If you’re a public-minded student or teacher committed to reducing the death toll from Covid-19, what is the morally correct way to behave?
According to the epidemiologist Sunetra Gupta, you should do just about the opposite of what’s being preached by college presidents, teachers’ unions, political leaders, and the scientific and media establishment. Unless you’re elderly or particularly vulnerable, you shouldn’t be wearing a mask all day, or shaming others for going unmasked. You should be careful not to endanger the vulnerable, but otherwise you should be exposing yourself to the virus in order to promote herd immunity.
Gupta, 55, wants to teach her classes at Oxford in person, without a mask, and she is appalled at her colleagues’ reluctance to go back to the classroom.
“It’s such a disservice to this generation of students,” she says. “Teachers and students who are vulnerable should have the option to go online, but for the rest of us this virus is no bigger than other risks we take in daily life. It’s not rational, and certainly not communitarian, to avoid being infected with a pathogen that carries such a low risk to you when there’s a high benefit to the community by helping to create herd immunity.”
Gupta’s strategy is heresy to the public-health establishment, but it seems to be paying off in Sweden, and her research team at Oxford has a far better track record on Covid-19 than the scientists whose work inspired the widespread lockdowns and mask mandates in the first place. In March, when Neil Ferguson’s team at Imperial College London terrified politicians and the public with its projections of Covid deaths—more than 500,000 in Britain and 2 million in the United States—Gupta’s team warned that this scenario was based on dubious assumptions about the virus’s spread and lethality.
The Imperial computer model assumed that most of the population had not yet been exposed to an exceptionally lethal virus, so lockdowns were the only way to avoid mass casualties. Gupta’s model, by contrast, assumed that many people had already been exposed without suffering serious consequences. That meant that the virus wasn’t so lethal and that the United Kingdom and other places were already developing herd immunity, making lockdowns unnecessary. Gupta was dubbed “Professor Reopen”—as opposed to Imperial’s “Professor Lockdown”—and she was pilloried along with the few others who shared her views.
Officials at the World Health Organization and the National Institutes of Health condemned the strategy of relying on herd immunity. Anthony Fauci, the White House advisor, said that it would lead to a “completely unacceptable” number of deaths—perhaps more than 10 million Americans, by one calculation published by scientists in the New York Times. A group of Swedish doctors and scientists denounced their country for keeping day-care centers, primary schools, bars, restaurants, and stores open, declaring in late July that the policy was leading to needless “death, grief and suffering” because Sweden was “nowhere near herd immunity.”
In fact, though, this strategy now seems to have fostered herd immunity in Sweden and other places. The number of daily Covid deaths in Sweden, which peaked at 115 in April, has averaged just two since the beginning of August. Fewer than 6,000 Swedes have died, a far cry from the nearly 100,000 deaths projected by the Imperial model. Per capita, the United States and Britain have suffered more Covid deaths than Sweden, and the fatality rates in the states of New York and New Jersey are three times higher than Sweden’s.
It’s true, as lockdown proponents often point out, that the fatality rate is higher in Sweden than in neighboring Nordic countries. But most of that disparity, according to a recent analysis by George Mason University economist Daniel Klein and colleagues from Scandinavia, is due to factors unrelated to those neighbors’ lockdowns, which were actually quite light and short-lived compared with those in Britain and the northeastern United States. (In Norway and Finland, for instance, schools reopened in May, and bars and restaurants reopened in early June.) Even before any of the lockdowns, Sweden was harder hit than its neighbors, partly because it had relatively more immigrants and international travelers, but mainly because of its larger proportion of highly vulnerable old people, particularly in nursing homes.
During the summer, Sweden’s critics pointed to seroprevalence surveys showing that fewer than 20 percent of Swedes had developed antibodies to the virus, well below the level of 60 percent to 70 percent assumed to be the threshold for herd immunity. But that was likely another mistaken assumption, Gupta’s team and other researchers believe, because the antibody tests miss so many people who are effectively immune to the virus.
Some of these people are immune because they have antibodies not detected by the tests, and many others—perhaps 20 percent to 50 percent of the population—have developed resistance through previous exposure to other coronaviruses. Once these people are accounted for, herd immunity could be reached even if the antibody tests show a prevalence as low as 10 to 20 percent.
That means that many places besides Sweden could have reached or approached herd immunity. In New York City, nearly a quarter of the residents tested positive for antibodies in the state’s survey in April. The city’s graph of Covid deaths maps a curve much like the one recorded in Sweden without a lockdown: a peak in April, falling to a straight line barely above zero since July, despite the city’s gradual reopening of restaurants and businesses. After looking at the data, one team of researchers recently concluded that New York City has likely crossed the herd-immunity threshold, meaning that a lockdown would not be necessary to protect the city against a much-feared strong second wave.
Herd immunity cannot eliminate deaths; like ordinary flu viruses, Covid-19 will remain endemic even if a vaccine arrives. But herd immunity ends the epidemic by greatly slowing the spread. The elderly and other high-risk people still need to be careful—and Gupta favors continuing policies to shield them from the virus—but the best long-term strategy for protecting them is letting low-risk people build up herd immunity right now.
That means reopening schools and allowing young people to study and congregate without masks. Martin Kulldorff, a Harvard epidemiologist and one of Gupta’s few allies, noted that not a single child in Sweden has died from Covid, and that Swedish teachers did not suffer unusually high rates of infection, even though the country never closed schools for those under 16 and didn’t force students to wear masks.
For American children under 14, the risk of dying from Covid is lower than the risk of dying from the flu or pneumonia, according to the calculations of Avik Roy, president of the Foundation for Research on Equal Opportunity. For teenagers and young adults, it’s much lower than the risk of being murdered. For anyone under 55, it’s lower than the risk of dying from accidents, from cancer, or from heart disease. If college students are willing to get in a car, why should they be terrified of sitting in a lecture hall? And why should they be reviled—much less expelled—for fraternizing with other students and helping to build up herd immunity?
“The Covid isolation strategies are accompanied by a lot of virtue-signaling and self-righteousness,” Gupta says, “but the costs are very high on the poor around the world as well as the young. I find it intolerable for teachers to ask youth to give up this important phase of their development—and to slow the development of herd immunity. If we really care about the common good and protecting the vulnerable, the rest of us should be willing to take a very small personal risk.”
The MacIver Institute:
A fundamental flaw in how the Evers’ Administration calculates Wisconsin’s daily COVID-19 positive test rate has excluded hundreds of thousands of test results and led to a wildly distorted picture of the state’s progress in confronting the virus.
