Official COVID-19 statistics for San Diego County.

sandiegocounty.gov-covid19-1.1.40. Modified 2020-08-14T18:09:29

Resources

• covid_stats. COVID-19 cases in San Diego County, by sex and age
• covid_jurisdiction. COVID-19 cases by San Diego jurisdiction
• covid_jurisdiction_geo. COVID-19 cases by San Diego jurisdiction, geographic
• covid_zip. COVID-19 cases by zip code
• covid_zip_geo. COVID-19 cases by zip code, geographic

Documentation

Documentation Links

• Documentation Page
• Homepage One of the pages linking to COVID-19 data posted on arcgis.com

Contacts

• Wrangler

Eric Busboom, Civic Knowledge

Forecasts for state and national utilization of hospital beads, ICUs and deaths ventilators

healthdata.org-hospitalizations-1.2.11. Modified 2020-06-22T00:17:43

Resources

• hospitalizations. All utilization estimates for state and the US from the model.

Documentation

This dataset supports a projection of hospital utilization created by IHME The data is presented in an interactive vizualization.

Documentation Links

• Research Report Overview and summary of the model.
• IHME Homepage
• Vizualization Interactive vizualization of the report

Contacts

• Wrangler

Eric Busboom, Civic Knowledge

State and country observations from the Covid Tracking Project

covidtracking.com-covid19-3.1.51. Modified 2020-07-08T04:54:16

Resources

• states. Cumulative cases, deaths, hospitalizations, etc for US states

Documentation

The COVID Tracking Project collects information from 50 US states, the District of Columbia, and 5 other US territories to provide the most comprehensive testing data we can collect for the novel coronavirus, SARS-CoV-2. They attempt to include positive and negative results, pending tests, and total people tested for each state or district currently reporting that data.

A very conprehensive collection of automatically scraped data.

coronadatascraper.com-covid19-1.2.24. Modified 2020-07-08T15:54:25

Resources

• source_tidy. Scraped coronavirus data, with one row for each type of observation.
• source_jhu. Scraped coronavirus data, in format similar to JHU
• source. Scraped coronavirus data, with one row per region per day and one type of observation per column.

Documentation

The Corona Data Scraper scrapes data from a wide variety of sources to produce a dataset with both global scope and regional granularity. See the project page for more details.

Cases, deaths, hospitalizations and other data scraped from the San Diego COunty COVID-19 website.

sandiegodata.org-covid19-1.2.43. Modified 2020-04-27T05:49:38

Resources

• sd_covid_cases. Notebook for creating dataset.

Documentation

This dataset is manually extracted from the daily updates to the San Diego County Coronavirus Disease 2019 (COVID-19) web page. The table on the web page is pulled into a [Google Spreadsheet](<https://docs.google.com/spreadsheets/d/1RkgOAgmZIcq7WdNvxn4dih_-aX6 im3fNd9yrfM1-0Ys/edit?usp=sharing>), and this dataset extracts the Summary tab of the Google spreadsheet.

Caveats

• The County changes the table format ocassionally, often adding columns, to not all variables are available for all dates.
• This dataset does not include the information for age groups that is available in the source tables.
• The cases value for March 14 is created by interpolating ( exponential ) from the values before and after it.

Contacts

• Wrangler

Eric Busboom, Civic Knowledge

COVID 19 cases data from Johns Hopkins, augmented and reformtted

jhu.edu-covid19-2.4.38. Modified 2020-07-08T04:59:37

Resources

• confirmed. Confirmed Non-US cases by date and country
• deaths. Non-US Death cases by date and country
• recovered. Non-US recoveries cases by date and country
• confirmed_us. Confirmed US cases by date and country
• deaths_us. US Death cases by date and country

Documentation

This dataset processed and augments the COVID-19 data provided by Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE). The source data is checked into Github daily. and is collected from a variety of sources.

This data is being manually scraped from the San Diego County Coronavirus update page. The first tab s the summary data, the second is tab uses the IMPORTHTML to get the most recent data, and the remaining tabs are the whole table for a particular date.

Feel free to contact the Data Library for help with using or analyzing this data. Email eric@sandiegodata.org, or call 619 89 7571.

Get the data here: SD Coronavirus Cases

Boundary shapes for San Diego neighborhoods, beats and divisions, with ACS 2019 estimates for populations, by race.

sandiego.gov-police_regions-2.1.2. Modified 2021-02-25T19:08:44

Resources

• pd_beats. Police beats
• pd_divisions. Police Divisions
• pd_neighborhoods. Police Neighborhoods
• beat_demographics. Counts of people in the beat, by race.

Documentation

This package links shapefiles for San Diego police beats to Census tracts and merges in ACS estimates for population, by race, from the 2016 5 year ACS. When a police beat boundry crosses a tract, the tract population is allocated to beats by the proportion of the overlap by area. See the Jupyter notebook that performs the procedure for details.

Pedestrian densities, based on data from San Diego’s CityIQ system, aggregated by city block, day of week and time of day.

sandiegodata.org-pedestrian-blocks-1

Resources

• ped_blocks. Pedestrian density per time by walkway, time of day and day of week
• blocks. Geographic data for San Diego city census blocks

Documentation

This datasets aggregates the cityiq.io-pedestrians-san_diego dataset by census block, time of day and day of week. The time of day is represented as:

Monthly homeless counts for the Gaslamp district in Downtown San Diego

downtownsandiego.org-homeless_count-gaslamp-2

Resources

• gaslamp.

Documentation

Since 2014, the Downtown San Diego Partnership has been conducting monthly counts of the homeless in the Downtown neighborhood. The positions of homeless sleepers are recorded on paper maps, which are compiled into a spreadsheet. The San Diego Regional Data Library is running a project to digitize these paper maps](https://downtown-homelesness.sandiegodata.org/) into geographic datasets.

This dataset covers only the Gaslamp district, from 2014-01-01 to 2018-06-28.