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Bill gates on corona

I don't believe that Bill Gates has any medical credentials. The guy is fear mongering. Here's a counter point.....



Is the Coronavirus as Deadly as They Say?
Current estimates about the Covid-19 fatality rate may be too high by orders of magnitude.



By
Eran Bendavid and
Jay Bhattacharya
March 24, 2020 6:21 pm ET (Wall Street Journal)

If it’s true that the novel coronavirus would kill millions without shelter-in-place orders and quarantines, then the extraordinary measures being carried out in cities and states around the country are surely justified. But there’s little evidence to confirm that premise—and projections of the death toll could plausibly be orders of magnitude too high.

Fear of Covid-19 is based on its high estimated case fatality rate—2% to 4% of people with confirmed Covid-19 have died, according to the World Health Organization and others. So if 100 million Americans ultimately get the disease, two million to four million could die. We believe that estimate is deeply flawed. The true fatality rate is the portion of those infected who die, not the deaths from identified positive cases.

The latter rate is misleading because of selection bias in testing. The degree of bias is uncertain because available data are limited. But it could make the difference between an epidemic that kills 20,000 and one that kills two million. If the number of actual infections is much larger than the number of cases—orders of magnitude larger—then the true fatality rate is much lower as well. That’s not only plausible but likely based on what we know so far.

Population samples from China, Italy, Iceland and the U.S. provide relevant evidence. On or around Jan. 31, countries sent planes to evacuate citizens from Wuhan, China. When those planes landed, the passengers were tested for Covid-19 and quarantined. After 14 days, the percentage who tested positive was 0.9%. If this was the prevalence in the greater Wuhan area on Jan. 31, then, with a population of about 20 million, greater Wuhan had 178,000 infections, about 30-fold more than the number of reported cases. The fatality rate, then, would be at least 10-fold lower than estimates based on reported cases.

Next, the northeastern Italian town of Vò, near the provincial capital of Padua. On March 6, all 3,300 people of Vò were tested, and 90 were positive, a prevalence of 2.7%. Applying that prevalence to the whole province (population 955,000), which had 198 reported cases, suggests there were actually 26,000 infections at that time. That’s more than 130-fold the number of actual reported cases. Since Italy’s case fatality rate of 8% is estimated using the confirmed cases, the real fatality rate could in fact be closer to 0.06%.

In Iceland, deCode Genetics is working with the government to perform widespread testing. In a sample of nearly 2,000 entirely asymptomatic people, researchers estimated disease prevalence of just over 1%. Iceland’s first case was reported on Feb. 28, weeks behind the U.S. It’s plausible that the proportion of the U.S. population that has been infected is double, triple or even 10 times as high as the estimates from Iceland. That also implies a dramatically lower fatality rate.

The best (albeit very weak) evidence in the U.S. comes from the National Basketball Association. Between March 11 and 19, a substantial number of NBA players and teams received testing. By March 19, 10 out of 450 rostered players were positive. Since not everyone was tested, that represents a lower bound on the prevalence of 2.2%. The NBA isn’t a representative population, and contact among players might have facilitated transmission. But if we extend that lower-bound assumption to cities with NBA teams (population 45 million), we get at least 990,000 infections in the U.S. The number of cases reported on March 19 in the U.S. was 13,677, more than 72-fold lower. These numbers imply a fatality rate from Covid-19 orders of magnitude smaller than it appears.

How can we reconcile these estimates with the epidemiological models? First, the test used to identify cases doesn’t catch people who were infected and recovered. Second, testing rates were woefully low for a long time and typically reserved for the severely ill. Together, these facts imply that the confirmed cases are likely orders of magnitude less than the true number of infections. Epidemiological modelers haven’t adequately adapted their estimates to account for these factors.

