See Also: COVID @ Phi Beta Iota
Everything we have been told about Coronavirus has been inaccurate and untrue. The projected millions dead, overwhelmed hospitals, the lack of hospital beds etc never happened. Those of us who reported on the actuals and questioned the panic and overreacion were designated fake news and tin foil hatters.
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The Bearer of Good Coronavirus News
Stanford scientist John Ioannidis finds himself under attack for questioning the prevailing wisdom about lockdowns.
The Wall Street, April 27, 2020:
Stanford scientist John Ioannidis finds himself under attack for questioning the prevailing wisdom about lockdowns.
Defenders of coronavirus lockdown mandates keep talking about science. “We are going to do the right thing, not judge by politics, not judge by protests, but by science,” California’s Gov. Gavin Newsom said this week. Michigan Gov. Gretchen Whitmer defended an order that, among other things, banned the sale of paint and vegetable seeds but not liquor or lottery tickets. “Each action has been informed by the best science and epidemiology counsel there is,” she wrote in an op-ed.
But scientists are almost never unanimous, and many appeals to “science” are transparently political or ideological. Consider the story of John Ioannidis, a professor at Stanford’s School of Medicine. His expertise is wide-ranging—he juggles appointments in statistics, biomedical data, prevention research and health research and policy. Google Scholar ranks him among the world’s 100 most-cited scientists. He has published more than 1,000 papers, many of them meta-analyses—reviews of other studies. Yet he’s now found himself pilloried because he dissents from the theories behind the lockdowns—because he’s looked at the data and found good news.
In a March article for Stat News, Dr. Ioannidis argued that Covid-19 is far less deadly than modelers were assuming. He considered the experience of the Diamond Princess cruise ship, which was quarantined Feb. 4 in Japan. Nine of 700 infected passengers and crew died. Based on the demographics of the ship’s population, Dr. Ioannidis estimated that the U.S. fatality rate could be as low as 0.025% to 0.625% and put the upper bound at 0.05% to 1%—comparable to that of seasonal flu.
“If that is the true rate,” he wrote, “locking down the world with potentially tremendous social and financial consequences may be totally irrational. It’s like an elephant being attacked by a house cat. Frustrated and trying to avoid the cat, the elephant accidentally jumps off a cliff and dies.”
Dr. Ioannidis, 54, likes metaphors. A New York native who grew up in Athens, he also teaches comparative literature and has published seven literary works—poetry and fiction, the latest being an epistolary novel—in Greek. In his spare time, he likes to fence, swim, hike and play basketball.
Early in his career, he realized that “the common denominator for everything that I was doing was that I was very interested in the methods—not necessarily the results but how exactly you do that, how exactly you try to avoid bias, how you avoid error.” When he began examining studies, he discovered that few headline-grabbing findings could be replicated, and many were later contradicted by new evidence.
Scientific studies are often infected by biases. “Several years ago, along with one of my colleagues, we had mapped 235 biases across science. And maybe the biggest cluster is biases that are trying to generate significant, spectacular, fascinating, extraordinary results,” he says. “Early results tend to be inflated. Claims for significance tend to be exaggerated.”
An example is a 2012 meta-analysis on nutritional research, in which he randomly selected 50 common cooking ingredients, such as sugar, flour and milk. Eighty percent of them had been studied for links to cancer, and 72% of the studies linked an ingredient to a higher or lower risk. Yet three-quarters of the findings were weak or statistically insignificant.
Dr. Ioannidis calls the coronavirus pandemic “the perfect storm of that quest for very urgent, spectacular, exciting, apocalyptic results. And as you see, apparently our early estimates seem to have been tremendously exaggerated in many fronts.”
Chief among them was a study by modelers at Imperial College London, which predicted more than 2.2 million coronavirus deaths in the U.S. absent “any control measures or spontaneous changes in individual behaviour.” The study was published March 16—the same day the Trump administration released its “15 Days to Slow the Spread” initiative, which included strict social-distancing guidelines.
Dr. Ioannidis says the Imperial projection now appears to be a gross overestimate. “They used inputs that were completely off in some of their calculation,” he says. “If data are limited or flawed, their errors are being propagated through the model. . . . So if you have a small error, and you exponentiate that error, the magnitude of the final error in the prediction or whatever can be astronomical.”
“I love models,” he adds. “I do a lot of mathematical modeling myself. But I think we need to recognize that they’re very, very low in terms of how much weight we can place on them and how much we can trust them. . . . They can give you a very first kind of mathematical justification to a gut feeling, but beyond that point, depending on models for evidence, I think it’s a very bad recipe.”
