There is no empirical evidence for these lockdowns

Comparing US states shows there is no relationship between lockdowns and lower Covid-19 deaths.

Wilfred Reilly

Several weeks ago, one of the USA’s better quantitative scientists, John Ioannidis of Stanford, made a critically important point. During the coronavirus pandemic, ‘we are making decisions without reliable data’, he said.

As Ioannidis and others have pointed out, we do not even know the actual death rate for Covid-19. Terrifying and widely cited case-fatality rates like ‘three per cent’ come from comparing known fatalities to the small pool of people who have officially been tested. Those test cases are mostly made up of sick and symptomatic people or those who had direct contact with someone known to have had Covid-19 – rather than to the far larger pool of people who may have had a mild version of the disease. Because of the same denominator problem, we also don’t know the true infection rate. A recent German study indicates this could be as high as 15 per cent.

Finally, we do not seem to know the effectiveness of the various strategies adopted by national and regional governments to respond to the disease – ranging from the advocacy of social distancing to full-on lockdowns.

This piece tackles that question. As a professional political scientist, I have analysed data from the Worldometers Coronavirus project, along with information about the population, population density, median income, median age and diversity of each US state, to determine whether states that have adopted lockdowns or ‘shelter in place’ orders experience fewer Covid-19 cases and deaths than those which pursue a social-distancing strategy without a formal lockdown. I then briefly extend this analysis to compare countries. In short, I do not find that lockdowns are a more effective way of handling coronavirus than well-done social-distancing measures.

The most basic way to test this thesis is by direct comparison. As of 6 April, seven US states had not adopted shelter-in-place orders, instead imposing social-distancing restrictions such as banning large gatherings and mandating six-foot spacing gaps and maximum customer limits inside all retail stores. Those seven states are Arkansas, Iowa, Nebraska, North Dakota, South Dakota, Utah and Wyoming. These states reported 1,620, 2,141, 952, 343, 1,311, 2,542 and 288 cases of Covid-19 respectively as of 3:40pm EST on 16 April – for an average of 1,321 cases. The states reported 37, 60, 21, 9, 7, 20, and 2 deaths respectively, for an average of 22.3 deaths. Throwing in South Carolina, which did not adopt a shelter-in-place order until 6 April, and still allows most religious services, does not dramatically alter these figures – these states averaged 1,613 cases and 33 deaths.

How do these states measure up to the rest of the US? Rather well. According to Worldometers, by the same time the number of officially tested Covid-19 cases across the US states – including Guam, Puerto Rico, and Washington, DC – ranged from 226,343 in New York to 135 in Guam. The average number of Covid cases in a US state was 12,520. The state-by-state number of deaths varied from 16,251 (New York) to two (Wyoming), with the average figure for deaths being 642. Removing the outlier case of New York state, where roughly half of all US Covid-19 deaths have taken place, shifted these figures downward somewhat – to 8,408 cases and 342 deaths in the average state. However, the social-distancing states experienced substantially fewer cases and deaths than the lockdown states, even with New York out of the mix.

An advocate of lockdowns could object that the social-distancing states are little places, located in America’s ‘flyover land’. While this charge might be based as much on bias as reality – Utah, Nebraska and South Carolina are sizable places – the next step of my analysis was to adjust for population, using a standard deaths-per-million metric. In alphabetical order, the seven social-distancing states experienced 12, 19, 11, 12, 8, 7 and three deaths per million – for an average of 10 deaths per million when you exclude South Carolina and 12 with South Carolina included.

Again, these numbers compare very favourably to the US as a whole, despite adjusting for population. Across all US states, the number of deaths per million varied from 828 (New York) to three (Wyoming), for an average of 69. With New York removed from the mix, the hardest-hit remaining state was New Jersey, with 8,480 cases and 396 deaths. The average number of cases-per-million across the states minus New York was 1,392 and the average number of deaths-per-million was 54. Comparing the social-distancing states plus South Carolina to US states minus New York, the social-distancing states experienced 663 fewer cases per million and 42 fewer deaths per million on average than the lockdown states.

Next, I ran a regression model. For those unfamiliar with academic statistical methods, regression – in this case linear regression – is a computerised mathematical technique that allows researchers to measure the influence of one variable on another with all of the other factors that might be relevant held constant. In this case, the variables for each state included in my model were: population, population density, median income, median age, diversity (measured as the percentage of minorities in a population), and the state’s Covid-19 response strategy (0 = lockdown, 1 = social distancing). The data set used to construct this model is available for anyone to request it.

The question the model set out to ask was whether lockdown states experience fewer Covid-19 cases and deaths than social-distancing states, adjusted for all of the above variables. The answer? No. The impact of state-response strategy on both my cases and deaths measures was utterly insignificant. The ‘p-value’ for the variable representing strategy was 0.94 when it was regressed against the deaths metric, which means there is a 94 per cent chance that any relationship between the different measures and Covid-19 deaths was the result of pure random chance.

The only variable to be statistically significant in terms of cases and deaths was population (p=0.006 and 0.021 respectively). Across the US states, each increase in the population of 100,000 correlated with 1,779 additional Covid-19 cases, even with multiple other factors adjusted for. Large, densely populated areas are more likely to struggle with Covid-19, no matter what response strategy they adopt – although erring on the side of caution might make sense for global megacities such as New York and Chicago.

Finally, I extended my analysis into the international arena. As has been widely reported, Sweden has opted not to lock down in the wake of Covid-19, and Swedes have instead followed similar social-distancing measures to those adopted in the seven US states I focused on.

