Ebola and Viral Epidemics; False Results, False Future.
A quick Google search for Ebola and you will see a formal CDC statement, followed by article after article of sensationalist media. The statement reads:
“Ebola is a rare and deadly disease caused by infection with a strain of Ebola virus. The 2014 Ebola epidemic is the largest in history, affecting multiple countries in West Africa. The risk of an Ebola outbreak affecting multiple people in the U.S. is very low.
What you need to know: Ebola is spread through direct contact with blood and body fluids of a person infected by and already showing symptoms of Ebola. Ebola is not spread through the air, water, food, or mosquitoes.”
Of course this statement seems to imply we should all regain composure, but why are we so worried in the first place? Although this question has no clear or decisive answer, one dramatic article essentially calls for us to reconsider Bayes’ theorem in light of Ebola testing. However, rather than recapitulate its points and tone, I will dissect the fundamental “fear” behind Bayes’ equation and attempt to generalize it.
As you may already know, lab tests are not always accurate. In this application, we consider positive and negative results to indicate if a virus is present. Further, we understand that, with some probability, a positive result can actually be negative and a negative result can actually be positive; these results indicate false positives and negatives. We can determine the accuracy of our testing procedures by applying Bayes theorem. We can view the generalized form,
P(A | B) = P(B | A) * P(A) / P(B)
in a form applicable to the test results of a virus,
P(Virus | Negative) = P (Negative | Virus) * P (Virus) / P(Negative).
For clarification, the first probability in the equation represents the likelihood that a person has the virus if his or her test came back negative. The second probability represents the likelihood the test comes back negative if he or she has the virus. The third probability represents the likelihood of having the virus, and finally the fourth probability, the denominator, represents the likelihood of a test coming back negative.
Although I’m not certain of the exact mechanics, the author seems to assume that the second term to be somewhat constant or at least non-diminishing. That is, the probability of a false negative does not become smaller or disappear. Rather false negatives are inherent to the testing method and not dependent on the environment.
And this is where the sensationalism begins. The author of the article questions our lack of knowledge about the new strain of Ebola and testing procedures as well as the CDC’s judgment. To clarify, much remains unclear about this form of Ebola. Although we are informed about past strains, the CDC claims and informs the public as if we were knowledgeable about this strain, like the Google statement implies. Firstly, there are too few cases to determine the validity or falsity of their claims. Secondly, the false negatives are a clear danger.
Although the author cites reasons specific to Ebola, I look at it from the more generalized non-Ebola view. The key point, however, remains the same. Introducing false negatives and falsely informing patients incurs a more rapid viral spread and should be avoided. But why is this so dangerous?
To start, by introducing false negatives, there is an uncontained viral population. By falsely reassuring them, this viral population is not only uncontained, but also incorrectly assumes that they are non-viral. This increases the dangerous contact amongst them and the non-viral population. As a result, the viral population increases. Obviously the viral population decreases as well. In doing so, the equation represented by Bayes’ theorem has now increased, though by how much we don’t know. With the numerator rising and the denominator falling, we have a recipe for disaster. The probability of false negatives rises and the vicious cycle continues.
Now, this too may seem somewhat sensationalized, and it is. Without numbers we cannot predict, but with theory we can dissect. With Ebola, however, there does seem to be some danger. It may not be important for everyone, but it can affect those close to people or places with the virus. Ebola is dangerous; it is temporarily invisible and we seem only so certain about its transmission. We may be getting wrong information from our authorities, as the author says the CDC does frequently, and we don’t know the extent to so many of these questions. But we should realize that this is merely an issue of approach. If we think with probabilities in mind, we can all relax just a little more!
Article: http://www.globalresearch.ca/genetic-strains-of-ebola-that-have-never-been-seen-before-media-lies-and-us-government-coverup/5406603