The positive test rate is important, because it is one of six gating criteria the Evers’ Administration uses to make public health policy decisions that affect the entire state. Specifically, the requirement is for the “Downward trajectory of positive tests as a percent of total tests within a 14-day period.”
Throughout August and September, Wisconsin’s positive test rate steadily increased from a weekly average of 6.2% to 19% (as of Sep. 21st).
The number of new people with a positive test result each day is less important, but gets more attention. That’s not surprising because the Department of Health Services (DHS) posts the number of new positive cases each day prominently at the top of its summary dashboard, while one must hunt for the actual test rate on the page.
As the test rate has steadily ticked up over the past two months, Wisconsin has had five record setting days for the number of new positive cases. Most of the increase has occurred among the 18-24 age group and is tied to college campuses. That’s where public officials are now focusing their efforts, but not every reporter has forgotten the importance of the rate.
“What’s behind the rise in percent positive rates?” Wispolitics’ Stephanie Hoff bluntly asked Dr. Ryan Westergaard, Wisconsin’s Chief Medical Officer on Sep. 15.
This systematic error means DHS is tossing hundreds of thousands of negative test results when calculating the positive test rate. The real rate could be half of what DHS claims.
“Well, it’s a ratio so it has two components: the numerator – the top number of course is the number of positive cases,” he replied. “The bottom number of the ratio is the denominator. That’s the number of people that have been tested overall.”
This was an incredible admission. If the goal is to calculate the daily positive test rate, then DHS is using the wrong numerator and denominator. What they’re actually calculating is the daily percentage of new COVID-19 cases among those who have never been tested before – a fairly meaningless statistic. It is not the positive test rate.
On that same day, Sep. 15th, DHS recorded the rate as 11%. That was calculated by comparing 1,352 new cases to 12,266 new people tested. However, there were almost 20,000 tests collected that day. If DHS compared that day’s number of positive tests to the total number of test results, the rate would have been much lower – possibly as low as 6.7%. They’ve been making this same mistake since the spring.
This systematic error means DHS is tossing hundreds of thousands of negative test results when calculating the positive test rate. The real rate could be half of what DHS claims.
Origin of the Error
When it first started collecting COVID-19 data, DHS recognized that people were getting tested multiple times. Some people tested positive for the virus one week, and then still had it when they were retested a week later. If the department wasn’t careful, it might be accidentally count single cases of COVID-19 over and over, and include them in the official tally. That would inflate Wisconsin’s total COVID-19 cases – a mistake that surely would be caught.
The department decided on a data collection method that would pick and choose which test results to use. Dr. Westergaard explained the reasoning during a June 11th press conference.
“Our data report individuals tested. So, if an individual is tested more than once because they were being followed to see if they cleared the infection or if they were tested a couple times weeks apart, they would be considered a single case and not multiple cases in our data,” Westergaard explained.
DHS acknowledges this method on its data summary dashboard. The fine print plainly states “Multiple tests per person are not included in these summary statistics.”
And so, every day DHS compares the number of new COVID-19 cases to the number of people who were tested for the first time to determine the positive test rate. Under this method, it throws away the results for everyone that has ever been tested before. That means every day thousands of negative test results are not included in the rate calculation.
DHS has discarded hundreds of thousands of results since it began reporting COVID-19 data. Most people who are tested for COVID-19 receive negative test results.
As the pool of people who have never been tested before continues to shrink, the number of negative results getting tossed will naturally increase. Subsequently the positive test rate will continue to artificially rise.
Scope of the Error
Each day’s positive test rate needs to be calculated using all the test results from that day. Only DHS can correct this error, because only it has access to all the test results.
Although DHS’ website is filled with all kinds of COVID-19 related data – it does not post the total number of test results it receives each day. However, it does report the number of total tests collected by health care professionals across the state each day. That figure cannot be used to calculate the daily rate, because there is a lag from the time a test is collected and when the results come back.
Each day’s positive test rate needs to be calculated using all the test results from that day.
However, we can still get a good look at the problem using weekly averages.
Altogether, there have been approximately 2.1 million tests, 1.4 million people tested, and 101,321 positive cases (as of Sep. 20th). Using DHS’ flawed methodology, officials have tossed around 600,000 test results in calculating the daily positive test rate. That results in an overall rate of 7%, while the real rate could be as low as 4.8%.
That might not seem like a big difference overall. However, public officials aren’t looking at the big picture. They’re looking at this rate on a day-to-day basis, and only 14 days back. The inherent flaws in DHS’ formula means the difference between the official rate and the real rate consistently grows.
When DHS first began collecting COVID-19 data, no one had been tested before, and few results were discarded. At that time, the rate calculated by DHS would have been fairly accurate.
However, as time goes on, more and more people are re-tested. That means more and more results are thrown out. Inevitably the rate will become more and more inaccurate unless DHS corrects its calculations.
Yesterday, 12,537 people in Wisconsin, who had never been tested before, got their #COVID19 test results. Those were the only results @DHSWI used to calculate the daily positive test rate. It’s been using this method from the beginning. https://t.co/8qx2wIe0lh #WIright pic.twitter.com/tYNOpDDVuW
— MacIver Institute (@MacIverWisc) September 23, 2020
The cracks in DHS’ methodology are beginning to show.
The Evers Administration is increasingly confronted with questions it cannot answer (even when the answers are right on DHS’ website.)
For example, some reporters have noticed that the state’s lab capacity is much higher than – what they believe to be – the number of new test results each day.
In August, lab capacity was around 26,000 tests a day, and an average of 15,600 test were administered each day. That meant labs were running at about 60% capacity. In September, lab capacity increased to 38,000 tests a day, and an average of 20,685 tests were administered each day. That meant labs were running at about 54% capacity. However, the way DHS presents its data could lead some to believe there are only around 10,000 tests being administered each day – or about 26 – 38%.
“Why do we continue to be at a quarter the rate of testing capacity? Is it a shortage of supplies or people just not getting tested?” a reporter asked Palm at a press conference on Sep. 16th.
“This is certainly a complicated question and therefor a complicated answer and some of it is just speculation,” Palm replied.
Clearly, the reporter had confused or did not realize that the number of new people being tested is different from the number of tests being collected. Palm had the opportunity to correct this confusion, but she either didn’t listen to the question or doesn’t understand the issue herself.
Even Dr. Westergaard, who has repeatedly demonstrated his understanding of what data is available and how the rate is calculated, has yet to point out the complete truth of these fundamental issues.
That reporter is not the first one to ask why test numbers always appear to be well below the state’s capacity. Once reporters begin to understand the difference between individuals tested and the number of tests actually collected, they will be able to identify the bad math DHS uses to calculate Wisconsin’s rate. They will then be able to ask why the state is making public policy decisions based on this bad math.
