After The CDC Made These Two Radical Changes, 30,000 Polio Cases Instantly Vanished

The eradication of polio, the oft-used debate tactic of pro-vaccine advocates, is perhaps one of the most misunderstood public health stories of the 20th century.

Through clever data manipulation, diagnostic changes, and a slew of media-generated hysteria, polio would eventually become a modern-vaccine ‘miracle’ that could quickly end any argument against vaccine efficacy.

The graph below, published by VacTruth, is from the Ratner report, a transcript of a 1960 panel sponsored by the Illinois Medical Society, on which sat three PhD statisticians and an MD, who met to discuss the problems with the ongoing polio vaccination campaign.

The polio vaccine was licensed in the U.S. in 1954. From ‘50 thru ‘55, the striped and clear portions of the bars represent about 85% of the reported cases, or 30,000 per year, on average, VacTruth reports.

Those cases were automatically eliminated by two radical changes the CDC made to the diagnostic parameters and labeling protocol of the disease as soon as the vaccine was licensed – 30,000 cases a year we were subsequently told were eliminated by the vaccine.

The ‘success’ of the polio vaccine was no more than a mere illusion. The CDC, always clever in their misrepresentation of data, fooled an entire global population so that they could hold ‘facts’ above the heads of anyone questioning vaccine efficacy.

When The CDC Changed The Definition of A Polio Epidemic

As addressed in the Ratner report, the CDC also changed the definition of a polio epidemic, greatly reducing the likelihood that any subsequent outbreaks would be so labeled – as though the severity, or noteworthiness, of paralytic polio had halved, overnight. It’s summed up thusly in the report:

Presently [1960], a community is considered to have an epidemic when it has 35 cases of polio per year per 100,000 population. Prior to the introduction of the Salk vaccine the National Foundation defined an epidemic as 20 or more cases of polio per year per 100,000 population. On this basis there were many epidemics throughout the United States yearly. The present higher rate has resulted in not a real, but a semantic elimination of epidemics.

In short, polio wasn’t really eliminated, but rather it was semantically eliminated through diagnostic changes.

Furthermore, in the decades following the release of the vaccine, additional changes were made to the diagnostic parameters of the disease, changes involving analysis of cerebrospinal fluid and stool and additional testing, each succeeding change making it less and less likely that a diagnosis of paralytic polio would result.

Before the polio vaccine was licensed, polio diagnoses were made objectively without any lab analysis required. Since the vaccine was licensed, only the CDC has been allowed to issue confirmations of paralytic polio – all suspected cases have to be sent to them for analysis and testing, which has clearly affected the number of actual instances reported.

How The Media Amplified The Public Perception Of Polio

Before the polio vaccine, video news coverage of polio symptoms spread like wild-fire, showcasing victims in leg braces, or immobilized, strapped to huge, inclined boards, or housed in foreboding iron lungs.

Because polio parameters had not yet been refined, the public perception was that tens of thousands of children were suffering greatly from the paralytic polio, when in fact the pictures and videos involved only a fraction of a percent of the diagnosed cases.

Something that also should be said is that while for many the perception was that the iron lung was a permanent fixture, in the majority of cases the machine was needed only temporarily – generally about one to two weeks.

The change in diagnostic parameters of polio from two months to three months is perhaps the biggest kicker (see the graph above, represented by the striped portions of the bars in the graph).  This resulted in the subsequent elimination of thousands of cases of polio, feeding into the illusion that polio had been eradicated by the vaccine.

All of the non-paralytic cases of polio (represented by the clear portion of the bar in the graph above), which were the majority of cases reported simply as polio each year, were all discarded.

Here is what a search through public health and disease statistics found:

It may be noted that the Dominion Council of Health at its 74th meeting in October 1958 recommended that for the purposes of national reporting and statistics the term non-paralytic poliomyelitis be replaced by “meningitis, viral or aseptic” with the specific viruses shown where known.

