Facebook
TwitterThis dataset tracks the updates made on the dataset "COVID-19 Cases, Tests, and Deaths by ZIP Code - Historical" as a repository for previous versions of the data and metadata.
Facebook
TwitterODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
License information was derived automatically
A. SUMMARY This dataset contains COVID-19 positive confirmed cases aggregated by several different geographic areas and by day. COVID-19 cases are mapped to the residence of the individual and shown on the date the positive test was collected. In addition, 2016-2020 American Community Survey (ACS) population estimates are included to calculate the cumulative rate per 10,000 residents.
Dataset covers cases going back to 3/2/2020 when testing began. This data may not be immediately available for recently reported cases and data will change to reflect as information becomes available. Data updated daily.
Geographic areas summarized are: 1. Analysis Neighborhoods 2. Census Tracts 3. Census Zip Code Tabulation Areas
B. HOW THE DATASET IS CREATED Addresses from the COVID-19 case data are geocoded by the San Francisco Department of Public Health (SFDPH). Those addresses are spatially joined to the geographic areas. Counts are generated based on the number of address points that match each geographic area for a given date.
The 2016-2020 American Community Survey (ACS) population estimates provided by the Census are used to create a cumulative rate which is equal to ([cumulative count up to that date] / [acs_population]) * 10000) representing the number of total cases per 10,000 residents (as of the specified date).
COVID-19 case data undergo quality assurance and other data verification processes and are continually updated to maximize completeness and accuracy of information. This means data may change for previous days as information is updated.
C. UPDATE PROCESS Geographic analysis is scripted by SFDPH staff and synced to this dataset daily at 05:00 Pacific Time.
D. HOW TO USE THIS DATASET San Francisco population estimates for geographic regions can be found in a view based on the San Francisco Population and Demographic Census dataset. These population estimates are from the 2016-2020 5-year American Community Survey (ACS).
This dataset can be used to track the spread of COVID-19 throughout the city, in a variety of geographic areas. Note that the new cases column in the data represents the number of new cases confirmed in a certain area on the specified day, while the cumulative cases column is the cumulative total of cases in a certain area as of the specified date.
Privacy rules in effect To protect privacy, certain rules are in effect: 1. Any area with a cumulative case count less than 10 are dropped for all days the cumulative count was less than 10. These will be null values. 2. Once an area has a cumulative case count of 10 or greater, that area will have a new row of case data every day following. 3. Cases are dropped altogether for areas where acs_population < 1000 4. Deaths data are not included in this dataset for privacy reasons. The low COVID-19 death rate in San Francisco, along with other publicly available information on deaths, means that deaths data by geography and day is too granular and potentially risky. Read more in our privacy guidelines
Rate suppression in effect where counts lower than 20 Rates are not calculated unless the cumulative case count is greater than or equal to 20. Rates are generally unstable at small numbers, so we avoid calculating them directly. We advise you to apply the same approach as this is best practice in epidemiology.
A note on Census ZIP Code Tabulation Areas (ZCTAs) ZIP Code Tabulation Areas are special boundaries created by the U.S. Census based on ZIP Codes developed by the USPS. They are not, however, the same thing. ZCTAs are areal representations of routes. Read how the Census develops ZCTAs on their website.
Rows included for Citywide case counts Rows are included for the Citywide case counts and incidence rate every day. These Citywide rows can be used for comparisons. Citywide will capture all cases regardless of address quality. While some cases cannot be mapped to sub-areas like Census Tracts, ongoing data quality efforts result in improved mapping on a rolling bases.
Related dataset See the dataset of the most recent cumulative counts for all geographic areas here: https://data.sfgov.org/COVID-19/COVID-19-Cases-and-Deaths-Summarized-by-Geography/tpyr-dvnc
E. CHANGE LOG
Facebook
Twitter
Facebook
TwitterThis dataset has been retired as of February 17, 2023. This dataset will be kept for historical purposes, but will no longer be updated. Similar data are available on the state’s open data portal: https://data.chhs.ca.gov/dataset/covid-19-time-series-metrics-by-county-and-state.
