Beware the Power of Untruth

When public trust is vital, when knowing the truth is what people want, when the reality is the key – do not feed them half-truths, not from sloppiness and not for political expediency.

Beware the power of an untruth, half-truth, sails that spill wind, calls to care – when the caller is only half there. We have been pressed to accept societal panic, tapering to stress around COVID. Now we learn, reported hospitalization numbers may have been wrong – a half-truth.

What did we learn? In New York, a representative state, hospitalized COVID cases are of two types:  Those admitted for COVID, and those admitted for other reasons who have COVID.

Data just released shows “how many hospitalized individuals who have tested positive for COVID-19 were admitted for COVID-19 complications, and how many were admitted for non-COVID-19 conditions” but later tested positive for COVID.  

You might think the first category is large, the second small. But the numbers out of New York are strangely balanced. That has implications big implications.

In New York, 43 percent of “hospital admissions” tested positive for COVID – but “COVID was not included …as one of the reasons for admission.” In other words, 4,928 cases – as of January 7^th – in New York’s hospitals have COVID but are there for another reason, while 6,620 patients were actually “admitted due to COVID or complications of COVID.” 

The distinction is vital, vital for public information and policy direction. If COVID was not serious enough to trigger admission, why count that case in hospitalizations? Why feed the public a higher number, suggesting COVID is filling hospitals, if some are just minor cases?

Counts we have been given for COVID hospitalizations that sound high, even scary, and assume patients with COVID in a hospital got there because of COVID. But 4-out-of-10 cases are not in the hospital for COVID, even if they have it.

Why has the ambiguity been permitted to persist, all cases lumped together as if COVID drove them all into a hospital? Shockingly, for New York City, the percentage is even higher. Some 51 percent of those hospitalized who have COVID came for totally different reasons. See, e.g., Almost half of reported NY COVID-19 hospitalizations are not due to COVID-19.

On the numbers, more have COVID yet came for another reason than came for serious COVID symptoms. Thus, 3,060 of those with COVID came for other reasons, only 2,992 for COVID.

This is like saying, 51 percent of those in the hospital have cavities, but only 49 percent came for cavity pain. Or maybe 51 percent have a cough, but only 49 percent are there for the cough.

In short, there are distinctions without a difference, things that do not matter – and there are distinctions that represent a serious difference, and this is one. This new data matters. See also Coronavirus Disease 2019 (COVID-19)-Associated Hospitalization Surveillance Network (COVID-NET).

If we are making national policy, pressing edgy federal mandates, scaring people into compliance with threats of federal OSHA penalties, worrying them about job loss, denial of benefits, loss of livelihood, forsaking of their faith, and trying to cajole, persuade, using federal money to advertise a frenzy over vaccines, should we not be using accurate data?

If the total number of cases requiring hospitalization is – in fact – half the overall number who are in hospitals and COVID-positive, is that not a material omission, knowing hype, misleading?

Should that not be made a big public issue? If the disease spreads widely but half with it – even in hospitals – are not there because of it? Does that change things, maybe lower the worry level?

It should. Here again, the federal government is missing the boat. When public trust is vital, when knowing the truth is what people want, when the reality is the key – do not feed them half-truths, not from sloppiness and not for political expediency.

Yet this appears to be what we have, national leaders – and media talkers – intent on stirring public anxiety, whether with good intentions or to push federal money hoping on a return in November, or to encourage mass mail-in ballots, or feed the next crisis.

The whole thing – like claiming certainty around the virus, vaccine, and testing kit data – looks cockeyed. The data is perilously thin, statistically unrepeatable, often contradictory – it stinks. People want reality, not breathless worries, not pandering puff, not cheap crisis talk. 

And the more people are fed half-truths, the more trust they lose. The more data does not support panic and federal mandates, the more they question motivation. Liberty, like health, matters – and both depend on truth.

George Orwell wrote, almost 100 years ago: “The enemies of intellectual liberty always try to present their case as a plea for discipline … The issue truth-versus-untruth is as far as possible kept in the background.” So it increasingly seems.  

Watch the data closely, think hard about what it means – and what it does not mean. Beware the power of untruth, half-truth, sails that spill wind, calls to care – when the caller is only half there.