COVID-19 Global Case and Death Data

Global COVID-19 Cases and Deaths Over Time

By Coronavirus (COVID-19) Data Hub [source]

About this dataset

The COVID-19 Global Time Series Case and Death Data is a comprehensive collection of global COVID-19 case and death information recorded over time. This dataset includes data from various sources such as JHU CSSE COVID-19 Data and The New York Times.

The dataset consists of several columns providing detailed information on different aspects of the COVID-19 situation. The COUNTRY_SHORT_NAME column represents the short name of the country where the data is recorded, while the Data_Source column indicates the source from which the data was obtained.

Other important columns include Cases, which denotes the number of COVID-19 cases reported, and Difference, which indicates the difference in case numbers compared to the previous day. Additionally, there are columns such as CONTINENT_NAME, DATA_SOURCE_NAME, COUNTRY_ALPHA_3_CODE, COUNTRY_ALPHA_2_CODE that provide additional details about countries and continents.

Furthermore, this dataset also includes information on deaths related to COVID-19. The column PEOPLE_DEATH_NEW_COUNT shows the number of new deaths reported on a specific date.

To provide more context to the data, certain columns offer demographic details about locations. For instance, Population_Count provides population counts for different areas. Moreover,**FIPS** code is available for provincial/state regions for identification purposes.

It is important to note that this dataset covers both confirmed cases (Case_Type: confirmed) as well as probable cases (Case_Type: probable). These classifications help differentiate between various types of COVID-19 infections.

Overall, this dataset offers a comprehensive picture of global COVID-19 situations by providing accurate and up-to-date information on cases, deaths, demographic details like population count or FIPS code), source references (such as JHU CSSE or NY Times), geographical information (country names coded with ALPHA codes) , etcetera making it useful for researchers studying patterns and trends associated with this pandemic

How to use the dataset

• Understanding the Dataset Structure:

  • The dataset is available in two files: COVID-19 Activity.csv and COVID-19 Cases.csv.
  • Both files contain different columns that provide information about the COVID-19 cases and deaths.
  • Some important columns to look out for are: a. PEOPLE_POSITIVE_CASES_COUNT: The total number of confirmed positive COVID-19 cases. b. COUNTY_NAME: The name of the county where the data is recorded. c. PROVINCE_STATE_NAME: The name of the province or state where the data is recorded. d. REPORT_DATE: The date when the data was reported. e. CONTINENT_NAME: The name of the continent where the data is recorded. f. DATA_SOURCE_NAME: The name of the data source. g. PEOPLE_DEATH_NEW_COUNT: The number of new deaths reported on a specific date. h.COUNTRY_ALPHA_3_CODE :The three-letter alpha code represents country f.Lat,Long :latitude and longitude coordinates represent location i.Country_Region or COUNTRY_SHORT_NAME:The country or region where cases were reported.

• Choosing Relevant Columns: It's important to determine which columns are relevant to your analysis or research question before proceeding with further analysis.

• Exploring Data Patterns: Use various statistical techniques like summarizing statistics, creating visualizations (e.g., bar charts, line graphs), etc., to explore patterns in different variables over time or across regions/countries.

• Filtering Data: You can filter your dataset based on specific criteria using column(s) such as COUNTRY_SHORT_NAME, CONTINENT_NAME, or PROVINCE_STATE_NAME to focus on specific countries, continents, or regions of interest.

• Combining Data: You can combine data from different sources (e.g., COVID-19 cases and deaths) to perform advanced analysis or create insightful visualizations.

• Analyzing Trends: Use the dataset to analyze and identify trends in COVID-19 cases and deaths over time. You can examine factors such as population count, testing count, hospitalization count, etc., to gain deeper insights into the impact of the virus.

• Comparing Countries/Regions: Compare COVID-19

Research Ideas

• Trend Analysis: This dataset can be used to analyze and track the trends of COVID-19 cases and deaths over time. It provides comprehensive global data, allowing researchers and po...