A. DATASET DESCRIPTION This dataset contains COVID-19 positive confirmed cases aggregated by several different geographic areas and by day. COVID-19 cases are mapped to the residence of the individual and shown on the date the positive test was collected. In addition, 2019 American Community Survey (ACS) 5-year population estimates are included to calculate the cumulative rate per 10,000 residents.
Dataset covers cases going back to March 18th, 2020 when the first person in Marin County tested positive for COVID-19. This data may not be immediately available for recently reported cases and data will change to reflect as information becomes available. Data updated daily.
COVID-19 case data undergo quality assurance and other data verification processes and are continually updated to maximize completeness and accuracy of information. This means data may change for previous days as information is updated.
Geographic areas summarized are: 1. City, Town, or Community Area 2. Census Tracts 3. Census ZIP Code Tabulation Areas (ZCTAs)
B. HOW THE DATASET IS CREATED Addresses from the COVID-19 case data are geocoded by Marin County HHS. Those addresses are spatially joined to the geographic areas. Counts are generated based on the number of address points that match each geographic area for a given date.
The 2019 ACS estimates for population provided by the Census are used to create a cumulative rate which is equal to ([cumulative count up to that date] / [acs_population]) * 10000) representing the number of total cases per 10,000 residents (as of the specified date).
C. UPDATE PROCESS Geographic analysis is scripted by Marin HHS staff and synced to this dataset each day.
D. HOW TO USE THIS DATASET This dataset can be used to track the spread of COVID-19 throughout Marin County in a variety of geographic areas. Note that the new cases column in the data represents the number of new cases confirmed in a certain area on the specified day, while the cumulative cases column is the cumulative total of cases in a certain area as of the specified date.
Privacy rules in effect To protect privacy, certain rules are in effect: 1. Any area with a cumulative case count less than 10 are dropped for all days the cumulative count was less than 10. These will be null values. For example if a zip code did not have 10 cumulative cases until June 1, 2020 that location will not be included in the dataset until June 1. 2. Once an area has a cumulative case count of 10 or greater, that area will have a new row of case data every day following. 3. 3. Cases are dropped altogether for areas where acs_population < 1000. Some adjacent geographic areas may be combined until the ACS population exceeds 1,000 to still provide information for these regions.
Note: 14-day case rate or 30-day case rate where the counts are lower than 20 may be unstable. We advise caution in interpreting rates at these small numbers.
A note on Census ZIP Code Tabulation Areas (ZCTAs) ZIP Code Tabulation Areas are special boundaries created by the U.S. Census based on ZIP Codes developed by the USPS. They are not, however, the same thing. ZCTAs are areal representations of routes.
Facebook
TwitterNOTE: This dataset has been retired and marked as historical-only.
Only Chicago residents are included based on the home ZIP Code as provided by the medical provider. If a ZIP was missing or was not valid, it is displayed as "Unknown".
Cases with a positive molecular (PCR) or antigen test are included in this dataset. Cases are counted based on the week the test specimen was collected. For privacy reasons, until a ZIP Code reaches five cumulative cases, both the weekly and cumulative case counts will be blank. Therefore, summing the “Cases - Weekly” column is not a reliable way to determine case totals. Deaths are those that have occurred among cases based on the week of death.
For tests, each test is counted once, based on the week the test specimen was collected. Tests performed prior to 3/1/2020 are not included. Test counts include multiple tests for the same person (a change made on 10/29/2020). PCR and antigen tests reported to Chicago Department of Public Health (CDPH) through electronic lab reporting are included. Electronic lab reporting has taken time to onboard and testing availability has shifted over time, so these counts are likely an underestimate of community infection.
The “Percent Tested Positive” columns are calculated by dividing the number of positive tests by the number of total tests . Because of the data limitations for the Tests columns, such as persons being tested multiple times as a requirement for employment, these percentages may vary in either direction from the actual disease prevalence in the ZIP Code.
All data are provisional and subject to change. Information is updated as additional details are received.