Modelers sometimes refuse to disclose their assumptions or data, so their errors go undetected. Los Angeles County predicted last week that 95.6% of its population would be infected by August if social distancing orders were relaxed. (Confirmed cases were 0.17% of the population as of Thursday.) But the basis for this projection is unclear. “At a minimum, we need openness and transparency in order to be able to say anything,” Dr. Ioannidis says.
Most important, “what we need is data. We need real data. We need data on how many people are infected so far, how many people are actively infected, what is really the death rate, how many beds do we have to spare, how has this changed.”
That will require more testing. Dr. Ioannidis and colleagues at Stanford last week published a study on the prevalence of coronavirus antibodies in Santa Clara County. Based on blood tests of 3,300 volunteers in the county—which includes San Jose, California’s third-largest city—during the first week of April, they estimated that between 2.49% and 4.16% of the county population had been infected. That’s 50 to 85 times the number of confirmed cases and implies a fatality rate between 0.12% and 0.2%, consistent with that of the Diamond Princess.
The study immediately came under attack. Some statisticians questioned its methods. Critics noted the study sample was not randomly selected, and white women under 64 were disproportionately represented. The Stanford team adjusted for the sampling bias by weighting the results by sex, race and ZIP Code, but the study acknowledges that “other biases, such as bias favoring individuals in good health capable of attending our testing sites, or bias favoring those with prior Covid-like illnesses seeking antibody confirmation are also possible. The overall effect of such biases is hard to ascertain.”
Dr. Ioannidis admits his study isn’t “bulletproof” and says he welcomes scrutiny. But he’s confident the findings will hold up, and he says antibody studies from around the world will yield more data. A study published this week by the University of Southern California and the Los Angeles County Department of Public Health estimated that the virus is 28 to 55 times as prevalent in that county as confirmed cases are. A New York study released Thursday estimated that 13.9% of the state and 21.2% of the city had been infected, more than 10 times the confirmed cases.
Yet most criticism of the Stanford study has been aimed at defending the lockdown mandates against the implication that they’re an overreaction. “There’s some sort of mob mentality here operating that they just insist that this has to be the end of the world, and it has to be that the sky is falling. It’s attacking studies with data based on speculation and science fiction,” he says. “But dismissing real data in favor of mathematical speculation is mind-boggling.”
In part he blames the media: “We have some evidence that bad news, negative news [stories], are more attractive than positive news—they lead to more clicks, they lead to people being more engaged. And of course we know that fake news travels faster than true news. So in the current environment, unfortunately, we have generated a very heavily panic-driven, horror-driven, death-reality-show type of situation.”
The news is filled with stories of healthy young people who die of coronavirus. But Dr. Ioannidis recently published a paper with his wife, Despina Contopoulos-Ioannidis, an infectious-disease specialist at Stanford, that showed this to be a classic man-bites-dog story. The couple found that people under 65 without underlying conditions accounted for only 0.7% of coronavirus deaths in Italy and 1.8% in New York City.
“Compared to almost any other cause of disease that I can think of, it’s really sparing young people. I’m not saying that the lives of 80-year-olds do not have value—they do,” he says. “But there’s far, far, far more . . . young people who commit suicide.” If the panic and attendant disruption continue, he says, “we will see many young people committing suicide . . . just because we are spreading horror stories with Covid-19. There’s far, far more young people who get cancer and will not be treated, because again, they will not go to the hospital to get treated because of Covid-19. There’s far, far more people whose mental health will collapse.”
He argues that public officials need to weigh these factors when making public-health decisions, and more hard data from antibody and other studies will help. “I think that we should just take everything that we know, put it on the table, and try to see, OK, what’s the next step, and see what happens when we take the next step. I think this sort of data-driven feedback will be the best. So you start opening, you start opening your schools. You can see what happens,” he says. “We need to be open minded, we need to just be calm, allow for some error, it’s unavoidable. We started knowing nothing. We know a lot now, but we still don’t know everything.”
He cautions against drawing broad conclusions about the efficacy of lockdowns based on national infection and fatality rates. “It’s not that we have randomized 10 countries to go into lockdown and another 10 countries to remain relatively open and see what happens, and do that randomly. Different prime ministers, different presidents, different task forces make decisions, they implement them in different sequences, at different times, in different phases of the epidemic. And then people start looking at this data and they say, ‘Oh look at that, this place did very well. Why? Oh, because of this measure.’ This is completely, completely opinion-based.”
People are making “big statements about ‘lockdowns save the world.’ I think that they’re immature. They’re tremendously immature. They may have worked in some cases, they may have had no effect in others, and they may have been damaging still in others.”
