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COVID-19 State Comparison

When I first created the chart in late March, there weren't many resources comparing states by "cases per capita" or by "days of outbreak". My goal was to create a fair comparison among all the states, so we could better isolate factors in each outbreak.

COVID-19 data has been freely provided by the New York Times.

There are two charts:

  1. Line chart - three different parameter choices:
    • Cases/1000 - number of cases per 1000 people in a state population
    • Total cases (log chart) - total number of cases. Log chart is used to better illustrate change in number of cases.
    • New Cases - daily new cases by day of outbreak.
  2. Gapminder chart - measures cases vs. deaths for all states over the first 105 days of outbreak ("date" of "day 1" varies by state). There are a number of parameter and filter choices.
  • Both charts have filter options to quickly see the outbreak in different regions, populations, etc.
  • There are options to save the chart as a PNG file, and "light mode" for a printer-friendly version. WARNING: currently, changing to "light mode" will re-render the chart.

Data sources

  1. State COVID-19 data: New York Times
  2. State population: U.S. Census Bureau
  3. State GDP: Bureau of Economic Analysis (BEA) *Gross domestic product (GDP) by state: All industry total (Millions of current dollars)

License:

You may freely explore and share these charts, but please credit the source: Data is from the New York Times, based on reports from state and local agencies.

Notes:

Day of first case = Day 1. Date of Day 1 may be different for different states. Although Washington and California had isolated cases since January, the first case of US community spread was reported on 2/26/20. Including January would lengthen the days since first case in Washington and California, possibly overstating the effectiveness of their policies.

I am not a health expert or statistician. This is a personal project and should not be cited without additional institutional or scientific research, but I hope it adds a new perspective and encourages data exploration.