28% in France;
23% in the US;
17% in Germany;
16% in Canada;
13% in the UK;

And at four New York hospitals, a recent study found that adding zinc sulfate with hydroxychloroquine and azithromycin significantly cuts both the need for intubation and mortality risks by half, researchers said.

Covid Inflation

The story of inflated coronavirus death statistics reminds of decades of climate science manipulations.  When the models produce big scary numbers, and reality fails to rise to predictions, data must be managed to keep scientists’ credibility.  With so much economic damage from shutdowns, many experts are vulnerable to be proven wrong and their advice unfounded.

How this is playing in the pandemic is reported by Timothy Allen & John Lott at Real Clear Politics U.S. COVID-19 Death Toll Is Inflated.  Excerpts in italics with my bolds.

The latest Centers for Disease Control data show that the COVID-19 fatality rate is 0.26% — four times higher than the worst rate for the seasonal flu over the past decade. That is dramatically lower than the World Health Organization’s estimate of 3.4% and Dr. Anthony Fauci’s initial guess of about 2%.

When the CDC projected 1.7 million deaths back in March, it used an estimated death rate of 0.8%. Imperial College’s estimate of 2.2 million deaths assumed a rate of 0.9%. The fear generated by the projections drives the public policy debate. The Washington Post headline, “As deaths mount, Trump tries to convince Americans it’s safe to inch back to normal,” were part of a steady diet of such fare. When Georgia opened up over a month ago, the Post warned: “Georgia leads the race to become America’s No. 1 Death Destination.”

The CDC currently puts the number of confirmed deaths at about 100,000. But even the “best estimate” 0.26% fatality rate is a significant overestimate because of how the CDC is counting deaths. The actual rate is fairly close to a recent bad year for the seasonal flu. And though public health officials have been transparent about how they are counting coronavirus deaths, the implications for calculating the infection fatality rate are not appreciated.

“The case definition is very simplistic,” Dr. Ngozi Ezike, director of Illinois Department of Public Health, explains. “It means, at the time of death, it was a COVID positive diagnosis. That means, that if you were in hospice and had already been given a few weeks to live, and then you also were found to have COVID, that would be counted as a COVID death. It means, technically even if you died of [a] clear alternative cause, but you had COVID at the same time, it’s still listed as a COVID death.”

Medical examiners from Colorado to Michigan use the same definition. In Macomb and Oakland counties in Michigan, where most of the deaths in that state occurred, medical examiners classify any death as a coronavirus death when the postmortem test is positive. Even people who died in suicides and automobile accidents meet that definition.

Such expansive definitions are not due to rogue public health officials. The rules direct them to do this. “If someone dies with COVID-19, we are counting that as a COVID-19 death,” White House coronavirus response coordinator Dr. Deborah Birx recently noted.

Beyond including people with the virus who clearly didn’t die from it, the numbers are inflated by counting people who don’t even have the virus. New York has classified many cases as coronavirus deaths even when postmortem tests have been negative. The diagnosis can be based on symptoms, even though the symptoms are often similar to those of the seasonal flu.

The Centers for Disease Control guidance explicitly acknowledges the uncertainty that doctors can face when identifying the cause of death. When coronavirus cases are “suspected,” the agency counsels doctors that “it is acceptable to report COVID-19 on a death certificate.” This advice has produced a predictable inflation in the numbers. When New York City’s death toll rose above 10,000 on April 21, the New York Times reported that the city included “3,700 additional people who were presumed to have died of the coronavirus but had never tested positive” – more than a 50% increase in the number of cases.

Nor can this be explained by false-negative results in the tests. For the five most commonly used tests, the least reliable test still scored a 96% accuracy rate in laboratory settings. Some doctors report feeling pressure from hospitals to list deaths as being due to the coronavirus, even when the doctors don’t believe that is the case “to make it look a little bit worse than it is.” That is pressure they say they never previously faced in reporting deaths from the seasonal flu.

There are financial incentives that might make a difference for hospitals and doctors. The CARES Act adds a 20% premium for COVID-19 Medicare patients. Birx and others are also concerned that the CDC’s “antiquated” accounting system is double-counting cases and inflating mortality and case counts “by as much as 25%.” When all these anomalies are added up, it becomes apparent that we simply don’t have an accurate death toll from this new coronavirus. But it seems clear that the correct rate is just a little worse than the rate for the 2017-2018 flu.

Meanwhile, the Washington Post, New York Times, and others claim that we are undercounting the true number of deaths. They reach that conclusion by showing that the total number of deaths from all causes is about 30% greater than we would typically expect from March through early May. They then conclude that the excess is due to deaths not being accurately labeled as due to the coronavirus.