Most disagreements among scientists, he notes, reflect differences in perspective, not facts. Some find the Stanford study worrisome because it suggests the virus is more easily transmitted, while others are hopeful because it suggests the virus is far less lethal. “It’s basically an issue of whether you’re an optimist or a pessimist. Even scientists can be optimists and pessimists. Probably usually I’m a pessimist, but in this case, I’m probably an optimist.”
“CORONA, FALSE ALARM?
FACTS & FIGURES
Are We Being Told The Truth About COVID-19?
Professor Sucharit Bhakdi
December 7, 2020
· The Facts:
Below is an interview with renowned scientist Dr.Sucharit Bhakdi discussing the COVID-19 pandemic. He’s one of many scientists who believe measures being taken to combat the virus are completely unnecessary and very harmful in many ways.
· Reflect On:
Why are so many doctors and scientists who oppose the mainstream narrative being censored by social media platforms, ridiculed, and labelled “conspiracy theorists?” What’s going on here?
What Happened: Below is an interview with Dr.Sucharit Bhakdi, who received his MD in 1970. He was a post-doctoral researcher at the Max Planck Institute of Immunobiology and Epigenetics in Freiburg from 1972 to 1976, and at The Protein Laboratory in Copenhagen from 1976 to 1977. He joined the Institute of Medical Microbiology at Giessen University in 1977 and was appointed associate professor in 1982. He was named chair of Medical Microbiology at the University of Mainz in 1990, where he remained until his retirement in 2012. Dr. Bhakdi has published over three hundred articles in the fields of immunology, bacteriology, virology, and parasitology, for which he has received numerous awards and the Order of Merit of Rhineland-Palatinate. He’s one of the most cited scientists in German history.
Himself and Karina Reiss Ph.D have published a book titled “Corona, False Alarm? Facts & Figures.“
Many people, including world renowned scientists from around the globe, are asking and have been asking since the beginning of the pandemic if we are being told the truth about COVID-19 from the mainstream media and government affiliated scientists and doctors. Many people are confused right now and don’t know what to believe, some have an open mind and are able to entertain different perspectives, and others are completely polarized in their belief of what’s happening and completely refuse to even consider another perspective.
When it comes to the scientific community, we’ve seen doctors and scientists gather in the tens of thousands opposing lockdown measures that’ve been put in place by multiple governments throughout this pandemic. For example, approximately 50,000 doctors and scientists have now signed The Great Barrington Declaration, strongly opposing lockdown measures. One of the initiators of that declaration, Dr. Jay Bhattacharya, MD, PhD, from the Stanford University School of Medicine, recently explained that COVID-19 has a 99.95 survival rate for people under the age of 70, and that the flu is more dangerous than COVID-19 for children. Other gatherings of doctors and scientists, among others, include the World Doctors Alliance, and the Corona Extra-Parliamentary Inquiry Committee.
The information above comes despite Facebook fact-checkers constantly emphasizing that the virus is as dangerous as it’s being made out to be.
Why This Is Important: There are concerns that in some parts of the world mental health issues are taking more lives than COVID-19. Peer-reviewed papers have been published hypothesizing that lockdown measures have, in some parts of the world, killed more people than COVID-19. Here’s one of multiple examples published in the British Medical Journal.
Concerns when it comes to the truth are many, for example, Kamran Abbas, executive editor of the British Medical Journal, and the editor of the Bulletin of the World Health Organization recently published an article about COVID-19, the suppression of science and the politicization of medicine.
Numerous scientists and doctors have raised concerns about PCR tests and the high potential for false positives being upwards of 50 to 90 percent. This idea gained even more traction when 22 researchers recently put out a paper explaining why, according to them, it’s quite clear that the PCR test is not effective in identifying COVID-19 cases.
Deaths being counted as COVID deaths when they are really not a result of COVID has also been a common theme throughout this pandemic.
And again, of course, the true severity of this virus seems to be the biggest issue that is being called into question.
How can tens of thousands of doctors, scientists, and some of the leading experts in infectious diseases, along with what appears to be millions upon millions of people who disagree with lockdown measures, mask mandates and potential vaccine mandates be crazy “conspiracy theorists?” Why are those who go against the mainstream narrative always ridiculed and labelled as such? Why are they constantly censored by social media platforms and why are experts in the field who oppose government measures never really given any air-time on mainstream media? Why aren’t we exploring everything, all evidence, and a wide range of opinions with regards to this pandemic and having a discussion? What’s going on here? Why have alternative therapies that have shown success been completely ignored and products that benefit big corporations, like vaccines, being made out to be our only option?