Again, there is very little evidence that Sweden has become an unlivable Covid-19 hotbed. As of 17 April, Sweden’s Covid-19 statistics were: 13,216 total cases, 1,400 total deaths, 1,309 cases per million and 139 deaths per million. In terms of cases per million residents, Sweden ranks slightly ahead of its close neighbours, Denmark (1,221) and Norway (1,274). But in Europe as a whole, Sweden ranks 23rd in terms of cases per million and 10th in terms of deaths per million.

I am reluctant to compare European examples to the many East Asian countries which avoided significant shutdowns – particularly since these countries had significantly better early-response strategies and there can be larger cultural differences which are difficult to quantify. But essentially, the same pattern holds true. When I conducted my analysis, Japan had 9,231 total cases, 190 total deaths, 73 cases per million citizens, and two deaths per million. South Korea had 10,635 cases, 230 deaths, 207 cases per million and four deaths per million. Taiwan had a total of 395 cases and only six deaths, alongside 17 cases per million and 0.03 deaths per million.

Of course, no single analysis can provide a truly conclusive answer to questions as huge as those posed by Covid-19. Scholars and curious citizens reading this one might want to re-run my analysis with current active cases as a dependent variable rather than total cases or cases per million – although I doubt that would make much difference. It certainly might make sense to redo my regression with ‘date of first case’ thrown in as a variable. I kept the model limited to five independent variables due to the small number of state-level observations available, and left that one out because onset dates were fairly similar for most US states. However, including this information could theoretically produce different results. The more data, the better.

Overall, however, the fact that good-sized regions from Utah to Sweden to much of East Asia have avoided harsh lockdowns without being overrun by Covid-19 is notable.

The original response to Covid-19 was driven by an understandable fear of an unknown disease. The epidemiologist Neil Ferguson projected that 2.2million people could die in the US alone, and few world leaders were willing to risk being the one who would allow such grim reaping to occur.

However, as time has passed, new data have emerged. A top-quality team from Stanford University has pointed out that the infection rate for Covid-19 must logically be far higher than the official tested rate, and the fatality rate for the virus could thus be much closer to 0.1 per cent than the 2 to 4 per cent that was initially expected. And empirical analyses of national and regional response strategies, including this one, do not necessarily find that costly lockdowns work better against the virus than social distancing.

It should not be taboo to discuss these facts.

Wilfred Reilly is author of Taboo: 10 Facts You Can’t Talk About, published by Regnery.

Picture by: Getty.

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Comments

Finbarr Bruggy

28th April 2020 at 4:49 pm

It’s very hard to pick sides on this one. In Professor Ioannidis’s native land, Greece, there has been a near total lockdown. A police letter or SMS with a numbered reason (eg 2 = shopping) to leave home is required by law. You must have your mobile and valid ID on leaving the house. And no more than the driver plus 1 passenger in a saloon car. To date there have been only 136 deaths. On the other hand, Sweden – a country with a different policy from and a similar population to Greece – has 2,355 deaths. So, on the face of it, the lockdown in Greece has been successful. Then again, if you multiply Sweden’s death toll to equate with the UK’s, the death rate in both countries is similar although their lockdown policies differ significantly. What’s the answer?

Aaron Goss

28th April 2020 at 12:36 am

Mr. Reilly, your analysis is good and anyone looking at the data, no matter how they slice it, will come to the same conclusion: lockdowns did nothing. However, as quality information about the virus was disseminated and people made good individual decisions, it does seem that individual measures made a difference. The widely available line graphs of cumulative Wuhan cases per day show a marked trendline shift on January 30, spot on 7 days after the Chinese public was seriously warned about this disease which has an approximate 7-day onset. The global data prove that it’s a coincidence that this was also 7 days after China quarantined Wuhan.

I am writing chiefly because your article states that the lockdown measures were a response to an “understandable” fear. I disagree. The same data set that gave rise to the fear also revealed that the set of people diagnosed with COVID-19 was distributed around an average two standard deviations above the median population age. It was never reasonable to believe that the virus was only spreading within that set. No society in which the disease was spreading is segregated in that way.

Every shred of evidence since day 1 has pointed to this. South Korea, through aggressive testing during the initial wash of the disease through the population, found active infections among many completely asymptomatic 20-somethings. This should have clued everyone in to the fact that VASTLY more people were infected than were being listed in the case counts. Nevertheless most people said “we don’t have enough data yet” and “we need antibody testing” despite the fact that the results of the antibody testing were inevitable. Now we have done several antibody studies and we still see people saying we don’t know enough about this disease. The Ferguson/Imperial model itself admitted in its own text that it made several utterly unreasonable assumptions.

Why aren’t intelligent people like you shouting about this? There was never any better evidence for a new plague than for an alien invasion or for Godzilla rising out of the oceans to kill us all. There has almost never been a better time to point out that the emperor has no clothes: that MSNBC, CNN, and Fox News are no more reliable than any conspiracy theory blog saying whatever sensational thing they can to get attention.

Tim Lundeen

25th April 2020 at 1:13 am

The /rt.live/ site linked in the comments supports the same conclusion. There are 7 states that allow people to work, using common-sense social-distancing to reduce the rate of SARS-Cov-2 infections. Can you pick them out from their Rt chart?

No, you can’t. Outcomes from lockdown are the same as common-sense social distancing (e.g. no lockdown).

