Uses MIT/MEDSL, New York Times, and US Census datasources to analyze per-county COVID-19 deaths.

Overview

Covid County

Executive summary

Deaths per-100k

Total deaths

Setup

Install miniconda, then in the command line, run

conda create -n covid-county
conda activate covid-county
conda install pandas ipython matplotlib tabulate

(Let me know if you want pure-Python no-Conda instructions via venv.)

2020 US presidential election

I've already downloaded countypres_2000-2020.csv from https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/VOQCHQ but you can download it again to ensure I haven't committed bad data.

2020 data is missing counts for District of Columbia (FIPS 11001)? Party split taken from 2016 election.

Census

From https://www.census.gov/programs-surveys/popest/technical-documentation/research/evaluation-estimates/2020-evaluation-estimates/2010s-counties-total.html I downloaded co-est2020.csv from the "Annual Resident Population Estimates for States and Counties: April 1, 2010 to July 1, 2019; April 1, 2020; and July 1, 2020 (CO-EST2020)" link. It's committed in this repo but you can download it yourself too.

Covid

Install Git and run this in this directory: git clone --depth 1 https://github.com/nytimes/covid-19-data.git (it might take a while)

Note five boroughs of NYC are combined into a single "county". This is taken into account by merging the 2020 Presidential votes from all five boroughs into a single county (since we can't split the Covid deaths into individual boroughs, this is the best we can do). Fix follows the recommendation per upstream issue 105.

Run

python main.py

(Takes ~45 seconds on my 2015-vintage laptop.)

More results

party bin total Covid-19 deaths
Rep 80+% 38284
Rep 60–79% 211416
Rep 50–59% 123587
Dem 50–59% 196084
Dem 60–79% 210070
Dem 80+% 18331
unknown 5243

Simply by party:

  • Dem: 424485
  • Rep: 373287
Owner
Ahmed Fasih
Full-stack & quantitative dev—not a banker 👟. He/him || they/them.
Ahmed Fasih
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