But these are not normal times. Many people with heart problems aren’t going to the hospital for fear of the virus. Delaying cancer surgeries and other serious medical treatments for months has real impacts on life expectancies. The stress of the situation is almost certainly increasing suicides and other illnesses. Which is not to minimize the threat: Even if the true death toll is now closer to 50,000 than 100,000, this pandemic is a big deal. But we need some perspective. During the 2017-18 flu season, 61,000 Americans died from the flu.

Public health officials need to face a lot of serious questions about how they counted Coronavirus deaths. We don’t have all the answers yet, but it’s clear the inflated numbers have helped mislead people into a state of alarmism.

Timothy Allen is a governor of the College of American Pathologists and chairs the Department of Pathology at the University of Mississippi Medical Center.

John Lott is the president of the Crime Prevention Research Center.

See also Man Made Warming from Adjusting Data

Cartoon by Josh at cartoonsbyjosh.com

Confusing Urgent with Important

One of the things we learned in organizational science was that managers are prone to focus attention and resources on urgent situations at the expense of more serious threats to viability.  Thus the aphorism:  “When you are up to your ass in alligators it’s difficult to remember that your initial objective was to drain the swamp”.  Many times we consultants saw clients working hard to put out fires (complaints, delays, etc.) while oblivious to strategic weaknesses eroding their ability to compete with rivals.  One memorable client responded to our product profitabilty analysis showing why they were losing money, “I can’t drop that product, it’s our best seller!”

All this by way of introduction to an article at Real Clear Politics Miscalculating Risk: Confusing Scary With Dangerous  In this case the subject is evaluating risks, but the mistake can also be made regarding opportunities. Excerpts in italics with my bolds.

The coronavirus kills, everyone knows it. But this isn’t the first deadly virus the world has seen, so what happened? Why did we react the way we did? One answer is that this is the first social media pandemic. News and narratives travel in real-time right into our hands.

This spreads fear in a way we have never experienced. Drastic and historically unprecedented lockdowns of the economy happened and seemed to be accepted with little question.

We think the world is confusing “scary” with “dangerous.” They are not the same thing. It seems many have accepted as fact that coronavirus is one of the scariest things the human race has ever dealt with. But is it the most dangerous? Or even close?

There are four ways to categorize any given reality. It can be scary but not dangerous, scary and dangerous, dangerous but not scary, or not dangerous and not scary.

Clearly, COVID-19 ranks high on the scary scale. A Google news search on the virus brings up over 1.5 billion news results. To date, the virus has tragically killed nearly 100,000 people in the United States, and more lives will be lost. But on a scale of harmless to extremely dangerous, it would still fall into the category of slightly to mildly dangerous for most people, excluding the elderly and those with preexisting medical conditions.

In comparison, many have no idea that heart disease is the leading cause of death in the United States, killing around 650,000 people every year, 54,000 per month, or approximately 200,000 people between February and mid-May of this year. This qualifies as extremely dangerous. But most people are not very frightened of it. A Google news search for heart disease brings up around 100 million results, under one-fifteenth the results of the COVID-19 search.

It’s critical to be able to distinguish between fear and danger. Fear is an emotion, it’s the risk that we perceive. As an emotion, it is often blind to the facts. For example, the chances of dying from a shark attack are minuscule, but the thought still crosses most people’s minds when they play in the ocean. Danger is measurable, and in the case of sharks, the danger is low, even if fear is sometimes high.

Imagine if an insurance actuary was so scared of something that she graded it 1,000 times riskier than the data showed. This might be a career-ending mistake. This is exactly what people have done regarding COVID-19: making decisions on fear and not data.

According to CDC data, 81% of deaths from COVID-19 in the United States are people over 65 years old, most with preexisting conditions. If you add in 55-64-year-olds that number jumps to 93%. For those below age 55, preexisting conditions play a significant role, but the death rate is currently around 0.0022%, or one death per 45,000 people in this age range. Below 25 years old the fatality rate of COVID-19 is 0.00008%, or roughly one in 1.25 million, and yet we have shut down all schools and day-care centers, some never to open again! This makes it harder for mothers and fathers to remain employed.

All life is precious. No death should be ignored, but we have allowed our fear to move resources away from areas that are more dangerous, but less scary, to areas that are scary, but less dangerous. And herein lies the biggest problem.

Hospitals and doctors’ offices have had to be much more selective in the people they are seeing, leaving beds open for COVID-19 patients and cutting out elective surgeries. According to Komodo, in the weeks following the first shelter-in-place orders, cervical cancer screenings were down 68%, cholesterol panels were down 67%, and the blood sugar tests to detect diabetes were off 65% nationally.