So why aren’t we all doing the same? The economic devastation caused by shutting down “non-essential” businesses doesn’t do any good, but does a LOT of harm.

top sop

24th April 2020 at 9:35 pm

Is this article some kind of joke?

Perry Greenfield

24th April 2020 at 8:21 pm

Quote from Andrew Gelman (well known statistician) on this study (see item 10 at this link https://statmodeling.stat.columbia.edu/2020/04/24/10-on-coronavirus/) “This is one of the worst studies I’ve ever seen in my life. It’s a master class in stupid.”

James Knight

24th April 2020 at 8:55 pm

I guess he never heard of Public Health England who draw conclusions by extropolating from the data of 5 cases. Or the bio statistician who recently claimed California was more successful than New York because they had a lockdown one day earlier. Conveniently ignoring Florida that delayed the lockdown for many days and still had fewer cases despite a large elderly population.

This wasn’t a study it was just data put into a hypothesis test. It isn’t changed by opinion. Opinion is like arse-holes, everyone has one.

John Hendy

23rd April 2020 at 5:17 pm

I think you’re [completely reasonably] looking at the wrong thing. “Lockdown” is a proxy for “reduced interactions.” I think you’re trying to show that stay at home date doesn’t reveal significant differences between death outcomes. But with lockdown as a proxy for interactions, surely you’re not hypothesizing that interaction levels have no effect on disease spread?

Unless you’re looking to upend disease theory… I think we’d both agree this is a dead end. How to explain this, then? I’ve been looking at the Google mobility data and to my surprise… there is approximately zero difference between some of the earliest states with stay at home orders (CA 3/19, NJ 3/21, NY 3/22) and those with the latest (e.g. FL and GA 4/3).[1] [2] [3]

Also, I’ve merged NY Times county level data with pop and land area census data to plot density vs. deaths/1000 colored by statewide stay at home duration.[4] [5] I would agree that there is little to no obvious correlation to statewide orders vs. deaths per capita. That said, there’s also little correlation between population density and death rates. I’d even say that between 0.01 and 0.1 deaths/1k, there’s a slight *negative* correlation (lower densities are suffering higher death rates).

My main point is to observe that I *think* you are saying lockdowns don’t have an effect, so let’s stop. My interpretation is lockdowns don’t correlate to interaction reduction, which is why they appear not to matter. I suspect businesses already acted (I’ve been WFH since 3/17, my state orders went into effect 3/27), which has a much higher effect than statewide orders. The Google data supports this, showing that *not a single county* went on with business as usual after ~3/15. [6]

The problem is that while social distancing may have pre-empted official orders, I do not think the reverse will be nearly as true. Namely, we may have seen a *vastly* reduced effect (vs. Italy for example) because interactions were already being reduced. Because this appears to have happened universally, we have no US control (there’s no state/county that continued at existing activity levels). The inverse will almost certainly not be true. Statewide orders will be removed, everyone will eagerly rush back to interacting and *now* we’ll get our control of what this really would have looked like given n seed cases and baseline interaction levels.

I’m open to discussion, but from actively looking at the data, this is the best I can figure out so far. I think we need a hypothesis that explains the worst of what we’ve seen (NY, NJ) *far* more than looking at non-event states as justification for “it’s can’t be that bad.”

Edit: it’s not letting me add my footnotes 🙁 Going to try and publish without them, then add them in after?

John Hendy

23rd April 2020 at 5:23 pm

Those two went, how about these?

[5] density vs. deaths/1000 by stay at home date: https://imgur.com/In6Z6yS
[6] Google mobility data, all US counties: https://imgur.com/jLs9MuS

John Hendy

23rd April 2020 at 5:27 pm

Maddening. Appears I can’t post links to github?

[3] statewide comparison by lockdown: https://imgur.com/zNgAApj
[4] just google “Ny times data github”

Rob Kleine

26th April 2020 at 3:52 pm

re: “My main point is to observe that I *think* you are saying lockdowns don’t have an effect, so let’s stop. My interpretation is lockdowns don’t correlate to interaction reduction, which is why they appear not to matter.”

This interpretation seems to fit the, admittedly post-hoc correlational analysis: lock-down measures don’t explain variance above and beyond individual’s social distancing efforts. This raises questions about the marginal benefit of ‘lock down’ initiatives relative to informed individuals.

Claire D

23rd April 2020 at 3:24 pm

The lockdown measures are based on a straightforward sum :

No lockdown measures = 1 infected human (child or adult) infects 2+ others, that growth of infection is completely unsustainable for the NHS to cope with.

Lockdown measures in place = right now 1 infected human is infecting LESS than 1 other human, this has meant the NHS can cope, just.

The purpose of the lockdown is to protect the NHS. If the NHS was overwhelmed and collapsed our present inconvenience would become widespread chaos and suffering.

Reality.

Claire D

24th April 2020 at 9:29 am

Amelia, from reading some of your previous comments I think you are probably much cleverer than I am at maths so I’m not about to argue with you about “integers”. However, my understanding of the ‘less than 1’ idea would be that it is calculated on a percentage, put into terms that the general public can grasp easily.

Claire D

24th April 2020 at 10:32 am

As for my reality being “alternate”, you’re getting in a muddle, there may well be hundreds of other “models”, but the fact is, the one I describe is the one being used in the UK right now, therefore it IS the reality we are living in, there’s nothing “alternate” about it.

James Knight

24th April 2020 at 8:36 pm

It is not “reality” it was one model prediction. It wasn’t even peer reviewed. The article looks at empirical data to see if the theory is backed up by evidence. But the evidence is lacking in actual data.

