Looks like the U.S. is stuck on repeat, in terms of a COVID-19 winter wave. I suppose that in addition to the case counts, this probably means a replay of much of the nonsense reporting we saw last winter.
In the interest of efficiency, in this post, let me try to handle some of the known nonsense in bulk, rather than piecemeal. We may see novel forms of it evolve. But at least I can efficiently dispose of the stuff that’s a straight-up repeat from last year.
To be clear, this post is all about things that are wrong. But that nevertheless make great click-bait, or allow people to feel all righteous about something, or otherwise seem to stick around despite clear evidence that they are incorrect.
This underscores yet again the fundamental problem with America today:
- Every citizen feels the unalienable right to have a strongly held and firmly expressed opinion.
- Nobody feels even the tiniest obligation to do their homework.
Hence, this list of pre-debunked items from last winter. I’ve already done the homework so you don’t have to.
1: Post-holiday surge.
So far, we have never had a post-holiday “surge” in cases in the U.S. Never. Not even once. Not post-Thanksgiving. Not post-Christmas. Not post-Superbowl, Memorial Day, 4th of July, Labor Day. Not not post-fill-in-the-blank. Never happened. Never never never never never.
And yet, you will almost surely hear solemn and dire warnings about the expected post-holiday surge in cases this winter.
When you hear that, bear two things in mind.
1) Nobody except me has ever bothered to define what “a surge” means. A “post-holiday surge” is a coordinated increase in daily new COVID-19 cases, above the pre-existing trend, occurring in all or most states, roughly two weeks following the holiday. (That last clause is consistent with the average lag between date of infection and date of case reporting.)
2) Consistent with that, I seem to be the only person who has actually bothered to look at the data, after the fact, to see whether or not a surge actually occurred as predicted. Among the reasons that you’ll never see that in the newspapers is that you have to wait two weeks to see whether or not a surge occurs. That’s far longer than the attention span of the American people and their news media.
The data-driven part of this is not exactly rocket science. U.S. reported COVID-19 cases fall on the holidays because state health departments are closed. Then (most of) the backlog of cases gets reported, and then cases return to their prior trend. Not just once. But over and over, holiday after holiday.
We have never had new COVID-19 cases surge, or jump, or suddenly rise after a holiday, so some level beyond the pre-holiday trend. Never.
Below, you can see that I looked for those post-holiday surges, really hard. Rather than walk you through it, I’ll refer you to many prior posts that go through this in detail for Thanksgiving, Christmas, and most specifically, for the Superbowl.
And Columbus Day. Labor Day. Labor Day again. You get the drift, I hope.
Near as I can tell, all of this “post-holiday surge” nonsense dates back to a single epidemiologist who incorrectly asserted that there had been a huge surge in cases following Canadian Thanksgiving. Why? Because case counts were higher the week after Thanksgiving than the week before it. But a) it takes two weeks for new infections to enter the data and b) that same statement had been true for every week so far that winter, up to that point, in Canada. (Because they were in their winter wave, and cases were increasing week-after-week.)
No matter how obviously stupid and illogical that “surge” conclusion was, that has stuck. And every holiday since, you’ve heard all the talking heads tut-tutting about the dangers of holidays and the inevitable post-holiday surge in new cases.
Accordingly, my favorite post-holiday-surge graphic is this one, suitable for the many Americans who know nothing about Canadian culture:
Stop: Before you read any further, take 30 seconds, study the graph above, and identify when Canadian Thanksgiving occurs, based on the huge surge in cases that occurred two weeks afterwards.
The other graph that gets the point across is this one, where I’ve simply filled in the trend line.
Source: Calculated from NY Times Githib COVID data repository. Thick blue line is the U.S. average.
What we actually get with major holidays, first and foremost, is a steep reduction in reported cases because state governments shut down. And, oddly, we also get small, permanent reductions in actual total cases. Seems as if a lot of people just don’t bother to get tested over a holiday.
This is followed by a return to the prior trend, as all that gets sorted out. What we never get is a surge in cases, above prior trend, two weeks after the holiday.
Finally, if you want to see what a surge actually looks like, try Post #920, Now That’s a Surge. That’s just a summary of the past two decades’ worth of U.S. flu seasons.
