*Here, we’ll quickly review a few very weighty MSM/U.S. Government Ebola lies before discussing what may be the most dangerous Ebola lie yet, which involves the risk of false negative Ebola tests. The lies in the next few paragraphs are mentioned in this article primarily because they might intersect in disconcerting ways with the false negative problem—a problem the CDC and MSM would rather lie about and pretend does not exist.*

[T]he current outbreak (which actually began on or before December, 2013) presents genetic strains of Ebola that have never been seen before. The Guinea variant of Ebola was itself novel enough to form its own clade. Now,

*via*Recombinomics and with respect to Sierra Leone, we have:

“The June Sierra Leone sequences have evidence of some drift from the March sequences from Guinea. A prior Zaire sub-clade, which was found in apes and a chimpanzee and was associated with an outbreak in Gabon in 2002 had strong evidence of recombination, which raises concerns of more evolution in the current sub-clade, which has produced a record number of reported Ebola cases and deaths.”

It is curious indeed that the Ruling Class seems uninterested in broaching, to its serfs, the possibility that these genetic alterations might be causally related to the current outbreak’s dramatically higher fatality counts and, evidently, higher contagion probability. As to whether the novel viral genotypes might signify that Ebola is now airborne, the CDC continues to insist that the only ones who think it might be airborne are paranoid tinfoil hat wearers—although the United Nations has uttered the heresy that even if Ebola isn’t airborne now, it soon might be regardless of its causal origins.

And then we have the incessantly repeated reckless claim that it is impossible for asymptomatic carriers to transmit Ebola. Who can say this with complete confidence given that we have novel genetic variants of Ebola in play? Furthermore, any scientist who is remotely competent will observe that asymptomatic transmission cannot possibly be completely ruled out regardless of the fact that we are dealing with new variants—simply because there can *never* be enough cases to statistically eliminate small probabilities of asymptomatic transmission. The only scientific question on this issue is whether such probabilities are so small that they can be considered negligible from a practical standpoint—and, right now, we don’t have a *tremendous* amount of cases at this point to base our conclusions on anyway.

Let’s pivot now to the Ebola test false-negative problem. False-negative results, of course, occur when tests indicate the absence of a condition even though the condition is in fact present. For many reasons (including human perceptual and cognitive errors), no test offers 100% accuracy in this respect or any other. Therefore, there is always some risk that tests returning negative results for Ebola are wrong. The U.S. Department of Defense has spoken to this issue with reference to the Ebola Zaire variant it says was detected in the current outbreak in West Africa:

“**If this test is negative, does that mean that I do not have Ebola Zaire infection**?

Most, but not all, people with Ebola Zaire infection will have a positive test. Therefore, if your test is negative, something else may be responsible for your illness. There is a small chance that this test can give a negative result that is wrong (called a false negative) meaning you could possibly still have an Ebola Zaire infection even though the test is negative. Therefore, while a negative test most likely means you do not have an Ebola Zaire infection, your health care provider must consider the test result together with all other aspects of your illness (such as symptoms, possible exposures, and geographical location) in deciding how to treat you.”

So, suppose, for example, that the “small chance” of an Ebola false negative rate is 1%. It’s bad enough that many will then jump to the conclusion that such a result indicates that there is a 99% chance that the negative result indicates absence of the disease, so let’s show why that construal is wrong.

It is true that, given a 1% false negative rate, the true* positive rate* is 99%. This is because the true positive rate is the complement of the false negative rate. But all a 99% true positive rate says is that positive test results capture 99% of cases that are in fact positive.

The Ebola-related practical concern addressed in this article is that a 99% true positive rate (also referred to as 99% “sensitivity”), which speaks to what might be informally called the “accuracy” of *positive* test results, does *not* really say much about the probability that *a negative *test result should be believed. To generate that probability, the false negative rate must be combined with the *prior probability* that the person tested is not afflicted (which of course is by definition the complement of the probability that they *are* afflicted) with the illness as well as with the true negative rate, which is the probability of negative results when persons are actually negative. This is the sort of thing Bayes’ Theorem does.

The “prior probability” is estimated on the basis of whatever information pertaining to the likelihood of Ebola infection exists *before* tests are administered. These are factors such as “symptoms, possible exposures, and geographical location” as the U.S. Department of Defense properly indicates (and isn’t it interesting that a military wing of the U.S. government admits the problem, while the civilian CDC lies by omission). As the application of Bayes’ Theorem makes clear, the significance of a negative test result varies in terms of its practical significance with the prior probability of Ebola affliction, which means that if the prior probability of affliction is high enough in particular cases, people shouldn’t feel comfortable even if the risk of false negative tests is very low and negative test results do a very good job of capturing those cases that are in fact negative.

What this means is simply that, particularly in view of scores on factors such as friendship and social networks, having *lived in* and travelled from hot zones might imply that *negative Ebola tests applied to such persons have very little significance—especially when cases are viewed in the aggregate. *When one puts this together with the reality that negative test results will often result in the release of persons who may well be infected into civil society, the extraordinary danger we face is obvious—the more so, again, if we keep hearing smiley-faced CDC/MSM stories about *bunches* of negative test results.

Let’s wrap up by synthesizing this conclusion with the U.S. Government/MSM lies noted at the outset. The lies mentioned at the beginning of the article were included because each interacts with the prospect of potentially widespread false negatives in harrowing ways. So, for example, all else equal, greater contagion potential suggests greater potential for false negative test results. And, clearly, all else equal the prospect of airborne contagion implies the same thing. Furthermore, it is even possible that the novel Ebola strains are such that false negative results are more likely than they were before.

But, even if none of these things is true, the more negative tests we hear about, the more confident we can be that at least one of them is false. At some point, a threshold will be passed beyond which we can be very confident indeed that someone who is in fact positive has nonetheless been released into civil society on the basis of an erroneous test result.

Viewed together, all of the above suggests that thoughtful observers should *be on the lookout for CDC/MSM lies and/or nondisclosures regarding specific biographical details about persons who test negative*—because these are what inform prior probability estimates.

**Republished from Centre for Research on Globalization.**

**Dr. Jason Kissner** is Associate Professor of Criminology at California State University. Dr. Kissner’s research on gangs and self-control has appeared in academic journals. His current empirical research interests include active shootings. You can reach him at crimprof2010[at]hotmail.com