It doesn’t stop there. The U.N. estimates that infant mortality rates could rise by hundreds of thousands in 2020 because of the global recession and diverted health care resources. Add in opioid addiction, alcoholism, domestic violence and other detrimental reactions from job loss and despair. It’s tragic.

The benefits gained through this fear-based shutdown (if there really are any) have massively increased dangers in the both the short term and the long term. Every day that businesses are shuttered, and people remain unemployed or underemployed, the economic wounds grow more deadly. The loss of wealth is immense, and this will undermine the ability of nations around the world to deal with true dangers for decades to come, maybe forever. We have altered the course of economic growth.

Shutting down the private sector (which is where all wealth is created) is truly dangerous even though many of our leaders suggest we shouldn’t be scared of it. Another round of stimulus is not what we need. Like a Band-Aid on a massive laceration, it may stop a tiny bit of the bleeding, but the wound continues to worsen, feeding greater and more elaborate intervention. Moreover, we are putting huge financial burdens on future generations because we are scared about something that the data reveal as far less dangerous than many other things in life.

A shutdown may slow the spread of a virus, but it can’t stop it. A vaccine may cure us. But in the meantime, we have entered a new era, one in which fear trumps danger and near-term risk creates long-term problems. It appears many people have come to this realization as the data builds. Hopefully, this will go down in history as a mistake that we will never repeat.

 

 

Georgians Dine Out, Pundits Eat Crow

Matthew Walther writes at the Week We should be grateful for good news in Georgia.  Excerpts in italics with my bolds.

I hate to be the bearer of bad news, but Atlanta is not burning. Bodies are not piled up in the streets. Hospitals in Georgia are not being overwhelmed; in fact, they are virtually empty. There is no mad rush for ventilators (remember those?). Instead, men, women, and children in the Peach State are returning to some semblance of normal life: working outside their homes, going to restaurants and bars, getting haircuts, exercising, and most important, spending time with their friends and families and worshipping God. The opening that began more than three weeks ago is continuing apace.

Oh, my apologies, you were waiting for bad news? Sorry, I forgot, we were actually not supposed to be rooting for the virus. Despite the apparent relish behind headlines like “Georgia’s Experiment in Human Sacrifice,” one assumes that most Americans, even the ones most committed to omnidirectional prophecies of doom, were actually hoping this would happen. While it really is a shame that we do not get to gloat about the cravenness and stupidity of yet another GOP politician, I think on balance most of us will be glad to hear that Gov. Brian Kemp was not badly wrong here.

What is happening instead of the widely predicted bloodbath? Confirmed cases of the virus are obviously increasing (though the actual rolling weekly average of new ones have been headed down for nearly a month) while deaths remain more or less flat. This is in fact what happens when you test more people for a disease that is not fatal or even particularly serious for the vast majority of those who contract it, for which the median age of death is higher than the American life expectancy.

How was this possible? One answer is that the lockdown did not in fact do what it was supposed to do, which is to say, meaningfully impede transmission of the virus.

In fact, data both from states like Georgia and from abroad suggests that the lifting of lockdowns is positively correlated with a decrease in rates of infection. This could be because lockdowns are inherently ineffective at slowing down a disease whose spread appears to be largely intrafamilial and nosocomial.

It could also be the weather. That’s right: another thing that we were told months ago not even to suggest aloud because it would be irresponsible to make assumptions of any kind about the virus, even sensible ones, like the idea that wearing masks just might help slow it down. This is not science. COVID-19 arrived from China, not from outer space. Unsurprisingly, it appears to behave very much like other respiratory viruses, including influenza. It hates sunlight and the outdoors generally and prefers cramped stuffy conditions, like those found in public transit systems and dense housing complexes with poor ventilation.

It is worth pointing out here that journalists and Democratic politicians (most notably Stacey Abrams, the former Georgia state representative who labors under the bizarre illusion that she won a statewide election there two years ago and would now like to be vice president) were not the only critics of Gov. Kemp. After a series of spasmodic muscular contractions that seemed to have resulted in tweets calling upon unnamed persons to “liberate” various states, President Trump changed his mind and insisted on more than one occasion that he “strongly disagreed” with the decision to open Georgia. Expecting anything resembling consistency from this president is a fool’s errand, but one hopes that at least some of his supporters remember that he was wrong here.

