Coronavirus corrections, data sources, and issues.

This post is by Phil Price, not Andrew.

I’ve got a backlog of COVID-related stuff I’ve been meaning to post. I had intended to do a separate post about each of these, complete with citations and documentations, but the weeks are flying by and I’ve got to admit that that’s not going to happen. So you get this instead.

1. Alert the media: I made a mistake! Alex Gamma pointed out (a month and a half ago!) that I made a mistake in my plots of Years of Life Lost to coronavirus: I switched the labels of men and women. Alex wonders if the fact that this went unnoticed by me, or the dozens of commenters, is a reflection of people being used to the idea that women have it harder than men in just about everything, so seeing women supposedly being hit harder by COVID didn’t draw scrutiny. I don’t think that’s it — for one thing, we’re used to the fact that women live longer than men, so I think Alex’s proposal doesn’t fit here — but anyway I want to correct the record: there are more deaths, and more years of life lost, among men than among women.

2. Also in the “years of life lost” department, Konrad pointed out that in early May The Economist displayed some data showing the number of victims by age group, along with number of long-term health conditions, and years of life lost. There’s a lot of information in that graphic and I really appreciate the work that went into it. I wonder if there is some better way to display that information.

3. If you want to take a look at issues like the ones discussed above: Daniel Lakeland points out that number of COVID-19 deaths by sex, age group, and state is available from the US Department of Health. They’ve made some odd and slightly irritating choices in that datafile, e.g. the age groups aren’t all numeric (not even the first part of the string): there’s an “Under 1 year”. Why not 0-1, following the same pattern as the other age groups? Just adds one more pre-processing step if you want to do something like map these to actuarial tables. Speaking of which: expected years of life remaining, as a function of age and sex, is available from the Social Security Administration.

4. One issue I hope someone will take a look at — this means you! — is whether and how the distribution of deaths (and thus years of life lost) has changed with time. Daniel Lakeland suggested that we might expect this to change as the pandemic progresses, as vulnerable populations are better protected. One might expect that we will see fewer deaths per case, but with a lower percentage of deaths being those of the very old. Is this in fact happening?

This post is by Phil.

8 thoughts on “Coronavirus corrections, data sources, and issues.

  1. >One might expect that we will see fewer deaths per case, but with a lower percentage of deaths being those of the very old. Is this in fact happening?<

    Judging by this interactive graph for hospitalizations, that would probably be the case:

    https://gis.cdc.gov/grasp/COVIDNet/COVID19_3.html

    Select the data 'display by weekly' drop-down, not cumulatively. There is a legend on the right to select a particular age group, but then you need to double-click the graph to get the scale right. I find this graph very informative and shows the good news overall.

    If you want to see the deaths, the data can be downloaded here:
    https://www.cdc.gov/nchs/nvss/vsrr/covid19/index.htm

    Again, it's gone down overall with only about a tenth of people dying these weeks compared to the peak, but not in all states. Looks like they back-date some deaths (I have seen different numbers from what was reported a few weeks ago).

    • Deaths and hospitalizations lag though, the country bottomed out in terms of new cases in June, it wasn’t until the 2nd half of June that cases really started to take off again, and the COVIDNet data is through July 11th, it is unlikely to reflect the giant increase in cases that has occurred this month.

      • Hmmm… but in TX and AZ (two of the states largely driving the current increase in deaths) hospitalizations were already rising sharply by mid-June. I And hospitalizations should lag cases.

        I agree we aren’t quite at the “peak” of the deaths curve for the Southwest but we are probably not that far off…

        There are other states earlier in their curve (Arkansas, South Carolina, maybe Georgia, Kansas, and North Dakota, etc.), but they probably won’t impact the US-wide numbers nearly as much since their populations are overall smaller. TX/AZ/CA/FL which are high right now are together about 30% of US population.

    • Another counterintuitive consequence of my comment below is that successfully protecting the elderly means the elderly who do die will be the oldest/frailest, and they will die over a longer period of time, thus skewing the average age at death of COVID higher.

      • Of course, I’m not claiming that’s happening–the size of this effect could be negligible. Just something to account for in modeling.

  2. “Daniel Lakeland suggested that we might expect [years of life lost] to change as the pandemic progresses…”

    Yep.

    “…as vulnerable populations are better protected.”

    Maybe. But, counterintuitively, we should expect the same even if we fail to protect them: after the oldest of the old die of COVID, additional COVID deaths among the elderly will have a smaller impact on years of life lost, both because the elderly who die of COVID later will be younger overall, and because there will be fewer elderly alive to die of COVID. So age at COVID death among the elderly falls, and the proportion of all COVID deaths that are elderly falls. So average years lost due to COVID falls for the total population, even as the COVID death rate stays the same among the (unprotected) elderly.

    Averages, amiright?

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