There is something called “confirmation bias”. If you bet the farm on a particular theory, then you have to believe it. At the moment the UK is betting the equivalent of 6 hospitals per week on the lockdown policy.

Claire D

25th April 2020 at 8:59 am

James,
. . . whichever ‘model’ had been chosen there would be “confirmation bias”. A leader who makes a decision that dramatically effects the lives of millions of people, and is then prepared to waft about exploring other approaches (I can think of someone who I’m glad to see the back of), is likely to get bogged down and get nowhere, with a pandemic that would have been disastrous. The government chose a model, a perfectly reasonable one I think and took the precaution of building more temporary hospitals fast.
Italy’s experience, about 3 weeks behind us, was the warning; they are the closest to us in terms of population : 60,500,000 (UK 68,000,000), people per Km2 : 206 (UK 279) and hospital capacity. Many on here seem to have forgotten very quickly the horrific situation in Italy a month ago, with sick patients in corridors and the numbers of deaths rising fast. Just look at the figures for people per square Km and it is obvious that the UK was going to suffer an even worse fate if the government did not act fast, which they did.

Claire D

25th April 2020 at 9:08 am

I meant to add . . the idea that there could be empirical data for the lockdown decision under the present circumstances is a bit daft anyway. This is a new disease, happening suddenly, in the modern world. To expect peer reviewed empirical data to be sitting waiting patiently for just such an occurrence is unrealistic.

Claire D

25th April 2020 at 10:45 am

Thanks Amelia, I’m guessing your second response above was meant to have come after this one. I do understand “confirmation bias”, I was responding to James’s use of it in his “farm” metaphor.

jan mozelewski

23rd April 2020 at 10:14 am

The lockdowns are not remotely logical or sustainable. Locking away healthy people, including sections of society which clearly have almost zero risk of a bad case of CO19, let alone dying…that isn’t a quarantine. Lockdown of everyone is then justified ‘because it protects the vulnerable’. In that case, it begs the question why the most vulnerable people…in care homes or hospitals…have so clearly been failed. No basic PPE for staff, no testing of staff in care homes to make sure that they are not spreading the virus to the patients. Basic stuff. All at the same time as stopping the relatives visiting.
Untested and unmasked coppers approaching lone sunbathers. Unmasked shoppers spreading droplets all over supermarkets. As a lockdown it is ludicrous.
Every step of these policies has been illogical from the standpoint of public health. So it is driven by something else. Probably several other priorities. So Project Fear was revved up.
The lack of tests and testing….was then justified by saying that tests and testing was unnecessary. And then of course when it because clear from other countries that actually it helped considerably there has been feet-dragging and obfuscation.
The lack of masks…..was justified by the elaborate fiction that mask did not stop infection. Focusing entirely on masks not stopping the wearer contracting it but totally failing to mention that they would prevent droplets from spreading and protect others. Countries where everyone wear masks in public have much lower rates of spread with or without a lockdown. The policy in the UK was framed entirely by a lack of honesty. PHE hadn’t prepared and they then had to deflect and double-down.
So. Whatever pandemic they were supposed to be well prepared for it certainly wasn’t this one. And that became clear months ago. Instead of putting energy into putting that right the civil servants and quangos have instead taken our civil liberties, weaponised fear, and made the policy fit their existing preparations. And when all else fails tell us to ‘protect the NHS’.

jan mozelewski

23rd April 2020 at 9:21 am

The biggest clue to the plain fact that lockdowns do not work is the clear problem of coming out of them without destroying the so-called benefit they were ostensibly intended to deliver.

John Hendy

23rd April 2020 at 5:31 pm

I *think* this is a convoluted way of saying “pausing the spread of a disease doesn’t work because when you un-pause, the disease spreads?” Is that fair? I found this pretty helpful to that effect: https://medium.com/@tomaspueyo/coronavirus-the-hammer-and-the-dance-be9337092b56

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22nd April 2020 at 11:47 pm

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Margaret Crump

22nd April 2020 at 7:08 pm

These are some interviews with Dr. Jay Bhattacharya who is an MD as well as having a PhD in economics. He is working with others at Stanford University in California to do antibody testing in order to come up with a denominator of how many people have had and recovered from the virus to help establish a real rate or mortality. https://www.hoover.org/research/questioning-conventional-wisdom-covid-19-crisis-dr-jay-bhattacharya and https://www.hoover.org/research/fight-against-covid-19-update-dr-jay-bhattacharya

Highland Fleet Lute

22nd April 2020 at 6:52 pm

It’s Game Over and the Swedish-Belarusian Herd Immunity Model Has Won

One third of Stockholmers have already had Covid-19, shook it off, and are now immune

https://www.anti-empire.com/its-game-over-and-the-swedish-belarusian-herd-immunity-model-has-won/

Michael Dorsey

22nd April 2020 at 9:01 pm

This is great news if it pans out, but as far as I know there is no way of knowing at this point how much immunity we have once we’ve been infected, or how long it protects us.

jan mozelewski

23rd April 2020 at 9:51 am

The Covid virus is much more stable than the flu virus and thus it seems highly likely that a reasonable level of protection will be given for some time. All the doom-sayers who talk of limited immunity etc are doing it to justify and smoke-screen their policy choices. Project fear to keep people obeying.

