Statistics and disinformation: Is there a link?

These examples from the peak COVID era show us how the interpretation of facts can also generate disinfo

Very often when we hear about statistics we think of credibility, truthfulness, and original research. Usually, the statistics are compiled by professionals in this field. However, such a factual tool can still be skilfully used to achieve controversial goals or produce misinformation and disinformation. In the early months of the Covid pandemic, this statement was particularly evident.

How can statistics be used to influence decisions improperly? Well, that largely depends on how we interpret them.

In an article for Forbes magazine from 2020, Dr Robert Pearl points out that there are at least three ways that statistics, related to coronavirus might be misleading.

Stats can obscure the larger picture

Take for example the statistics related to the confirmed cases of Covid 19. When working with numbers one must be careful because when you hear confirmed cases it does not automatically mean that this describes the complete spread of the infection - there are many people who have been infected and contagious but have not been tested. That is, the number can vary continuously.

A second example is the number of tests done. To what extent do they even indicate that the pandemic is under control? Based on the evidence provided by the author, it turns out that the tests done couldn’t prove the pandemic was under control.

When it comes to the many tests done daily, several questions arose. Did the tests done show that the mass situation was under control at that moment? And were the tests themselves reliable at all?

Apparently, it was not reliable, because no matter how many people you test daily, this is still not a guarantee for mastering the situation. For one, their effectiveness was not 100%, and in addition, it took up to a week, at the time, for results to be confirmed during which period a contagious person could unknowingly infect others. Statistics were thus, at best, a precarious and incomplete snapshot of reality.

In third place, there was the question of the fatality of cases with Covid 19. Perhaps this was the most important thing to pay attention to because such statistics could seriously influence public perception of the new disease. To date, it is known that the case fatality rate compared to the number of infected represents a fairly small ratio.

This statement in no way belittles the number of deaths, but the point is different. That is, if one chooses to point out to the mass audience only the number of those who have died from Covid 19, without providing any reference points and comparisons, then the information itself could confusion and anxiety.

It can therefore be concluded that when we focus on only one aspect of something from a given statistic report, we shouldn’t assume that it shows the whole picture. This could be a fertile ground for misinformation generation. And if we interpret any given information according to our desires and goals, then this would also produce intentional disinformation, or at the very least, a debatable truth.