VacTruth sums it up nicely:

Of the “35,000 cases of polio reported on average in the late 1940s and early 1950s,” only 15,000 were paralytic – the reduction to 2,500 cases of paralytic polio in 1957, and the complete disappearance of all the non-paralytic cases, was a direct result of the diagnostic changes. It’s smoke ‘n mirrors.

Polio Eradication Initiatives In India & Africa

In the 90s, “polio eradication initiatives” were also implemented in India and Africa.

The WHO quickly established the same diagnostic changes in those nations as were made in the U.S. in 1955. The result, as expected, was the announcement two years ago that India is now polio free.

What the WHO so conveniently omitted was any mention of the skyrocketing incidence, in both nations, of acute flaccid paralysis, clinically identical to polio, and following in the wake of the use of the oral polio vaccine, abandoned fifteen years ago in the U.S. because it triggers Vaccine Associated Paralytic Polio.

As you can see in the graph, incidences of acute flaccid paralysis soared while polio cases coincidentally plummeted.

The Take-Away From This

The polio lie has been the go-to ammunition for vaccine proponents for many years, but just as data continues to become more accessible to the public, so too do secrets and deceit become more transparent.

This stands as just another example of how medical institutions stretch data to suit their financial initiatives. Lest we not forget about the multi-billion dollar industry ($50+billion to be exact) that vaccines comprise.

Truthfully, anyone should know that information built on a foundation of lies is only waiting to eventually implode.

For the truth seekers, the parents, the medical professionals, the pro-choice advocates, and the families who have witnessed the pain of vaccine injuries, no secret, no matter how well hidden it may be, will be left unburied until the truth is at last disclosed to the people.

What are your thoughts on the manipulated polio data? Share your thoughts in the comment section below!

Source: VacTruth

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Western official confirms Turkey-ISIL secret oil business

A Western official has confirmed the existence of clandestine business links between Takfiri ISIL terrorists and the Turkish government.

In a report published on Sunday, The Guardian quoted an unnamed senior Western official as saying that evidence on direct dealings between Turkish officials and ranking ISIL members was “undeniable.”

According to the Western official, the documents on the undeclared alliance were obtained following a US raid on the compound of the key ISIL figure, Abu Sayyaf, in Syria in May, which led to his killing.

“There are hundreds of flash drives and documents that were seized there,” the official said. “They are being analyzed at the moment, but the links are already so clear that they could end up having profound policy implications for the relationship between us and Ankara.”

A member of the Syrian government forces stands next to a well at Jazel oil field, near the ancient city of Palmyra in the east of Homs province, after they retook the area from ISIL militants on March 9, 2015. ©AFP 

The ISIL operative was responsible for smuggling oil from fields in eastern Syria. The oil then found its way into the black market to become the main driver of revenues for ISIL, with Turkish buyers as its main clients.

Turkey has been facing criticism for facilitating militants’ border crossings to join ISIL in Syria, which has been grappling with foreign-backed militancy since March 2011. Ankara has also been criticized for providing assistance to Takfiri terrorists waging war in the Arab country.

The report comes against the backdrop of airstrikes conducted by the Turkish military against targets controlled by Takfiri ISIL terrorists inside Syria as well as the positions of the Kurdistan Workers’ Party (PKK) in northern Iraq.

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Deep Neural Nets Can Now Recognize Your Face in Thermal Images

Matching an infrared image of a face to its visible light counterpart is a difficult task, but one that deep neural networks are now coming to grips with.

One problem with infrared surveillance videos or infrared CCTV images is that it is hard to recognize the people in them. Faces look different in the infrared and matching these images to their normal appearance is a significant unsolved challenge.  

The problem is that the link between the way people look in infrared and visible light is highly nonlinear. This is particularly tricky for footage taken in the mid- and far-infrared, which tends to use passive sensors that detect emitted light rather than the reflected variety.

Today, Saquib Sarfraz and Rainer Stiefelhagen at the Karlsruhe Institute of Technology in Germany say they’ve worked out how to connect a mid- or far-infrared image of a face with its visible light counterpart for the first time. The trick they’ve perfected is to teach a neural network to do all the work.