Whether or not the Evers Administration or the Capitol press corps figure this out on their own eventually won’t matter. As the number of new individuals getting tested continues to drop, the day will come when there are more positive test results than new individuals being tested. Once the daily positive test rate rises above 100%, no one will be able to ignore the math any longer.
Solving the Problem
DHS was right to take steps to ensure its total case count was accurate, but the positive test rate is just as important.
DHS should also calculate the positive test rate every day using all the results from that day. Since no one is tested twice in the same day, this will ensure that each day’s rate is accurate. That will ensure the gating requirement is reflecting the correct data.
This is something DHS could start doing today. It needs to start doing this today, because it’s current method is producing inaccurate results – which the Evers continues to use in its gating criteria to make pivotal public policy decisions that affect everyone in Wisconsin.
The positive test rate since this pan(dem)ic began, by the way, is 7.17 percent. The hospitalization rate as a percentage of positive tests is 6.53 percent and dropping. The death rate as a percentage of positive tests is 1.2 percent and dropping.
A news release from the office of state Sen. Steve Nass (R–Whitewater):
Senator Steve Nass (R-Whitewater) issued the following statement in response to Governor Tony Evers illegally issuing his third Covid-19 emergency declaration (Executive Order 90) that allows for the Governor and DHS Secretary-Designee Andrea Palm to issue dictatorial public health edicts. The first order issued today is a renewed statewide face mask mandate until November 21, 2020:
“Assembly Speaker Robin Vos has enabled the continuing illegal conduct of Governor Evers in issuing repeated emergency declarations and a failed statewide mask mandate. The Legislature has the constitutional and statutory authority to call an extraordinary session and put an end to the improper actions of the Governor.
“I fear that some Republican leaders will now hide behind a court challenge to avoid taking an up-or-down vote on rescinding the Governor’s third Covid-19 emergency declaration. A court challenge could take weeks or months to get a final decision, but citizens would still be under the dictatorial rule of an incompetent Governor.
“We can vote to rescind the emergency declaration in extraordinary session and still commence court challenges to the Governor’s abusive actions to prevent future illegal conduct.
“I am calling on Speaker Robin Vos and Senate Majority Leader Scott Fitzgerald to immediately call the Legislature back into session to pass a joint resolution ending Governor Evers’ new illegal and unnecessary emergency declaration. The Legislature is empowered to end any emergency declaration issued by a Governor through the simple passage of a joint resolution that doesn’t require the Governor’s approval.”
The Chinese government intentionally manufactured and released the COVID-19 virus that led to mass shutdowns and deaths across the world, a top virologist and whistleblower told Fox News host Tucker Carlson on Tuesday.
Carlson specifically asked Dr. Li-Meng Yan whether she believed the Chinese Communist Party released the virus “on purpose.” “Yes, of course, it’s intentionally,” she responded on “Tucker Carlson Tonight.”
Yan said more evidence would be released but pointed to her own high-ranking position at a World Health Organization reference lab as a reason to trust her allegation.
“I work[ed] in the WHO reference lab, which is the top coronavirus lab in the world, in the University of Hong Kong. And the thing is I get deeply into such investigation in secret from the early beginning of this outbreak. I had my intelligence because I also get my own unit network in China, involved [in] the hospital … also I work with the top corona[virus] virologist in the world,” she said.
“So, together with my experience, I can tell you, this is created in the lab … and also, it is spread to the world to make such damage.”
Yan’s comments conflicted with the opinion of Dr. Anthony Fauci, director of the National Institute of Allergy and Infectious Diseases and White House coronavirus adviser, who previously cast doubt on the idea the virus was artificially created. In May, he told National Geographic: “If you look at the evolution of the virus in bats, and what’s out there now is very, very strongly leaning toward this [virus] could not have been artificially or deliberately manipulated — the way the mutations have naturally evolved.”
Other scientists have panned the idea that COVID-19 served as a sort of bioweapon or was released by a lab.
Fox News previously reported on Yan back in July, when she blew the whistle on China’s alleged attempts to suppress information about its handling of the virus. With a vast network of contacts in Chinese medical facilities, Yan attempted to gather more information about the virus as China blocked overseas experts from conducting research in the country.
Her revelations fueled ongoing complaints that the Chinese government failed to tell the world early on about the virus’ threat. Specifically, she believes the Chinese government ignored research that could have saved lives. The State Department did not immediately respond to Fox News’ request for comment.
In response, her former employer, the University of Hong Kong, criticized her account. A press release noted “that the content of the said news report does not accord with the key facts as we understand them.”
“Specifically, Dr Yan never conducted any research on human-to-human transmission of the novel coronavirus at [the University of Hong Kong] during December 2019 and January 2020, her central assertion of the said interview.”
Yan, who said she was one of the first scientists in the world to study the novel coronavirus, fled China and currently fears retaliation. She was allegedly asked by her supervisor at the University/WHO reference lab, Dr. Leo Poon, in 2019 to look into the odd cluster of SARS-like cases coming out of mainland China at the end of December 2019.
What was social media’s reaction to this? Fox News again:
Facebook and other tech giants have engaged in a troubling pattern of censoring speech surrounding major issues in the coronavirus debate, Fox News host Tucker Carlson argued during his Wednesday night monologue.
Carlson’s comments came after Facebook slapped a warning label on video of his Tuesday interview with Chinese virologist Dr. Li-Meng Yan, who claimed to have evidence showing China “intentionally” released COVID-19 onto the general population.
“Within a few hours of her interview last night,” Carlson said, “a video of the segment reached 1.3 million people on Facebook.”
“And why wouldn’t it? The coronavirus pandemic has touched the life of every American. And justifiably, people want to know where it came from. But Facebook still doesn’t want you to know that. So Facebook suppressed the video, presumably on behalf of the Chinese government. Facebook executives made it harder for users to watch our segment. Those who found the video had to navigate a warning that the interview ‘repeats information about COVID-19 that independent fact-checkers say is false,” he added.
“Instagram, which Facebook also owns did the same thing. Twitter suspended Dr. Yan’s account entirely. It did not explain why. Nor did the tech companies explain how they would know more about disease transmission than an MD, PhD virologist like Dr. Li-Meng Yan. Instead, Facebook and Instagram linked to three so-called fact checks which supposedly proved Yan was lying.
“But if you clicked on the provided links, you’d noticed something odd. The fact checks were all published months ago, many months — in January, February, and March, and they had nothing whatsoever to do with what Dr. Li-Meng Yan said on our show… One of the fact checks attacks a completely unrelated claim, the virus was patented and that a vaccine was prepared and ready to go.