The epidemic started in China sometime in November or December. The first confirmed U.S. cases included a person who traveled from Wuhan on Jan. 15, and it is likely that the virus entered before that: Tens of thousands of people traveled from Wuhan to the U.S. in December. Existing evidence suggests that the virus is highly transmissible and that the number of infections doubles roughly every three days. An epidemic seed on Jan. 1 implies that by March 9 about six million people in the U.S. would have been infected. As of March 23, according to the Centers for Disease Control and Prevention, there were 499 Covid-19 deaths in the U.S. If our surmise of six million cases is accurate, that’s a mortality rate of 0.01%, assuming a two week lag between infection and death. This is one-tenth of the flu mortality rate of 0.1%. Such a low death rate would be cause for optimism.

This does not make Covid-19 a nonissue. The daily reports from Italy and across the U.S. show real struggles and overwhelmed health systems. But a 20,000- or 40,000-death epidemic is a far less severe problem than one that kills two million. Given the enormous consequences of decisions around Covid-19 response, getting clear data to guide decisions now is critical. We don’t know the true infection rate in the U.S. Antibody testing of representative samples to measure disease prevalence (including the recovered) is crucial. Nearly every day a new lab gets approval for antibody testing, so population testing using this technology is now feasible.

If we’re right about the limited scale of the epidemic, then measures focused on older populations and hospitals are sensible. Elective procedures will need to be rescheduled. Hospital resources will need to be reallocated to care for critically ill patients. Triage will need to improve. And policy makers will need to focus on reducing risks for older adults and people with underlying medical conditions.

A universal quarantine may not be worth the costs it imposes on the economy, community and individual mental and physical health. We should undertake immediate steps to evaluate the empirical basis of the current lockdowns.

Dr. Bendavid and Dr. Bhattacharya are professors of medicine at Stanford. Neeraj Sood contributed to this article.
 
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Bill Gates has lotsa money, and with that he can have any other credentials he wants.
 
I don't believe that Bill Gates has any medical credentials. The guy is fear mongering. Here's a counter point.....



Is the Coronavirus as Deadly as They Say?
Current estimates about the Covid-19 fatality rate may be too high by orders of magnitude.



By
Eran Bendavid and
Jay Bhattacharya
March 24, 2020 6:21 pm ET (Wall Street Journal)

If it’s true that the novel coronavirus would kill millions without shelter-in-place orders and quarantines, then the extraordinary measures being carried out in cities and states around the country are surely justified. But there’s little evidence to confirm that premise—and projections of the death toll could plausibly be orders of magnitude too high.

Fear of Covid-19 is based on its high estimated case fatality rate—2% to 4% of people with confirmed Covid-19 have died, according to the World Health Organization and others. So if 100 million Americans ultimately get the disease, two million to four million could die. We believe that estimate is deeply flawed. The true fatality rate is the portion of those infected who die, not the deaths from identified positive cases.

The latter rate is misleading because of selection bias in testing. The degree of bias is uncertain because available data are limited. But it could make the difference between an epidemic that kills 20,000 and one that kills two million. If the number of actual infections is much larger than the number of cases—orders of magnitude larger—then the true fatality rate is much lower as well. That’s not only plausible but likely based on what we know so far.

Population samples from China, Italy, Iceland and the U.S. provide relevant evidence. On or around Jan. 31, countries sent planes to evacuate citizens from Wuhan, China. When those planes landed, the passengers were tested for Covid-19 and quarantined. After 14 days, the percentage who tested positive was 0.9%. If this was the prevalence in the greater Wuhan area on Jan. 31, then, with a population of about 20 million, greater Wuhan had 178,000 infections, about 30-fold more than the number of reported cases. The fatality rate, then, would be at least 10-fold lower than estimates based on reported cases.

Next, the northeastern Italian town of Vò, near the provincial capital of Padua. On March 6, all 3,300 people of Vò were tested, and 90 were positive, a prevalence of 2.7%. Applying that prevalence to the whole province (population 955,000), which had 198 reported cases, suggests there were actually 26,000 infections at that time. That’s more than 130-fold the number of actual reported cases. Since Italy’s case fatality rate of 8% is estimated using the confirmed cases, the real fatality rate could in fact be closer to 0.06%.

