Israeli Professor Debunks Government Claims That Lockdowns Slow Coronavirus Infection, Proves Worldwide Decline In Spread

Professor Isaac Ben-Israel (also known as Yitzhak Ben Israel) published an English translation of his analysis on worldwide coronavirus infection decline, The End of Exponential Growth: The Decline in the Spread of Coronavirus.

As I wrote last week, professor Ben-Israel published a Hebrew paper comparing the rates of coronavirus infections in the U.S., the U.K., Sweden, Italy, Israel, Switzerland, France, Germany, and Spain over an eight-week period. His team's graphs showed a contradiction to what Americans would have expected to see after listening to our governors' lockdown orders: irrespective of whether a country quarantined like Israel, or went about business as usual like Sweden, coronavirus peaked and subsided in the exact same way. In the exact, same, way. Ben-Israel's graphs show that all countries experienced seemingly identical coronavirus infection patterns, with the number of infected peaking in the sixth week and rapidly subsiding by the eighth week.

Professor Isaac Ben-Israel has provided Townhall with a copy of the English version of his study.

"Our analysis shows that this is a constant pattern across countries. Surprisingly, this pattern is common to countries that have taken a severe lockdown, including an economy paralysis, as well as to countries that implemented a far more lenient policy and have continued in ordinary life," writes Professor Isaac Ben-Israel in the introduction of the translated study. His conclusion is simple: coronavirus "declines even without a complete lockdown."

Professor Ben-Israel began the analysis to find out whether the hypothesized coronavirus exponential growth rate is accurate. His research proved the answer is no. But aside from proving that the infection rate was not exponential in Israel, or anywhere else in the world, his investigation showed "a global phenomenon" of infection rate decline as opposed to exponential growth. "The spread of the virus starts at an exponential rate, however, it continues to moderate and ultimately fades after 8 weeks or so since its outbreak," Professor Ben-Israel explains.

"It is interesting to note," he writes, "that this pattern, mainly the onset rapid growth and the following decline in the number of new daily patients, is still shared amongst countries that responded in significantly different ways." He demonstrates this point by comparing infection rates in Italy, a country that imposed a complete lockdown, with Sweden, which did not.

Most importantly, Professor Ben-Israel debunks the misconception of government lockdowns or controls as a leading cause of coronavirus infection rate reductions. "Some may claim that the decline in the number of additional patients every day is a result of the tight lockdown imposed by the government and health authorities. Examining the data of different countries around the world casts a heavy question mark on the above statement. It turns out that similar pattern - a rapid increase in infections that reaches a peak in the sixth week and declines from the eighth week – is common to all countries in which the disease was discovered, regardless of their response policies: some imposed a severe and immediate lockdown that included not only 'social distancing' and banning crowding, but also an economic shutdown (like Israel); some 'ignored' the infection and continued almost a normal life (such as Taiwan, Korea or Sweden), and some initially adopted a lenient policy but soon reversed to a complete lockdown (such as Italy or the State of New York). Nonetheless, the data shows similar time constants amongst all these countries in regard to the initial rapid growth and the decline of the disease."

Professor Ben-Israel concludes the same as we have heard from some conservative pundits, like Jesse Kelly. "Severe lockdown has some negative implications. Its immediate result is an increase in the level of unemployment and the drop in GDP ... This will eventually lead to an increase in poverty, as well as an increase in loss of human life due to other diseases."

Nonetheless, Ben-Israel recognizes the risk of the disease and notes that "it is advisable to continue with low-cost measures, such as wearing masks, expanding testing for defined populations and prohibiting mass gatherings."

President Trump's Guidelines for Opening Up America Again include these low-cost infection prevention measures such as social distancing and masks. Still, liberal Governors, such as Virginia's Ralph Northam, are not inclined to give up their authoritarian control of the people and businesses. In the meantime, 78% of Virginia restaurant workers have lost their jobs since Northam implemented his closures in March. Northam advised just a day ago that he's not budging and doubled down on this compulsory closure policy, claiming his policy is saving lives. Economic well-being, while a legal requirement for the exercise of a Virginia governor's authority, appears to be of no concern to Northam.

All American leaders need to review Professor Isaac Ben-Israel's analysis. We need to stop our reliance on Dr. Fauci and company, who have demonstrated time and time again that reality and economics play no role in their decision-making. Fauci does not understand the limitations of government powers in the United States, nor the spirit of the American people. Professor Ben-Israel showed us that closures do not reduce the spread of coronavirus. We need to accept this reality, we need to admit we overreacted and that coronavirus closures were a mistake, and we need to go back to work. Now.

“So, we blew up our economy for no good reason? Trump needs to make sure every so-called expert whose opinion he heeded, is identified publicly and is excised from government.”

Yes, but right now we need to all lean on our Governors to end this madness. Push hard!!! Call your state reps every day, tell them to push the governor.

Every. Day.

America’s enemies can’t have Sweden succeed. Beware of being duped.

800,000 people PER DAY are losing their jobs. We are closing in on Great Depression unemployment numbers. Every single day of this madness matters.