To compare ZIP Codes to Chicago Community Areas, please see http://data.cmap.illinois.gov/opendata/uploads/CKAN/NONCENSUS/ADMINISTRATIVE_POLITICAL_BOUNDARIES/CCAzip.pdf. Both ZIP Codes and Community Areas are also geographic datasets on this data portal.
Data Source: Illinois National Electronic Disease Surveillance System, Cook County Medical Examiner’s Office, Illinois Vital Records, American Community Survey (2018)
Facebook
TwitterThis dataset tracks the updates made on the dataset "COVID-19 Vaccine Progress Dashboard Data by ZIP Code" as a repository for previous versions of the data and metadata.
Facebook
TwitterThis data set provides Bexar County CoVID-19 resident Vaccination information, as well as confirmed positive CoVID-19 cases by zip code, as they appear of the City of San Antonio CoVID-19 Vaccination Dashboard and CoVID-19 Surveillance Dashboard. The data is updated weekly. Features Bexar County Zip Code boundaries that have been clipped to Bexar County, and Geo-Enriched with Census and Esri Demographic Data.The purpose of this data set is to track COVID-19 vaccinations in Bexar County; authored by San Antonio Metro Health Department.Last Updated:**June 22nd, 2021
Facebook
Twitter
Facebook
TwitterDetroit Health Departments COVID-19 Dashboard that tracks cases and deaths over time, demographics, testing, hospital capacity, zip code level information, nursing home cases and deaths, and vaccination breakdowns.
Facebook
TwitterThis dataset tracks the updates made on the dataset "COVID-19 Vaccinations by ZIP Code - Historical" as a repository for previous versions of the data and metadata.
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Archived as of 9/25/2025: The datasets will no longer receive updates but the historical data will continue to be available for download. Note: 11/1/2023: Publication of the COVID data will be delayed because of technical difficulties. Note: 9/20/2023: With the end of the federal emergency and reporting requirements continuing to evolve, the Indiana Department of Health will no longer publish and refresh the COVID-19 datasets after November 15, 2023 - one final dataset publication will continue to be available. Note: 5/10/2023: Due to a technical issue updates are delayed for COVID data. New files will be published as soon as they are available. Note: 3/22/2023: Due to a technical issue updates are delayed for COVID data. New files will be published as soon as they are available. Note: 3/15/2023 test data will be removed from the COVID dashboards and HUB files in recognition of the fact that widespread use of at-home tests and a decrease in lab testing no longer provides an accurate representation of COVID-19 spread. Historical Changes: 1/11/2023: Due to a technical issue updates are delayed for COVID data. New files will be published as soon as they are available. 1/5/2023: Due to a technical issue the COVID datasets were not updated on 1/4/23. Updates will be published as soon as they are available. 9/29/22: Due to a technical difficulty, the weekly COVID datasets were not generated yesterday. They will be updated with current data today - 9/29 - and may result in a temporary discrepancy with the numbers published on the dashboard until the normal weekly refresh resumes 10/5. 9/27/2022: As of 9/28, the Indiana Department of Health (IDOH) is moving to a weekly COVID update for the dashboard and all associated datasets to continue to provide trend data that is applicable and usable for our partners and the public. This is to maintain alignment across the nation as states move to weekly updates. 8/19/2022 - The first and second dose columns are being removed as of 8/22/22 as the Health department has transitioned to reporting on Fully/Partially vaccinated. The final historical file including these columns from 8/19 will continue to be available. 2/10/2022: Data was not published on 2/9/2022 due to a technical issue, but updated data was released 2/10/2022. 10/13/2021: This dataset now includes columns for new and total booster shots administered. Please see the data dictionary for additional details. 08/06/2021: There are updates today to county-level vaccination rates to reflect a correction to records that were assigned to the wrong location based on ZIP code. 06/23/2021: COVID Hub files will no longer be updated on Saturdays. The normal refresh of these files has been changed to Mon-Fri. 06/10/2021: COVID Hub files will no longer be updated on Sundays. The normal refresh of these files has been changed to Mon-Sat. 06/07/2021: Today’s new counts include doses newly reported to the Indiana Department of Health on Saturday and Sunday. 06/03/2021: Individuals are able to update their personal and demographic information during the vaccination registration process. Today’s data reflects changes made by individuals to their race, ethnicity, or county of residence over the course of their vaccination series. 05/06/2021: On Monday 5/3, individuals classified as "Unknown" county of residence were inadvertently converted to "Out of State." These individuals have been corrected in today's dataset. 03/17/2021: This dataset has been updated to include zeros for dates where there is no reported data. 03/11/2021: This dataset has been updated to include totals and newly administered single dose vaccination data.
