{{ chosen_domain == 'US' ? 'USA' : chosen_domain == 'Intl' ? 'International' : 'Local' }} COVID-19 Live Chart API

Showing {{ chosen_top }} {{ chosen_domain == 'US' ? 'states' : chosen_domain == 'Intl' ? 'countries outside China' : 'localities in ' + chosen_domain }} with highest numbers. Compare other countries, states, and counties by searching below. Click on the colored squares to focus on a locality. Hover on points for specific numbers. Data are from coronadatascraper.com Johns Hopkins CSSE. Print the chart.

Customized charts are directly linkable by URL. URL parameters can be edited directly, or in the form below.

Domain: (US/Intl)
Series: (confirmed/deaths)
Stat: (totals/daily/7day/growth)
Scale: (linear/log10)
Norm: (none/first/pop)
Start: (>=num, or m/d/y)
Top: (integer)
Include: (';' between states)
Select: (';' between states)
Theme: (white/dark/paper)
Ratio: (3/4, or octave...)
Advanced: (1 or 0)
Bare: (1 or 0)
Bare chart embed code:

For policymakers, the chart can compare exponental growth of coronavirus cases on a log scale, or visualize the exponential trends directly on a log-log scale. Both these reval the similarities of epidemic in differnt parts of the world, and give a sense for whether specific local policies are succeding at decreasing exponential spread of the virus. Plots can be normalized by population, so you can compare your small county to New York or S Korea.

For doctors who must deal with the patients who walk into the ER and who who lie sick in ICU beds, the linear view of day-to-day changes is more appropriate. To see these plots, switch to the 'delta linear' view in the current month. The spikes show why the panic is justified, and why minor policy changes have massive ramifications.

The graph you make will automatically update every day based on current data. Please share. And please isolate.

I made this plot to help my physician wife see summaries of US COVID-19 stats that are not being graphed in the press. The logarithmic view is inspired by the FT COVID-19 plot by John Burn-Murdoch. And the log-log view is adopted from the Minute Physics plot by Aatish Bhatia and Henry Reich. This is an easy-to-modify HTML page (using chartist.js, vue.js, lodash.js); pull requests are welcome.

⮕{{ chosen_advanced == 1 ? 'Close' : 'Open' }} advanced mode. Blog post. Code on github. Open source. (MIT license.) Thanks to the support of MIT Quest. Seeking Vue.js+D3 people to help improve this resource.

- David Bau