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Old 27-03-2020, 12:27 AM   #1
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Covid19 - Dissenting views from around the world.

https://news.yahoo.com/oxford-study-...221100162.html

New Oxford study suggests millions of people may have already built up coronavirus immunity
The Week
Tim O'Donnell
,The Week•March 25, 2020

A model predicting the progression of the novel coronavirus pandemic produced by researchers at Imperial College London set off alarms across the world and was a major factor in several governments' decisions to lock things down. But a new model from Oxford University is challenging its accuracy, the Financial Times reports.

The Oxford research suggests the pandemic is in a later stage than previously thought and estimates the virus has already infected at least millions of people worldwide. In the United Kingdom, which the study focuses on, half the population would have already been infected. If accurate, that would mean transmission began around mid-January and the vast majority of cases presented mild or no symptoms.

The head of the study, professor Sunetra Gupta, an Oxford theoretical epidemiologist, said she still supports the U.K.'s decision to shut down the country to suppress the virus even if her research winds up being proven correct. But she also doesn't appear to be a big fan of the work done by the Imperial College team. "I am surprised that there has been such unqualified acceptance of the Imperial model," she said.

If her work is accurate, that would likely mean a large swath of the population has built up resistance to the virus. Theoretically, then, social restrictions could ease sooner than anticipated. What needs to be done now, Gupta said, is a whole lot of antibody testing to figure out who may have contracted the virus. Her research team is working with groups from the University of Cambridge and the University of Kent to start those tests for the general population as quickly as possible.
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Old 27-03-2020, 12:28 AM   #2
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Old 27-03-2020, 12:29 AM   #3
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Old 27-03-2020, 12:30 AM   #4
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webby to monitor if there is ANY INCREASE from baseline level in deaths in the EU.

https://www.euromomo.eu/outputs/zsco...try_total.html
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Old 27-03-2020, 12:31 AM   #5
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https://www.statnews.com/2020/03/17/...reliable-data/

A fiasco in the making? As the coronavirus pandemic takes hold, we are making decisions without reliable data
By JOHN P.A. IOANNIDISMARCH 17, 2020

The current coronavirus disease, Covid-19, has been called a once-in-a-century pandemic. But it may also be a once-in-a-century evidence fiasco.

At a time when everyone needs better information, from disease modelers and governments to people quarantined or just social distancing, we lack reliable evidence on how many people have been infected with SARS-CoV-2 or who continue to become infected. Better information is needed to guide decisions and actions of monumental significance and to monitor their impact.

Draconian countermeasures have been adopted in many countries. If the pandemic dissipates — either on its own or because of these measures — short-term extreme social distancing and lockdowns may be bearable. How long, though, should measures like these be continued if the pandemic churns across the globe unabated? How can policymakers tell if they are doing more good than harm?

Vaccines or affordable treatments take many months (or even years) to develop and test properly. Given such timelines, the consequences of long-term lockdowns are entirely unknown.

Related: We know enough now to act decisively against Covid-19. Social distancing is a good place to start
The data collected so far on how many people are infected and how the epidemic is evolving are utterly unreliable. Given the limited testing to date, some deaths and probably the vast majority of infections due to SARS-CoV-2 are being missed. We don’t know if we are failing to capture infections by a factor of three or 300. Three months after the outbreak emerged, most countries, including the U.S., lack the ability to test a large number of people and no countries have reliable data on the prevalence of the virus in a representative random sample of the general population.

This evidence fiasco creates tremendous uncertainty about the risk of dying from Covid-19. Reported case fatality rates, like the official 3.4% rate from the World Health Organization, cause horror — and are meaningless. Patients who have been tested for SARS-CoV-2 are disproportionately those with severe symptoms and bad outcomes. As most health systems have limited testing capacity, selection bias may even worsen in the near future.

The one situation where an entire, closed population was tested was the Diamond Princess cruise ship and its quarantine passengers. The case fatality rate there was 1.0%, but this was a largely elderly population, in which the death rate from Covid-19 is much higher.