George Whale

23rd April 2020 at 12:26 am

Also in California: “Coronavirus Infections May Not Be Uncommon, Tests Suggest” https://www.nytimes.com/2020/04/21/health/coronavirus-antibodies-california.html

George Whale

23rd April 2020 at 12:53 am

“Antibody testing studies suggest mortality rate is up to 70 TIMES lower than official figures” https://www.dailymail.co.uk/news/article-8244533/What-REAL-death-rate-COVID-19-Data-LA-suggests-kill-0-18-patients.html

jan mozelewski

23rd April 2020 at 9:37 am

Which, of course, is why the public health Nazis who appear to be deciding policy (based largely on the need to cover up their own inadequacies and keep their gravy train on track) have been so reticent to actually get on with it and do the tests. They know they won’t like the results. And that isn’t because they will find the death rate is high.

Jerald King

22nd April 2020 at 6:50 pm

As a professional number cruncher whose graduate degree involved new uses of multiple regression I can state clearly this author has no clue about statistics or their use. The single largest variable, which is missing from the analysis, is the time to or from the peak death rate. The states (Arkansas, Iowa, Utah, etc) ALL had projected peak death rates (by IHME on April 21) between April 29 and May 14, with four of them after May 6. The projected death rates per day at peak were all move than SIX (6 !) times greater than the numbers used by the author. The states which imposed early social restrictions all had peaks near April 16, e.g. California peaked on April 17.

SO – the author is comparing death rates at peak times to death rates that are many weeks prior to their possible peaks. An entirely bogus comparison.

Darth Saddius

22nd April 2020 at 6:57 pm

Well spotted. I was a bit suspicious about this geezer statistical bona fides when he wrote ‘…..linear regression – is a computerised mathematical technique……..’. This must be news to all those mathematicians etc who used linear regression in the 19th century.

Darth Saddius

22nd April 2020 at 7:02 pm

‘Geezers’ – an edit button would be good!

Erik Nelson

23rd April 2020 at 8:26 am

https://en.m.wikipedia.org/wiki/Wilfred_Reilly

He’s a PhD in political science and a tenured professor, so I’d venture to guess he does know a thing or two about stats…but may not be an expert. He says in the article that you can contact him to get the data and discuss the model and findings. Instead of lobbing bombs with little to no knowledge or low credibly on his actual work, I’d challenge you to take the harder route and collaborate with him to prove this wrong with all that knowledge you have, and that big brain!

John Hendy

23rd April 2020 at 5:39 pm

True, but it’s also 2020 and this is the internet. Here’s a counter-example: https://rt.live/

1) they lay things out visually vs. having to follow a lesson in statistics by literally reading prose containing numbers and groups, which you can’t possibly keep straight through the article. Use visualizations/tables, not paragraphs!

2) pre-emptively show your data and code. That linked site explains the theory *and* provides the actual code generating their numbers. Pretty awesome.

Again, yes we *can* email request this stuff… but surely you’d agree it would be soooo much better if he just laid it out in advance.

Linda Payne

22nd April 2020 at 6:03 pm

Sounds like we will have some form of ‘social distancing’ for another 7 months can’t see the economy or social fabric will survive this

Michael Dorsey

22nd April 2020 at 5:17 pm

Mr.Reilly says that the states that have established “lockdowns” have COVID deaths per million ranging from 7 to 19. He mentions Sweden, which has much more liberal policies, and which started having known cases later than the US (and is thus probably in earlier stage of its contagion curve), as having 139 deaths per million. He doesn’t consider this statistically significant. Wow.

Laramie evan

22nd April 2020 at 6:03 pm

He’s expressly comparing Europe to Europe with Sweden. Quite fair in my opinion.

A look at even the most basic “by country” COVID data shows that the death rate in the US is much lower than in Europe, rendering any state comparison with any European country unfair and meaningless. For example as of 04/22/20:

Country Deaths Deaths/1MM pop

United States 45,967 140.5
Italy 24,648 407.9
Spain 21,717 464.8
France 20,796 310.4
United Kingdom 18,100 272.2
Belgium 6,262 548.2

Michael Dorsey

22nd April 2020 at 7:01 pm

In that case, why does he bring Europe into his article at all, if he wants to make the point that US policies aren’t effective?

Noah Potash

22nd April 2020 at 4:28 pm

Being a “professional political scientist” doesn’t qualify you to analyze this data. Stay in your lane.

Alan Blair

23rd April 2020 at 12:16 am

Much of political science is based on statistics. You are incorrect.

Erik Nelson

23rd April 2020 at 8:40 am

Yeah, this is a super ignorant comment… He’s not just a ‘professional political scientist’s, he’s a PhD tenured track professor at Kentucky State and a lawyer.

Rick Witten

22nd April 2020 at 3:42 pm

Reilly mentions in passing that he did not consider the “date of first case” as a variable. This is arguably the most significant factor to consider. The time period between the first known case and the start of social distancing measures is when the virus has the opportunity to spread widely. Ignoring that factor throws his results, and even his motivations, into question.
The reference to Sweden demonstrates ignorance or dishonesty. Reilly acknowledged the importance of cases or deaths per million rather than total cases per country or state. Sweden currently ranks 10th globally in deaths per million (not 10th in Europe), and 8th if Sint Maarten and Channel Islands are removed due to their tiny populations. Denmark is 20th (14th excluding small countries) and Norway 28th (20th). Perhaps that qualifies as “close”, as Reilly characterizes it. In deaths per million, however, Sweden is nearly 300% higher than Denmark and 580% higher than Norway. Close?
Reilly points out that the actual mortality rate can’t be determined because of the unknown number of cases. This of course, is always true. How many unknown H1N1 cases were there in the 1918 pandemic? Of course our knowledge will increase with time, but what we know now is that in terms of symptomatic cases this virus is very deadly. There will never be a single mortality rate because of all the factors that affect outcomes, such as overwhelmed healthcare systems. But let’s look at those Stanford numbers. If true, the actual number of cases in the US tops 45 million, with only 1.8% of those cases having been identified. We know the impact of the virus varies greatly, from perhaps no symptoms to major organ damage and death. But is it realistic to think that 98% of cases completely evade detection?
Why does Reilly not consider the highly significant variable of date of onset? With exponential growth, the largest impact is gained in the earliest stages. Reilly is either ignorant of this very basic fact, he is blinded by his implicit biases, or he has knowingly created a skewed article to bolster his personal interests. Biased analysis as the basis of public policy increases the risk of a prolonged crises and ever increasing death counts.