If you believe those who oppose lockdowns, mask mandates and vaccine mandates are are crazy conspiracy theorists, you’re a big part of the problem. If you believe those who support these measures are stupid people who don’t know how read, research and look into things, you’re also part of the problem. Can we, even for a minute, take on a perspective and examine evidence that completely contradicts and challenges our belief systems surrounding this pandemic? The more people that do this, the clearer the picture becomes as to what’s really going on.
Can we continue to rely on mainstream media to provide us with accurate and balanced information? How much of our perspective has been influenced by watching television? How much of our perspective has been influenced by actually doing our own research?
Do we really want to live in a world and create a human experience where we are constantly listening and taking orders from governments that clearly don’t represent the will of all people? Why have we given them so much power to enforce whatever measures they please on the population? Why do we live this way and simply accept this? Why is there so much resistance against those who oppose these measures? Is this really the kind of world we want to live in and create for ourselves, or do we have the potential do create something better?
These days, it’s not just knowing information and facts that will create change, it’s changing ourselves, how we go about communicating, and re-assessing the underlying stories, ideas and beliefs that form our world. We have to practice these things if we truly want to change. At Collective Evolution and CETV, this is a big part of our mission.
Amongst 100’s of hours of exclusive content, we have recently completed two short courses to help you become an effective changemaker, one called Profound Realization and the other called How To Do An Effective Media Detox.
OPEN LETTER TO CHANCELLOR MERKEL
Mar 31, 2020
Open Letter from Prof Sucharit Bhakdi to Chancellor Merkel
An Open Letter from Dr. Sucharit Bhakdi, Professor Emeritus of Medical Microbiology at the Johannes Gutenberg University Mainz, to the German Chancellor Dr. Angela Merkel. Professor Bhakdi calls for an urgent reassessment of the response to Covid-19 and asks the Chancellor five crucial questions. The letter is dated March 26. This is an unofficial translation.
As Emeritus of the Johannes-Gutenberg-University in Mainz and longtime director of the Institute for Medical Microbiology, I feel obliged to critically question the far-reaching restrictions on public life that we are currently taking on ourselves in order to reduce the spread of the COVID-19 virus.
It is expressly not my intention to play down the dangers of the virus or to spread a political message. However, I feel it is my duty to make a scientific contribution to putting the current data and facts into perspective – and, in addition, to ask questions that are in danger of being lost in the heated debate.
The reason for my concern lies above all in the truly unforeseeable socio-economic consequences of the drastic containment measures which are currently being applied in large parts of Europe and which are also already being practiced on a large scale in Germany.
My wish is to discuss critically – and with the necessary foresight – the advantages and disadvantages of restricting public life and the resulting long-term effects.
To this end, I am confronted with five questions which have not been answered sufficiently so far, but which are indispensable for a balanced analysis.
I would like to ask you to comment quickly and, at the same time, appeal to the Federal Government to develop strategies that effectively protect risk groups without restricting public life across the board and sow the seeds for an even more intensive polarization of society than is already taking place.
With the utmost respect,
Prof. em. Dr. med. Sucharit Bhakdi
In infectiology – founded by Robert Koch himself – a traditional distinction is made between infection and disease. An illness requires a clinical manifestation.  Therefore, only patients with symptoms such as fever or cough should be included in the statistics as new cases.
In other words, a new infection – as measured by the COVID-19 test – does not necessarily mean that we are dealing with a newly ill patient who needs a hospital bed. However, it is currently assumed that five percent of all infected people become seriously ill and require ventilation. Projections based on this estimate suggest that the healthcare system could be overburdened.
My question: Did the projections make a distinction between symptom-free infected people and actual, sick patients – i.e. people who develop symptoms?
A number of coronaviruses have been circulating for a long time – largely unnoticed by the media.  If it should turn out that the COVID-19 virus should not be ascribed a significantly higher risk potential than the already circulating corona viruses, all countermeasures would obviously become unnecessary.
The internationally recognized International Journal of Antimicrobial Agents will soon publish a paper that addresses exactly this question. Preliminary results of the study can already be seen today and lead to the conclusion that the new virus is NOT different from traditional corona viruses in terms of dangerousness. The authors express this in the title of their paper “SARS-CoV-2: Fear versus Data.” 
My question: How does the current workload of intensive care units with patients with diagnosed COVID-19 compare to other coronavirus infections, and to what extent will this data be taken into account in further decision-making by the federal government? In addition: Has the above study been taken into account in the planning so far? Here too, of course, „diagnosed“ means that the virus plays a decisive role in the patient’s state of illness, and not that previous illnesses play a greater role.
