Do Lockdowns Work ? If not, why not? Do they cause worse?

         Do Lockdowns Work? Well of course they do! Maybe not.

I’m a little embarrassed but it seems from the heavy REAL Science it makes things worse

At least that is what this article ,published in The Wall  street Journal says

The Failed Experiment of Covid Lockdowns

New data suggest that social distancing and reopening haven’t determined the spread.

TrendMacro, my analytics firm, tallied the cumulative number of reported cases of Covid-19 in each state and the District of Columbia as a percentage of population, based on data from state and local health departments aggregated by the Covid Tracking Project. We then compared that with the timing and intensity of the lockdown in each jurisdiction. That is measured not by the mandates put in place by government officials, but rather by observing what people in each jurisdiction actually did, along with their baseline behavior before the lockdowns. This is captured in highly detailed anonymized cellphone tracking data provided by Google and others and tabulated by the University of Maryland’s Transportation Institute into a “Social Distancing Index.”

Measuring from the start of the year to each state’s point of maximum lockdown—which range from April 5 to April 18—it turns out that lockdowns correlated with a greater spread of the virus. States with longer, stricter lockdowns also had larger Covid outbreaks. The five places with the harshest lockdowns—the District of Columbia, New York, Michigan, New Jersey and Massachusetts—had the heaviest caseloads.

The lesson is not that lockdowns made the spread of Covid-19 worse—although the raw evidence might suggest that—but that lockdowns probably didn’t help, and opening up didn’t hurt. This defies common sense. In theory, the spread of an infectious disease ought to be controllable by quarantine. Evidently not in practice, though we are aware of no researcher who understands why not.

We’re not the only researchers to have discovered this statistical relationship. We first published a version of these findings in April, around the same time similar findings appeared in these pages. In July, a publication of the Lancet published research that found similar results looking across countries rather than U.S. states. “A longer time prior to implementation of any lockdown was associated with a lower number of detected cases,” the study concludes. Those findings have now been enhanced by sophisticated measures of actual social distancing, and data from the reopening phase.

There are experimental controls that all this research lacks. There are no observable instances in which there were either total lockdowns or no lockdowns at all. But there’s no escaping the evidence that, at minimum, heavy lockdowns were no more effective than light ones, and that opening up a lot was no more harmful than opening up a little. So where’s the science that would justify the heavy lockdowns many public-health officials are still demanding?

With the evidence we now possess, even the most risk-averse and single-minded public-health officials should hesitate before demanding the next lockdown and causing the next economic recession.

Mr. Luskin is chief investment officer of TrendMacro.

According to the Guardian , they really can’t work

The millions of people who cannot afford to self-isolate face a choice between Covid compliance and financial devastation

Passengers at Heathrow airport, London, March 2020

Passengers at Heathrow airport, London, March 2020. Photograph: Tolga Akmen/AFP/Getty Images

Lockdowns only work if they reduce transmission. And transmission only reduces if those who are sick self-isolate. But what if that comes at too great a cost? The millions of people who cannot afford to self-isolate face a choice between financial devastation and compliance. By not providing proper support, the government is forcing people to decide between their families and their communities. This choice is cruel. And it is avoidable.


The evidence is clear that Covid-19 disparities are driven by differences in exposure both at home and at work. Those of lower socioeconomic status are hit hardest by both the virus and the collateral damage of restrictions. In lockdown, almost all risk is shifted on to the 10 million key workers who cannot work from home, as well as those living in deprived areas and overcrowded houses – two groups that often overlap.

Like lockdowns, testing and tracing will only reduce transmission if infectious cases are able to isolate effectively. Yet possibly fewer than 20% of those who should isolate do so fully. The data shows that, while most people intend to adhere to government advice, only 12% get a test, 18% isolate, and 11% of contacts isolate properly. Crucially, self-reported ability to self-isolate is three times lower in those who earn less than £20,000 per year or have less than £100 saved.

(Note this fits in with the observation observation above that the only correlation researchers found was mass transit)

WMBriggs , the statician explains


Why Lockdowns Spread Bugs Faster Than Liberty:


Suppose a bug is 100% transmissible. Everybody in contact with somebody infected therefore gets it, and passes it on with certainty to the next person they meet.

A lockdown will spread this bug faster than allowing people to remain at liberty.

