All my various postings tracking the COVID-19 pandemic through the end of 2022.
The semester is nearly over, so this now hardly matters. But I’m still tracking the cumulative count of COVID-19 cases for the semester, each Friday. Still seeing them at rate of a less than one a day.
Source: Tabulated from William and Mary COVID dashboard, last accessed 12/4/2021.
Early in the pandemic, a small group of epidemiologists recognized that a significant portion of the population would likely refuse vaccination. Those scientists teamed with virologists to develop an alternative way to achieve herd immunity at modest cost. With NIH backing, they used recombinant-DNA technology to create a genetically modified (GMO) version of COVID-19 that was far less lethal, but easier to spread, than the naturally-occurring variants. After extensive testing, they released this new strain of COVID. The new GMO-COVID is now displacing the earlier variant, and thereby reducing mortality and morbidity and hastening the end of the pandemic.
Source: My keister. And why not? Generically speaking, half the nonsense you read on the internet comes from the same place. Continue reading Post #1338: Embrace Omicron?
Today’s data provided a surprise. Where to start? We just had a second day in a row showing a huge increase in the seven-day moving average of daily new COVID-19 cases per capita.
Do I really want to make anything out of that? Upon reflection, I think I do. One maxim of data analysis is that new information comes in the true surprises. Today’s figure was quite a surprise. The only question is whether it’s true, or merely an artifact of holiday data reporting.
Data source for this and other graphs of new case counts: Calculated from The New York Times. (2021). Coronavirus (Covid-19) Data in the United States. Retrieved 12/4/2021, from https://github.com/nytimes/covid-19-data.” The NY Times U.S. tracking page may be found at https://www.nytimes.com/interactive/2020/us/coronavirus-us-cases.html.
First, I didn’t expect that, based on last year’s behavior. Last Thanksgiving, the seven-day moving average data had more-or-less returned to trend by this time. And this year, because the just-prior trend was flat-ish, I didn’t expect to see a big jump in the data reported today.
Second, when I line up the first and second pandemic years in their entirety, by eye, there’s now a neat parallel between the two Thanksgiving regions. As if we’re now going to see a trend, moving forward, that’s similar to what we saw last year. As if history is going to repeat itself. Which is more-or-less what I expected, early on, given that the balance between COVID-19 infectiousness and population immunity is about where it was last year.
Third, that view is kind-of consistent with the weather. Viewed this way, the lag (or horizontal gap) between last year’s winter wave and this year’s winter wave stands at just over three weeks. Which is just at the outside of what I might have guessed, based on the much warmer weather we had this year, compared to last year. (I went through all of that in Post #1315, where I came up with a figure of two weeks. Winter is two weeks later this year, compared to last year, in the key Mountain and Midwest regions that led last year’s winter wave).
October of last year, and October of this year, from NOAA. Blue is cold, red is hot. (The November map for this year isn’t out yet.)
And speaking of weather, do you recall the ID/MT/WY anomaly from prior posts? Those states were at the forefront of last year’s winter wave. But this year, they form a sort of “hole” in the tier of states abutting Canada, in terms of new COVID-19 cases.
Turns out, it’s been unseasonably warm in that part of the country. As in, postpone-the-skiing-season warm. As in — as of yesterday — record-high-tempertures warm. Plausibly, their winter wave hasn’t really started this year because their winter hasn’t really started.
But, surely some portion of the jump is an artifact of data reporting over the Thanksgiving holiday. And that might be significantly different from last year, because the quality of data reporting deteriorated. The majority of states no longer report new data on the weekends. As of June 2021, I was complaining about it (Post #1171). As of July 2021, I had modified my data processing to “gap fill” the missing weekend data.
Sounds good, but in fact, the “deteriorated quality of data reporting” argument goes in the opposite direction. This last data point is the seven-day average of data reported from Saturday 11/27/2021 through Friday 12/3/2021. Last year, most states would have reported fresh data on that Saturday, and so caught up with their backlogs. This year, more states will have skipped Saturday reporting. For those, we’re still waiting for the full catch-up to have occurred on the following Monday.
In other words, the deterioration of data reporting means that states will “smear” the catch-up cases over a longer time period. It means that we haven’t seen the full extent of those catch-up cases yet.
