Delta Surge Update – Demographics Focus 8/13/21

Hospitalization (Arizona)

One question that hasn’t been well addressed in the media (all political bents) is whether the COVID Delta surge was driving hospitalization and who, indeed, was being hospitalized. My thinking is that this is our prime metric of the danger of a COVID surge these days. Here’s a chart showing the Arizona hospitalization numbers by demographic. It’s a bit messy for a couple of reasons: 1) Arizona keeps “catching up” on hospitalization numbers by dumping large count backlogs into a single day. I suspect this is a hard metric to keep up with due to all the hospital systems in the state and their state of enthusiasm (?) about reporting data… 2) I stopped capturing the daily snapshot from AZDHS’ web site sometime in May when the data got really boring and moved to weekly (or so). This means my trends aren’t as granular as before, but they’re still accurate.

Arizona Hospitalization (beds used) Data by Age – AZDHS data, collected by T.N. – 8/13/21

What do we see above? Note that at the left of the chart, the hospitalization by age is fairly random and driven by low numbers and statistics. However, if you can ignore the glitch in the middle, the trend is pretty clear towards the right (the Delta Surge). Hospitalization numbers are clearly trending up (but are still not significantly higher than in May. What does this trend reveal? Surprisingly, the over65 age group is still getting hospitalized at much higher rates than their percentage of the population would indicate. No way to know if these are vaccinated people or not. That’s a big gap in the data. They’re matched in numbers by the much-larger 20-44 age group and followed closely by the 45-54 and 55-64 groups. The under 20 age group remains the least hospitalized. This seems to go against some of the news reports that are indicating that the Delta variant is having more severe outcomes in the youngest cases. That doesn’t seem to be the case right now in Arizona at least.

Below I’m showing the hospitalization numbers for all age demographics. As you can see, the Delta surge (furthest right) has not been surging in the hospitals the same way the earlier two surges did. Keep your eye on this chart as things move forward.

AZ Hospitalization since 4/20 (

Cases – Pima County

In my county (Pima) the Delta surge has resulted in proportionately less cases than in the much-larger Maricopa County. My suspicion is that this is due to the notably higher vaccination rates in Pima County. But again, the big question is which demographics are getting infected during the current surge?

Pima County Cases by Age Demographic – 8/13/21

Again, ignoring the loss of granularity by my moving to weekly data capture, you can see the trending on cases from the lows of May until now. It’s no surprise that the 20-44 age group is leading the case counts. In general, across Arizona, this group is much less likely than older demographics to get vaccinated. Plus, there’s more of them. However, the most interesting part of this chart is that the under 20 group is the next highest increase in cases. This group is largely unvaccinated, but it’s not clear how many of them are between 12 and 20 and how many are under 12. This is an error in data collection “strategy” that’s been a problem throughout COVID. Perhaps no one expected at the start that the under 16 demographic (school age) would be so interesting for this pandemic. The rest of the demographics (more vaccination and older) are barely seeing any case rate uptick since May. So, again, fairly surprising that the youngest demographics are the primary ones getting the Delta variant of COVID. No doubt “breakthrough” cases are happening in vaccinated people, but perhaps they’re not symptomatic enough to get counted. Or maybe there are just very few of them (despite what the headlines would indicate).

I just show Pima County here, but statewide, the trend is similar. At the state level, the case rates in the older demographics are slightly higher than Pima county and the younger demographic case rates are noticeably higher. This, again, is driven by the much higher rates and lower vaccination in huge Maricopa County.


There isn’t much change to death rates during the Delta surge from the low period of May. Deaths are still very low, as you can see from the height of the stacked blue and red bars in the chart below. The only thing that *might* be interesting is that the ratio of deaths in the over65 demographic to deaths in every other demographic is much lower now. Sometimes we see this when deaths are low, but during the two previous surges, this ratio trended between 2.5 and 4. Right now it ranges around 2 or lower. This ratio is the green line in the chart below (and the red bars are “over65” deaths and blue bars are “under65” deaths). What might this mean? Again, I suspect it is the power of the vaccine to limit deaths in the over 65 community. I keep tracking this number and I hope that it doesn’t trend up again.

4 Replies to “Delta Surge Update – Demographics Focus 8/13/21”

  1. Hi Tod, I love your articles and your approach to analysis. While you mention that the size of the various age groups is different and imply that this can have an effect, why not eliminate that effect entirely by using only “per thousand population” stats, e.g. deaths per thousand in the 65+ age group instead of absolute deaths. Without this, what’s the meaning of the ratio of deaths between groups? Say we have a group of 10 and 2 die for 20%. Then we have a group of 100 and 20 die–also 20%. But the ratio is 1:10 which seems pretty meaningless since the death rate is actually the same in both groups. I bet there are lots more deaths from accidents in Toyotas than from Teslas, but there are LOTS more Toyotas out there. Deaths per thousand cars of each make could tell a different story.

    1. Agree, makes more sense to compare using only the death rate “per thousand population” stats. Or “per ten thousand population “
      Otherwise kind of misleading (using just the absolute death #, vaccination rate etc.)

    2. Thanks Barclay… here’s my thoughts on this one analytic… I’m constantly shifting between normalized data and non-normalized data based of off the data story that makes the most sense. Sometimes I show “deaths per 1000 people per day” as a rate, for instance, but I find that this is less relevant to people who aren’t attuned with statistics than “deaths per day”. I’m not happy with the latter because then I can’t compare, say, New York with Rhode Island, but it makes more sense broadly for communication.

      I think that the analytic you’re referring to is one of these… I’m trying to show the ratio of deaths over age 65 to those under 65, this is an interesting metric that could benefit from normalization… but if I do, the ratio becomes too large to be understandable (the number of deaths for over 65 to the population of over 65 is HUGE) and conversely for everyone else it is really tiny. Therefore the ratio is too big to be reasonable in most minds.

      This is a pretty interesting thing to think about… I definitely learned a lot about the divide of when to normalize or when not to from COVID.

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