For a summary of this Block's Dashboards, Explores & the project on Github click here
This COVID-19 Block consists of LookML models, pre-built dashboards, and explores, built off of data from the Johns Hopkins Center for Systems Science and Engineering (JHU CSSE), the New York Times, the COVID Tracking Project, Definitive Healthcare, the Kaiser Family Foundation, and Italy’s Dipartimento della Protezione Civile. The data that powers the block is currently only available in BigQuery and will work with any Looker instance with an existing BigQuery connection.
Views that pull data from BQ Public Datasets program (details on the data can be found here):
• nyt_data Light modifications to the NYT dataset so that we can merge with other data sources
• covid_combined Combines the JHU and NYT datasets, and houses core calculations at the State level (internationally) and the county level (US Only)
• covid_combined_pdts Stores PDTs built off of covid_combined for calculations looking back in time or comparing aginst other geographies
• italy_province and italy_region Calculates COVID19 metrics based on the data provided by Presidenza del Consiglio dei Ministri - Dipartimento della Protezione Civil
• mobility compares communities' mobility (as measured via anonymized cell phone location data) visiting different types of locations. Data is compared to baseline values computed as the median in the 5‑week period Jan 3 – Feb 6, 2020 by day of the week. Data is updated regularly, but not daily. For more information, we strongly encourage you to read the full documentation.
Views that pull data from datasets we've made available in BigQuery - the ETL for these has not been fully tested, and data should be treated with somewhat less certainty:
• covid_tracking_project Pulls in data from the COVID-19 Tracking project and houses calculations on testing in the US. ** The Covid Tracking Project stopped reporting updates on March 7, 2021. Similiar measures were introduced with open_data_main.**
• open_data_main (New!) Pulls in data from the COVID-19 Open Data project and reports on testing, hospitalizations, and vaccination progress in the US.
• policies_by_state Pulls in data from the Kaiser Family Foundation on policies that states have implemented in response to COVID-19
• hospital_bed_summary Pulls in data from Definitive Healthcare on average hospital bed availability for hospitals within the US
Views that pull data from Mapping / Population tables we've created (based on Census + Wikipedia data):
• country_region Maps countries to global regions
• state_region Maps states to global regions
• population_by_county_state_country Calculated the total estimated population for each geographical region for US counties and International States
• italy_province_stats Population estimates and Area by Italy Province
• italy_region_stats Population estimates and Area by Italy Region
In order to extend the LookML from this block and join it with your own proprietery data sources please use this guide.
Looking at the coronavirus data is like looking at funhouse mirrors. Everything is distorted in some direction or another; some things look much bigger than they really are, others much smaller. - Nate Silver, Twitter
With that in mind, here are some of the articles that have informed our understanding around how to explore, present, and share COVID-19 data.
Ten Considerations Before You Create Another Chart About COVID-19 by Amanda Makulec
Coronavirus Case Counts Are Meaningless* by Nate Silver
Improve Your COVID-19 Cases Map by Jim Herries
Mapping coronavirus, responsibly by Kenneth Field
Checkout our instructions on how to leverage this block with other databases here