New Interface
Below, I lay out the narrative for the by-cause-and-jurisdiction excess mortality graphs available at https://www.covid-excess-mortality.net/
Here, a screenshot of a new interface I’m prototyping, that attempts to marry the use of surveillance algorithms with basic excess estimates. Feedback welcome! https://covid-dash-py.herokuapp.com/
2020 Interface
This app has been featured on KHOU’s pandemic coverage: https://twitter.com/KHOU/status/1446477984169439235
Use the app here: https://www.covid-excess-mortality.net/
Quick Overview
- The CDC’s National Center for Health Statistics has been publishing granular historical mortality data relevant to COVID-19
- There appears to be an undercount of US deaths caused by the pandemic.
Recent JAMA articles
- COVID-19 may be the Leading Cause of Death in US (Dec. 17)
- COVID-19 deaths in mauy be undercounted by as much as 60% (Dec. 16)
Visualization
This visualization shows:
- In blue, the average number of deaths attributed to a selected cause(s) of death in a selected state(s), from 2015-19.
- In orange, the number of weekly 2020-21 deaths in excess of that average (again, in that state/s and attributed to that cause/s).
This graph suggests that ~7,100 people in Texas, whose 2020-21 deaths were attributed to Diabetes or Alzheimer’s, would likely not have died but for the pandemic.
This could be read as a failure of infrastructure as hospitals are overwhelmed and people are under unprecedented stress during the COVID depression; or a failure of reporting mechanisms as COVID-related deaths are improperly coded. But in the context of an epidemic that has been fueled by deliberate misinformation, official negligence, and an utter disregard for the lives of anyone who can be opportunistically othered, I read these failures in reporting, prevention, and treatment as related aspects of a general failure of public health bordering on the necropolitical.