The way a face emits infrared light is entirely different from the way it reflects it. These emissions vary according to the temperature of the air and the temperature of the skin, which in turn depends on the person’s activity levels, whether he or she has a fever and so on.

There’s another problem that makes comparisons difficult. Visible light images tend to have a high resolution while far infrared pictures tend to have a much lower resolution because of the nature of the cameras that take them. Together, these factors make it hard to match an infrared face with its visible light counterpart.

But the recent improvements in deep neural networks in tackling all kinds of complex problems gave Sarfraz and Stiefelhagen an idea. Why not train a network to recognize visible light faces by looking at infrared versions?

There are two important factors that have combined in recent years to make neural networks much more powerful. The first is a better understanding of how to build and tweak the networks to perform their task, a technique that has led to the creation of so-called deep neural nets. That’s something Sarfraz and Stiefelhagen could learn from other work.

The second is the availability of huge annotated datasets that can be used to train these networks. For example, accurate automated face recognition has only become possible because of the creation of vast banks of images in which people’s faces have been isolated and identified by human observers thanks to crowdsourcing services such as Amazon’s Mechanical Turk.

These data sets are much harder to come by for infrared/visible light comparisons. However, Sarfraz and Stiefelhagen found one they thought could do the trick. This was created at the University of Notre Dame and consists of 4,585 images of 82 people taken either in visible light at a resolution of 1600 x 1200 pixels or in the far infrared at 312 x 239 pixels.

The data set contains images of people smiling, laughing and with a neutral expression taken in different sessions to capture the way people’s appearance changes from day to day, and in two different lighting conditions.

They then divided each image into a set of overlapping patches, 20 x 20 pixels in size, to dramatically increase the size of the database.

Finally, Sarfraz and Stiefelhagen used the images of the first 41 people to train their neural net and the images of the other 41 people to test it.

The results make for interesting reading. “The presented approach improves the state-of-the-art by more than 10 percent,” say Sarfraz and Stiefelhagen.

What’s more, the net can match a thermal image to its visible counterpart in just 35 milliseconds. “This is therefore, very fast and capable of running in real-time at ∼ 28 fps,” they say.

It is by no means perfect, however. At best, its accuracy is just over 80 percent when it has a wide range of visible light images to compare the thermal image against. The one-to-one comparison accuracy is just 55 percent, however.

Better accuracy is clearly possible with bigger datasets and a more powerful network. Of these, the creation of a data set that is bigger by orders of magnitude will be by far the harder of the two tasks.

But it’s not difficult to imagine such a database being created relatively quickly, given that interested customers are likely to be the military, law enforcement agencies and governments who generally have deeper pockets when it comes to security-related technology.

Ref: http://bit.ly/1SdHcee : Deep Perceptual Mapping for Thermal to Visible Face Recognition

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US Middle Class Stays Dead: Homeownership Drops To 48 Year Low; Median Asking Rent Soars To All Time High

Three months ago, just as the last Census Homeownership and residential vacancy report hit, Gallup released its latest survey which confirmed just how dead the American Dream has become for tens if not hundreds of millions of Americans.

According to the poll, the number of Americans who did not currently own a home and say they do not think they will buy a home in "the foreseeable future," had risen by one third to 41%, vs. "only" 31% two years ago. Non-homeowners' expectations of buying a house in the next year or five years were unchanged, suggesting little change in the short-term housing market.

As Gallup wryly puts it, "what may have been a longer-term goal for many may now not be a goal at all, and this could have an effect on the longer-term housing market."

Earlier today, the US Census released its latest homeownership data, which confirmed that for what is left of America's middle class, owning a home has become virtually impossible, with the homeownership rate plunging from the lowest level since 1986, or 63.7%, to just 63.4% the lowest reading since the first quarter of 1967.