Lockdowns are not quarantines in the old-fashioned sense of that term, where infected people were isolated—kept separate in every way from the non-infected. If you think lockdown and hear quarantine your ears are busted. Quarantines can make sense; lockdowns never do.

Lockdowns are merely forced gatherings. People in lockdown are allowed to venture forth from their dwellings to do “essential” activities, like spending money at oligarch-run stores. These stores are collection points, where people are concentrated. Some are allowed to go to jobs, such as supporting oligarch-run stores.

Which stores are allowed to remain open which are forced to close are arbitrary. No standalone restaurants, for instance, but you can eat in oligarch-run company cafeterias, like at Costco. Google employees can eat in their own cafeterias or break rooms, too. Restaurants can still come to you, via delivery. Another concentration point. You can go to to grocery store, but some aisles, those containing forbidden items, might be closed off, thus forcing people into fewer spaces.

Lockdowns are not quarantines. Lockdowns concentrate people into fewer areas. Lockdowns are only pain.

Lockdowns allow people outside to mingle for a time, then it forces them back inside to mingle with a vengeance.

It’s clear that our 100% transmissible bug will spread much faster when people are forced to spend more time indoors with each other. Once one person gets it, he will spread it to those at his home immediately. If people were at liberty, and therefore more separated, the bug would still spread to everybody, but more slowly (the speed here is relative).

Now suppose the bug only has a 1 in a 1,000 chance of spreading per contact. Low. Lockdowns will still spread it more quickly than liberty. And for the same reason. Lockdowns force people together. The venues they are allowed to venture to are restricted, and therefore concentrate contact, and they force people inside their homes where it’s obvious contact time increases. Lockdowns concentrate contact spaces and times.

Transmission rate, then, has little to do with the efficacy of lockdowns. There is no efficacy of lockdowns preventing transmission, only in controlling where the transmissions will take place.

The opposite of the lockdown is quarantine-liberty. The ill are quarantined, kept entirely separate from the healthy until they are dead or no longer communicable. Because of cheating, transmission is still possible, but it’s far less likely. Liberty of the healthy allows people to live their normal lives, which slows transmission. And does not concentrate power into the hands of the government or oligarchy.

It was obvious before 2020 that lockdowns (with then only weather forcing people to gather inside for long periods) not only did not stop the transmission of bugs, but helped spread them. A look (below) at the all-cause death numbers peaking every single winter without exception (this year, too) proved that. It was in no way controversial. It was so well known that forced contact spread bugs that mentioning it was like saying the sun rose in the east.

Then came 2020 and the “expert” idea of lockdowns would do the opposite of what everybody had always known they would do. Suddenly, instead of spreading bugs, as they always did before, they would stop or at least slow the spread. Experts said so.

Finally , according to this article at Aier  https://www.aier.org/

New Study Links Lockdowns to Potential Long-Term Increases In Excess



Anew working paper published by the National Bureau of Economic Research gives a stark prediction that the economic damage brought about by lockdowns will lead to a significant increase in excess deaths for the long-term future. The authors of the study, a team of three researchers at Duke, John Hopkins, and Harvard, assert in their study that although they believe lockdown policies have saved lives, policymakers must be conscious of the long-term damage unemployment will have on public health. Rather than solely focusing on preventing deaths caused by Covid-19, we must also be cognizant of the deaths that will be caused by the economic damage of Covid-19 and lockdowns. There is much-documented discussion about the immediate tradeoffs of lockdowns from short-term economic devastation, to mental health problems, and drug overdoses. The authors explain the significance of their study on long-term damage when they write,

“Overall, the economic literature has extensively analyzed the short-run trade-off between economic activity and the containment of the pandemic. We emphasize that an equally important long-run trade-off exists. It is worth clarifying that with this claim, we do not want to suggest that policymakers should refrain from ordering lockdowns, as necessary lifesaving measures, but rather that, if they decide to do so, they should provide alongside enhanced health and economic support for the most vulnerable portions of the population.”

The aforementioned economic support is necessary because contrary to the prevailing narrative, a bad economy kills too. Although many would be quick to dismiss the catastrophic economic damage that has been done to the country as a sort of inconvenience (like Dr. Fauci) the authors contend that this damage will also lead to excess deaths in the long term. They write,

“We estimate the size of the COVID-19-related unemployment to be between 2 and 5 times larger than the typical unemployment shock, depending on race/gender, resulting in a 3.0% increase in mortality rate and a 0.5% drop in life expectancy over the next 15 years for the overall American population. We also predict that the shock will disproportionately affect African-Americans and women, over a short horizon, while white men might suffer large consequences over longer horizons. These figures translate in a staggering 0.89 million additional deaths over the next 15 years.”