Projecting the Diamond Princess mortality rate onto the age structure of the U.S. population, the death rate among people infected with Covid-19 would be 0.125%. But since this estimate is based on extremely thin data — there were just seven deaths among the 700 infected passengers and crew — the real death rate could stretch from five times lower (0.025%) to five times higher (0.625%). It is also possible that some of the passengers who were infected might die later, and that tourists may have different frequencies of chronic diseases — a risk factor for worse outcomes with SARS-CoV-2 infection — than the general population. Adding these extra sources of uncertainty, reasonable estimates for the case fatality ratio in the general U.S. population vary from 0.05% to 1%.

STAT Reports: STAT’s guide to interpreting clinical trial results
That huge range markedly affects how severe the pandemic is and what should be done. A population-wide case fatality rate of 0.05% is lower than seasonal influenza. If that is the true rate, 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.

Could the Covid-19 case fatality rate be that low? No, some say, pointing to the high rate in elderly people. However, even some so-called mild or common-cold-type coronaviruses that have been known for decades can have case fatality rates as high as 8% when they infect elderly people in nursing homes. In fact, such “mild” coronaviruses infect tens of millions of people every year, and account for 3% to 11% of those hospitalized in the U.S. with lower respiratory infections each winter.

These “mild” coronaviruses may be implicated in several thousands of deaths every year worldwide, though the vast majority of them are not documented with precise testing. Instead, they are lost as noise among 60 million deaths from various causes every year.

Although successful surveillance systems have long existed for influenza, the disease is confirmed by a laboratory in a tiny minority of cases. In the U.S., for example, so far this season 1,073,976 specimens have been tested and 222,552 (20.7%) have tested positive for influenza. In the same period, the estimated number of influenza-like illnesses is between 36,000,000 and 51,000,000, with an estimated 22,000 to 55,000 flu deaths.

Note the uncertainty about influenza-like illness deaths: a 2.5-fold range, corresponding to tens of thousands of deaths. Every year, some of these deaths are due to influenza and some to other viruses, like common-cold coronaviruses.

In an autopsy series that tested for respiratory viruses in specimens from 57 elderly persons who died during the 2016 to 2017 influenza season, influenza viruses were detected in 18% of the specimens, while any kind of respiratory virus was found in 47%. In some people who die from viral respiratory pathogens, more than one virus is found upon autopsy and bacteria are often superimposed. A positive test for coronavirus does not mean necessarily that this virus is always primarily responsible for a patient’s demise.

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If we assume that case fatality rate among individuals infected by SARS-CoV-2 is 0.3% in the general population — a mid-range guess from my Diamond Princess analysis — and that 1% of the U.S. population gets infected (about 3.3 million people), this would translate to about 10,000 deaths. This sounds like a huge number, but it is buried within the noise of the estimate of deaths from “influenza-like illness.” If we had not known about a new virus out there, and had not checked individuals with PCR tests, the number of total deaths due to “influenza-like illness” would not seem unusual this year. At most, we might have casually noted that flu this season seems to be a bit worse than average. The media coverage would have been less than for an NBA game between the two most indifferent teams.

Some worry that the 68 deaths from Covid-19 in the U.S. as of March 16 will increase exponentially to 680, 6,800, 68,000, 680,000 … along with similar catastrophic patterns around the globe. Is that a realistic scenario, or bad science fiction? How can we tell at what point such a curve might stop?

The most valuable piece of information for answering those questions would be to know the current prevalence of the infection in a random sample of a population and to repeat this exercise at regular time intervals to estimate the incidence of new infections. Sadly, that’s information we don’t have.

In the absence of data, prepare-for-the-worst reasoning leads to extreme measures of social distancing and lockdowns. Unfortunately, we do not know if these measures work. School closures, for example, may reduce transmission rates. But they may also backfire if children socialize anyhow, if school closure leads children to spend more time with susceptible elderly family members, if children at home disrupt their parents ability to work, and more. School closures may also diminish the chances of developing herd immunity in an age group that is spared serious disease.

This has been the perspective behind the different stance of the United Kingdom keeping schools open, at least until as I write this. In the absence of data on the real course of the epidemic, we don’t know whether this perspective was brilliant or catastrophic.

Flattening the curve to avoid overwhelming the health system is conceptually sound — in theory. A visual that has become viral in media and social media shows how flattening the curve reduces the volume of the epidemic that is above the threshold of what the health system can handle at any moment.