Three months ago, when compiling this data we said that "at this rate, by the end of the 2015 and certainly by the end of Obama's second term, the US homeownership rate will drop to the lowest in modern US history." That moment, as shown on the chart below, came far sooner than ever we had expected. The only question is whether the lowest homeownership print on record reported in 1965 and standing at 62.9% will be taken out in the next 2 quarters or in early 2016.

 

There is no surprise why this is happening. As Bloomberg notes, the biggest culprit is wage growth which "hasn’t kept up with surging home prices. The average household income in June was 4 percent below a record high set in early 2008, even as unemployment dropped to its pre-recession rate, according to Sentier Research LLC."

 

 

“We’re still suffering the effects of the housing collapse and the financial crisis,” said Mark Vitner, senior economist with Wells Fargo Securities in Charlotte, North Carolina. “We may have another percentage point to go before we see a bottom” in the homeownership rate, he said.

Yes, it is safe assume that the imminent lowest homeownership print in US history may be the "bottom."

Still, the ongoing death of the middle class is not bad news to everyone: landlords, of which private equity firm

Blackstone

recently became the biggest in the US, are reaping unseen profits courtesy of runaway inflation in at least one item: rent.

Because as homeownership falls, demand for rental housing is booming. The vacancy rate for rented homes in the U.S. fell to 6.8% in the first quarter from 7.5% a year earlier. It was the lowest first-quarter rate since 1986.

Words, however do not do the relentless increase in rent justice, so here is something far better. Charts.

 

The same, only broken down by region.

 

And as we showed just two days ago, these are the cities where rents have increased by at least 10% in the past year:

Our condolences dear former members of what was once the world's most vibrant middle class and is anything but any more. Our only advice, the same as last quarter: BTFATH as you turn off the light, and pray that central banks never lose control of this so-called "market" or else having any roof above your head will promptly become an unaffordable luxury.... As many Chinese investors just found out the hard way.

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Majority Of Americans Now See Guns As The Solution To Mass Shootings

Obama failed: in the aftermath of the 2012 Newtown, CT school massacre which left 26 unarmed, defenseless people dead, the president pushed as hard as he could to pass legislation that would enact strict gun control and further limit the applicability of the Second Amendment. Not only did he not succeed, but according to a 2014 Pew Research Poll there has been a 9% rise in the number of Americans who think gun ownership could "protect people from becoming victims of crime."

 

Incidentally, this conforms with what former Texas governor Rick Perry, and a 2016 GOP presidential candidate, said after last week's deadly shooting at a Lafayette, La., movie theater when he claimed that Americans should be allowed to bring guns into movie theaters - and everywhere else - to prevent such crime.

It is also a recapitulation of what NRA head Wayne LaPierre has said in the past: "The only thing that stops a bad guy with a gun is a good guy with a gun."

According to Pew, the recent shift was driven by republicans who have become even more convinced their outlook is correct: in the two years since the Newtown attack,  rose from 63 percent to 80 percent.

The poll also marked the first time in two decades of Pew surveys that more Americans supported gun rights rather than gun control (though public opinion had been shifting that way for years).

 

Incidentally, WaPo which caught these revelations first, despite its anti-gun bias was largely accurate in its conclusion: the findings "likely won't move the needle on gun debate. Both sides can -- and are -- using these two most recent incidents to argue their points: Gun-control supporters say they prove that the background check system needs to be revamped and expanded, while gun-rights supporters say a slip in the system does not a trend make.

 

It's even clearer that gun laws likely won't change when you zoom out to Americans' overall feelings on guns; with every mass shooting, in fact, we seem to be embracing the idea of more guns rather than fewer.

Which means that the biggest loser is none other than the president, for whom his way of gun-control was one of the key targets, so to say, of his tenure.

It also means that current and future mass shootings will do nothing to change public opinion but merely further solidify beliefs. And while politicians debate who is right or wrong, and for what reason, many more innocent Americans will be, for whatever the reason may be, innocent casualties of what has become a very lethal political war.

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