“What does that have to do with the interview we did last night? No one will tell us that. The truth is, and you know it if you’ve watched carefully, experts have been wrong frequently throughout this pandemic … They have changed their prescriptions many times.”
Carlson argued that the solution to experts being fallible was more speech. “The solution to this age-old problem, and we used to understand this intuitively is more informed voices in the conversation. That’s how you make wise decisions, that’s how you get to the truth. Diversity of view. Facebook doesn’t believe this,” he said.
“They believe in censorship. Censorship does not make us wiser. It does not make us better informed. If it did, we’d be speaking Russian right now, the Soviet Union would run the world. It would have worked. But instead the Soviet Union is extinct. It collapsed under the weight of its own absurdities — absurdities abetted by censorship. And that’s the most basic lesson of dictatorships, all of them. Anything built on lies falls apart over time.”
Carlson also defended Yan and her research. “COVID-19 is not from nature, she said. It was created in a lab in Wuhan, China. The Chinese government intentionally unleashed it on the world. Those are her claims. Are they true? We have no way of verifying them. We do know that Dr. Li-Meng Yan is not a quack,” Carlson said.
“She’s authored peer-reviewed papers on coronavirus transmission in both Nature Magazine and The Lancet. Those are two of the most respected publications in all of science. Her paper on the origin of COVID-19, which she has published online, is not frivolous. In it, she points to specific evidence for the claims that she makes. She identifies so-called cut sites which are frequently used in genomic engineering that would allow scientists to swap in sequences from other viruses to create what she described last night as a Frankenstein bioweapon.”
Whether or not the doctor is correct, Carlson certainly is. The solution to speech you disagree with has never been censorship. The solution to science you think is incorrect is more science. Liberals used to believe these sorts of things.
Kind of ironic for this to take place the week of Constitution Day, isn’t it?
It has been five months since the American people were told they would be under house arrest for three weeks to “flatten the curve.” Under the guise of protecting us from Covid-19, America’s politicians completed one of the greatest nonviolent power grabs in US history, pushing the lockdowns well beyond the initial three-week prediction, thereby taking control of 330 million lives.
To justify this, they shifted the goal posts from flattening the curve, to halting transmission of the coronavirus entirely. Some even talked about maintaining lockdowns, at least in part, until a vaccine is developed. That could take years.
How did it come to pass that a nation of 330 million was effectively imprisoned, with virtually every sector of the economy shut down either in part or in total? The answer to this question is as clear as it was wrong: In the early days of Covid-19, politicians and experts lined up to tell us that, if we did nothing, up to 2.2 million Americans would die over the balance of 2020.
As of late August, there have been fewer than 170,000 Covid-19 deaths in the United States. If the 2.2 million projection was accurate, then the US lockdown saved in the neighborhood of 2 million lives. But at what cost?
In early March, the Congressional Budget Office predicted that the economic output of the United States economy over the period 2020 through 2025 would total $120 trillion. Just four months later and because of the Covid lockdown, the CBO reduced its projection by almost $10 trillion. That $10 trillion difference is income Americans would have earned had the lockdown not happened, but now won’t.
Economists outside the CBO have estimated this loss at almost $14 trillion. For perspective, the median US household earns $63,000. A $10 trillion loss is equivalent to wiping out the incomes of 30 million US households each year for more than five years.
Our desire to keep people safe, no matter the cost, has already resulted in 10 million Americans being unemployed. By the time things have returned to normal, the total price tag, just in terms of lost incomes and adjusted for inflation, will have exceeded the costs of all the wars the US has ever fought, from the American Revolution to Afghanistan – combined.
And the costs are staggering. As of August, estimates from Chambers of Commerce indicate that around one-third of the 240,000 small businesses in New York City have permanently closed. If that ratio holds for small businesses elsewhere, we could see around 10 million small businesses close permanently across the country. Major retail bankruptcies in the US have been every bit as disconcerting.
All in, the effort to save two million lives from Covid-19 will end up costing us somewhere in the neighborhood of $7 million per life saved. People generally assume the lockdown was worth this massive cost, but there are a couple of things to consider before drawing that conclusion. First, for the same cost, could we have saved even more lives than we did by doing other things? Second, how plausible was the prediction of two million dead in the first place?
If saving lives simply, rather than saving lives from Covid-19 were our goal, we could have likely saved more than two million lives and at a lower cost. How so? For every $14,000 spent on smoke and heat detectors in homes, a life is saved. For every $260,000 spent on widening shoulders on rural roads, a life is saved. For every $5 million spent putting seat belts on school buses, a life is saved.
Each year, 650,000 Americans die from heart disease, 600,000 die from cancer, 430,000 die from lung disease, stroke, and Alzheimer’s. To fight these diseases Congress allocated $6 billion for cancer research to the National Cancer Institute and another $39 billion to the National Institutes of Health in 2018.
The lockdown will cost us more than three hundred times this amount. For a three-hundred fold increase to NCI and NIH budgets, we might well have eradicated heart disease, cancer, lung disease, and Alzheimer’s. Over just a couple of years, that would have saved far more than two million lives.
The lesson here is a simple one: There is no policy that just simply “saves lives.” The best we can do is to make responsible tradeoffs. Did the lockdowns save lives? Some people claim they did – at a cost of $7 million per life saved if the initial estimates were correct – while others fail to establish any connection between lockdowns and lives saved.
Regardless, there are all manner of other tradeoffs here. The lockdowns didn’t just cost millions of people’s livelihoods, they also cost people’s lives. Preliminary evidence points to a rise in suicides. Nationwide, calls to suicide hotlines are up almost 50 percent since before the lockdown. People are less inclined to keep medical appointments, and as a result life-saving diagnoses are not being made, and treatments are not being administered. Drug overdoses are up, and there is evidence that instances of domestic violence are on the rise also.
But what if the lockdown actually didn’t save 2 million lives? There is strong, if not irrefutable, evidence that the initial projections of Covid-19 deaths were wildly overstated.
We can refer to a natural experiment in Sweden for some clarity. Sweden’s government did not lock down the country’s economy, though it recommended that citizens practice social distancing and it banned gatherings of more than 50 people. Swedish epidemiologists took the Imperial College of London (ICL) model – the same model that predicted 2.2 million Covid-19 deaths for the United States – and applied it to Sweden. The model predicted that by July 1 Sweden would have suffered 96,000 deaths if it had done nothing, and 81,600 deaths with the policies that it did employ. In fact, by July 1, Sweden had suffered only 5,500 deaths. The ICL model overestimated Sweden’s Covid-19 deaths by a factor of nearly fifteen.