Finally, it would be a heck of a coincidence if a true pickup in the trend just happened to occur at the same time as these Thanksgiving data reporting anomalies. To be clear, for sure, this isn’t due to people who were infected over Thanksgiving. Those new cases — if any — will show up some time next week, owing to the roughly two-week interval between the time infection occurs and those new cases are fully reported in the seven-day-moving-average data.
As I noted in earlier posts, there’s a lot less discretion in the hospitalization data than in the reported-cases data. You might defer a test or even fail to get a test if you’re only slightly sick. States can defer reporting of new cases. But if you’re sick enough to require hospitalization, chances are pretty good that you’re going to get hospitalized, holiday weekend or not.
The CDC hospitalization data show rising rates of new COVID-19 hospitalizations through 12/2/2021.
Source: CDC COVID data tracker accessed 12/4/2021.
Finally, if this is some broad national trend, then I can filter out the data reporting noise by focusing on those states that appear to report true numbers every day. Based on the last seven days, the following states appeared to report “true” data last Saturday and Sunday: NY, PA, OH, NJ, AZ, MD, AL, AR, HI, DE, ND.
Here’s the seven-day moving average data for those states, where you should focus on the end point, not necessarily the trend lines. With the exception of the two southernmost states (AL, HI), I’d say that the trend is up across-the-board.
The ambiguity isn’t going to resolve fully until next week.
But as of this moment, I’d say that maybe the U.S. winter wave has finally started in earnest. That’s based on the — oh, call it a week or two’s worth of normal new case growth — that showed up in the data today.
If so, the winter wave is a little over three weeks behind last year’s wave. That’s at the outer edge of what you could justify based on this year’s warmer weather, compared to last year. It’s also plausible that unseasonably warm weather explains the lack of new case growth in the ID/MT/WY area.
What can I say? Things are only perfectly clear in hindsight. If then. Today’s number was a big surprise that I can’t quite seem to wish away as an artifact of data reporting. And so, when the facts change, I change my mind.
We’ll know more next week.
Today there’s a big jump in the seven-day moving average of U.S. new COVID-19 cases per 100,000 per day. But I don’t think it signals any fundamental change. I think it’s mostly an artifact of this year’s holiday data reporting.
Details follow.
I’m just marking time in this post. The situation isn’t greatly different from the way things stood yesterday. It still doesn’t look like we’re going to have much of a winter wave, for the U.S. as a whole.
Arguably the most interesting thing happening right now is the lack of new cases in ID, MT, WY. Continue reading Post #1335: COVID-19 trend to 12/1/2021
New case counts continued to rebound from the Thanksgiving low. Continue reading Post #1334: COVID-19 trend to 11/30/2021
Today we get an initial look at the post-Thanksgiving trend in daily new COVID-19 cases. So far, this seems to be shaping up for a much milder winter wave than last year.
And, as a bonus, I’ll add that if Omicron follows the path set by Delta, it’ll be too late to contribute to this year’s winter wave. If the U.S. sees its first few cases of omicron today, and if omicron spreads at about the same rate that delta spread, it will be mid-March 2022 before Omicron is the dominant strain in the U.S.
Lot of “ifs” in that last sentence, but that’s the best estimate I can come up with at the moment. Continue reading Post #1333: COVID-19 trend post-Thanksgiving
You read a lot of hype every time a new variant of COVID-19 is discovered.
Stories on COVID-19 variants are a nearly-ideal source of click-bait. They combine a high fear content, a broad target audience, and a near-infinite repeatability. The virus has an almost unlimited ability to spawn variants, and each one has the potential to do any number of scary things (avoid your immune system, avoid current vaccines, spread rapidly, and so on). Report on some scientist talking about that potential, and you’re done. Eyeballs captured.
These days, stories on COVID-19 variants rank right up there with school bus crashes and mass-murder events involving children as the lowest common denominator of fear-based journalism.
And yet … well, yeah, Delta.
And Alpha. Everybody forgets about Alpha (a.k.a. the British variant) because it got its butt kicked so swiftly by vaccination. And Delta. But in its day, it was a threat to be reckoned with. If the virus had stopped at Alpha, we’d be done by now.
Press reporting on COVID-19 variants is one of those ugly situations where almost all the information is irrelevant. But some isn’t. How do you filter out the signal from the noise?