None of what I have written above should be taken to suggest that Kemp’s handling of the pandemic is above reproach, or that he should receive a medal for clear-sightedness here. (I might give one instead to Gov. Ron DeSantis of Florida, where amid shrill moaning about the non-existent dangers of people standing on beaches, thousands of lives may have been saved by a swift executive order banning the re-introduction of coronavirus patients to elder care facilities). Nor am I suggesting that things in the Peach State cannot possibly take a turn for the worse, especially if appropriate measures are not taken in nursing homes.

Two much narrower claims are being made. The first is that those who insisted that Georgia would be transformed into a post-apocalyptic wasteland within days or even weeks of reopening were wrong, and predictably so.

The second is that this is something about which we should be happy.

Update: Canadians Are Safer Than They Think

Update at End May 20, 2020
It took a lot of work, but I was able to produce something akin to the Dutch advice to their citizens.

Original Post:

The media and governmental reports focus on total accumulated numbers which are big enough to scare people to do as they are told.  In the absence of contextual comparisons, citizens have difficulty answering the main (perhaps only) question on their minds:  What are my chances of catching Covid19 and dying from it?  The map shows a lot of cases, and the chart looks like an hockey stick, going upward on a straight line. So why do I say canadians are safer than it looks like from such images?

First let’s look at daily numbers to see where we are in this process.  All the statistics come from Canada Public Health Coronavirus disease (COVID-19): Outbreak update.

By showing daily tests, new cases and reported deaths, we can see how the outbreak has built up over the last 2 months or so.  The green line shows how testing has grown to a sustained daily rate of 30,000 (all numbers are smoothed with 7 day averages ending with the stated date.) Note that the curve is now descending after peaking at 1800 on May 3, now down to 1156 new cases per day.  This lower rate of infections is despite the highest rate of testing since the outbreak began. Deaths have also peaked at 177 on May 6, down to 121 yesterday.  The percentage of people testing positive is down to 4%, and deaths are 0.42% of the tests administered.

But it matters greatly where in Canada you live.  In the map at the top, Quebec is the dark blue province leading the nation in both cases and deaths.  Quebec has always celebrated being a distinct society, but not in this way. Below is the same chart for the Quebec epidemic from the same dataset. The province has about 23% of the national population and does about 25% of the tests.  But Quebec contributes 56% of the cases and 62% of the deaths, as of yesterday.  Here how the outbreak has gone in La Belle Province.

Cases have dropped off recently, from 1100 May 9 down to 737 yesterday.  Deaths are also slowing, declining from 110 on May 7 to 83 yesterday. The animation below shows the epidemic in Canada with and without Quebec statistics.

But clearly everywhere else in Canada, people are much safer than those living in Quebec.  So what is going on?

To enlarge image, open in new tab.

The graph shows that people in Quebec are dying in group homes, the majority in CHSLD (long term medical care facilities) and also in PSR (private seniors’ residences).  The huge majority of Quebecers in other, more typical living arrangements have very little chance of dying from this disease. Not even prisoners are much at risk.

Of course the other dimension is years of age, since this disease has punished mostly people suffering from end-of-life frailties.  A previous post reported that the Netherlands parliament was provided with the type of guidance everyone wants to see.

For canadians, the most similar analysis is this one from the Daily Epidemiology Update: :

The table presents only those cases with a full clinical documentation, which included some 2194 deaths compared to the 5842 total reported.  The numbers show that under 60 years old, few adults and almost no children have anything to fear.

Update May 20, 2020

It is really quite difficult to find cases and deaths broken down by age groups.  For Canadian national statistics, I resorted to a report from Ontario to get the age distributions, since that province provides 69% of the cases outside of Quebec and 87% of the deaths.  Applying those proportions across Canada results in this table. For Canada as a whole nation:

Age  Risk of Test +  Risk of Death Population
per 1 CV death
<20 0.05% None NA
20-39 0.20% 0.000% 431817
40-59 0.25% 0.002% 42273
60-79 0.20% 0.020% 4984
80+ 0.76% 0.251% 398

In the worst case, if you are a Canadian aged more than 80 years, you have a 1 in 400 chance of dying from Covid19.  If you are 60 to 80 years old, your odds are 1 in 5000.  Younger than that, it’s only slightly higher than winning (or in this case, losing the lottery).

As noted above Quebec provides the bulk of cases and deaths in Canada, and also reports age distribution more precisely,  The numbers in the table below show risks for Quebecers.

Age  Risk of Test +  Risk of Death Population
per 1 CV death
0-9 yrs 0.13% 0 NA
10-19 yrs 0.21% 0 NA
20-29 yrs 0.50% 0.000% 289,647
30-39 0.51% 0.001% 152,009
40-49 years 0.63% 0.001% 73,342
50-59 years 0.53% 0.005% 21,087
60-69 years 0.37% 0.021% 4,778
70-79 years 0.52% 0.094% 1,069
80-89 1.78% 0.469% 213
90  + 5.19% 1.608% 62

While some of the risk factors are higher in the viral hotspot of Quebec, it is still the case that under 80 years of age, your chances of dying from Covid 19 are better than 1 in 1000, and much better the younger you are.

