Coronavirus Disease 2019 (COVID-19) Cases Tracker

This web map is an open source version of the COVID-19 global cases website by Johns Hopkins CSSE. It uses OpenLayers for mapping, Plotly.js for plotting, and Iconify for icons.

UPDATES

Single-country maps are now supported:

As of March 27, 2020 at 6pm EDT, fetch_data.py's count of the United States cases is 697 greater than CSSE's. I checked individual states and created the following table:

County	State	CSSE CSV	CSSE REST
Coffee	Alabama	1	0
Fairbanks North Star	Alaska	11	10
Cleburne	Arkansas	47	46
Dawson	Georgia	3	2
Unassigned	Hawaii	8	6
Bannock	Idaho	3	2
Bingham	Idaho	2	1
Unassigned	Illinois	668	N/A
LaSalle	Illinois	3	0
Logan	Illinois	1	0
Ascension	Louisiana	91	90
Morehouse	Louisiana	3	2
Jackson	Michigan	17	16
Newaygo	Michigan	2	1
Amite	Mississippi	1	0
Houston	Tennessee	3	2
Guadalupe	Texas	9	8
Walker	Texas	3	2
Unassigned	Vermont	8	6
Norfolk	Virginia	9	8
Fairfax City	Virginia	1	0
Unassigned	Washington	69	67
Preston	West Virginia	2	1
Ohio	West Virginia	2	1
Hancock	West Virginia	1	0

Data from the REST API is supposed to be current because their web map directly uses this data for visualization, but some of those numbers are decreasing for some counties in the United States. I have no idea which version to trust more between their daily reports vs. REST data.

Configuration

Create and secure your Bing Maps key at https://www.bingmapsportal.com/
Copy config-example.py to config.py
Set bing_maps_key and bing_maps_referer (your secured URL from step 1)
Set app_url to your covid-19 web map URL
Set use_local_data_only to True if you don't want to fetch remote data and just want to use files in the data folder
Add country names to countries_to_display to save data only for those countries

Data Sources

Main data source: CSSE's time series data and REST API
China: DXY
South Korea: KCDC
Italy: StatisticheCoronavirus
Chile: Minsal

I found CSSE's data unreliable because they keep changing country names and adding duplicate entries with incomplete records. I am trying to clean up their data as much as possible to avoid double counting (e.g., as of March 17, Guam vs. Guam, US and French Guiana vs. French Guiana, France), so there can be some discrepancy between my cleaned up data and their original data.

Data Files

geodata.json: GeoJSON file with case locations and time series data
data.csv: CSV file with the same information in a tabular format

Disclaimer

Data that fetch_data.py collects from various data sources is copyrighted by its original owners. Post-processing of the data by the script may introduce errors and the author is not responsible for any damages caused by using the processed data and the web map.

License

This program is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License for more details.

You should have received a copy of the GNU Affero General Public License along with this program. If not, see <https://www.gnu.org/licenses/>.

ymkjp/covid-19