If the ICL model overestimated US Covid-19 deaths merely by a factor of ten, the number of Americans who would have died had we not locked down the country, but instead practiced social distancing and banned gatherings of more than 50 people, would have been around 220,000.
To date, the CDC reports around 170,000 covid deaths in the United States. In other words, adjusting – even conservatively – for the ICL model’s demonstrated error, it appears that the $14 trillion lockdown perhaps saved about 50,000 US lives. If that’s the case, the cost of saving lives via the lockdown was not $7 million each. The cost was over a quarter of a billion dollars each.
Finally, there is mounting evidence that even if targeted closures had been necessary, a general lockdown wasn’t. Eighty percent of Covid-19 deaths in the US are among those 65 and older. Even if ICL’s flawed model had been correct, and we had been facing the possibility of 2.2 million deaths, only 400,000 of those would have been among working-age Americans. That’s less than two-tenths of one percent of working-age Americans. Social distancing and mandatory masks might have reduced that further. We could have quarantined the elderly, saved nearly all the lives that even the most dire predictions anticipated, and let the economy continue on as usual.
But we didn’t.
Of course, in March, we knew a lot less than we do now. In the face of 2.2 million likely deaths, many claimed that locking down the economy was the right thing to do. Over the subsequent weeks, as data emerged that the threat was far less deadly and far more focused than it had at first appeared, politicians could have released the lockdown.
But they didn’t.
They didn’t because politicians invariably feel the need to “do something.” Despite volumes of evidence from disparate fields like economics, social work, ecology, and medicine, it never seems to occur to politicians that sometimes doing less, or even doing nothing, is by far the better approach. Why should it occur to them? When politicians act and their actions do more harm than good, they always say the same thing: “Imagine how bad it would have been had we not acted.”
But this time, we have evidence. We can compare what happened where politicians reacted with a heavy hand to what happened where they reacted with a light touch. And the evidence we have so far points to the same conclusion: Our politicians destroyed our economy unnecessarily.
This won’t stop our politicians from congratulating themselves, of course. Nothing ever does. When the next crisis comes along they will land on the same sorts of heavy-handed solutions they did this time. The only thing that will chasten them is the anger of the American people. Politicians did far more harm to Americans than Covid-19 did, and that’s what the American people need to remember next time our politicians start down the same pointless road.
Because they will.
The headline is a quote from U.S. Sen. George Aiken of Vermont about the Vietnam War.
James Freeman has a current parallel:
Politicians and pundits have been recklessly casting the effort to resist Covid-19 as a “war” for months. Maybe they’re finally ready to sound the metaphorical retreat. For starters, this catastrophically costly war of choice doesn’t seem to have resulted in the capture of any territory or the destruction of the enemy. Don Luskin of TrendMacrolytics writes in a Journal op-ed:
Six months into the Covid-19 pandemic, the U.S. has now carried out two large-scale experiments in public health—first, in March and April, the lockdown of the economy to arrest the spread of the virus, and second, since mid-April, the reopening of the economy. The results are in. Counterintuitive though it may be, statistical analysis shows that locking down the economy didn’t contain the disease’s spread and reopening it didn’t unleash a second wave of infections.
Just like a real military force, the Covid warriors have wreaked severe destruction, but it’s all been inflicted on our own society. Speaking of the domestic destruction, this is perhaps the one way in which the campaign against Covid really has been similar to a war. The Journal’s Kate Davidson reports:
U.S. government debt is on track to exceed the size of the economy for the 12 months ended Sept. 30, a milestone not hit since World War II that has been brought into reach by a giant fiscal response to the coronavirus pandemic.
The Congressional Budget Office is expected to report on Wednesday that federal debt held by the public is projected to reach or exceed 100% of U.S. gross domestic product, the broadest measure of U.S. economic output. That would put the U.S. in the company of a handful of nations with debt loads that exceed their economies, including Japan, Italy and Greece—though investors remain unfazed by the rising red ink.
Federal taxpayers will someday have to pay all these bills, but state and local governments are primarily responsible for waging the campaign against prosperity and public health. And one of the country’s most committed warriors, Gov. Gavin Newsom (D., Calif.), seems to have selected his latest targets almost at random. It is perhaps another lesson in the inhumanity of war. Chris Woodyard writes in USA Today:
…California has embarked on a new tiered plan for reopening businesses that has some crying foul.
Critics say the system doesn’t take into account that some businesses can operate safely even in counties with relatively high numbers of COVID-cases. And it hits some businesses harder than others, even when it appears they perform similar services.
“While certain businesses are allowed to open … many others continue to be greatly limited, hampered or even closed,” said San Diego County Supervisor Jim Desmond, who held a news conference on the issue Monday. “The state continues to change the targets and move the goal posts.”
This column appreciates Mr. Desmond’s effort to introduce a sports metaphor into the discussion. But it is the language of warfare that has been used to justify the abuse of children who are currently being denied educational opportunities–which will reduce their future earnings–even as the grown-ups inflict upon them a World War II level of debt. The financial obligation forced on today’s students keeps getting bigger as government school closures reduce their ability to service it. Perhaps some enterprising tyke will consider starting a Young Lives Matter protest movement.
Another way in which the Covid campaign is very different from actual combat is that typically war mongers are not simultaneously serving as conscientious objectors. But there is a disturbing recent pattern of government officials displaying an unwillingness to engage in the fighting they demand of others. Now this week Fox News reports:
House Speaker Nancy Pelosi visited a San Francisco hair salon on Monday afternoon for a wash and blow-out, despite local ordinances keeping salons closed amid the coronavirus pandemic…
In security footage obtained by Fox News, and timestamped Monday at 3:08 p.m. Pacific Time, the California powerhouse is seen walking through eSalon in San Francisco with wet hair, and without a mask over her mouth or nose.
Perhaps like many Americans, the speaker doesn’t really think Covid is as deadly as she says. Perhaps she read a New York Times report saying that many Covid tests come back positive even when the patient carries an insignificant amount of virus and began to wonder how many people have died with Covid rather than of Covid. Given that the overwhelming majority of Covid-related deaths occur in older people with co-morbidities, perhaps the speaker is also privately questioning how many patients died of Covid shortly before they were likely to die of another underlying condition. In New York State alone, thousands of recorded Covid deaths have involved people at least 80 years old and suffering from dementia. Does the speaker wonder if perhaps such deaths are not exactly the same in terms of lost years of life as an 18-year-old dying in battle? Maybe the speaker has considered all of this and has also noticed that states like New York with the highest death totals also imposed the most extreme lockdowns.