Mr. Trudeau, Take Down This Wall !

Canadians Are Safer Than They Think

The media and governmental reports focus on total accumulated numbers which are big enough to scare people to do as they are told.  In the absence of contextual comparisons, citizens have difficulty answering the main (perhaps only) question on their minds:  What are my chances of catching Covid19 and dying from it?  The map shows a lot of cases, and the chart looks like an hockey stick, going upward on a straight line. So why do I say canadians are safer than it looks like from such images?

First let’s look at daily numbers to see where we are in this process.  All the statistics come from Canada Public Health Coronavirus disease (COVID-19): Outbreak update.

By showing daily tests, new cases and reported deaths, we can see how the outbreak has built up over the last 2 months or so.  The green line shows how testing has grown to a sustained daily rate of 30,000 (all numbers are smoothed with 7 day averages ending with the stated date.) Note that the curve is now descending after peaking at 1800 on May 3, now down to 1156 new cases per day.  This lower rate of infections is despite the highest rate of testing since the outbreak began. Deaths have also peaked at 177 on May 6, down to 121 yesterday.  The percentage of people testing positive is down to 4%, and deaths are 0.42% of the tests administered.

But it matters greatly where in Canada you live.  In the map at the top, Quebec is the dark blue province leading the nation in both cases and deaths.  Quebec has always celebrated being a distinct society, but not in this way. Below is the same chart for the Quebec epidemic from the same dataset. The province has about 23% of the national population and does about 25% of the tests.  But Quebec contributes 56% of the cases and 62% of the deaths, as of yesterday.  Here how the outbreak has gone in La Belle Province.

Cases have dropped off recently, from 1100 May 9 down to 737 yesterday.  Deaths are also slowing, declining from 110 on May 7 to 83 yesterday.

But clearly everywhere else in Canada, people are much safer than those living in Quebec.  So what is going on?

To enlarge image, open in new tab.

The graph shows that people are dying in group homes, the majority in CHSLD (long term medical care facilities) and also in PSR (private seniors’ residences).  The huge majority of Quebecers in other, more typical living arrangements have very little chance of dying from this disease. Not even prisoners are much at risk.

Of course the other dimension is years of age, since this disease has punished mostly people suffering from end-of-life frailties.  A previous post reported that the Netherlands parliament was provided with the type of guidance everyone wants to see.

For canadians, the most similar analysis is this one from the Daily Epidemiology Update: :

The table presents only those cases with a full clinical documentation, which included some 2194 deaths compared to the 5842 total reported.  The numbers show that under 60 years old, few adults and almost no children have anything to fear.

#1 Pandemic Question: Dutch Answer & CDC Silence

Only one question matters to people:  What is my risk of getting Covid19 and dying from it?  Daniel Horowitz explains that the Dutch have answered this question while the US CDC has not. See One chart exposes the lie behind universal lockdowns in the Conservative Review. Excerpts in italics with my bolds.

What is the true infection fatality rate of COVID-19, broken down by age and health status?

This is a simple question for which the CDC should have a clear answer by now, accompanied by a readable chart – a chart showing everyone’s demographic risk assessment so that we can better target our infection mitigation efforts.

Yet it’s the one thing our government hasn’t done. Wonder why?

Take a look at the above chart (which I translated into English using Google Translate) prepared by the Economisch Statistische Berichten (ESB), a Dutch economics magazine, quantifying the infection fatality rate for the Dutch population based on age bracket. The data were calculated from an antibody test of 4,000 blood donors conducted by Dutch blood bank Sanquin to see how many have been infected for the purpose of donating blood plasma to those currently suffering from the virus. The data were presented to the Dutch House of Representatives in mid-April by the National Institute for Public Health and the Environment (RIVM).

Based on this serology test, they were able to determine that 3% of the population (at the time) were infected and were therefore able to divide the numerator of those who died of COVID-19 by the extrapolated denominator of those who were likely infected and break out the infection fatality rate by age group.

Study this chart for a few minutes and take in all the data – from the asymptomatic/mildly symptomatic rates to the hospital and fatality rates divided by age. You have to get to the 50-59 age group just to reach a 0.1% fatality rate, the level often cited as the overall death rate for the seasonal flu. Those are all lower odds than an individual has of dying in a giving year of any cause and in the case of an average 50-year-old, five times lower.

