Deaths attributed to COVID-19 are frequently assumed or guessed, or just not recorded at all in many venues. Hence we see the death tolls being revised for all sorts of reasons.
To exaggerate the matter: Man eaten by shark dies of Coronavirus!
Real infection rates are totally unknown. Many of the tests are highly unreliable, both for positive and negative results and lack statistical validity in a population with a low infection rate—the error rate overwhelms the infection rate—see the Bill Gates interview about that.
The false positive rate on that serology test [Santa Clara and LA county tests] is very, very high. It’s just the way the statistics work. When you have 98 percent who certainly aren’t infected, false positives completely overwhelm the real data.
In short, what passes for data and science today with regards to COVID-19 is pure GIGO. That is, JUNK data upon which rational decisions cannot be made. Thus the call for dealing with COVID-19 using “data and science” is a reassuring soundbite slogan good for network TV and politicians and rationalizing mandates, but little else. That could change with reliable and widespread diagnostic tests along with proper post-mortem followup, but achieving that may be an insurmountable problem in the short or even medium term.
Readers should not infer my viewpoint from what I link to here. I am not a member of any political tribe, and any assumptions along those lines would be Bad Thinking. Do not engage in mind reading!
One thing I will say in general however: I discount the credibility of all articles that needlessly insert partisan political viewpoints into the discussion—and some do, to the point of “here we go again...’ tedium—a waste of credibility and time in the face of a real crisis.
Seemingly Small Differences in the Accuracy of COVID-19 Antibody Tests Can Make a Big Practical Difference
When infection prevalence is low, a test with relatively low specificity can generate highly misleading results.
Dozens of different tests are currently available, and their accuracy varies widely. Evaluate Vantage's Elizabeth Cairns looked at 11 tests and found that their reported sensitivity (the percentage of positive samples correctly identified as positive in validation tests) ranged from 82 percent to 100 percent, while their reported specificity (the percentage of negative samples correctly identified as negative) ranged from 91 percent to 100 percent.
A recent study by the COVID-19 Testing Project evaluated 12 antibody tests and found a wider specificity range, from 84 percent to 100 percent. Most of the tests had specificities higher than 95 percent, while three had rates higher than 99 percent.
Maybe. And maybe not, see the article that follows. Testing the dead won’t tell us whether the real underlying cause was COVID-19—association does not prove causation and is faux science.
To get an accurate picture of the pandemic, US needs to test more of the dead.
The novel coronavirus has already claimed the lives of more than 61,000 Americans. But experts fear that number could be far higher at this point in the outbreak -- perhaps by tens of thousands -- once the pandemic subsides enough for officials to go back and make a true reckoning of the dead. Experts are urging leaders to take measures right now to preserve data and medical specimens so that science has the chance to determine the precise number of people who succumbed during one of the most severe global pandemics in memory. "Under-counting deaths in this particular epidemic is happening all over," said Dr. Daniel Lopez-Acuna, an epidemiologist and former top World Health Organization official, who spent 30 years at the organization. "It’s almost inevitable."
..."We need to have the testing available because the big question now with COVID-19 is the denominator -- of anything," said Dr. Alex Williamson of the College of American Pathologists. "How many people get it? How many people recover? How many are hospitalized? How many died? We don't know the true denominator. More testing is the most important thing we need to do."
Another reason that it is Bad Thinking to compare countries.
The federal government is classifying the deaths of patients infected with the coronavirus as COVID-19 deaths, regardless of any underlying health issues that could have contributed to the loss of someone’s life.
Dr. Deborah Birx, the response coordinator for the White House coronavirus task force, said the federal government is continuing to count the suspected COVID-19 deaths, despite other nations doing the opposite. “There are other countries that if you had a pre-existing condition, and let’s say the virus caused you to go to the ICU [intensive care unit] and then have a heart or kidney problem,” she said during a Tuesday news briefing at the White House. “Some countries are recording that as a heart issue or a kidney issue and not a COVID-19 death. “The intent is … if someone dies with COVID-19, we are counting that,” she added.
Reason: In Sweden, Will Voluntary Self-Isolation Work Better Than State-Enforced Lockdowns in the Long Run?
