Media Turn Math Dopes into Dupes

Those who have investigated global warming/climate change discovered that the numbers don’t add up. But if you don’t do the math you wouldn’t know that, because in the details is found the truth (the devilish contradictions to sweeping claims). Those without numerical literacy (including apparently most journalists) are at the mercy of the loudest advocates. Social policy then becomes a matter of going along with herd popularity. Shout out to AOC!

Now we get the additional revelation regarding pandemic math and the refusal to correct over-the-top predictions. It’s the same dynamic but accelerated by the more immediate failure of models to forecast contagious reality. Sean Trende writes at Real Clear Politics The Costly Failure to Update Sky-Is-Falling Predictions. Excerpts in italics with my bolds.

On March 6, Liz Specht, Ph.D., posted a thread on Twitter that immediately went viral. As of this writing, it has received over 100,000 likes and almost 41,000 retweets, and was republished at Stat News. It purported to “talk math” and reflected the views of “highly esteemed epidemiologists.” It insisted it was “not a hypothetical, fear-mongering, worst-case scenario,” and that, while the predictions it contained might be wrong, they would not be “orders of magnitude wrong.” It was also catastrophically incorrect.

The crux of Dr. Specht’s 35-tweet thread was that the rapid doubling of COVID-19 cases would lead to about 1 million cases by May 5, 4 million by May 11, and so forth. Under this scenario, with a 10% hospitalization rate, we would expect approximately 400,000 hospitalizations by mid-May, which would more than overwhelm the estimated 330,000 available hospital beds in the country. This would combine with a lack of protective equipment for health care workers and lead to them “dropping from the workforce for weeks at a time,” to shortages of saline drips and so forth. Half the world would be infected by the summer, and we were implicitly advised to buy dry goods and to prepare not to leave the house.

Interestingly, this thread was wrong not because we managed to bend the curve and stave off the apocalypse; for starters, Dr. Specht described the cancellation of large events and workplace closures as something that would shift things by only days or weeks.

Instead, this thread was wrong because it dramatically understated our knowledge of the way the virus worked; it fell prey to the problem, common among experts, of failing to address adequately the uncertainty surrounding its point estimates. It did so in two opposing ways. First, it dramatically understated the rate of spread. If serological tests are to be remotely believed, we likely hit the apocalyptic milestone of 2 million cases quite some time ago. Not in the United States, mind you, but in New York City, where 20% of residents showed positive COVID-19 antibodies on April 23. Fourteen percent of state residents showed antibodies, suggesting 2.5 million cases in the Empire State alone; since antibodies take a while to develop, this was likely the state of affairs in mid-April or earlier.

But in addition to being wrong about the rate of spread, the thread was also very wrong about the rate of hospitalization. While New York City found its hospital system stretched, it avoided catastrophic failure, despite having within its borders the entire number of cases predicted for the country as a whole, a month earlier than predicted. Other areas of the United States found themselves with empty hospital beds and unused emergency capacity.

One would think that, given the amount of attention this was given in mainstream sources, there would be some sort of revisiting of the prediction. Of course, nothing of the sort occurred.

This thread has been absolutely memory-holed, along with countless other threads and Medium articles from February and March. We might forgive such forays on sites like Twitter and Medium, but feeding frenzies from mainstream sources are also passed over without the media ever revisiting to see how things turned out.

Consider Florida. Gov. Ron DeSantis was castigated for failing to close the beaches during spring break, and critics suggested that the state might be the next New York. I’ve written about this at length elsewhere, but Florida’s new cases peaked in early April, at which point it was a middling state in terms of infections per capita. The virus hasn’t gone away, of course, but the five-day rolling average of daily cases in Florida is roughly where it was in late March, notwithstanding the fact that testing has increased substantially. Taking increased testing into account, the positive test rate has gradually declined since late March as well, falling from a peak of 11.8% on April 1 to a low of 3.6% on May 12.

Notwithstanding this, the Washington Post continues to press stories of public health officials begging state officials to close beaches (a more interesting angle at this point might be why these health officials were so wrong), while the New York Times noted a few days ago (misleadingly, and grossly so) that “Florida had a huge spike in cases around Miami after spring break revelry,” without providing the crucial context that the caseload mimicked increases in other states that did not play host to spring break. Again, perhaps the real story is that spring breakers passed COVID-19 among themselves and seeded it when they got home. I am sure some of this occurred, but it seems exceedingly unlikely that they would have spread it widely among themselves and not also spread it widely to bartenders, wait staff, hotel staff, and the like in Florida.

Florida was also one of the first states to experiment with reopening. Duval County (Jacksonville) reopened its beaches on April 19 to much national skepticism. Yet daily cases are lower today than they were they day that it reopened; there was a recent spike in cases associated with increased testing, but it is now receding.

Or consider Georgia, which one prominent national magazine claimed was engaging in “human sacrifice” by reopening. Yet, after nearly a month, a five-day average of Georgia’s daily cases looks like this:

What about Wisconsin, which was heavily criticized for holding in-person voting? It has had an increased caseload, but that is largely due to increased testing (up almost six-fold since early April) and an idiosyncratic outbreak in its meatpacking plants. The latter is tragic, but it is not related to the election; in fact, a Milwaukee Journal-Sentinel investigation failed to link any cases to the election; this has largely been ignored outside of conservative media sites such as National Review.

We could go on – after being panned for refusing to issue a stay-at-home order, South Dakota indeed suffered an outbreak (once again, in its meatpacking plants), but deaths there have consistently averaged less than three per day, to little fanfare – but the point is made. Some “feeding frenzies” have panned out, but many have failed to do so; rather than acknowledging this failure, the press typically moves on.