They didn’t test kids under 20, but their fatality rate is likely near zero.

While the Netherlands is an entirely different country, it has actually experienced a 30% higher death rate per capita than America. So the numbers are likely not any higher here for those under 70, especially because the macro serology tests showing a 0.2% fatality rate (but grossly distorted by the death rate of those over 80), as well as what we are seeing in prisons and ships in younger populations, seems to harmonize with this data. A brand-new study from France also shows very similar estimates of fatality rates, at least for those under 60.

If anything, those who are sicker tend to stay away from blood donation, so it could be that infection rate was even higher than this sample suggests, thereby driving down the fatality rate even lower.

Moreover, several weeks later, another research group in the Netherlands did a second serology test that broke down even more groups and came up with almost identical results:

As you can see, the death rate doesn’t even climb above 1% until you reach over 70, with a steep and dangerous growth of risk over 75 and 80. However, it’s important to remember that even those death rates might need to be cut in half for those outside nursing homes, given that half the deaths in most countries are in senior care facilities.

Why has our government not put out a similar chart? How many Americans even know that children have near-zero threat and anyone under 60 has next to no risk of dying from the virus? Even those between 60 and 69 are at much lower risk than anything the government has suggested and that the level of panic indicates. The World Health Organization wrongly pegged the overall death rate for all ages at 3.4% on average. This simple fact makes a world of difference both to our targeted response to the virus and also to the degree of panic that should and should not be infused into society so as not to keep people away from hospitals when they are experiencing other potentially dangerous medical conditions.

But even this chart doesn’t tell the full story. The virus lopsidedly targets people with particular underlying conditions, such as heart disease and diabetes. It is simply criminal that, with the tens of billions of dollars in “emergency” funding, the CDC has not conducted or published the results of a survey of 20,000 or so Americans to determine the exact number of infections and the fatality rate broken down by each health and age status. To most Americans, based on what the government and media have been putting out, it’s all the same and even babies will all die, as if there is a 50% fatality rate. Most people I know think their infants are in danger from COVID-19, even though the threat of flu and SIDS is much more pervasive in infants than that of coronavirus.

Consequently, we destroyed our entire country and sacked the Constitution all for a very narrow and specific problem that required a precise and balanced approach. Yet two months into this mistake, our government won’t even put out the simple math demonstrating this obvious point. As one commentator so aptly observed,

“Homogenous intervention in the face of heterogenous risk is just cruelty passed off as equality.”

Media Turn Math Dopes into Dupes

Those who have investigated global warming/climate change discovered that the numbers don’t add up. But if you don’t do the math you wouldn’t know that, because in the details is found the truth (the devilish contradictions to sweeping claims). Those without numerical literacy (including apparently most journalists) are at the mercy of the loudest advocates. Social policy then becomes a matter of going along with herd popularity. Shout out to AOC!

Now we get the additional revelation regarding pandemic math and the refusal to correct over-the-top predictions. It’s the same dynamic but accelerated by the more immediate failure of models to forecast contagious reality. Sean Trende writes at Real Clear Politics The Costly Failure to Update Sky-Is-Falling Predictions. Excerpts in italics with my bolds.

On March 6, Liz Specht, Ph.D., posted a thread on Twitter that immediately went viral. As of this writing, it has received over 100,000 likes and almost 41,000 retweets, and was republished at Stat News. It purported to “talk math” and reflected the views of “highly esteemed epidemiologists.” It insisted it was “not a hypothetical, fear-mongering, worst-case scenario,” and that, while the predictions it contained might be wrong, they would not be “orders of magnitude wrong.” It was also catastrophically incorrect.

The crux of Dr. Specht’s 35-tweet thread was that the rapid doubling of COVID-19 cases would lead to about 1 million cases by May 5, 4 million by May 11, and so forth. Under this scenario, with a 10% hospitalization rate, we would expect approximately 400,000 hospitalizations by mid-May, which would more than overwhelm the estimated 330,000 available hospital beds in the country. This would combine with a lack of protective equipment for health care workers and lead to them “dropping from the workforce for weeks at a time,” to shortages of saline drips and so forth. Half the world would be infected by the summer, and we were implicitly advised to buy dry goods and to prepare not to leave the house.

Interestingly, this thread was wrong not because we managed to bend the curve and stave off the apocalypse; for starters, Dr. Specht described the cancellation of large events and workplace closures as something that would shift things by only days or weeks.