According to a report in the Süddeutsche Zeitung, not even the much-cited Robert Koch Institute knows exactly how much is tested for COVID-19. It is a fact, however, that a rapid increase in the number of cases has recently been observed in Germany as the volume of tests increases. 
It is therefore reasonable to suspect that the virus has already spread unnoticed in the healthy population. This would have two consequences: firstly, it would mean that the official death rate – on 26 March 2020, for example, there were 206 deaths from around 37,300 infections, or 0.55 percent  – is too high; and secondly, it would mean that it would hardly be possible to prevent the virus from spreading in the healthy population.
My question: Has there already been a random sample of the healthy general population to validate the real spread of the virus, or is this planned in the near future?
The fear of a rise in the death rate in Germany (currently 0.55 percent) is currently the subject of particularly intense media attention. Many people are worried that it could shoot up like in Italy (10 percent) and Spain (7 percent) if action is not taken in time.
At the same time, the mistake is being made worldwide to report virus-related deaths as soon as it is established that the virus was present at the time of death – regardless of other factors. This violates a basic principle of infectiology: only when it is certain that an agent has played a significant role in the disease or death may a diagnosis be made. The Association of the Scientific Medical Societies of Germany expressly writes in its guidelines: „In addition to the cause of death, a causal chain must be stated, with the corresponding underlying disease in third place on the death certificate. Occasionally, four-linked causal chains must also be stated.“ 
At present there is no official information on whether, at least in retrospect, more critical analyses of medical records have been undertaken to determine how many deaths were actually caused by the virus.
My question: Has Germany simply followed this trend of a COVID-19 general suspicion? And: is it intended to continue this categorisation uncritically as in other countries? How, then, is a distinction to be made between genuine corona-related deaths and accidental virus presence at the time of death?
The appalling situation in Italy is repeatedly used as a reference scenario. However, the true role of the virus in that country is completely unclear for many reasons – not only because points 3 and 4 above also apply here, but also because exceptional external factors exist which make these regions particularly vulnerable.
One of these factors is the increased air pollution in the north of Italy. According to WHO estimates, this situation, even without the virus, led to over 8,000 additional deaths per year in 2006 in the 13 largest cities in Italy alone.  The situation has not changed significantly since then.  Finally, it has also been shown that air pollution greatly increases the risk of viral lung diseases in very young and elderly people. 
Moreover, 27.4 percent of the particularly vulnerable population in this country live with young people, and in Spain as many as 33.5 percent. In Germany, the figure is only seven percent . In addition, according to Prof. Dr. Reinhard Busse, head of the Department of Management in Health Care at the TU Berlin, Germany is significantly better equipped than Italy in terms of intensive care units – by a factor of about 2.5 .
My question: What efforts are being made to make the population aware of these elementary differences and to make people understand that scenarios like those in Italy or Spain are not realistic here?
 Fachwörterbuch Infektionsschutz und Infektionsepidemiologie. Fachwörter – Definitionen – Interpretationen. Robert Koch-Institut, Berlin 2015. (abgerufen am 26.3.2020)
 Killerby et al., Human Coronavirus Circulation in the United States 2014–2017. J Clin Virol. 2018, 101, 52-56
 Roussel et al. SARS-CoV-2: Fear Versus Data. Int. J. Antimicrob. Agents 2020, 105947
 Charisius, H. Covid-19: Wie gut testet Deutschland? Süddeutsche Zeitung. (abgerufen am 27.3.2020)
 Johns Hopkins University, Coronavirus Resource Center. 2020. (abgerufen am 26.3.2020)
 S1-Leitlinie 054-001, Regeln zur Durchführung der ärztlichen Leichenschau. AWMF Online (abgerufen am 26.3.2020)
 Martuzzi et al. Health Impact of PM10 and Ozone in 13 Italian Cities. World Health Organization Regional Office for Europe. WHOLIS number E88700 2006
 European Environment Agency, Air Pollution Country Fact Sheets 2019, (abgerufen am 26.3.2020)
 Croft et al. The Association between Respiratory Infection and Air Pollution in the Setting of Air Quality Policy and Economic Change. Ann. Am. Thorac. Soc. 2019, 16, 321–330.
 United Nations, Department of Economic and Social Affairs, Population Division. Living Arrangements of Older Persons: A Report on an Expanded International Dataset (ST/ESA/SER.A/407). 2017
 Deutsches Ärzteblatt, Überlastung deutscher Krankenhäuser durch COVID-19 laut Experten unwahrscheinlich, (abgerufen am 26.3.2020)