James Knight

22nd April 2020 at 4:58 pm

“The time period between the first known case and the start of social distancing measures is when the virus has the opportunity to spread widely. ”

The operative word is “known” case. All the graphs show a cumulative increase from when we started testing for covid19. If we stopped testing the graph would go back to zero.

If you are going to put an atomic bomb under the global economy and have a virtual police state, the onus is on those proposing the policy to prove it is effective. This was not a well thought out policy it was a panic reaction to one non-peer reviewed study which was a model only. The point of this article is the models need to be tested empirically. Note how global warming models repeatedly fail due to running hot, but that doesn’t invalidate them apparently. Attachment to the theory is too strong.

I can imagine an early but far more draconian lockdown could work. Prohibition stopped people drinking when applied in a sufficiently authoritarian manner, it is just the collateral damage of that was higher than the original problem. The lockdown we have could be like a half completed course of anti-biotics.

steve moxon

22nd April 2020 at 5:54 pm

Well said.
And a neat analogy at the end.

Erik Nelson

23rd April 2020 at 8:42 am

Rick, I don’t think we can guess date of first case…that’s kinda the point of the antibody studies showing it’s already much more widespread than we knew.

K Tojo

22nd April 2020 at 1:38 pm

Is there anything quite so depressing as logging on to an online publication and seeing a headline which begins…
“Experts have called on the government to…’
because you know that the “experts” will be calling on the government to bring in even more restrictions on personal freedom – all to save “our” NHS of course (or should that be “their” NHS).

Phil Shaffer

22nd April 2020 at 1:03 pm

it is not surprising in the least the the most siginficant factor influencing raw deaths was population. Fore example, if the death rate were uniform across the nation, meaning identical death rate per million population, then the death rate would be a pure reflection of the population. What I am most interested in is the results of your multiple regression when the variable being predicted is not deaths or infections, but deaths per million, and infections per million. That does not appear to be reported in this article, but I have to think you tested this. What was that result??

Ann Ceely

22nd April 2020 at 11:55 am

However, if you look at the density of cases within the UK, you will see that Gloucestershire is badly hit. This is where Prince Charles and company caught the virus as they went around Cheltenham Racecourse.

That gives a pretty good indication that the virus replicates wherever large mobs of pleasure-seekers are gathered together in a tight bunch.

Cheltenham Festival has gone out with a bang after four days of action at the races.
Day four of the Cheltenham Races saw crowds of 68,859 people flock to Cheltenham racecourse.

https://www.gloucestershirelive.co.uk/sport/racing/cheltenham-festival-2020-sees-crowds-3949872

James Knight

22nd April 2020 at 1:10 pm

This sounds like the “narrative fallacy”.

Mike Ovington

22nd April 2020 at 11:50 am

I started to read this article but I gave up when I got to “These states reported 1,620, 2,141, 952, 343, 1,311, 2,542 and 288 cases of Covid-19 respectively as of 3:40pm EST on 16 April – for an average of 1,321 cases. The states reported 37, 60, 21, 9, 7, 20, and 2 deaths respectively, for an average of 22.3 deaths.”
Jumping back and forth to relate numbers to states caused nausea.
Scanning ahead showed that one or more tables would have made this article comprehensible.

Christopher Tyson

22nd April 2020 at 10:18 am

I did a course in statistics (compulsory) while at university, in the words of my tutor, my result was ‘a disaster’. I leave the statistical analysis to others.
My question is more practical, in terms of ending the lockdown. If we are to end the lockdown in London, we will have to open up the transport system. The transport system is designed to ferry large numbers of people quickly and efficiently. It is (or seems to me) inconceivable that we could have social distancing on the London Underground. If we stopped people getting on trains, they would be waiting at platforms. If we stopped them entering the station they would be waiting outside. Basically we would have to stop them going to work at all. We would have to control the number of people entering London to go to work. We would have to make decisions about who should be allowed in to work. Workplaces such as open plan offices and call centres, could no longer function. Business plans would have to be re-worked from scratch. These new structures may require government subsidy to remain sustainable, but for how long? Do individual companies decide who should or shouldn’t come to work? Do they continue to pay those who have to stay at home? In retail there would be no point in opening businesses unless customers were free to travel and shop.
My point is that if you try to make London a ‘little bit’ open, with everything being interconnected, little by little you are opening up the whole thing. I wonder if this is what is giving the government a headache. Behind this is the fear that the pandemic would spread in all kinds of unimagined ways, and those making the decision would be held to account.
In the words of TV series ‘Yes Minister’ any decision made by government, would have to be ‘courageous’. But there are people like the writer of this article, who have logistical and statistical nous, who might be able to help.