If you wonder why we never get a surge, consider how one-sided the pundits’ discussion of the holidays is. Two things happen on major holidays. One, work stops. Or at least, slows down for most of us. Two, families gather. All you ever hear about from the talking heads is the second aspect. But, arguably, the reduced risk from time off work may more-than-offset the increased risk from family gatherings.
2: Massive increase in air travel for the holidays.
Ah, just see Post #939. Here’s the graph of actual TSA passenger screenings at U.S. airports. Spot the huge holiday-related surges, please:
This is the fourth quarter of the year, and the blue line is 2020. The thin wavy line is the actual daily data, and the thicker line is a seven-day moving average. So, yes, there are more airline passengers in the holiday season. But the increase is only about 100,000 per day above the baseline. Against a U.S. population of 330,000,000, any modest rate of infections occurring on those flights is just rounding error. I went through all that arithmetic in Post #939.
3: Predictions of smooth sailing from now on.
So far, official predictions of the course of the pandemic have had poor accuracy. I’m hardly the first person to note that. Or to have shown that with some degree of formality.
In the first year of the pandemic, when you’re still trying to figure things out, that’s forgivable, I guess. But now? When we have more than a year’s worth of experience? When a few simple factors such as indoor relative humidity appear to explain the Southern summer wave and Northern winter wave? When state after state goes right to the point where hospital beds are completely filled, but rarely goes much beyond that?
By now, it seems like we pretty much ought to have a fairly good grip on the likely ups and downs.
Arguably, some of the worst predictions have come from CDC, from the consortium of modelers that they tasked to provide some sort of official prediction. Let me just repeat the last one, which is that there would be no winter wave this year. That prediction was made in September.
Source: Cited just above
These predictions suffer from the same basic problem as “the surge”. Our collective attention span is so short that no news agency can be bothered to look back and check the accuracy of the forecast. And so, assess the forecaster’s history of inaccuracy. Before presenting the next forecast.
As a result, the same forecasters who repeatedly provided poor predictions in the past remain free to provide equally poor predictions going forward. And whenever those predictions match something that somebody wants to hear, you’ll see them in the popular media. And the long track record of being incorrect will just be swept under the rug.
The CDC-organized group that made the projection above, in early September, is slated to redo their projections again in December. Without a doubt, given the CDC imprimatur, whatever they say will be duly reported in the news. And equally without doubt, their incorrect prior predictions will simply be ignored.
4: Florida has fewer cases than fill-in-the-blank now, thus proving fill-in-the-second-blank.
I went through one of these in Post #1319. The current Fox push seemed to be “thus proving that masks don’t work”. I’m sure at some point that second blank will morph into “vaccines”, or maybe “Biden”. Whatever fits the need of the moment.
All of that is aimed at people who are too stupid and lazy to take literally one minute to look at the actual data.
All you have to do is Google “COVID Florida”, and Google will provide you with a graph of new COVID-19 cases in Florida over time. Barring that, Googling “NY Times Florida COVID” will give you a graph of COVID-19 cases in Florida over time. Either of which could then be compared to (say) California. In either case, you’d see that most of the time, Florida has exceeded California in terms of daily new case count.
It’s not as if we lack for ready sources of the data, available with absolutely minimal effort.
It’s just straight up Rule 1 and Rule 2 above:
- Every citizen feels the unalienable right to have a strongly held and firmly expressed opinion.
- Nobody feels even the tiniest obligation to do their homework.
Normally, I would add a third rule:
3: And nobody cares whether or not they are right on the facts.
But Rule 3 is a misstatement. Near as I can tell, it’s far worse: Nobody wants to see facts that might contradict a firmly-held belief. It might make then have to think, and thinking is hard.
And so, as outlined in Post #1319, any set of statistics that varies over time or in a cross-section becomes a ready propaganda tool. Wait until the numbers are leaning your way, add whatever semi-attached figure you wish, and loudly proclaim that the data make your point. When they lean the other way, say nothing. And you can reliably count on the laziness and stupidity of your audience to do the rest.
It’s cheap, simple, and effective. Of course it’s going to be re-used this winter. To stop it, people would have to wise up. And I predict that is unlikely to happen, based on our experience to date.