Related: The novel coronavirus is a serious threat. We need to prepare, not overreact
Yet if the health system does become overwhelmed, the majority of the extra deaths may not be due to coronavirus but to other common diseases and conditions such as heart attacks, strokes, trauma, bleeding, and the like that are not adequately treated. If the level of the epidemic does overwhelm the health system and extreme measures have only modest effectiveness, then flattening the curve may make things worse: Instead of being overwhelmed during a short, acute phase, the health system will remain overwhelmed for a more protracted period. That’s another reason we need data about the exact level of the epidemic activity.

One of the bottom lines is that we don’t know how long social distancing measures and lockdowns can be maintained without major consequences to the economy, society, and mental health. Unpredictable evolutions may ensue, including financial crisis, unrest, civil strife, war, and a meltdown of the social fabric. At a minimum, we need unbiased prevalence and incidence data for the evolving infectious load to guide decision-making.

In the most pessimistic scenario, which I do not espouse, if the new coronavirus infects 60% of the global population and 1% of the infected people die, that will translate into more than 40 million deaths globally, matching the 1918 influenza pandemic.

The vast majority of this hecatomb would be people with limited life expectancies. That’s in contrast to 1918, when many young people died.

One can only hope that, much like in 1918, life will continue. Conversely, with lockdowns of months, if not years, life largely stops, short-term and long-term consequences are entirely unknown, and billions, not just millions, of lives may be eventually at stake.

If we decide to jump off the cliff, we need some data to inform us about the rationale of such an action and the chances of landing somewhere safe.

John P.A. Ioannidis is professor of medicine and professor of epidemiology and population health, as well as professor by courtesy of biomedical data science at Stanford University School of Medicine, professor by courtesy of statistics at Stanford University School of Humanities and Sciences, and co-director of the Meta-Research Innovation Center at Stanford (METRICS) at Stanford University.
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Old 27-03-2020, 12:38 AM   #6
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remember how people panic before...

https://www.cdc.gov/flu/pandemic-res...-pandemic.html

On August 10, 2010, WHO declared an end to the global 2009 H1N1 influenza pandemic. However, (H1N1)pdm09 virus continues to circulate as a seasonal flu virus, and cause illness, hospitalization, and deaths worldwide every year.
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Old 27-03-2020, 12:40 AM   #7
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who is really at risk?

https://www.dailymail.co.uk/health/a...-COVID-19.html

Experts question whether vaping epidemic is behind younger adults being hospitalized with coronavirus, as it’s revealed that smokers were 14-times more at risk of their illness becoming severe
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Old 27-03-2020, 12:44 AM   #8
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We want solutions, not their nonsense thoughts. Monkeys behaviour are far more greater than man on our mother earth.
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Old 27-03-2020, 06:07 PM   #9
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https://www.gov.uk/government/collec...el-coronavirus

Status of COVID-19
As of 19 March 2020, COVID-19 is no longer considered to be a high consequence infectious diseases (HCID) in the UK.

The 4 nations public health HCID group made an interim recommendation in January 2020 to classify COVID-19 as an HCID. This was based on consideration of the UK HCID criteria about the virus and the disease with information available during the early stages of the outbreak. Now that more is known about COVID-19, the public health bodies in the UK have reviewed the most up to date information about COVID-19 against the UK HCID criteria. They have determined that several features have now changed; in particular, more information is available about mortality rates (low overall), and there is now greater clinical awareness and a specific and sensitive laboratory test, the availability of which continues to increase.
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Old 27-03-2020, 06:07 PM   #10
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We want solutions, not their nonsense thoughts. Monkeys behaviour are far more greater than man on our mother earth.
bugger off.
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Old 27-03-2020, 06:12 PM   #11
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oxford scientist challenges imperial college scientist and...

https://www.ft.com/content/5ff6469a-...f-41bea055720b

The new coronavirus may already have infected far more people in the UK than scientists had previously estimated — perhaps as much as half the population — according to modelling by researchers at the University of Oxford.

If the results are confirmed, they imply that fewer than one in a thousand of those infected with Covid-19 become ill enough to need hospital treatment, said Sunetra Gupta, professor of theoretical epidemiology, who led the study. The vast majority develop very mild symptoms or none at all.

“We need immediately to begin large-scale serological surveys — antibody testing — to assess what stage of the epidemic we are in now,” she said.

