Absolute Risk Reduction

As we travel further into the future history of John's Revelation, a brief lesson in applied mathematics seems relevant. Let's say, strictly for the sake of argument, that a novel medical treatment is offered to the general public for an evolving disease process which affects public health. This treatment is touted as "safe and effective", and initially all adults (over age 16) are strongly encouraged to participate. Eventually the treatment will be offered to children as well, but I digress.

Hypothetically, the usual process for approval of said treatment involves three lengthy phases. Past examples have taken around 10 years to complete. In this case, the process has been accelerated via an emergency use authorization process. The study is ongoing, but the general public has now been unwittingly recruited to participate for the sake of expediency and "saving lives". Let's look at the numbers.

In the first trial phase, let's say (again hypothetically) that 43,998 healthy adults were recruited. These were then separated randomly into a treatment and nontreatment group. As the study was blinded, neither the recipient or treating providers were aware of any given individual participant's treatment status. Among the nontreatment (or placebo) group, 162 of the 21,999 participants became ill. Among the treatment group, 8 of the 21,999 participants became ill.

At this point, a brief explanation of the difference between Absolute Risk Reduction (ARR) and Relative Risk Reduction (RRR) is relevant. This can be found here:


This distinction is very important, as RRR can be used to bolster a weak argument. Using the example above, we obtain:

RRR = [(162/21,999) - (8/21,999)/(162/21,999)] = 0.95 (or 95%)

ARR = (162/21,999) - (8/21,999) = 0.007 (or 0.7%)

Now, for the sake of argument, if you were to tell someone that an experimental medical therapy would cut their risk of disease by 95% that would certainly sound impressive. On the other hand, if you were to tell the same person that said treatment would in reality reduce their risk of disease by 0.7%, this might be less than inspiring.

Of relevance here is also the Number Needed to Treat (NNT), which represents the number of individuals who will have to receive the treatment to spare a single person from developing the disease. In this case:

NNT = (1/ARR) = 143

In other words, 143 people would have to be exposed to the unknown short and long-term risks of the proposed treatment in order to spare a single individual from the targeted disease process. Of course, if the proposed treatment is indeed "safe and effective", receiving the treatment would be an altruistic and admirable action on the part of the 143. On the other hand, if the treatment ultimately produced a greater burden of disease than the target, the entire project would be foolish on everyone's part.

I will leave it to the reader to digest this information.

"All the world’s a stage,

And all the men and women merely players;

They have their exits and their entrances;

And one man in his time plays many parts,

His acts being seven ages."

- William Shakespeare

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