Category: COVID through 2022

This is about the rising hospitalization rate of diagnosed COVID-19 cases in Virginia.  It’s about new hospitalizations per newly diagnosed case.

This posting is long enough to require an executive summary.  Briefly.

• Hospitalizations for COVID-19 are concentrated among the elderly.
• The age of Virginia COVID-19 cases has been dropping.
• That trend toward “a young person’s pandemic” sped up rapidly with the onset of COVID-19 vaccination, focused first on vaccinating the elderly.
• And yet, the rate of COVID-19 hospitalization per new case has risen sharply.
• How sharply?  Among the oldest old, half of those newly diagnosed with COVID-19 are now being hospitalized for it.

Why has the hospitalization rate per new COVID-19 case skyrocketed among the oldest old?  My guess is that the un-vaccinated geriatric population has a high fraction of individuals who had difficulty getting the vaccine.  And I’ll bet that’s because a lot of them are living alone, on the margins of living independently.  That population — elderly, living alone, no formal caregiver — is the population that physicians will choose to hospitalize, for safety’s sake, rather than let them try to ride out a moderate illness at home. Continue reading Post #1076: Virginia’s COVID-19 hospitalization rate: Home alone?

The U.S. count of daily new COVID-19 cases rose yesterday. 

That was due, in some part, to a data reporting issue with New York.  New York added about 15,000 excess cases to their COVID-19 case count on 3/24/2021.  (Relative to a recent daily count of about 5,000).  That excess case count was large enough to bump up the national number a bit.

But even without that, the U.S. new case count would have risen slightly.   (Calculated by redoing all the numbers without those 15,000 additional cases). Given that, I’m just leaving those additional NY cases in the file.  It’s just another data reporting “speed bump”.

On any given day, the new COVID case count rises in about half of states, and falls in about half.  But unlike the situation two weeks ago, we’re now starting to see persistent trends by state, not just random noise.  Essentially the entire Northeast is now on a slow upward trend.  The outbreak in Michigan continues unabated.   Florida’s case count seems to have bottomed last week and is now slowly rising.  And so on.  What was random day-to-day variation a few weeks back is now resolving into some persistent state-level trends.

We really are in a race between vaccination and spread of COVID-19.  I think vaccination will win, but it’s far from clear.

If your main focus is on avoiding further economic damage from this pandemic, then, rationally, you should be pushing a pro-vaccination, pro-mask-use, pro-COVID-hygiene agenda.  That’s the agenda that maximizes our chances of avoiding any re imposition of restrictions on commerce.

All you have to do is look to Europe to know that we remain at risk.  Great Britain, France (Paris), Italy, and to some extent Germany have reimposed partial or full shutdowns.

Three factors have helped the U.S. to avoid the same fate, so far:  The luck of timing, the heavy toll the disease has already taken here, and our rapid rate of vaccination. Perturb the current fragile equilibrium and we could easily end up in the same situation Europe is in now.

End of rant.  Graphs follow.

Continue reading Post #1074: COVID-19 trend to 3/24/2021, Michigan outbreak continues, NY reporting issue.

Vaccinated fraction of the elderly rose by 0.4 percentage points from yesterday.  That’s half the rate of the three days prior, and a third the rate of the three weeks prior to that.  I wouldn’t normally track this from day-to-day, but as I noted in Post #1064, when that stops rising, I expect it to stop fairly abruptly.

Source:  US CDC COVID data tracker.

The number of new US new COVID-19 cases per day continues to drift downward.  There’s no consistency across regions or states.  So that’s not a case of stable rates across the states, that’s a case of states with increases just by-chance offsetting states with decreases.

Source for this and subsequent graphs:  Calculated from The New York Times. (2021). Coronavirus (Covid-19) Data in the United States. Retrieved 3/23/2021, from https://github.com/nytimes/covid-19-data.  The NY Times on-line U.S. tracking page may be found at this link.

New York:  New cases rates are rising in nearly all Northeast states except New York.  And they appear to be rising at an oddly uniform and similar rate.  So the Northeast as a whole has a flat trend, consisting of falling new case rates in NY and rising new case rates pretty much everywhere else.

Florida:  Florida has gone from a modest downward trend to flat.  Florida, recall, is one of the states that ought to be showing the effects of the more-infectious U.K. variant.

California:  The long-standing downward trend in California may be flattening out.

Michigan.  Michigan is still a hotspot, with rising case counts.  And note that this is on a log scale, so the they are not just rising, they are rising at an increasing rate, compared to a couple of weeks ago.  Looks like Minnesota has rising counts as well.  Michigan’s increase, recall, is concentrated among high school students and young adults.

It’s worth re-posting that using a natural units (as opposed to log) scale, so you can see the upturn.  Another few days of this and Michigan will be back to where it was at the peak of the U.S. COVID third wave.

South-Central and Mountain:  Posted here just for completeness.

And just as an after thought, Canada.  The U.S. and Canadian experience was eerily parallel through roughly 3/2/2021.  (Except that they didn’t have much of a summer wave, but neither did the cool-climate states of the U.S.).  But now, the Canadian new-case rate is rising, when the U.S. new case rate is flag.

I think the natural assumption is that this is an effect of vaccination.  As of today, they have well under 2% of their population fully vaccinated, versus about 14% of the U.S. population.

 

So maybe having no particular trend is a good thing, in this context.

 

This post is about what I believe to be a new page of information from the CDC regarding COVID-19 variants of concern.  Either the CDC just recently began posting this information, I have managed to miss it earlier.

As of today (3/20/2021), the CDC has an entire page showing the prevalence of COVID-19 variants in the U.S., based on four weeks of data ending 2/13/2021.  Clicking this link will take you to that page.  I think that’s new.  In the past, the CDC would only show a count of cases.  That didn’t tell you the proportion of cases that was attributable to each COVID-19 variant.