Instead, this thread was wrong because it dramatically understated our knowledge of the way the virus worked; it fell prey to the problem, common among experts, of failing to address adequately the uncertainty surrounding its point estimates. It did so in two opposing ways. First, it dramatically understated the rate of spread. If serological tests are to be remotely believed, we likely hit the apocalyptic milestone of 2 million cases quite some time ago. Not in the United States, mind you, but in New York City, where 20% of residents showed positive COVID-19 antibodies on April 23. Fourteen percent of state residents showed antibodies, suggesting 2.5 million cases in the Empire State alone; since antibodies take a while to develop, this was likely the state of affairs in mid-April or earlier.

But in addition to being wrong about the rate of spread, the thread was also very wrong about the rate of hospitalization. While New York City found its hospital system stretched, it avoided catastrophic failure, despite having within its borders the entire number of cases predicted for the country as a whole, a month earlier than predicted. Other areas of the United States found themselves with empty hospital beds and unused emergency capacity.

One would think that, given the amount of attention this was given in mainstream sources, there would be some sort of revisiting of the prediction. Of course, nothing of the sort occurred.

This thread has been absolutely memory-holed, along with countless other threads and Medium articles from February and March. We might forgive such forays on sites like Twitter and Medium, but feeding frenzies from mainstream sources are also passed over without the media ever revisiting to see how things turned out.

Consider Florida. Gov. Ron DeSantis was castigated for failing to close the beaches during spring break, and critics suggested that the state might be the next New York. I’ve written about this at length elsewhere, but Florida’s new cases peaked in early April, at which point it was a middling state in terms of infections per capita. The virus hasn’t gone away, of course, but the five-day rolling average of daily cases in Florida is roughly where it was in late March, notwithstanding the fact that testing has increased substantially. Taking increased testing into account, the positive test rate has gradually declined since late March as well, falling from a peak of 11.8% on April 1 to a low of 3.6% on May 12.

Notwithstanding this, the Washington Post continues to press stories of public health officials begging state officials to close beaches (a more interesting angle at this point might be why these health officials were so wrong), while the New York Times noted a few days ago (misleadingly, and grossly so) that “Florida had a huge spike in cases around Miami after spring break revelry,” without providing the crucial context that the caseload mimicked increases in other states that did not play host to spring break. Again, perhaps the real story is that spring breakers passed COVID-19 among themselves and seeded it when they got home. I am sure some of this occurred, but it seems exceedingly unlikely that they would have spread it widely among themselves and not also spread it widely to bartenders, wait staff, hotel staff, and the like in Florida.

Florida was also one of the first states to experiment with reopening. Duval County (Jacksonville) reopened its beaches on April 19 to much national skepticism. Yet daily cases are lower today than they were they day that it reopened; there was a recent spike in cases associated with increased testing, but it is now receding.

Or consider Georgia, which one prominent national magazine claimed was engaging in “human sacrifice” by reopening. Yet, after nearly a month, a five-day average of Georgia’s daily cases looks like this:

What about Wisconsin, which was heavily criticized for holding in-person voting? It has had an increased caseload, but that is largely due to increased testing (up almost six-fold since early April) and an idiosyncratic outbreak in its meatpacking plants. The latter is tragic, but it is not related to the election; in fact, a Milwaukee Journal-Sentinel investigation failed to link any cases to the election; this has largely been ignored outside of conservative media sites such as National Review.

We could go on – after being panned for refusing to issue a stay-at-home order, South Dakota indeed suffered an outbreak (once again, in its meatpacking plants), but deaths there have consistently averaged less than three per day, to little fanfare – but the point is made. Some “feeding frenzies” have panned out, but many have failed to do so; rather than acknowledging this failure, the press typically moves on.

This is an unwelcome development, for a few reasons. First, not everyone follows this pandemic closely, and so a failure to follow up on how feeding frenzies end up means that many people likely don’t update their views as often as they should. You’d probably be forgiven if you suspected hundreds of cases and deaths followed the Wisconsin election.

Second, we obviously need to get policy right here, and to be sure, reporting bad news is important for producing informed public opinion. But reporting good news is equally as important. Third, there are dangers to forecasting with incredible certitude, especially with a virus that was detected less than six months ago. There really is a lot we still don’t know, and people should be reminded of this. Finally, among people who do remember things like this, a failure to acknowledge errors foments cynicism and further distrust of experts.

The damage done to this trust is dangerous, for at this time we desperately need quality expert opinions and news reporting that we can rely upon.

Addendum:  Tilak Doshi makes the comparison to climate crisis claims Coronavirus And Climate Change: A Tale Of Two Hysterias writing at Forbes.  Excerpts in italics with my bolds.

