USA: Excess mortality for 1790 ICD-10 keys

Age-stratified, based on death certificates and monthly population estimates

Introduction

In order to gain a better understanding of what happened in the USA, I created a new website, which offers a total of 39,452 mortality charts based on

• 20.83 million death certificates

• 1790 ICD-10 keys

• 16 age groups

• 4 mortality variables

Content

• Methods: Information on how the data was sourced and processed

• Instructions: A usage guide for the website

• Charts: A selection of charts that stood out in some way will be presented in another article.

Methods

Data sources

• CDC Mortality Multiple Cause-of-Death Public Use death certificate files 2015-2021, excluding territories files

• Census Bureau Public Use Microdata Sample files 2015-2021

Data processing

• I derive national monthly population estimates for each age group by calculating 12-month moving averages forward and backward.

• The same thing is done to the Puerto Rican estimates which are then subtracted from the national estimates, since I do not include US territories files

• I count the number of occurrences of each ICD-10 key on death certificates for each month and age group of the years 2015-2021

• The number of mentions are divided by the population estimates to yield deaths per 100k

• For each month of the year I calculate the average number of occurrences per 100k in the years 2015-2019

• The number of occurrences per 100k of each diagnostic key in each age group and month is divided by the 2015-2019 averages to yield excess mortality

• For excess deaths per 100k I simply substract the average number of occurrences per 100k in the years 2015-2019 from the number of occurrences per 100k

We end up with 4 variables to be displayed for each age group and diagnostic key:

• total deaths

• deaths per 100k (based on monthly population estimates)

• excess mortality (based on monthly population estimates)

• total number of excess deaths per month (based on monthly population estimates)

I am mainly interested in 2020 and 2021. While what I did here may be a quick and dirty approach to the problem, I still wanted to see what happened in 2019, so the period displayed on the charts begins with January 2019.

Inclusion criteria

To be included, any given combination of ICD-10 diagnostic key and age group needs at least 1 mention every month from January 2015 through December 2021.

There are a total of

• 1790 ICD-10 keys

• 16 age groups (85+, 75-84, 65-74, 55-64, 45-54, 35-44, 25-34, 20-24, 15-19, 10-14, 5-9, 0-4, 0+, 65+, 0-64, 0-24)

included on the website, for a total of 4 x 9,863 = 39,452 charts.

The website

I suck at HTML, CSS and SVG, albeit not as hard as the CDC staff. Pervaers.com is the only website I’ve ever created. Since I tried to solve the problem in less than a day, I had no time to acquire the skills needed to polish the website. It does what it should, but it could surely be improved, especially when it comes to mobile devices. If you are better than I am at these things, I would appreciate your help.

Instructions

On PC

• To pick a diagnostic key you can…

  • pick one from the ICD-10 Key navigation bar button as shown in the screenshot. The dropdown list can be scrolled by using the Mousewheel.

  • press the Previous/Next button above the chart

• Pick an age group from the Age Group dropdown

• Change the variable displayed on the charts via the Mortality Variable dropdown

• Enter a filter expression into the filter input box matching either the ICD-10 key without periods or the first 50 characters of the key’s description according to the WHO. Text entered is interpreted as Regular Expressions. E.g. cardi(ac|tis)

On phones

You cannot scroll the dropdown list via Swiping when using your mobile device, because I’m really bad at CSS. This forces you to enter a filter expression when you are looking for a specific key, matching either the ICD-10 key without periods or the first 50 characters of the key’s description according to the WHO.

Entering a filter expression will both shorten the dropdown list and allow you to cycle through the list much faster when using the buttons.

Charts

Just so you don’t have to go home empty-handed in case the website isn’t for you, here’s an image I like:

Notes

Feel free to tell me your findings in the comment section. I have yet to analyze the data myself.

If you can code HTML/CSS, I would really appreciate your help with allowing users to cycle through the ICD-10 Key dropdown menu by swiping.

You could just edit the source files and send them via email and I’d forever be your fan.