C-19: State-level Cases, Deaths, Rates

Today, let’s drill down for some perspective…
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First, as oft-reported, NY & NJ lead the list for total deaths … the 2 states represent about 30% of the US total.

The Top 10 states account for 2/3’s of the US total.

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Let’s dig deeper…

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Per capita deaths

As logically to be expected, several big states have the highest death tallies … a function of their death rates and their population.

Adjusting for population:

  • NY & NJ still top the list … MA & CT are the only other states with deaths per million over 1,000.
  • Rhode Island, D.C. and Delaware aren’t in the top 10 with the highest death totals … but they are in the top 10 with highest per capita death totals.

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Total Cases

Much recent attention has been focused on new confirmed cases.

  • 3 Sun Belt states (CA, FL, TX) top the list in confirmed cases … and, their numbers keep growing
  • NY is still #4 on the list despite their restricted testing when only people with severe symptoms were being tested (and possibly confirmed … that is, asymptomatic persons didn’t qualify for testing.

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Deaths-to-cases Ratio

The ratio of deaths to confirmed cases is substantially higher in NY (8.5%) and NJ (7.4%) than it is in CA (1.8%), TX (1.6%) and FL (1.5%).

A likely explanation: Many of the cases being confirmed today are persons with no or mild symptoms who weren’t being tested (and confirmed) in NY & NJ.

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Takeaways:

  • Fixating on on total deaths by state limits perspective … and obscures some important situations, e.g. the high per capita death rates in RI, DC and DE.
  • The current haphazard testing scheme muddies the water … and makes it difficult to draw firm conclusions and doesn’t provide the data needed to answer many key questions (e.g. what’s the virus’ prevalence rate?).

See: Why is COVID testing still so haphazard?

One Response to “C-19: State-level Cases, Deaths, Rates”

  1. Niki Simoneaux Says:

    I totally agree that deaths per MM is the only real way to track COVID. It is annoying that hasn’t been more broadly accepted since every other measure is misleading because of variables.

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