Last December, an official UK Office for National Statistics release recorded a total of only 6,183 Covid deaths from February of 2020 through December of 2021 in England and Wales. Media sources, including the the BBC, then railed against legitimate medical professionals who shared this data as spreading “disinformation”. So what what was this all about?

Most would agree that facts aren’t the same as values. Facts are objective, certain, and verifiable. They occupy a domain of things that are both observable and quantifiable, able to be recorded in precise descriptions and measured in the universal language of numbers. Values, however, are subjective.

Values are among that which emerge from an intangible universe of relative importance, classified into vague hierarchies by whatever social entity determines worth. These occupy a domain of emotion and opinion, and are conveyed in passages of rhetoric and persuasion.

And then, there are statistics.

In, Mark Twain’s Own Autobiography, Twain wrote that, “Figures often beguile me, particularly when I have the arranging of them myself; in which case the remark attributed to Disraeli would often apply with justice and force: ‘There are three kinds of lies: lies, damned lies and statistics.‘”

Twain was certainly no denier of facts, especially with regard to the sciences. These he held in high regard, and especially in relation to that which he saw as the promotion of superstition in his time. Rather, his words expressed the sense of inaccessibility commonly felt by many. Facts may indeed be objective, certain, and verifiable. But merely stating this doesn’t necessarily mean that most of us have either the means or the ability to verify, or to fully understand things for ourselves.

The result can be a sense of something like the last words in his, …Own Autobiography, “Now, then, that is the tale. Some of it is true.”

This is the first of two great problems with the use of statistical representations in decision-making, that their actual meanings may be inaccessible to the people who consult them. Consider a scientific study of a treatment for a common quality-of-life issue. If the treatment is found to double the risk of a heart attack, this would seem to indicate that it is perhaps unacceptably dangerous.

Now assume that the data from which this conclusion was drawn equated two sample groups of 10,000 participants each, with one heart-attack in the control group, and two in the treatment group. This indeed indicates a doubling of risk. But also assuming all else to be equal, this means the real world risk of experiencing a heart attack increased by 1 in 10,000. And whether or not this is acceptable is subjective, which leads to the second problem.

Isolated within that domain of numbers, statistics tend to ignore those kinds of subjective meanings rooted in both cultural and individual values. And yet, these may be the very things to which these numbers are applied. Which is the more important: the easily quantifiable length of a life, or the more subjective health of the individual? And to what extent is one interchangeable with the other?

The problem here is that most real-world experiences can’t be reduced to numbers. And yet, a scientific approach compels objective forms of measurement. Even properties that seem as though they should be easily measurable, “wealth” for example, ultimately require consideration of numerous subjective factors as well as the comparative weights of value applied to each of them. And there’s simply no objective way in which to simplify multiple measures into a single value.

This means that numerical comparisons made without understanding the values applied to their underlying sources can lead to uninformed choices, if not deception. And this is especially the case when we hear only one perspective of a set of interrelated statistics when the bigger picture is rather more complicated.

Consider the statement that, “Electric cars are ‘greener’ than internal combustion vehicles.” A comparison made at the exhaust pipe will render an easily quantifiable conclusion, where one produces something noxious while the other does not. But this ignores context.

In a 2020, like-for-like study between two otherwise identical vehicles, Volvo Motors concluded that the manufacturing of its XC40 electric vehicle generates 70-percent more emissions than that of its internal-combustion XC40 counterpart. So is the internal combustion version actually “greener”?

The answer requires considering each vehicle’s entire life-cycle, from the mining of raw materials and production processes, fueling of the vehicle using average global energy sources, maintenance, and final disposal at a projected 124,000-mile lifetime.  Based on all of this, Volvo concluded that an electric XC40 breaks even with the internal-combustion version at around 68,000 miles (110,000 km). So the more comprehensive conclusion is that the electric version becomes greener at somewhat over half of the vehicle’s projected lifetime.

Before I continue, I need to make it very clear that I’m not an “anti-vaxxer”. After a feral dog bite in Thailand, I was happy to have had a Human Rabies series available. And having experienced hemorrhagic Dengue, I’d happily consent to a “Dengvaxia” series if it’s ever made available to American adults. That said, how medical information can be presented to various populations by presumably honest and objective sources can be shrouded in some degree of statistical fog. Hence, back to that, UK Office for National Statistics report.

On December 16^th 2021, the UK Office for National Statistics responded to a Freedom of Information request: “Please supply deaths caused solely by covid 19, where covid is the only cause of death listed on the death certificate, broken down by age group and gender between feb 2020 up to and including dec 2021.” As it turned out, the data set already existed, had been updated every two months, and had likewise been available to doctors, epidemiologists, scientists, public health policymakers, and media. But it had not been publicized.

[The official British government response covering England and Wales: (FOI Ref: FOI/2021/3368)]

At that point in time, Great Britain had officially reported more than 150,000 Covid deaths. The official FOI response, however, recorded a considerably smaller, 6,183 total deaths with a median age in the mid 80s, with 90-years or above accounting for almost a quarter of all deaths. Only 241 total deaths occurred below the age of 50-years. And these were by all accounts accurate numbers. So what was going on?

Researches have long known that Covid was primarily killing those already compromised by other conditions. And the British population includes many with medical conditions that greatly increased their risk of death from a Covid infection. Likewise, the United States Center for Disease Control (CDC) reports that the average number of “comorbidities”, or conditions that contributed to deaths among US Covid cases is four. So, Covid is fundamentally a killer of the weak and the old.

But is this really a message that one wants to spread among a general population when the overall social objective is to prevent deaths? In this case, government officials and others have had to consider the ramifications of how they present statistical data, and especially with regard to supporting a particular strategy to save lives. But this is a subjective judgment.

Whether or not one considers a particular statistical presentation to be “misinformation” can consequently depend upon perspective. To those who endeavored to hold out with hopes to fight off the pandemic with vaccines while “flattening the curve”, appealing to those larger numbers seemed the best presentation. But to countries endeavoring to follow something more along the lines of the “Great Barrington” approach, those lower numbers became a salient appeal to allowing natural infections among the young and healthy to quickly build up a buffer within their populations.

Unfortunately, as the US has exceeded one-million deaths attributed to Covid, the backlash here has been to erode public confidence in the information it receives. The result is that government officials, medical authorities and media sources have had to harden their positions in order to protect egos, careers and reputations.  So in the wake of… “lies, damned lies, and statistics,” it may be difficult for the public to learn anything useful at all from the mere numbers.