Covid: Mainstream media's meaningless musings

July 21, 2021. What does 'surge' mean to you? In the past eighteen months, how many times have you read the word 'surge' or, for that matter, 'spike' in a clickbait headline about Covid 'cases'? In fact, what does the term 'case' mean in this context? Insurgents surge, as do waves, but how do numbers 'surge' or 'spike' and what does it mean if they do? In my dissertation paper, I studied how people judged uncertainty, complexity and dynamism in their work environment. How you asked the question was critical. If asked, "how unpredictable is your sales estimate on a scale of one (unpredictable) to five (predictable)," one's answer was much more a function of the person than of the reality of the work environment. People more sensitive to detecting uncertainty were more likely to see uncertainty in just about about change in the environment. If you asked, "How often can you have a correct forecast within ten percent of the actual results, using a percentage scale from 0 (never), to 50 (half the time), to 100 (all the time)," the answer was usually a much more accurate reflection of what was really going on than it was a measure of the person's lack of confidence or personal uncertainty. Some people are nervous, some are confident, but how you measure their behavior accurately depends on asking the question in a clear, relatively objective fashion.

Or this bit of CDC/media rhetoric: Wash your hands "often" and for "twenty seconds," or the equivalent time it takes to sing "Mary had a little lamb," twice. Putting aside the demeaning, sexist ditty, if it is so hard to get the germs washed off your hands, how are they so easy to transmit by touch? Have you ever seen an article justifying the "twenty seconds," or explaining what "often" means in this context. Reminds me of the old college binge drinking studies that asked for student self-reports of how often they drank five drinks "in a row"? How can drinks not be "in a row"?

Or take yesterday's "news" story from NPR, "India's Pandemic Death Toll Estimated At About 4 Million: 10 Times The Official Count,"reporting on a 'study' that claims "our analysis of the Consumer Pyramid Household Survey, a longitudinal panel of over 800,000 individuals across all states, yields an estimate of 4.9 million excess deaths."To make it sound like science, or facts, the report includes this: "We provide code and workbooks to replicate all our calculations here." So a report on a study using code and workbooks to provide estimates based on.....well, I think you know where this is going. Thank heavens that this study decided to throw in every possible death connection to Covid to explain "excess deaths," with a justification that goes like this: 'When counting "excess deaths," the cause of death is not part of the data set. But during a health crisis like the pandemic, the assumption is that these additional deaths are part of the COVID-19 toll, says Mokdad. They reflect not only those who died of the virus but those who might have died, say, of heart disease or diabetes because they were afraid to seek treatment during lockdowns, and those who killed themselves due to pandemic stresses, he adds.' So, basically, during a pandemic, throw in estimates of untested deaths and deaths wholly unrelated to the virus into the count. Why? No 'report,' 'study,' 'code,' or 'workbook' can justify or explain the multiple guesses that go into the formula used to calculate this number of 'excess deaths.' Suffice it to say, the old adage, "Garbage in, garbage out,' explains a lot...of garbage.

Worse, as I have noted in earlier blogs, the very concept of 'excess deaths' is highly problematic, based on the assumption of the modelers as to what the 'expected deaths' are expected to be, the ignoring of other causes of death or explanations, and the time frame chosen for the 'excess deaths.' Today the Wall Street Journal reported a drop in life expectancy in the United States, apparently believing that life expectancy can and should only ever increase. Even then, 'life expectancy' remains just that, an expectancy, and estimate. It's not like they took a random sample of a representative number of death certificates from the United States in 2020 and counted the average age at death in the past year. It's like claiming that half of marriages end in divorce when at the same time, an examination of marital records at the time of death will show that well more than half of those dying that year were married just once. The problem is that a lot of people get divorced a number of times. so that at marriage, your 'odds' might be something like 70% never to divorce, 20% to get divorced once, and 10% to get divorced two or more times. The 'average' is a statistic, a mathematical calculation, not a good predictor nor explanation as to what is going on in reality.

Warren Buffet -- I believe it was he who said this -- got this right about 'journalists' when he said he won't speak to them because they only look for confirmation of their pre-conceptions, and not an honest, empirical, objective, analytical response. It's why teaching students 'rhetoric,' which basically means 'argument based on personal assumptions, without evidence or critical thinking,' is effectively a dis-service and, in truth, a lie when schools claim to instead teaching 'critical thinking.' Most people -- including journalists or, maybe 'almost every' journalist -- don't really know an understand statistical terms like mean, median and mode, or the difference between a guess and a credible prediction, between an opinion and a forecast, between 'the science' and 'a consensus of scientists,' or between causal and correlated relationships. No journalist seems to know that 'data' is a plural noun, or that a peer-reviewed study is not a true 'gold standard' without an unbiased review, a replication of the study, and meaningful rather than just 'statistically significant' results.

Do yourself a huge favor and read this lengthy, thoughtful, quite unbiased and rational analysis of the 'pandemic.' The first four paragraphs of this illuminating dissection of the pandemic policies follow.

The United States suffered through two lethal waves of contagion in the past year and a half. The first was a viral pandemic that killed about one in 500 Americans—typically, a person over 75 suffering from other serious conditions. The second, and far more catastrophic, was a moral panic that swept the nation’s guiding institutions.

Instead of keeping calm and carrying on, the American elite flouted the norms of governance, journalism, academic freedom—and, worst of all, science. They misled the public about the origins of the virus and the true risk that it posed. Ignoring their own carefully prepared plans for a pandemic, they claimed unprecedented powers to impose untested strategies, with terrible collateral damage. As evidence of their mistakes mounted, they stifled debate by vilifying dissenters, censoring criticism, and suppressing scientific research.

If, as seems increasingly plausible, the coronavirus that causes Covid-19 leaked out of a laboratory in Wuhan, it is the costliest blunder ever committed by scientists. Whatever the pandemic’s origin, the response to it is the worst mistake in the history of the public-health profession. We still have no convincing evidence that the lockdowns saved lives, but lots of evidence that they have already cost lives and will prove deadlier in the long run than the virus itself.

One in three people worldwide lost a job or a business during the lockdowns, and half saw their earnings drop, according to a Gallup poll. Children, never at risk from the virus, in many places essentially lost a year of school. The economic and health consequences were felt most acutely among the less affluent in America and in the rest of the world, where the World Bank estimates that more than 100 million have been pushed into extreme poverty.