It did not take long after the onset of the global pandemic for people to observe the many parallels between the covid-19 pandemic and climate change. An invisible novel virus of the SARS family now represents an existential threat to humanity. As does CO2, a colourless trace gas constituting 0.04% of the atmosphere which allegedly serves as the control knob of climate change. Lockdowns are to the pandemic what decarbonization is to climate change. Indeed, lockdowns and decarbonization share much in common, from tourism and international travel to shopping and having a good time. It would seem that Greta Thunberg’s dreams have come true, and perhaps that is why CNN announced on Wednesday that it is featuring her on a coronavirus town-hall panel alongside health experts.

But, beyond being a soundbite and means of obtaining political cover, ‘following the science’ is neither straightforward nor consensual. The diversity of scientific views on covid-19 became quickly apparent in the dramatic flip-flop of the UK government. In the early stages of the spread in infection, Boris Johnson spoke of “herd immunity”, protecting the vulnerable and common sense (à la Sweden’s leading epidemiologist Professor Johan Giesecke) and rejected banning mass gatherings or imposing social distancing rules. Then, an unpublished bombshell March 16th report by Professor Neil Ferguson of Imperial College, London, warned of 510,000 deaths in the country if the country did not immediately adopt a suppression strategy. On March 23, the UK government reversed course and imposed one of Europe’s strictest lockdowns. For the US, the professor had predicted 2.2 million deaths absent similar government controls, and here too, Ferguson’s alarmism moved the federal government into lockdown mode.

Unlike climate change models that predict outcomes over a period of decades, however, it takes only days and weeks for epidemiological model forecasts to be falsified by data. Thus, by March 25th, Ferguson’s predicted half a million fatalities in the UK was adjusted downward to “unlikely to exceed 20,000”, a reduction by a factor of 25. This drastic reduction was credited to the UK’s lockdown which, however, was imposed only 2 days previously, before any social distancing measures could possibly have had enough time to work.

For those engaged in the fraught debates over climate change over the past few decades, the use of alarmist models to guide policy has been a familiar point of contention. Much as Ferguson’s model drove governments to impose Covid-19 lockdowns affecting nearly 3 billion people on the planet, Professor Michael Mann’s “hockey stick” model was used by the IPCC, mass media and politicians to push the man-made global warming (now called climate change) hysteria over the past two decades.

As politicians abdicate policy formulation to opaque expertise in highly specialized fields such as epidemiology or climate science, a process of groupthink emerges as scientists generate ‘significant’ results which reinforce confirmation bias, affirm the “scientific consensus” and marginalize sceptics.

Rather than allocating resources and efforts towards protecting the vulnerable old and infirm while allowing the rest of the population to carry on with their livelihoods with individuals taking responsibility for safe socializing, most governments have opted to experiment with top-down economy-crushing lockdowns. And rather than mitigating real environmental threats such as the use of traditional biomass for cooking indoors that is a major cause of mortality in the developing world or the trade in wild animals, the climate change establishment advocates decarbonisation (read de-industrialization) to save us from extreme scenarios of global warming.

Taking the wheels off of entire economies on the basis of wildly exaggerated models is not the way to go.

Footnote: Mark Hemingway sees how commonplace is the problem of uncorrected media falsity in his article When Did the Media Stop Running Corrections? Excerpts in italics with my bolds.

Vanity Fair quickly recast Sherman’s story without acknowledging its error: “This post has been updated to include a denial from Blackstone, and to reflect comments received after publication by Charles P. Herring, president of Herring Networks, OANN’s parent company.” In sum, Sherman based his piece on a premise that was wrong, and Vanity Fair merely acted as if all the story needed was a minor update.

Such post-publication “stealth editing” has become the norm. Last month, The New York Times published a story on the allegation that Joe Biden sexually assaulted a former Senate aide. After publication, the Times deleted the second half of this sentence: “The Times found no pattern of sexual misconduct by Mr. Biden, beyond the hugs, kisses and touching that women previously said made them uncomfortable.”

In an interview with Times media columnist Ben Smith, Times’ Executive Editor Dean Baquet admitted the sentence was altered at the request of Biden’s presidential campaign. However, if you go to the Times’ original story on the Biden allegations, there’s no note saying how the story was specifically altered or why.

It’s also impossible not to note how this failure to issue proper corrections and penchant for stealth editing goes hand-in-hand with the media’s ideological preferences.

In the end the media’s refusal to run corrections is a damnable practice for reasons that have nothing to do with Christianity. In an era when large majorities of the public routinely tell pollsters they don’t trust the media, you don’t have to be a Bible-thumper to see that admitting your mistakes promptly, being transparent about trying to correct them, and when appropriate, apologizing and asking for forgiveness – are good secular, professional ethics.