Short answer: Transmissibility, a.k.a. “R-nought”, a measure of how readiliy the mutated virus can spread. That’s the minimum screen for filtering out the noise from the potentially relevant.
Why? The way that a new variant takes over is by “out-competing” its rivals. For that, it doesn’t matter how deadly it is, or how sick it makes you. All that matters is that it can spread more effectively. If it can, it will eventually become the dominant strain. If it can’t, it won’t.
The reason the Alpha (British) strain took over from the original (Wuhan or native) strain was that it was more transmissible. The reason Delta took over from Alpha was the same.
Like so, from this seemingly-plausible reference, where R0 = “R-nought”:
Professor Cheng said last year's Wuhan strain had an R0 value of around 2.5, the Alpha strain was about 3.75 and the Delta strain was about 5. That means if we were living life like we were in 2019, one person with the Delta strain would likely infect five other people, compared to just 2.5 last year.
As a result, until I see those words — “more transmissible” — I just ignore it. Because anything that’s not more transmissible than Delta is not going to displace Delta as the dominant strain. No matter what else it does.
As a result, I rarely talk about new variants. The last time I talked about a new variant was back on June 15 2021. (Post #1160: COVID-19 Delta variant bodes for a 5th U.S. COVID-19 wave. )
This post puts a marker down for the latest variant out of South Africa, currently termed B.1.1.529. This one ticks all my boxes for indicators of being “more transmissible” than the Delta variant. Per popular press reporting, a) it’s spreading rapidly in South Africa, b) the South Africans have ruled out mere chance (e.g., a few super-spreader clusters), c) it’s rapidly displacing Delta as the dominant strain, where it exists, d) it’s spreading rapidly in other countries where it has already spread to, and e) other countries (Israel, Great Britain) are already taking steps to try to contain it or slow its spread.
Anything else you may read about it seems to be speculation, at this point. It may evade current vaccines, evade the immune system, blah blah blah. Sure, it may. And it may not. Nobody knows yet.
There isn’t even an estimate of it’s native transmissibility (its “R-nought”) yet. So nobody has even done the analysis to take a guess as to where it ranks relative to prior strains.
We’re still at that stage where the reporting is confused, and the likely future of this new strain is uncertain. All I can say is that after reading through the reporting this morning, this one seems to be worth watching. Despite the lack of any hard estimate of transmissibility. Despite the small number of cases so far. As with the Delta variant, this one — likely to be given the Greek letter omicron as its designation — is worth keeping your eye on.
This is the last look we’ll have at the trend until next Tuesday, owing to the combination of the Thanksgiving holiday and the subsequent weekend.
As of now, the story remains the same: So far, it’s a slow and mild winter wave for the U.S. as a whole, compared to last year.
For me, beyond that, the only thing to have changed is the reduced rhetoric about massive increases in air travel and the inevitable “surge” (a.k.a., “explosion”) in post-holiday cases. That seems largely lacking this year, compared to last.
Plausibly, our experts have learned from last year. Equally plausibly, nobody cares any more. Either way, as with (e.g.) the monthly count of U.S. military personnel killed in Afghanistan, the lack of that in the news is something to be thankful for today.
Data source for this and other graphs of new case counts: Calculated from The New York Times. (2021). Coronavirus (Covid-19) Data in the United States. Retrieved 11/25/2021, from https://github.com/nytimes/covid-19-data.” The NY Times U.S. tracking page may be found at https://www.nytimes.com/interactive/2020/us/coronavirus-us-cases.html.
If we were to compare the regions in turn, only the Northeast is on the same track as last year:
Every other region is on some version of “not as fast”, “not as soon”, or “too early to tell”.
Finally, it looks like holiday air travel has very nearly returned to the pre-pandemic level. Below, gray = 2019, blue = 2021. The chart as aligned so that the day before Thanksgiving is the last day for each year shown.
Prior to Thanksgiving, it looks like air travel was running about half-a-million passengers shy of the 2019 level. But the large uptick in Thanksgiving air travel this year (end of the blue line) brings this past week’s air traffic quite close to the 2019 level.
Source: Calculated from the U.S. Transportation Safety Administration website.
There’s still a low but persistent rate of new COVID-19 cases each week among William and Mary students. It’s under one new case per day, on average.
The last entry below is through the Wednesday before Thanksgiving.
Source: Calculated from the William and Mary COVID-19 dashboard.