Comparisons to Sweden or any other country are just bad thinking, bad comparing. Even in the USA, the way deaths are reported or diagnosed (or assumed or guessed) varies from locale to locale! When you have junk data, making comparisons is just GIGO.
In the Stockholm region of Sweden, 42 percent of deaths took place in nursing homes for the elderly. In many countries, and some U.S. states, those deaths would not show up in the data.
This has a major effect on where you are compared to other countries. According to Johns Hopkins University, Belgium has twice as many COVID-19 deaths per capita as the Netherlands. But in Belgium, almost half of those deaths are from nursing homes, while testing is more rare in Dutch nursing homes so fewer deaths there are attributed to the disease. After France started to include nursing homes in the statistics, the total number of French COVID-19 deaths jumped by almost a third.
The interview is well worth reading (and count me out on the Bill Gates conspiracy theories).
The false positive rate on that serology test is very, very high. It’s just the way the statistics work. When you have 98 percent who certainly aren’t infected, false positives completely overwhelm the real data. So that study would say there’s like 10 times as many people who’ve been exposed as who’ve shown symptoms...
A therapeutic is easier. If your therapeutic has a dramatic benefit, you know, you can see that with just 100 patients. So you can go through a large number at a time. This is happening right now — we have studies going on. The UK is doing a good job on this. Germany is doing a good job. There are particular compounds — and not necessarily the ones that get mentioned — that look very promising. There’s one where you look in the blood of recovered patients and find the best antibodies. And then you either directly use that blood or you manufacture that antibody. That one has got quite a bit of promise. So we’re orchestrating, who’s got the best antibodies? Who has that manufacturing capacity? And trying to get that up and going well before the end of the year.
...Some people have access to testing who have no symptoms, and some people with symptoms have no access to testing. So a substantial percentage of the testing is not helpful. It’s almost corrupt in the sense that if you have a close relationship with your doctor in a hospital, you’ll get onto their PCR machine no matter what your circumstances are. And if you don’t have that type of connection, even if you’re a health care worker, you can get tests back five days later. So it’s a hard one to understand why people aren’t outraged about this.
The Atlantic: Why the Coronavirus Is So Confusing—aguide to making sense of a problem that is now too big for any one person to fully comprehend
Half useful and half political screed.
But much else about the pandemic is still maddeningly unclear. Why do some people get really sick, but others do not? Are the models too optimistic or too pessimistic? Exactly how transmissible and deadly is the virus? How many people have actually been infected? How long must social restrictions go on for? Why are so many questions still unanswered?
Read the Bill Gates interview for someone who thinks hard and deeply about issues while not trying to score political points. Here, the frequent anti-Trump claims and multiple links to more of the same are a constant distraction. This will surely please most readers of The Atlantic, but it makes the article a chore to read. The author seems not to realize his his own article suffers from the same problems he calls out:
It does not help that online information channels are heavily personalized and politicized...
Scientific American has it wrong: it’s like comparing a crude model-based estimate to a crude ballpark guess (based on “real numbers” for COVID-19 that are highly suspect)—at least an orange and an apple are what they are, an honest A and B.
Sadly, the author chooses to make what might have been a neutral informative article into an anti-Trump screed. Mixing politics and science is like mixing poison and water—unfit for consumption. Still, the article correctly calls out the GIGO inherent to flu but fails to do so for COVID-19—sloppy workand not even well informed.
The former are actual numbers; the latter are inflated statistical estimates.
...The 25,000 to 69,000 numbers that Trump cited do not represent counted flu deaths per year; they are estimates that the CDC produces by multiplying the number of flu death counts reported by various coefficients produced through complicated algorithms. These coefficients are based on assumptions of how many cases, hospitalizations, and deaths they believe went unreported. In the last six flu seasons, the CDC’s reported number of actual confirmed flu deaths—that is, counting flu deaths the way we are currently counting deaths from the coronavirus—has ranged from 3,448 to 15,620, which far lower than the numbers commonly repeated by public officials and even public health experts.
No one really knows for sure under what conditions and what distance how the virus is acquired through the air (or not).