Covidtrends Save

Tracking the growth of COVID-19 Cases worldwide

Project README

What is this?

All Contributors

This is an interactive graph / animation that charts the trajectory of global COVID-19 cases.

The graph plots the number of new confirmed cases in the past week, versus the total number of confirmed cases.

When plotted in this way, exponential growth is displayed as a straight line.

Notice that most countries follow a similar straight line path, indicating that the growth rate is similar across countries. We're all in this together.

Tips: Press Space (or the play button) to Play/Pause. Press +/- keys (or the slider) to see daily changes. Hover over the graph for more info. Drag cursor to zoom into graph, double-click to zoom back out. Use dropdown menus to switch between Confirmed Cases ↔ Deaths, between regions, or between a logarithmic ↔ linear scale. And don't forget to wash your hands!

Credits

This interactive pulls data on COVID-19 provided by Johns Hopkins CSSE and NYTimes. Huge thanks to them for making this invaluable data source publicly available.

Created by Aatish Bhatia in collaboration with Henry Reich.

Created using Plotly.js and Vue.js

Contributors ✨

Thanks goes to these wonderful people (emoji key):


Aatish Bhatia

πŸ’» 🚧

Mustafa "Moose" Paksoy

🚧

Henry Reich

πŸ€”

Patrick Plenefisch

πŸ’»

Ed S

πŸ’» πŸ”§

exclipy

πŸ’»

S Aufrecht

πŸ“–

Nick Young

πŸ’»

Thea Lanherne

πŸ›

Arjo Chakravarty

πŸ’»

Lucy Xu

πŸ’¬

Ben Darfler

πŸ’»

Waldir Pimenta

πŸ‘€

Nikita Kniazev

🎨

Henry

πŸ–‹

Ralf Koller

πŸ’» πŸ‘€ ️️️️♿️

Joachim Neumann

πŸ›

Arkarup Banerjee

πŸ€”

Ann Bybee-Finley

πŸ€”

Connie Sun

🎨

Upasana Roy

πŸ€” 🎨

archiewood

πŸ€”

Reagan Chandramohan

πŸ›

CharsiBabu

πŸ’»

Ricardo Gonçalves

πŸ’»

Berkeley Churchill

πŸ’»

This project follows the all-contributors specification. Contributions of any kind welcome!

Special thanks to Ritwick Ghosh, Nicky Case, Shekhar Bhatia, and Igor Kholopov for their very helpful feedback & suggestions!

Participate and Contribute

If you would like to participate or contribute, please read our Contributor's Guide and Code of Conduct.

License

Code in this repository which is not otherwise licensed is licensed under the MIT License; see LICENSE.txt for complete text.

This repository pulls data from 2019 Novel Coronavirus COVID-19 (2019-nCoV) Data Repository by Johns Hopkins CSSE and New York Times Coronavirus (Covid-19) Data in the United States. Please consult these repositories for terms of use on the data.

Open Source Agenda is not affiliated with "Covidtrends" Project. README Source: aatishb/covidtrends
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