If Speaker Pelosi isn’t harboring such doubts, why would she run the risk of an unmasked hair appointment? Perhaps she is simply following the dictates of her conscience and must adhere to a deep-seated belief in professional styling. But probably not.
It’s time to declare an armistice.
Or something. As of mid-week, after 5½ months of Gov. Tony Evers’ lockdowns and mask order:
- 6.07 percent of Wisconsinites who are either sick enough to be tested or have a reason to be tested (suspected exposure), have tested positive for COVID-19 — 1.3 percent of the state’s estimated population.
- Of that population, 7.69 percent (0.467 percent of those tested) have been sick enough to be hospitalized.
- 1.48 percent of those who tested positive (0.09 percent of those tested) have died. According to the Centers for Disease Control, 94 percent of those who have died had additional contributing conditions.
There’s an awful lot these days that can rightly be called “unprecedented.” Whether it’s the pandemic itself, the government lockdowns, or the massive bailout programs, it seems like everything we’re contending with is unexplored territory.
The hardest part about having no precedent is that it complicates the decision-making process. Normally, precedent acts as a guide that helps us determine our approach, and it plays a vital role in simplifying the decisions we face. In these times, however, the absence of precedent has made us desperate for simplicity, and in our desperation, I believe we have subconsciously succumbed to our natural predilection for mental shortcuts, also known as cognitive biases.
The study of cognitive biases is fascinating, but also unsettling. Increasingly, researchers are realizing that our biases cause significant errors in judgment, often more than we realize. In light of this, I think it’s worth taking some time to reflect on how our biases have influenced our response to this pandemic. To this end, let’s start by thinking back to when this whole fiasco began.
Before the Lockdowns
Back in mid-March, a number of biases played a role in shaping our initial response. One of the most significant biases in this regard was the availability heuristic. First described by Kahneman and Tversky in 1973, the availability heuristic is the tendency to misjudge the importance, frequency, or likelihood of events by giving excessive weight to events that are easier to recall (such as events that are more recent). This concept is closely related to salience bias, which is the tendency to focus on things that are more prominent or vivid and ignore things that are inconspicuous.
When considering the events leading up to the lockdowns, it’s not hard to see how these biases were at play. The imminent danger of a global pandemic dominated the media discourse in a matter of days, so it makes sense that we gave it a lot of attention.
But while COVID-19 infections and deaths were widely publicized and therefore widely salient, the negative impacts of the impending lockdowns went largely unnoticed. In fact, the disregard for these impacts eventually got so perilous that a group of over 600 physicians sent a letter to President Trump warning about “the exponentially growing negative health consequences of the national shutdown,” and pointing out that “the downstream health effects…are being massively underestimated and under-reported”.
The unintended consequences of the lockdowns have proven to be a sobering reminder of what can happen when we fail to look beyond the immediate intentions of narrow-minded policies. Indeed, this shortsightedness is the very thing Hazlitt warned us about in his book, Economics In One Lesson. But even though our blindness to these secondary effects is natural and understandable, it is by no means inevitable. We are perfectly capable of seeing the unseen so long as we remember to look.
Another consequence of the media’s preoccupation with COVID-19 is that we quickly became familiar with a host of ominous projections. This familiarity likely produced an illusory truth effect, which is the tendency to believe information to be true as a result of repeated exposure, even if it turns out to be false. On top of that, many people developed exaggerated expectations (arguably another bias) and displayed a great deal of overconfidence and hubris.
Finally, as more and more people bought into the alarmist narrative, there was an ever-increasing amount of availability, salience, repetition, and overconfidence. The ensuing positive feedback loop was inexorable, as was the corresponding bandwagon effect.
During the Lockdowns
A few weeks after the lockdowns were imposed it became apparent that the curve had been flattened and the extreme risk had subsided. But as weeks turned into months, the bureaucrats were incredibly reluctant to lift the lockdowns, and when they finally did it was a slow and gradual process. But why was that? Well, the official answer is that they were concerned for our health (unintended consequences be damned), but I think there’s another factor involved called status quo bias.
Status quo bias is our inclination to prefer the current state of affairs and avoid change. To be sure, it didn’t stop the politicians from imposing the lockdowns in the first place, largely because other factors took precedence. But once the lockdowns were imposed, they became the new status quo, the “new normal,” and this meant that there was now a psychological resistance to removing them.
Many explanations for status quo bias have been proposed, and it’s likely that they each contribute to varying degrees. Some of the more common explanations are loss aversion, omission bias, and the sunk-cost fallacy. Let’s briefly explore these in turn.
Loss aversion is the idea that we generally prefer avoiding losses to acquiring equivalent gains. What this means practically is that we often reject a change on account of its potential drawbacks, even if they are outweighed by its potential benefits.
Another explanation is omission bias, which is our proclivity to favor acts of omission over acts of commission. In the trolley problem, for instance, people feel more justified in allowing harm to happen than in actively causing harm. This preference for inaction seems to reflect an underlying moral sentiment, but it may also involve a fear of regret, since we might expect to regret our actions more than our inactions.
Lastly, the sunk-cost fallacy is the tendency to justify the status quo on account of past investments, even when it has become apparent that the investments were misguided and the approach should be revised. Under this framework, our resistance to change stems from our unwillingness to admit we were wrong. The temptation is that as long as we don’t change course, we don’t have to acknowledge that we made a mistake.
Even after we manage to deviate from the status quo, we are still reluctant to change too quickly. This hesitancy is likely a manifestation of conservatism bias, which is the tendency to insufficiently revise our beliefs when presented with new evidence. Although it’s impossible to ascertain the full extent of its influence, conservatism bias offers a compelling explanation for why the restrictions were eased so slowly even after the curve had been flattened. “The lockdowns are already in place,” we told ourselves. “Why not just a little longer, just to be safe?”
The common element in all of these concepts is fear. Fear of loss, fear of regret, and hence, fear of change. And it makes sense, because our natural reaction to fear is paralysis. It feels safer to stay the course than to begin moving in a different direction.
But the politicians aren’t just worried about loss and regret. They’re also worried about optics. And though they wouldn’t like to admit it, their concern for their reputation has probably played a considerable role in their decisions.
Just imagine how it would look if the lockdowns were lifted any faster. First, it would be an implicit admission that the initial lockdowns had been misguided and probably weren’t necessary in the first place. Second, they would run the risk of getting blamed for a rise in infections. But as long as they kept the strict lockdowns in place then they could blame any outbreaks on us because they were “doing everything they could”.
