Opioids in MA, 2017

I am surprised that the death rate from drug overdoses is so high on Cape Cod (Barnstable County). The simplistic reading of the opioid crisis usually associates it with deprivation and poverty; the typical narrative does not particularly associate the crisis with affluent or vacation communities. But Barnstable's age-adjusted opioid death rate of 53.8/100,000 puts it at about 2.5x the national average
A couple of technical points:
  • To protect individuals' privacy, the CDC does not report counts in counties with low numbers of deaths. The number of deaths in Franklin County and Nantucket County fall below this threshold, hence they are absent from the above map.
  • The rates of almost all causes of deaths vary with age. Age adjustment is a technique that removes the effects of age from crude rates and allows meaningful comparisons between populations of different age profiles. See the CDC's description of the process here.
  • The map shows rates not raw counts. See the wikipedia entry on choropleths for the justification.
So what is causing these high rates of drug overdoses? It is impossible to tell from the CDC data alone. A good first stop for other data that could contribute to a model is the US census. More on that later. The R-code that produces the above map is available in my git repository here.

Opioid deaths: 2017 figures

The day after my earlier post I found that the CDC had released the 2017 files. Here is the updated version of the plot that shows the histories of death rates in the 12 counties with the highest rates. Click to enlarge.

The numbers just keep going up. I know this is a highly selective snapshot (by definition I am looking at the worst hit counties) but the full national picture is sobering. From the CDC's 2017 report:

  • Average rate in 2017 was 10% higher in 2017 than in 2016
  • Amongst the synthetic opioids (e.g. fentanyl and tramadol) the increase was 45%

Opioid deaths: rates or counts?

The CDC have just updated their annual report "Drug Overdose Deaths in the United States, 1999-2017". The average age-adjusted rate in 2017 is almost 22 per 100,000; up 10% on the 2016 figures. Some individual states are well above these numbers: the highest death rates are in West Virginia (58 per 100,000), Ohio (46), Pennsylvania (44) and District of Columbia (44).

What does this look like at the county level? The CDC make the Detailed Mortality Files—on which the above report is based—available through WONDER, the Wide-ranging OnLine Data for Epidemiologic Research. Unfortunately this has not been updated with the 2017 numbers, so a county-level analysis can only go through to 2016.

The counties with the highest death rates are shown below (click to enlarge).

As a New Mexico resident I am not surprised that Rio Arriba is at the top. Its largest town, Española, has been identified as a "drug capital of America" for a decade or more (for example, see this Forbes article from 2009). The West Virginia counties are not surprising either, given the state figures.

But the figures that really shock me are those for the counties in Maryland and Ohio. Yes, the rates are somewhat lower (though still north of 50 per 100,000) but the populations of these counties are much higher than you see in counties in NM and WV. The numbers of deaths in Baltimore, Montgomery, Butler, and Clermont Counties are—to my eyes—startlingly high.

This raises the question of how to measure "worst". Is it death rate (i.e. deaths per 100,000 population), deaths, or some combination? Although the use of rate has a mathematical appeal, I think it carries an inherent assumption that may not be correct. Specifically, that if county A has 10 times the population of county B, the threshold at which local services get overloaded is also 10 times higher in A than it is in B. I suspect (though I don't have evidence for this) that this is not the case and that the threshold in A would be substantially less than 10 times the threshold in B.

Note: The R code for the above plots and a discussion of assumptions is available here.