The CDC data are useful, but the huge drawback is that they are ancient, in this context.  That’s because the growth rates for these variants are so high.  For example, the U.K. variant was reported to double its share of all new cases every 10 days.  If that were true, and if that were constant, we’ve now seen four doubling times since the mid-point of the CDC data collection period.  And the U.K. variant share would therefore be (2^4 = ) about 16 times higher than the share of cases shown by the CDC.

Compare CDC to Helix

The exact age is important, because I want to try to square the CDC web page with the information I have been tracking from the Helix Corporation.  The Helix data, recall, provide an extremely timely snapshot of incidence of the U.K. variant.  But the sample Helix uses is not a systematic sample of the U.S., and in fact omits many states entirely.

Note that the image below is live-linked to the CDC web page, so while this will read correctly today, it’s not going to read correctly if the CDC updates this.  (But this blog page is pretty much disposable anyway.)

Source:  CDC

As I work my way through that chart, I’m pretty sure that each bar represents two weeks of data.  So that the last bar represents tests taken between 2/14/2021 and 2/27/2021, inclusive.  However, that last bar is provisional data, subject to revision, so the CDC actually used the two bars next to that, combined, for the table of numbers on the right.

Upshot:  Those numbers, in that table, are from tests obtained (collected) on 1/17/2021 to 2/13/2021, inclusive.  And from those, the CDC concluded that the U.K. variant (B.1.1.7) accounted for 2.6% of new cases.

Data sourced from the Helix^® COVID-19 Surveillance Dashboard. Accessed at Helix.com/covid19db on 3/20/2021.

If I take the relevant days from the Helix dashboard , take five dates evenly spanning that range, and average them, I come up with an estimated U.K prevalence of just about 3.7% of new cases.  (But there would be a pretty wide standard error around that.)

Assuming the new CDC data are the gold standard, this means that the Helix dashboard sample overstates the actual prevalence of the U.K. variant by a factor of about 1.4.  (With considerable uncertainty around that figure).  Or, to put that in growth terms, it’s about 5 days “too fast” compared to (what should be) the actual cross-section of the U.S., assuming a 10-day doubling time for the U.K. variant’s share of cases.

Finally, comparing the last two bars on the chart above, by eye, you can see that the B.1.1.7 (U.K.) strain slightly more than doubled its share, during the 14 days that separates the two sampling periods.  That’s just about what you’d expect, based on the doubling period.  And so, the estimate shown in the table above isn’t a one-time fluke, but appears to be consistently replicated across the sampling periods.

The upshot is that, for estimating the current national incidence of the U.K. variant, the Helix data are not an exact match to the newly-published CDC data, but they are close enough.  By relying on that, my timing might be a few days “too fast” compared to the presumed gold-standard CDC.  But you actually get the data out of Helix roughly a month faster than you do out of the CDC.

For example, the Helix data currently show a point estimate for 3/17/2021 of 50% of U.S. cases being the U.K. variant.  (That’s a bit of a one-day outlier, so I’d be temped to knock that back to maybe 47%, by eye.)  By contrast, the midpoint of the provisional data on the CDC web page is 2/20/2021, or almost a month earlier.

But the upshot is that my simple model, which runs a little faster than the Helix data, is probably running just over a week too fast, compared to the (now) gold-standard CDC estimate.  That’s still good enough for the amateur epidemiology that I’ve been doing here.

The comparison of the CDC data and the Helix data by state is a) a lot more ragged, b) a lot of work to do well, and c) probably isn’t going to work out well, due to the skewed coverage of states by the Helix set of COVID-19 test sample.

Both sources agree that incidence of the U.K. variant appears high in Florida.  But, for example, the new CDC data (which actually date to a midpoint of about 1/30/2021) show that New Jersey has (had) a higher incidence than Florida.  By contrast, the Helix data has far too few samples from New Jersey to be able to provide an estimate.

That said, let me do one last quick comparison between the CDC’s U.K. incidence figure for Florida (8.6%, from tests spanning 1/17/2021 to 2/13/2021, inclusive.) If I use the same five-sample-days method with the Helix data, I come up with 8.9%.  Given the standard errors here, that’s pretty much an exact match.  So where Helix has data, the published numbers appear to be a good match to CDC.  Plausibly, that’s because the CDC number in those places is, in fact, based largely on the Helix samples.

Source:  CDC

The current U.S. COVID-19 situation is best characterized as a race between more infectious variants of COVID-19, on the one hand, and COVID-19 vaccination, on the other.  Will we get enough people vaccinated, fast enough, to avoid a fourth wave of COVID-19 cases caused by the spread of these new, more-infectious variants.

My best guess is that vaccination will win (Post #1051).  For what that’s worth.  And you can find formally-trained epidemiologists that share that opinion.

But there’s still plenty of opportunity to pull defeat from the jaws of victory.  The situation is not helped by the states that are actively reducing COVID-19 hygiene.

I need to do a separate posting on the most common new variants in the U.S., because the U.S. CDC has greatly expanded the information they now provide.  (Or I was just too dumb to find it earlier.)

With that as context, I guess it’s no surprise that any sense of a nation-wide trend in cases is completely gone at this point.  The regions are going their own separate ways within the country, and the states are (largely) going their own separate ways within the regions.

And so, while the daily new case count continues to drift downward, that in no sense reflects any common trend across states.  It’s just that, at present, states with falling case counts more-than-offset states with rising case counts.   In that sort of situation, that could turn around any day, just by chance.

Details follow. Continue reading Post #1066: Trends to 3/19/2021: MI & MN, AZ & NV, CA