Facebook
TwitterThis dataset tracks the updates made on the dataset "New York State Statewide COVID-19 Testing by Zip Code (Archived)" as a repository for previous versions of the data and metadata.
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Poisson model of individual- and zip code-level factors associated with receipt of primary COVID-19 vaccination series and booster.
Facebook
TwitterThis dataset tracks the updates made on the dataset "New York State Statewide COVID-19 Admissions by Zip Code (Archived)" as a repository for previous versions of the data and metadata.
Facebook
Twitterhttps://www.usa.gov/government-works/https://www.usa.gov/government-works/
NYC Coronavirus (COVID-19) data
This repository contains data on coronavirus (COVID-19) in New York City (NYC), updated daily. Data are assembled by the NYC Department of Health and Mental Hygiene (DOHMH) Incident Command System for COVID-19 Response (Surveillance and Epidemiology Branch in collaboration with Public Information Office Branch). You can view these data on the Department of Health's website. Note that data are being collected in real-time and are preliminary and subject to change as COVID-19 response continues.
Files summary.csv This file contains summary information, including when the dataset was "cut" - the cut-off date and time for data included in this update.
Estimated hospitalization counts reflect the total number of people ever admitted to a hospital, not currently admitted.
case-hosp-death.csv This file includes daily counts of new confirmed cases, hospitalizations, and deaths.
Cases are by date of diagnosis Hospitalizations are by date of admission Deaths are by date of death Because of delays in reporting, the most recent data may be incomplete. Data shown currently will be updated in the future as new cases, hospitalizations, and deaths are reported.
boro.csv This contains rates of confirmed cases, by NYC borough of residence. Rates are:
Cumulative since the start of the outbreak Age adjusted according to the US 2000 standard population Per 100,000 people in the borough by-age.csv This contains age-specific rates of confirmed cases, hospitalizations, and deaths.
by-sex.csv This contains rates of confirmed cases, hospitalizations, and deaths.
testing.csv This file includes counts of New York City residents with specimens collected for SARS-CoV-2 testing by day, the subsets who tested positive as confirmed COVID-19 cases, were ever hospitalized, and who died, as of the date of extraction from the NYC Health Department's disease surveillance database. For each date of extraction, results for all specimen collection dates are appended to the bottom of the dataset. Lags between specimen collection date and report dates of cases, hospitalizations, and deaths can be assessed by comparing counts for the same specimen collection date across multiple data extract dates.
tests-by-zcta.csv This file includes the cumulative count of New York City residents by ZIP code of residence who:
Were ever tested for COVID-19 (SARS-CoV-2) Tested positive The cumulative counts are as of the date of extraction from the NYC Health Department's disease surveillance database. Technical Notes This section may change as data and documentation are updated.
Estimated number of COVID-19 patients ever hospitalized At this time, NYC DOHMH does not have the ability to robustly quantify the number of people currently admitted to a hospital given intense resource and time constraints on hospital reporting systems. Therefore, we have estimated the number of individuals diagnosed with COVID-19 who have ever been hospitalized by matching the list of key fields from known cases that are reported by laboratories to the NYC DOHMH Bureau of Communicable Disease surveillance database to other sources of hospital admission information. These other sources include:
The NYC DOHMH syndromic surveillance database that tracks daily hospital admissions from all 53 emergency departments across NYC The New York State Department of Health Hospital Emergency Response Data System (HERDS). Rates per 100,000 people Annual citywide, borough-specific, and demographic specific intercensal population estimates from 2018 were developed by NYC DOHMH on the basis of the US Census Bureau’s Population Estimates Program, as of November 2019.