In Iceland, deCode Genetics is working with the government to perform widespread testing. In a sample of nearly 2,000 entirely asymptomatic people, researchers estimated disease prevalence of just over 1%. Iceland’s first case was reported on Feb. 28, weeks behind the U.S. It’s plausible that the proportion of the U.S. population that has been infected is double, triple or even 10 times as high as the estimates from Iceland. That also implies a dramatically lower fatality rate.

The best (albeit very weak) evidence in the U.S. comes from the National Basketball Association. Between March 11 and 19, a substantial number of NBA players and teams received testing. By March 19, 10 out of 450 rostered players were positive. Since not everyone was tested, that represents a lower bound on the prevalence of 2.2%. The NBA isn’t a representative population, and contact among players might have facilitated transmission. But if we extend that lower-bound assumption to cities with NBA teams (population 45 million), we get at least 990,000 infections in the U.S. The number of cases reported on March 19 in the U.S. was 13,677, more than 72-fold lower. These numbers imply a fatality rate from Covid-19 orders of magnitude smaller than it appears.

How can we reconcile these estimates with the epidemiological models? First, the test used to identify cases doesn’t catch people who were infected and recovered. Second, testing rates were woefully low for a long time and typically reserved for the severely ill. Together, these facts imply that the confirmed cases are likely orders of magnitude less than the true number of infections. Epidemiological modelers haven’t adequately adapted their estimates to account for these factors.

The epidemic started in China sometime in November or December. The first confirmed U.S. cases included a person who traveled from Wuhan on Jan. 15, and it is likely that the virus entered before that: Tens of thousands of people traveled from Wuhan to the U.S. in December. Existing evidence suggests that the virus is highly transmissible and that the number of infections doubles roughly every three days. An epidemic seed on Jan. 1 implies that by March 9 about six million people in the U.S. would have been infected. As of March 23, according to the Centers for Disease Control and Prevention, there were 499 Covid-19 deaths in the U.S. If our surmise of six million cases is accurate, that’s a mortality rate of 0.01%, assuming a two week lag between infection and death. This is one-tenth of the flu mortality rate of 0.1%. Such a low death rate would be cause for optimism.

This does not make Covid-19 a nonissue. The daily reports from Italy and across the U.S. show real struggles and overwhelmed health systems. But a 20,000- or 40,000-death epidemic is a far less severe problem than one that kills two million. Given the enormous consequences of decisions around Covid-19 response, getting clear data to guide decisions now is critical. We don’t know the true infection rate in the U.S. Antibody testing of representative samples to measure disease prevalence (including the recovered) is crucial. Nearly every day a new lab gets approval for antibody testing, so population testing using this technology is now feasible.

If we’re right about the limited scale of the epidemic, then measures focused on older populations and hospitals are sensible. Elective procedures will need to be rescheduled. Hospital resources will need to be reallocated to care for critically ill patients. Triage will need to improve. And policy makers will need to focus on reducing risks for older adults and people with underlying medical conditions.

A universal quarantine may not be worth the costs it imposes on the economy, community and individual mental and physical health. We should undertake immediate steps to evaluate the empirical basis of the current lockdowns.

Dr. Bendavid and Dr. Bhattacharya are professors of medicine at Stanford. Neeraj Sood contributed to this article.
Thanks RC. i really enjoyed you post on, evidence over hysteria, but can't find it now. Was it moved/ removed ?
 
Thanks RC. i really enjoyed you post on, evidence over hysteria, but can't find it now. Was it moved/ removed ?

Thanks. Apparently, those in charge of the interwebs pulled it because they don't want any dissenting opinion.


From the WSJ......

Controlling the Virus Narrative
Medium takes down an essay arguing against ‘hysteria.’
By The Editorial Board
March 22, 2020 1:55 pm ET

The coronavirus threat creates new challenges for social-media companies already grappling with the limits of free speech online. China is waging an information war to whitewash its handling of the virus and impugn the U.S. Meanwhile, charlatans hawking bogus science or false cures could endanger the public.