This of course is just an estimate as there are a variety of factors that could shift this statistic, such as the fact that the true unemployment rate is likely far higher as many have simply given up on searching for a job. Although it is well-established that unemployment has a variety of immediate lethal consequences such as an increase in suicides and drug overdoses, the authors note that stressors associated with unemployment lead to shortened life expectancies and higher death rates years down the line.

The Data

The authors pool data on life expectancy, age-adjusted death rates, and unemployment rates from the CDC and the Bureau of Labor Statistics. They then inputted those numbers into a vector autoregression (VAR), which is a time series model that tracks the relationship of multiple variables. Provided below is the raw data featured in the study. The data is disaggregated to demonstrate the differences between demographics that are affected disproportionately by unemployment.

The above VAR demonstrates the relationship between the three variables: life expectancy, age-adjusted death rates, and unemployment rate over time from 1950-2017. Congruent with the authors’ thesis, life expectancy decreases and the death rate increases for years following a spike in unemployment. Furthermore, the authors explain the immediate increase in life expectancy at the onset of an unemployment spike when they write

“On impact, unemployment can lead to a reduction in mortality as deaths due to work-related causes or motor vehicle accidents declined, but over time economic distress takes a toll on human well-being. We consider this an interesting direction for future research.”

The data shows that there is a clear relationship between spikes in unemployment and an increase in mortality rates within the coming years, likely due to the various negative side effects associated with unemployment. The study provides disaggregated graphs showing individual trends for various demographics. They note that African-Americans and women tend to experience more extreme shocks in unemployment as well as more severe long-term health consequences.

Figure 4 is regarded as one of the most important graphs by the authors. That is because it shows the direct relationship between a drop in the unemployment rate and average life expectancy as well as death rates. The unemployment rate on the far right is shown spiking and then dropping off through the years. The two graphs to the left show that life expectancy and death rates continue to be affected years after the unemployment spike. They reach their peak severity about three years after the unemployment spike and don’t return to pre-spike levels for over ten years. In other words, life expectancies can be suppressed and death rates are higher for over two decades following a spike in unemployment.

Provided above is the disaggregated data to show the disproportionate effects an employment shock will have on various demographics. In particular, African-Americans and women will be hit hardest.

Potential Variables

It is worth noting that the study was conducted with data that is likely an imperfect representation of reality as all models are. The authors note that it is entirely possible that a swift or slow economic recovery may play a sizable role in the overall effects on future mortality. They also note that changing political and social circumstances may also affect the speed of economic recovery as well as the performance of the healthcare sector. Other important variables that could cause more severe outcomes are the disruptions to the healthcare sector during the pandemic, apprehension to seeking healthcare because of a fear of infection, and the massive loss of employer-provided healthcare. Finally, the authors note that this is the first recession with the Affordable Care Act in place, which may have an effect on an individual’s ability to access healthcare while unemployed.

What Does This All Mean

The study itself is quite numbers-dense and full of equations, but the message is clear. Unemployment is a real public health issue that if left unmitigated will lead to excess deaths in the future. The bulk of excess deaths do not occur suddenly but years in the future and they don’t return to normal for up to 20 years down the line. It is important that policymakers see past the fantasy that economic turmoil is simply a necessary inconvenience in a pandemic. That lockdowns are simply a necessary evil that are needed to stop Covid-19 and can do so without any serious repercussions at all. Whether you support more or less government intervention to address Covid-19, it is important to understand that economic turmoil has serious consequences and also harms public health.

Regardless of your position on lockdowns, addressing the economic damage these policies have created is just as important to preventing excess death as containing the virus. Failing to heed this lesson will simply be fighting one disease by creating another.

Ethan Yang

Ethan Yang

Ethan joined AIER in 2020 as an Editorial Assistant and is a graduate of Trinity College. He received a BA in Political Science alongside a minor in Legal Studies and Formal Organizations.

He currently serves as Local Coordinator at Students for Liberty and the Director of the Mark Twain Center for the Study of Human Freedom at Trinity College.

Prior to joining AIER, he interned at organizations such as the American Legislative Exchange Council, the Connecticut State Senate, and the Cause of Action Institute.

Ethan is currently based in Washington D.C.

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