Call your state reps. Call your governor. Every day!

End. The. Lockdowns.

NOW!!!!!

Since I have been tracking (beginning March 13), the death rate has been increasing. At the beginning, it was 3.702%, and has steadily increased. Over the last four days, it has remained relatively steady at about 6.84-6.89%. So I do not know if it will reach 7%, but that is a definite possibility.

I keep track of worldwide numbers. I only started tracking the US separately on April 9. The US death rate has climbed from 3.424% to 5.376% in that time, and is still climbing.

A true case fatality rate cannot be determined until all cases are resolved. At this time, there are 1.67 million active cases worldwide, and 672 thousand of them are in the US.

Your analysis doesn’t make sense. While you can say the lock down will affect the number of deaths, you can not say that the lock down affects the rate of death. It makes sense that if people do not lock down the rate of infection will be higher, and thus higher infection numbers AND higher infection rates. However, the death rate is affected by so many variables-the age of the patient, co-morbidity, level of care, etc etc. The article you point to doesn’t mention “reason” the death rate is higher. Basically it just says the death rate is higher so they are wrong. Add to this that the death rate is determined by the number of dead divided by the number of infected. Nobody knows how many people in either Finland or Sweden or any other country for that matter have been infected. We will not get any of these answers until there has been large serology testing. Plus doing comparisons to Sweden at this point doesn’t make sense. Sweden’s strategy is to gain herd immunity. While at this point we don’t know how much of their population has been infected, and in theory they would be immune or somewhat immune, it makes sense since they have not locked down that they will have immunity rates greater than Finland or any other country that has locked down. Therefore in any second wave they should have an advantage. You know when you point out that Swedish infectious disease experts penned a letter urging Sweden to change course, that only means they penned a letter. That doesn’t mean they are right. Sweden’s approach is also based on information from infectious disease experts. It doesn’t mean that they are right. Really at this point we just do not have the real data to make these determinations. I believed we relied too much on the models. They didn’t have all the data either.

First, OMG WALL OF TEXT.

Okay, now that I got that out of the way, a case fatality rate is ALWAYS calculated on the basis of diagnosed cases. Once you start adding in hypotheticals, things start to get messy and wildly inaccurate. (Would you accept a census count based on statistics instead of an actual count?)

I am well aware of the various models and speculations that zillions of people have been already infected. However, there is a) no evidence to support such an assertion, and b) such rapid spread from one case in November 2019 to millions of cases a month or so later would make Covid-19 the most contagious virus ever discovered. It isn't. It is a killer cold virus, and is about as contagious as ordinary cold viruses.

About the studies that are supposedly showing high numbers of people who are already seropositive (they have antibodies to the disease), there are major flaws in those studies. The serological testing has a certain error rate, and the number of positives they have found, for example in the study conducted at Stanford, is close to the margin of error. That study also recruited subjects in such a way that it actually selected for people who might have been exposed, or who might show false positives. The real take-home message is that they are not finding vast numbers of people who have had undetected Covid-19--on the contrary, even in a self-selected group, they did not find levels of seroconversion above the error rate of the antibody test. That study was not, contrary to claims otherwise, evidence that millions of people have already had Covid-19 but without symptoms. There remains, to date, no solid evidence that there are people who contract Covid-19 who never display symptoms.

Now I understand. Every study that doesn’t give you the outcome you desire is flawed. I didn’t add in any hypotheticals. I said the data is incomplete. That’s what makes things “wildly inaccurate and messy”. I did not point to any serology studies. I did not say there were millions of people infected who were not counted. I said we need more data. And we will need to have those types of serology studies. There are only three studies that I am aware of that even tested for antibodies. The one being the Stanford test and a German study and a Dutch study. The Stanford study isn’t the be all and end all antibody studies. It was just a small study. That’s all. There will be more. Two more in fact from Stanford.
However, if any of these studies show that there are 3% positive or 5 or 10% I get the impression that you will find those tests flawed too.

I’m in the business of reading scientific studies and identifying where they fall short, or where their analyses are flawed. This is something that scientists do. So of course I’m going to look for flaws in the studies. I do this with my own work just as readily as with other work; my opinion of what the result should be has nothing to do with it. In this case, the antibody studies have a lot of drawbacks, in that antibodies tend to have cross reactivity and a certain amount of people have colds caused by coronaviruses every year, introducing a huge source of cross-reactivity into any serology studies. Is it too much to ask that anyone using a serology study does the proper controls for cross-reactivity? Or that they account for the error rates inherent in such studies? Or that, if they are using human subjects, they use methodology that does not result in a large number of self-selected subjects? And so on. If I were peer-reviewing these papers prior to recommending them for publishing, I would want these questions addressed.

I very specifically said that a true case fatality rate, as it is defined by epidemiologists, ONLY takes into account diagnosed cases. That means, BY DEFINITION, that the data is not incomplete, at least where cases are concerned. The only incomplete data is the case outcome; as long as there are active cases, that data set will remain incomplete.

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