In short, it was much better optics for them to extend the lockdowns “for your safety” than to admit that they were wrong and that they overreacted. And if a few million people had to lose their jobs so the politicians could save face, so be it.
After the Lockdowns
Now that the lockdowns are being lifted and life is slowly returning to normal, another slew of biases is taking hold. The most obvious example here is hindsight bias, which is the tendency to perceive historical events as being more predictable than they actually were. In the same way that many people displayed overconfidence before the lockdowns, many people are now patting themselves on the back, confident that they “knew it all along”.
This ties in closely with confirmation bias, which is our proclivity to search for, interpret, favor, and recall evidence in a way that confirms our pre-existing beliefs. As Sherlock Holmes puts it, we “twist facts to suit theories instead of theories to suit facts.” A great example of this has been our propensity to interpret declining infection rates as a confirmation that the lockdowns “worked”, when in fact this is a textbook example of the post hoc fallacy.
The apparent success of the lockdowns has also led many people to conclude that the initial decisions were necessary and justified. But this conclusion is merely an example of outcome bias, whereby we judge the quality of the decision based on the quality of the outcome. In reality, the presence of a positive outcome doesn’t necessarily prove that the initial decisions were justified. And besides, if we consider the unintended consequences, there’s a decent chance that the lockdowns did more harm than good anyway.
The Most Dangerous Bias
Though all of the biases mentioned so far are important, there’s one that concerns me the most, and it’s called authority bias. Authority bias is the tendency to attribute greater accuracy to the opinion of an authority figure and be more influenced by that opinion. It was most notably established by the infamous Milgram experiment in 1961, which demonstrated people’s surprising propensity to trust and obey authority figures even to the point of violating their own conscience.
The pervasive influence of authority bias throughout the pandemic has been particularly disconcerting. From the very beginning, people have blindly trusted “the experts” even as they shut down our businesses, undermined our response efforts, and trampled our civil liberties.
And quite frankly, that scares me.
Whatever happened to having a healthy distrust of authority? When did we lose our skepticism and suspicion? Have we forgotten that they too are mere mortals? Have we forgotten how to think for ourselves and how to take responsibility for our own lives?
Perhaps. Or perhaps we have simply forgotten to be mindful of our biases. Perhaps we were unwittingly drawn to the easy answers, the herd mentality, the status quo, and the confirming evidence. If that’s the case, then I think there is still hope. But if we’re going to overcome our biases, we need to begin by learning to identify them.
And then we need to lead by example. We need to be honest about our own susceptibility to error. We need to model a healthy suspicion of our own predispositions. We need to take responsibility for our own blindness and be open to correction. And perhaps, in this way, we can show the world what true rationality looks like.
Shortly after normal office hours on Friday (08-21-2020) Madison/Dane County Public Health issued an order closing down in-school education for students above second grade at private schools for the upcoming school year — matching the voluntary stance taken by area public schools.
“This is clearly about making sure private schools aren’t allowed to show up the [unionized] MTI teachers in the public schools,” one of the attorneys, Andy Cook, told the Werkes.
In response, the Catholic Diocese of Madison plans to file lawsuit this week contesting the coronavirus pandemic order. Many Catholic schools had been scheduled to open today (Monday 08-24-2020). Fourteen diocesan Catholic schools are located in Dane County; another 20 outside the county in southwest Wisconsin.
“As expected, Dane County Public Health [was] less focused on actual health and science and more so on social justice,” attorney Cook told the Werkes. “They pulled the rug out from beneath the private schools after hours on a Friday night.”
The diocese says it has taken steps to assure safety of staff and students amid the coronavirus pandemic.
According to one source, the diocese will hire the same law firm that turned back Public Health’s limit on attendance at Holy Mass. That would be Troutman Pepper Hamilton Sanders LLP, a law firm that earlier this year helped the Diocese of Madison defeat attempts to place strict limits on Mass attendance due to COVID-19. The diocese scheduled a Rosary prayer rally for 3 p.m. today on the State Street steps of the Wisconsin Capitol.
“We are extraordinarily disappointed at this order and its timing. You have told us of your sadness, your anger and your children’s grief as they burst into tears when you told them of the county’s decision.” — Bishop Donald J. Hying and Michael J. Lancaster, superintendent of diocesan Catholic schools. in a letter to parents.
In June 3, the Madison Catholic Diocese protesting the limits on Mass attendance and threatened litigation; less than 48 hours Madison/Dane County Public Health backed off.
The importance of reopening America’s schools this fall
The best available evidence indicates if children become infected, they are far less likely to suffer severe symptoms. Death rates among school-aged children are much lower than among adults. At the same time, the harms attributed to closed schools on the social, emotional, and behavioral health, economic well-being, and academic achievement of children, in both the short- and long-term, are well-known and significant. — U.S. Centers for Disease Control and Prevention
Meme Nation lists the currently known COVID-19 symptoms:
There is another symptom, reported by Franklin Templeton:
The first round of our Franklin Templeton–Gallup Economics of Recovery Study has already yielded three powerful and surprising insights:
- Americans still misperceive the risks of death from COVID-19 for different age cohorts—to a shocking extent;
- The misperception is greater for those who identify as Democrats, and for those who rely more on social media for information; partisanship and misinformation, to misquote Thomas Dolby, are blinding us from science; and
- We find a sizable “safety premium” that could become a significant driver of inflation as the recovery gets underway.
What? The party that supposedly follows the science …
… gets the science wrong?
Six months into this pandemic, Americans still dramatically misunderstand the risk of dying from COVID-19:
- On average, Americans believe that people aged 55 and older account for just over half of total COVID-19 deaths; the actual figure is 92%.
- Americans believe that people aged 44 and younger account for about 30% of total deaths; the actual figure is 2.7%.
- Americans overestimate the risk of death from COVID-19 for people aged 24 and younger by a factor of 50; and they think the risk for people aged 65 and older is half of what it actually is (40% vs 80%).
These results are nothing short of stunning. Mortality data have shown from the very beginning that the COVID-19 virus age-discriminates, with deaths overwhelmingly concentrated in people who are older and suffer comorbidities. This is perhaps the only uncontroversial piece of evidence we have about this virus. Nearly all US fatalities have been among people older than 55; and yet a large number of Americans are still convinced that the risk to those younger than 55 is almost the same as to those who are older.
This misperception translates directly into a degree of fear for one’s health that for most people vastly exceeds the actual risk: we find that the share of people who are very worried or somewhat worried of suffering serious health consequences should they contract COVID-19 is almost identical across all age brackets between 25 and 64 years old, and it’s not far below the share for people 65 and older.
