CDC's wild disease hysteria overestimates disease transmission by up to 6,400%

(NaturalNews) In August 2014, the U.S. Centers for Disease Control and Prevention (CDC) loudly publicized the prediction of one of its most famous disease modelers, Martin Meltzer, that there could be 500,000 to 1.4 million new Ebola cases in western Africa over the next few months if the world did not immediately step in to assist.

The prediction was admittedly a worst-case scenario. Even so, it was off by an astonishing 65 times. By January, there had only been 21,000 new cases.

The shocking inaccuracy of the much-publicized prediction is causing some health experts to turn scrutiny on the CDC's disease prediction models and question whether they are more political than scientific. Questions are also arising as to whether they do more harm than good.

Losing control of the computer

Disease modeling has become the foundation of many of the CDC's health recommendations. For example, its controversial count of yearly flu mortalities -- a cornerstone of its vaccine-promotion efforts -- are based largely on computer models rather than actual clinical reports.

Sometimes, modeling seems to serve the goal of responsible medicine, such as Meltzer's 2011 finding that the CDC had over-reported the effectiveness of vaccines and antiviral drugs in preventing illness, hospitalization and death during the 2009 flu season.

At other times, modeling seems to serve the realm of hyperbole and politics. In 2001, Meltzer drew mockery for a paper he co-authored warning that a global smallpox epidemic could reach 77 trillion cases within a year given worst-case conditions of no intervention and an unlimited number of susceptible people.

The global population in 2001 was, however, only about 6 billion.

"Every now and again, Dr. Meltzer loses control of his computer," said public health expert Donald A. Henderson, who led the global smallpox eradication effort in the 1970s.

Corrupting both politics and science

The World Health Organization released an Ebola estimate at around the same time as Meltzer's, and theirs turned out to be almost exactly correct; they estimated 21,000 new cases by November 2014. Meltzer and other defenders of the CDC models say that the point of the models is not to accurately predict the future. Meltzer says he uses simplified, dramatic models because those are easier for policymakers to understand. The point, modeling advocates say, is to spur action.

To critics of the approach, this is as good as an admission of guilt.

"The way risk assessment is done in this country is the policy makers shoot the arrow and the risk assessors paint a target around it," said environmental health scientist David Ozonoff of Boston University. "There's a flavor of this with modeling, too. If you say the purpose (of a modeling estimate) is motivational, that's another way of saying it's not scientific."

Critics accuse CDC modelers of fabricating baseless numbers in order to make the case for vaccines by inflating the need for them or their effectiveness, to gain increased funding, or for other political purposes. This is a corruption of both politics and science, they say.

"Public health officials are well aware that their statistics get used - and misused - to justify an increase in their funding" or for other political purposes, such as vaccination campaigns, said Peter Doshi of the University of Maryland. Doshi is also an associate editor of the British Medical Journal.

Doshi said that because modeling is based on assumptions written into computer code rather than real-world evidence, it is easy for people to essentially fabricate numbers for political purposes.

"This is an area again where the CDC is free to produce numbers and nobody can really say they're right or wrong," Doshi said.

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