Alan Blair

23rd April 2020 at 12:13 am

I think you are correct, but that was the original plan. Do Social Distancing so you get the curve down and do not overwhelm the healthcare system. Slowly and eventually everyone who is going to get the disease gets it. You get to Herd Immunity at between 60% to 80% infection. The theory is that you get more deaths early one, but after 12 months you have around the same number of deaths as those who did a Complete Shut Down. However, I have seen no clear data on this yet.

What might make shut-down better is that it gives you more time to: (1) Develop better Treatments (lower mortality rate), (2) Get you to a Vaccine (around 18 months), or (3) you survive until the Virus gets less deadly (over time most diseases have a decreasing virulance).

steve moxon

22nd April 2020 at 9:49 am

The article is spot on, though actually conservative re the likely overall infection rate. Researchers at the London School of Hygiene & Tropical Medicine and Oxford University put it at fully a third or a half of the total UK population (I forget which said which, but both reckon it’s way higher than 15%).
‘Lockdown’ must be ended pronto.

Philip Humphrey

22nd April 2020 at 9:35 am

Interesting that the most significant variable was population (presumably population density ). Cannot help wondering whether in densely populated areas such as London or New York the virus could reach a critical concentration in the air generally and lockdown and social distancing will not stop its spread. We know that air normally contains all sorts of viruses and bacteria, if the virus can survive several hours in air and there is a sufficient concentration of sufferers or carriers emitting virus particles, then there will be virus particles in the air all the time. And if the number of virus particles needed to start an infection is low enough, then it could spread that way.

James Knight

22nd April 2020 at 9:22 am

Lockdowns are the largest uncontrolled experiment in history. They may make sense if they are early, very draconian and short lived with an exit strategy.

A virus is like a fire and the fuel load for the fire is the number of susceptible people. The lockdowns just maintain largest possible fuel load for the virus later on.

Steve Roberts

22nd April 2020 at 9:18 am

Apologies for being a lay man in terms of epidemiology and statistics. although i do have a capability for understanding logic and reason. No apologies for been an ardent, from the outset, dissenter to the irrational madness unleashed on society by the government and wider establishment.
Reilly seems to be trying to prove that there is no difference between lockdown and social distancing in terms of the effects on the spread of the virus.
Does that mean he still supports social distancing ? He doesn’t make it clear, and how exactly is society to get back to the old normal while social distancing is still in place ? That’s an impossibility, it is also a weakness in the face of the moral fervour around the virus we have been bombarded with, i doubt it will convince many who are genuinely fearful of something that has been treated as the black death.
Social distancing , when almost all viruses appear, as they do every year, used to mean sneezing into a handkerchief, not going to a confined workplace and spreading “germs” not visiting granny as she is frail or not the neighbours as they have a new born, and the one piece of good advise to come from all this , wash hands more frequently.
This is what social distancing used to mean, fellow citizens been reasonable as part of an accepted viral management programme then pursued by the authorities by the resources it has to protect the vulnerable, inadequate from the authorities and we should demand more. It is not what SD means today.
But even Reilly’s study is flawed, and he acknowledes it right at the beginning, infection rates and death rates are unknown, they cannot be known until mass testing is done on a huge proportion of the population and the deaths are more accurately identified as definetly being caused by covid.
While Reilly’s attempt is no doubt in good faith and perhaps he hopes it can build the evidence to stop the lockdown , as a dissenter it does not seem to me to be logical or able to dismiss the variables of rates he alludes to.
It is eminently feasable that the differing outcomes and amounts of deaths are directly related to the infection rates of the population at different stages and acted upon very differently but all this is unquantifiable. Some people are suggesting the virus is taking its course, petering out in some places, not yet reached peak in others, it could also mean , in terms of rates of infection that social distancing and lockdown neither have any or little effect on healthcare capabilities to cope or even saving lives of those most vulnerable.
The only way to rebuff this now destructive path is to refute its basic premise of extrapolated evidence. there is lots of expert evidence and opinion that makes clear all this was unnecessary and a different path taken that would not have involved what has occured and is likely , as the evidence is mounting, to cause more deaths than may have been saved.

Erik Nelson

23rd April 2020 at 8:57 am

My take is as a political scientist he’s less interested in giving his personal point of view about which is the best course of action to follow from a medical perspective, but to show the impact of outcomes related to the political decisions being made for lockdowns vs social distancing. But it stands to reason he thinks social distancing is an acceptable risk for us to take since he wrote this thing and the whole point he’s trying to make is that social distancing is no different in outcomes from lockdowns in terms of deaths.

Mark Houghton

22nd April 2020 at 9:12 am

The lockdown is ostensibly there to stop the NHS being overwhelmed. Since most younger people in good health don’t need the NHS when they get the virus, why are they being locked down?

Steve Roberts

22nd April 2020 at 9:44 am

Mark Houghton, the capacity of the NHS is an issue of resourses, logistics, in 2020 it is not beyond the capabilities of a modern state to mobilise resources to cope, quickly ,not at all. With the exception of a few areas where there have been specific spikes of illness the nationwide situation is not of overcrowding or lack of resources at all. And where is the evidence that social distancing or lockdown are preventing hospital admissions or deaths, correlation or causation would suffice, where is it ? See other Spiked article today and many articles by expert “dissenters”

steve moxon

22nd April 2020 at 9:45 am

Precisely.

James Conner

22nd April 2020 at 10:00 am

“Since most younger people in good health don’t need the NHS when they get the virus, why are they being locked down?”