The modelling by Oxford’s Evolutionary Ecology of Infectious Disease group indicates that Covid-19 reached the UK by mid-January at the latest. Like many emerging infections, it spread invisibly for more than a month before the first transmissions within the UK were officially recorded at the end of February.

The research presents a very different view of the epidemic to the modelling at Imperial College London, which has strongly influenced government policy. “I am surprised that there has been such unqualified acceptance of the Imperial model,” said Prof Gupta.

However, she was reluctant to criticise the government for shutting down the country to suppress viral spread, because the accuracy of the Oxford model has not yet been confirmed and, even if it is correct, social distancing will reduce the number of people becoming seriously ill and relieve severe pressure on the NHS during the peak of the epidemic.

The Oxford study is based on a what is known as a “susceptibility-infected-recovered model” of Covid-19, built up from case and death reports from the UK and Italy. The researchers made what they regard as the most plausible assumptions about the behaviour of the virus.

The modelling brings back into focus “herd immunity”, the idea that the virus will stop spreading when enough people have become resistant to it because they have already been infected. The government abandoned its unofficial herd immunity strategy — allowing controlled spread of infection — after its scientific advisers said this would swamp the National Health Service with critically ill patients.

But the Oxford results would mean the country had already acquired substantial herd immunity through the unrecognised spread of Covid-19 over more than two months. If the findings are confirmed by testing, then the current restrictions could be removed much sooner than ministers have indicated.

Although some experts have shed doubt on the strength and length of the human immune response to the virus, Prof Gupta said the emerging evidence made her confident that humanity would build up herd immunity against Covid-19.

To provide the necessary evidence, the Oxford group is working with colleagues at the Universities of Cambridge and Kent to start antibody testing on the general population as soon as possible, using specialised “neutralisation assays which provide reliable readout of protective immunity,” Prof Gupta said. They hope to start testing later this week and obtain preliminary results within a few days.
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Old 27-03-2020, 06:13 PM   #12
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and imperial college scientist backpedals furiously...

https://www.washingtonexaminer.com/n...to-20k-or-less

Imperial College scientist who predicted 500K coronavirus deaths in UK adjusts to 20K or fewer
by Andrew Mark Miller
| March 26, 2020 11:59 AM

A scientist who warned that the coronavirus would kill 500,000 people in the United Kingdom has presented evidence that if current measures work as expected the death toll would drop to roughly 20,000 people or fewer.

Scientist and Imperial College author Neil Ferguson said Wednesday the coronavirus death toll is unlikely to exceed 20,000 and could be much lower if lockdown measures continue, according to New Scientist. He added that he is “reasonably confident” that Britain’s health system can handle the burden of treating coronavirus patients.
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Old 27-03-2020, 06:19 PM   #13
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a point made from videos except now with data.

***
Report shows up to 88% of Italy’s alleged Covid19 deaths could be misattributed

“The way in which we code deaths in our country is very generous in the sense that all the people who die in hospitals with the coronavirus are deemed to be dying of the coronavirus […] On re-evaluation by the National Institute of Health, only 12 per cent of death certificates have shown a direct causality from coronavirus, while 88 per cent of patients who have died have at least one pre-morbidity – many had two or three,”

– Professor Walter Ricciardi, scientific adviser to Italy’s minister of health

https://www.epicentro.iss.it/coronav..._marzo_eng.pdf
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Old 28-03-2020, 03:43 PM   #14
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https://coronadaten.wordpress.com/20...ahrscheinlich/

Corona epidemic? - Update 03/27/20 Death rate unchanged, infection rate around 15%, hospitalization in New York shows worrying trend - pandemic unlikely


Go google translate this.
Deals with 2 primary issues.
Conflating increasing testing and increased discovery of infection with virulency and lethality.
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Old 28-03-2020, 03:45 PM   #15
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https://www.rt.com/news/484098-coron...gerated-italy/

How lethal is Covid-19 REALLY? Why massive fatality rates from Italy are MISLEADING

...

But the key point to take away from this is that the 10 percent mortality rate being reported from Italy is grossly misleading. It is being waved around by the mainstream media as a bit of old-fashioned sensationalism at best, and a calculated tool of propaganda at worst. A figure like 0.3 percent - barely higher than the common flu - simply does not have the same power in getting people to swallow unprecedented legislation that gives the state tremendous new powers in a host of new areas... all in the name of public health of course.
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