Rates of cases at the borough-level were calculated using direct standardization for age at diagnosis and weighting by the US 2000 standard population.
https://github.com/nychealth/coronavirus-data/blob/master/README.md
Facebook
TwitterA shapefile for mapping data by Modified Zip Code Tabulation Areas (MODZCTA) in NYC, based on the 2010 Census ZCTA shapefile. MODZCTA are being used by the NYC Department of Health & Mental Hygiene (DOHMH) for mapping COVID-19 Data.
Facebook
TwitterThis dataset tracks the updates made on the dataset "COVID-19 Vaccinations by ZIP Code" as a repository for previous versions of the data and metadata.
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Characteristics of individuals completing the primary series.
Facebook
Twitterhttps://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
This dataset contains the results of real-time PCR testing for COVID-19 in Mexico as reported by the [General Directorate of Epidemiology](https://www.gob.mx/salud/documentos/datos-abiertos-152127).
The official, raw dataset is available in the Official Secretary of Epidemiology website: https://www.gob.mx/salud/documentos/datos-abiertos-152127.
You might also want to download the official column descriptors and the variable definitions - e.g. SEXO=1 -> Female; SEXO=2 -> Male; SEXO=99 -> Undisclosed) - in the following [zip file](http://datosabiertos.salud.gob.mx/gobmx/salud/datos_abiertos/diccionario_datos_covid19.zip). I've maintained the original levels as described in the official dataset, unless otherwise specified.
IMPORTANT: This dataset has been maintained since the original data releases, which weren't tabular, but rather consisted of PDF files, often with many/different inconsistencies which had to be resolved carefully and is annotated in the .R script. More later datasets should be more reliable, but earlier there were a lot of things to figure out like e.g. when the official methodology to assign the region of the case was changed to be based on residence rather than origin). I've added more notes on very early data here: https://github.com/marianarf/covid19_mexico_data.
[More official information here](https://datos.gob.mx/busca/dataset/informacion-referente-a-casos-covid-19-en-mexico/resource/e8c7079c-dc2a-4b6e-8035-08042ed37165).
I hope that this data serves to as a base to understand the clinical symptoms 🔬that characterize a COVID-19 positive case from another viral respiratory disease and help expand the knowledge about COVID-19 worldwide.
👩🔬🧑🔬🧪With more models tested, added features and fine-tuning, clinical data could be used to predict a patient with pending COVID-19 results will get a positive or a negative result in two scenarios:
The value of the lab result comes from a RT-PCR, and is stored in RESULTADO, where the original data is encoded 1 = POSITIVE and 2 = NEGATIVE.
The data was gathered using a "sentinel model" that samples 10% of the patients that present a viral respiratory diagnosis to test for COVID-19, and consists of data reported by 475 viral respiratory disease monitoring units (hospitals) named USMER (Unidades Monitoras de Enfermedad Respiratoria Viral) throughout the country in the entire health sector (IMSS, ISSSTE, SEDENA, SEMAR, and others).
Data is first processed with this [this .R script](https://github.com/marianarf/covid19_mexico_analysis/blob/master/notebooks/preprocess.R). The file containing the processed data will be updated daily until. Important: Since the data is updated to Github, assume the data uploaded here isn't the latest version, and instead, load data directly from the 'csv' [in this github repository](https://raw.githubusercontent.com/marianarf/covid19_mexico_analysis/master/mexico_covid19.csv).
'ID_REGISTRO' as well as a (new) unique reference 'id' to remove duplicates.ENTIDAD_UM (the region of the medical unit) but now uses ENTIDAD_RES (the region of residence of the patient).In addition to original features reported, I've included missing regional names and also a field 'DELAY' which corresponds to the lag in the processing lab results (since new data contains records from the previous day, this allows to keep track of this lag).
...
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Characteristics of individuals receiving a booster vaccination.
Facebook
TwitterThis dataset tracks the updates made on the dataset "COVID-19 Cases, Tests, and Deaths by ZIP Code - Historical" as a repository for previous versions of the data and metadata.