The discrepancy with the actual mortality data is staggering: for people aged 18–24, the share of those worried about serious health consequences is 400 times higher than the share of total COVID deaths; for those age 25–34 it is 90 times higher. The chart below truly is worth a thousand words:
Our question asks about fear of serious health consequences, not fear of death, but the evidence to-date indicates that the two follow a very similar age distribution; indeed the CDC has clearly stated on its website that “Among adults, the risk of severe illness from COVID-19 increases with age, with older adults at the highest risk.” Recent concerns of possible adverse long-term consequences are by necessity speculative, since we obviously do not have long-term data yet.
On to the next point:
For the last six months, we have all read and talked about nothing but COVID-19; how can there be still such a widespread, fundamental misunderstanding of the basic facts? Our poll results identify two major culprits: the quality of information and the extreme politicization of the COVID-19 debate:
- People who get their information predominantly from social media have the most erroneous and distorted perception of risk.
- Those who identify as Democrats tend to mistakenly overstate the risk of death from COVID-19 for younger people much more than Republicans.
This, sadly, comes as no surprise. Fear and anger are the most reliable drivers of engagement; scary tales of young victims of the pandemic, intimating that we are all at risk of dying, quickly go viral; so do stories that blame everything on your political adversaries. Both social and traditional media have been churning out both types of narratives in order to generate more clicks and increase their audience.
The fact that the United States is in an election year has exacerbated the problem. Stories that emphasize the dangers of the pandemic to all age cohorts and tie the risk to the Administration’s handling of the crisis likely tend to resonate much more with Democrats than Republicans. This might be a contributing factor to why, in our survey results, Democrats tend to overestimate the risk of dying from COVID-19 for different age cohorts to a greater extent than Republicans do.
Our susceptibility to how the information is presented also plays a role. The same data can be portrayed in different forms on a graph—some reassuring and some alarming. Our study finds that how the data are presented has a very strong impact on people’s attitudes. For example, respondents who were shown COVID-19 case trends for Texas and Florida in isolation were much less willing to reopen schools and businesses than those who were shown the same trends compared to New York. And more alarming graphics tend to be used more frequently, as they generate greater engagement.This misinformation has a very concrete adverse impact. Our study results show that those who overstate deaths among young people are more cautious about making purchases, more reluctant to travel, and favor keeping businesses and schools shut.
Here again, we find a significant difference across partisan lines. According to our study, political affiliation is as powerful as age in predicting whether someone would be likely to eat at a restaurant indoors; Democrats have roughly the same willingness to eat in a restaurant at 25% capacity as Republicans do in a restaurant at full capacity. Individual risk from COVID-19 depends on age and health, but perceived risk depends on one’s politics— and it’s perceived risk that drives behavior. Conversely, previous Gallup research has found that Republicans have been less likely to accept public health guidelines like wearing a mask, regardless of the local rate of infection—again evidence that partisanship plays an important role.
This misinformation also causes another fundamental problem. The policy decision of what activities to keep shut and for how long is a very difficult and consequential one. It requires balancing two opposite effects of uncertain scale: on the one hand the benefits in terms of slowing COVID-19 contagion, on the other hand the harm to the economy and to people’s long-term health and livelihoods. This decision is strongly influenced by public perceptions of dangers, not only because politicians are sensitive to the public’s concerns but also because politicians are people too, subject to some of the same biases. Our poll results suggest fundamental misperceptions of the risk of death or serious adverse health consequences from COVID-19 could be distorting these decisions.
Click on the link for the third piece of depressing news.
Wisconsin Governor Tony Evers instituted a statewide mask mandate on July 30. The mandate is likely unconstitutional, as the governor only has the power to declare an emergency declaration for 60 days for a particular crisis, and he already used that power in March.
But perhaps an even more important question is whether the mask mandate has had any impact on the spread of the virus that it is purported to help mitigate. With the benefit of time, we can now begin to answer that question.
According to the Centers for Disease Control and Prevention (CDC), COVID symptoms take 1-14 days to develop. We have surpassed the 14-day mark, and should be well into a period of secondary spread for anyone who has developed the virus since the mandate went into effect. But, to give the governor the benefit of the doubt, we will only look for the effect of the mandate starting a week after its implementation. This gives us 13 days of data after the mandate, which we will compare to 13 days before. The chart below shows the daily positive test rate in Wisconsin. The red line represents the point which we consider to be “post mandate (August 6).”
COVID Positivity Rates, July 24-August 18 (Wisconsin)
Visually, the mask mandate has had no effect. Indeed, average positivity rates for this period are actually slightly higher than for the period preceding the mandate (6.5% before compared to 7.3% after). But to be doubly sure of this, we also need to account for the number of tests that are being conducted. Additional testing tends to drive down positivity rates, meaning that, theoretically, there could be some impact of the mandate still if testing had substantially changed.
The table below uses regression analysis to simultaneously account for the mandate and the daily number of tests in the thousands. Accounting for daily tests, the mask mandate is actually significantly related to an increase in positive tests of about 1.7%. Daily tests has the expected relationship to positivity rates—more testing tends to lower them.
Does this mean that the mask mandate has had a negative impact on the state’s COVID rates? Likely not. But when the effect is in the wrong direction, we can be relatively certain that the mandate has not had the intended impact of mitigating the virus.
A similar pattern holds if we look at an area of the state that implemented a mandate earlier than the statewide mandate, Milwaukee. Below is the trend in cases in Milwaukee County, again using the same number of days before and after the mandate, plus a seven day buffer.
COVID Positivity Rates, June 27th-August 18th (Milwaukee County)
One caveat to this is that we are using county-level data while the mandate only affected the city. However, given that more than 62% of county residents live in the city, we ought to see some relationship here if one exists. There is a slight drop in positivity following the mandate, from about 11.2% to 10.2%. But this drop does not reach the level of statistical significance.
All of this is not to say that wearing masks is the wrong thing to do. Citizens ought to have the common decency to respect the wishes of others, and to follow the rules of businesses on private property. There is scientific evidence that the proper wearing of a mask can reduce the risk of transmission.
But the incremental impact of mandates remains an open question. Indeed, it appears that many Wisconsinites wear masks on their own, without government interference. The bottom line is that Evers’ mandate, in addition to being unconstitutional, is ineffectual.
The argument can actually be made that, contrary to what Evers and his apologists want you to believe, that nothing the state has done, including the Safer at Home orders, has slowed the spread of the coronavirus. (And the evidence of mask-wearing reducing the spread is not persuasive.) “Flattening the curve” has, as predicted, made the pandemic last longer, which means it may have infected, and be infecting, more people than otherwise would have happened.