This is an unwelcome development, for a few reasons. First, not everyone follows this pandemic closely, and so a failure to follow up on how feeding frenzies end up means that many people likely don’t update their views as often as they should. You’d probably be forgiven if you suspected hundreds of cases and deaths followed the Wisconsin election.

Second, we obviously need to get policy right here, and to be sure, reporting bad news is important for producing informed public opinion. But reporting good news is equally as important. Third, there are dangers to forecasting with incredible certitude, especially with a virus that was detected less than six months ago. There really is a lot we still don’t know, and people should be reminded of this. Finally, among people who do remember things like this, a failure to acknowledge errors foments cynicism and further distrust of experts.

The damage done to this trust is dangerous, for at this time we desperately need quality expert opinions and news reporting that we can rely upon.

Addendum:  Tilak Doshi makes the comparison to climate crisis claims Coronavirus And Climate Change: A Tale Of Two Hysterias writing at Forbes.  Excerpts in italics with my bolds.

It did not take long after the onset of the global pandemic for people to observe the many parallels between the covid-19 pandemic and climate change. An invisible novel virus of the SARS family now represents an existential threat to humanity. As does CO2, a colourless trace gas constituting 0.04% of the atmosphere which allegedly serves as the control knob of climate change. Lockdowns are to the pandemic what decarbonization is to climate change. Indeed, lockdowns and decarbonization share much in common, from tourism and international travel to shopping and having a good time. It would seem that Greta Thunberg’s dreams have come true, and perhaps that is why CNN announced on Wednesday that it is featuring her on a coronavirus town-hall panel alongside health experts.

But, beyond being a soundbite and means of obtaining political cover, ‘following the science’ is neither straightforward nor consensual. The diversity of scientific views on covid-19 became quickly apparent in the dramatic flip-flop of the UK government. In the early stages of the spread in infection, Boris Johnson spoke of “herd immunity”, protecting the vulnerable and common sense (à la Sweden’s leading epidemiologist Professor Johan Giesecke) and rejected banning mass gatherings or imposing social distancing rules. Then, an unpublished bombshell March 16th report by Professor Neil Ferguson of Imperial College, London, warned of 510,000 deaths in the country if the country did not immediately adopt a suppression strategy. On March 23, the UK government reversed course and imposed one of Europe’s strictest lockdowns. For the US, the professor had predicted 2.2 million deaths absent similar government controls, and here too, Ferguson’s alarmism moved the federal government into lockdown mode.

Unlike climate change models that predict outcomes over a period of decades, however, it takes only days and weeks for epidemiological model forecasts to be falsified by data. Thus, by March 25th, Ferguson’s predicted half a million fatalities in the UK was adjusted downward to “unlikely to exceed 20,000”, a reduction by a factor of 25. This drastic reduction was credited to the UK’s lockdown which, however, was imposed only 2 days previously, before any social distancing measures could possibly have had enough time to work.

For those engaged in the fraught debates over climate change over the past few decades, the use of alarmist models to guide policy has been a familiar point of contention. Much as Ferguson’s model drove governments to impose Covid-19 lockdowns affecting nearly 3 billion people on the planet, Professor Michael Mann’s “hockey stick” model was used by the IPCC, mass media and politicians to push the man-made global warming (now called climate change) hysteria over the past two decades.

As politicians abdicate policy formulation to opaque expertise in highly specialized fields such as epidemiology or climate science, a process of groupthink emerges as scientists generate ‘significant’ results which reinforce confirmation bias, affirm the “scientific consensus” and marginalize sceptics.

Rather than allocating resources and efforts towards protecting the vulnerable old and infirm while allowing the rest of the population to carry on with their livelihoods with individuals taking responsibility for safe socializing, most governments have opted to experiment with top-down economy-crushing lockdowns. And rather than mitigating real environmental threats such as the use of traditional biomass for cooking indoors that is a major cause of mortality in the developing world or the trade in wild animals, the climate change establishment advocates decarbonisation (read de-industrialization) to save us from extreme scenarios of global warming.

Taking the wheels off of entire economies on the basis of wildly exaggerated models is not the way to go.

Footnote: Mark Hemingway sees how commonplace is the problem of uncorrected media falsity in his article When Did the Media Stop Running Corrections? Excerpts in italics with my bolds.

Vanity Fair quickly recast Sherman’s story without acknowledging its error: “This post has been updated to include a denial from Blackstone, and to reflect comments received after publication by Charles P. Herring, president of Herring Networks, OANN’s parent company.” In sum, Sherman based his piece on a premise that was wrong, and Vanity Fair merely acted as if all the story needed was a minor update.

Such post-publication “stealth editing” has become the norm. Last month, The New York Times published a story on the allegation that Joe Biden sexually assaulted a former Senate aide. After publication, the Times deleted the second half of this sentence: “The Times found no pattern of sexual misconduct by Mr. Biden, beyond the hugs, kisses and touching that women previously said made them uncomfortable.”

In an interview with Times media columnist Ben Smith, Times’ Executive Editor Dean Baquet admitted the sentence was altered at the request of Biden’s presidential campaign. However, if you go to the Times’ original story on the Biden allegations, there’s no note saying how the story was specifically altered or why.

It’s also impossible not to note how this failure to issue proper corrections and penchant for stealth editing goes hand-in-hand with the media’s ideological preferences.

In the end the media’s refusal to run corrections is a damnable practice for reasons that have nothing to do with Christianity. In an era when large majorities of the public routinely tell pollsters they don’t trust the media, you don’t have to be a Bible-thumper to see that admitting your mistakes promptly, being transparent about trying to correct them, and when appropriate, apologizing and asking for forgiveness – are good secular, professional ethics.

 

 

 

One comment

  1. Hifast · May 15, 2020

    Reblogged this on HiFast News Feed.

    Like

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