One reason might be that although children are unlikely to need the NHS when they get infected, they could still become infected themselves and transmit the virus to people who ‘will’ need the NHS, ie old farts like me.

Mark Houghton

22nd April 2020 at 10:37 am

Well then let’s help the vulnerable groups to self isolate and we do our very best to make sure they don’t get the virus and let everyone else get on with it. Or lock everyone up and screw the economy. Forever.

James Conner

22nd April 2020 at 11:12 am

I agree 100%. The wrong people (ie. everyone) are being locked down. Compare the approach of Sweden to that of the UK. Both countries will ultimately have a similar % of their population die, but the difference is, at the end of it all, Sweden will still have a functioning economy.

Adamsson 66

22nd April 2020 at 9:06 am

You’re completely wrong the lockdown in Wuhan was to control the narrative and silence any criticism of the CCP it was a complete success. Any effect on the spread of the virus was entirely coincidental.

Highland Fleet Lute

22nd April 2020 at 7:17 am

Fires, rioting & ambushes: Police say Paris suburbs ‘BACK TO NORMAL’ after month of lockdown (VIDEOS)
https://www.rt.com/news/486464-paris-suburbs-riots-lockdown/

George Whale

22nd April 2020 at 7:50 am

Parisians must be thrilled at how diversity has enriched their city.

Highland Fleet Lute

22nd April 2020 at 9:11 am

What I wondered was, WTF do you buy fireworks in Paris at this time of the year, and under these circumstances?

Your comment seems to suggest that you may lack prioritisation skills, George. In the shoes that you’re in, where your government has made the historically without precedent move of putting you under house-arrest for over a month, and thrown the UK economy under a bus, don’t you think taking a pop at the darkies is something that should go on the back-burner for a bit?

Adamsson 66

22nd April 2020 at 9:07 am

The French are showing the way out of lockdown. Burn it down

George Whale

22nd April 2020 at 10:22 am

The French?

steve moxon

22nd April 2020 at 5:58 pm

Islamic migrants now living in migrant enclaves around french cities, you mean.
They burn large number of cars belonging to actual French people each weekend, as they’ve been doing for about 20 or 30 years. So it’s nothing new.

George Whale

22nd April 2020 at 10:21 am

HFL – But look at it from a Parisian’s point of view: is it worse to be put under curfew by government; or to be driven off the streets by vibrant car-burners?

Highland Fleet Lute

22nd April 2020 at 12:46 pm

The Terror of The Situation.

I look at it like this, George….

I imagine you’ve he(a)rd the term “blue funk” before.

There’s a lot of it about.

Please Mr Police Officer, don’t arrest me, I’m good…

Arrest those Darkies instead.
Arrest those Brexiteers, instead.
Arrest those Remainers, instead.
Arrest those anti-vaxxers, instead.
Arrest those conspiracy theorists, instead.
Arrest those right-wingers, instead.
Arrest those left-wingers, instead.
Arrest those sunbathers, instead.

etc.

In Nazi Germany, The Gestapo was a comparatively small organisation that didn’t have to do too much in terms of snooping, investigating, and “your-papers-please”-ing, ’cause the base-line German population loved finger-pointing, ratting on each other and fitting each other up to such a high extent that the whole operation pretty much ran itself. Echoes of which we can see in The UK today with all of this Covid 19 nonsense.

A lot of the worst of this is coming from journalists, bloggers, podcasters who should know better, but clearly don’t.

George Galloway, Sargon of Akkad, Paul Joseph Watson, to name a few.

George Whale

22nd April 2020 at 2:12 pm

Street rioting, unlike sunbathing or holding different opinions, can cause actual harm to people or property. To conflate them is disingenuous.

jan mozelewski

23rd April 2020 at 9:47 am

These riots are instigated by North African immigrants. Second or third generation but identifying as not French. Like it or not, that is the fact. The problems have been simmering (not just in Paris) for decades and every so often they boil over. The lockdown has meant that the security and emergency services are already over-stretched policing it. So a perfect opportunity to make trouble if one has a mind to do so.
Just as in the UK and other countries similarly run by a corrupt and ineffectual trough-snouting civil service/ bureaucracy, France is more concerned with policing the law-abiding than policing the law-breakers. So their priority is stopping cars with two family members in at a time (tut tut) or lecturing a mother with a buggy for sitting on a bench.

Highland Fleet Lute

22nd April 2020 at 6:30 am

“The original response to Covid-19 was driven by an understandable fear of an unknown disease.”

Seems bizarre to me that The British Government implemented the lockdown AFTER they’d downgraded coronavirus as “no longer dangerous”….

https://www.armstrongeconomics.com/international-news/politics/uk-government-downgrade-coronavirus-as-no-longer-highly-dangerous/

Does that not seem a bit strange to you? Or does a pertinent line of enquiry into that, or anything else with a bit of a squiffy look about it, set your sphincter a-wobbling re: “conspiracy theorists”?

This is not by any means a tough generation.

James Knight

22nd April 2020 at 10:16 am

By that measure the government could say ISIS is “not dangerous”.

Norman Baker

22nd April 2020 at 1:23 pm

They decided to no longer classify it as an HICD which is good because there are only two hospitals in the country equipped to treat HICDs.

What seems strange to me is there are people dumb enough to think that because cv-19 isn’t the same as ebola it must be the same as a cold.

James Knight

22nd April 2020 at 3:25 pm

There are always some people dumb enough to put their hand in a toaster or saw off the branch they are sitting one. You cannot extrapolate from outliers.

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