The Coronavirus and Shutdown Send the Economy into Recession

Yet some of the web’s gatekeepers are tempted to go further and stamp out the free debate that helped alert Americans to the threat of the virus in the first place. They want to require conformity with the judgment of expert institutions, even as many of those institutions themselves woefully misjudged the situation months or weeks ago.

Over the weekend Medium, a web-publishing platform, took down a long article entitled “Evidence over hysteria—COVID-19” that had been viewed millions of times. The piece, by Silicon Valley technologist Aaron Ginn, was an exhaustive case for optimism about the coronavirus. It highlighted some of the most hopeful available estimates, mostly from good authorities, of the virus’s growth rate, severity, transmissibility, and responsiveness to warmer weather.

Those estimates may be wrong, and the piece doesn’t address more troubling evidence. Yet Mr. Ginn did not deny the virus is a public-health threat or urge people in hot zones to go to nightclubs. The page now says “this post is under investigation or was found in violation of the Medium Rules.”

Meanwhile, Twitter has unveiled sweeping restrictions on posts about the coronavirus. The company says it will restrict “content that goes directly against guidance from authoritative sources of global and local public health information.” If you click on the link to the Medium post from Twitter, you get a page warning it is “potentially harmful.”

The problem is that the situation is changing with blinding speed and so has “guidance from authoritative sources.” The World Health Organization—widely seen as subject to pressure from Beijing—tweeted in January that “Chinese authorities have found no clear evidence of human-to-human transmission of the novel #coronavirus.” And while the U.S. public-health response has finally kicked into gear, organizations like the Centers for Disease Control and Prevention have hardly been perfect oracles.

Twitter users and bloggers were sounding the alarm about the potential damage from coronavirus and inadequate testing before the authorities and major media. The idea that “democratizing information” leads to better outcomes is often exaggerated, but the freewheeling marketplace of ideas has sometimes performed better than the central authorities. The churn of arguments and data will improve the response to coronavirus as new information becomes available, and shutting it down may undermine public faith in the official response.
 
Here is another eye brow raiser i found. Though the guys voice is somewhat hard to understand.
 
Look up a documentary film called "Pandemic", and guess who is featured in that ? None other than BG & #44...
 
I could care less about Bill Gates just as he could care less about me.......he's just another mouth piece because he can be with his money....
 
Y'all realize 5G is using the old analog tv frequencies, right? I've heard some tin foil hat ideas but this is so silly I can only laugh. The corna in Corona virus describes a family of viruses, the one now is Covid 19.
 
He is ugly and he dresses like a dork.
 
Here's a couple of interesting articles that the major news networks don't want you to know about. They've got to keep the panic going because panic = ratings......


Coronavirus misperceptions widespread in early weeks, according to Stanford study

https://scopeblog.stanford.edu/2020...d-in-early-weeks-according-to-stanford-study/


Nobel laureate predicts US will have much faster coronavirus recovery than expected

https://thehill.com/changing-americ...15-nobel-laureate-predicts-us-will-experience
 
Here's a couple of interesting articles that the major news networks don't want you to know about. They've got to keep the panic going because panic = ratings......


Coronavirus misperceptions widespread in early weeks, according to Stanford study

https://scopeblog.stanford.edu/2020...d-in-early-weeks-according-to-stanford-study/


Nobel laureate predicts US will have much faster coronavirus recovery than expected

https://thehill.com/changing-americ...15-nobel-laureate-predicts-us-will-experience
Correct......A certain RAG news paper in this area has the same identical headline this morning as it did yesterday morning regarding the number of deaths in the state. Yesterday it said 19 more deaths. This morning same headline, 19 more deaths......so your saying that 38 people have died in these 24 hours.....the other same story line was about the Ford Motor Company stock going very low, 3 days in a row on this exact story. Enough already! The media loves to scream 'The Sky Is Falling!'
 
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