Note: DPH is updating and streamlining the COVID-19 cases, deaths, and testing data. As of 6/27/2022, the data will be published in four tables instead of twelve. The COVID-19 Cases, Deaths, and Tests by Day dataset contains cases and test data by date of sample submission. The death data are by date of death. This dataset is updated daily and contains information back to the beginning of the pandemic. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Cases-Deaths-and-Tests-by-Day/g9vi-2ahj. The COVID-19 State Metrics dataset contains over 93 columns of data. This dataset is updated daily and currently contains information starting June 21, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-State-Level-Data/qmgw-5kp6 . The COVID-19 County Metrics dataset contains 25 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-County-Level-Data/ujiq-dy22 . The COVID-19 Town Metrics dataset contains 16 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Town-Level-Data/icxw-cada . To protect confidentiality, if a town has fewer than 5 cases or positive NAAT tests over the past 7 days, those data will be suppressed. COVID-19 cases, hospitalizations, and associated deaths that have been reported among Connecticut residents. All data in this report are preliminary; data for previous dates will be updated as new reports are received and data errors are corrected. Hospitalization data were collected by the Connecticut Hospital Association and reflect the number of patients currently hospitalized with laboratory-confirmed COVID-19. Deaths reported to the either the Office of the Chief Medical Examiner (OCME) or Department of Public Health (DPH) are included in the daily COVID-19 update. Data on Connecticut deaths were obtained from the Connecticut Deaths Registry maintained by the DPH Office of Vital Records. Cause of death was determined by a death certifier (e.g., physician, APRN, medical examiner) using their best clinical judgment. Additionally, all COVID-19 deaths, including suspected or related, are required to be reported to OCME. On April 4, 2020, CT DPH and OCME released a joint memo to providers and facilities within Connecticut providing guidelines for certifying deaths due to COVID-19 that were consistent with the CDC’s guidelines and a reminder of the required reporting to OCME.25,26 As of July 1, 2021, OCME had reviewed every case reported and performed additional investigation on about one-third of reported deaths to better ascertain if COVID-19 did or did not cause or contribute to the death. Some of these investigations resulted in the OCME performing postmortem swabs for PCR testing on individuals whose deaths were suspected to be due to COVID-19, but antemortem diagnosis was unable to be made.31 The OCME issued or re-issued about 10% of COVID-19 death certificates and, when appropriate, removed COVID-19 from the death certificate. For standardization and tabulation of mortality statistics, written cause of death statements made by the certifiers on death certificates are sent to the National Center for Health Statistics (NCHS) at the CDC which assigns cause of death codes according to the International Causes of Disease 10th Revision (ICD-10) classification system.25,26 COVID-19 deaths in this report are defined as those for which the death certificate has an ICD-10 code of U07.1 as either a primary (underlying) or a contributing cause of death. More information on COVID-19 mortality can be found at the following link: https://portal.ct.gov/DPH/Health-Information-Systems--Reporting/Mortality/Mortality-Statistics Data are reported d

Note: DPH is updating and streamlining the COVID-19 cases, deaths, and testing data. As of 6/27/2022, the data will be published in four tables instead of twelve. The COVID-19 Cases, Deaths, and Tests by Day dataset contains cases and test data by date of sample submission. The death data are by date of death. This dataset is updated daily and contains information back to the beginning of the pandemic. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Cases-Deaths-and-Tests-by-Day/g9vi-2ahj. The COVID-19 State Metrics dataset contains over 93 columns of data. This dataset is updated daily and currently contains information starting June 21, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-State-Level-Data/qmgw-5kp6 . The COVID-19 County Metrics dataset contains 25 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-County-Level-Data/ujiq-dy22 . The COVID-19 Town Metrics dataset contains 16 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Town-Level-Data/icxw-cada . To protect confidentiality, if a town has fewer than 5 cases or positive NAAT tests over the past 7 days, those data will be suppressed. COVID-19 cases and associated deaths that have been reported among Connecticut residents, broken down by gender. All data in this report are preliminary; data for previous dates will be updated as new reports are received and data errors are corrected. Deaths reported to the either the Office of the Chief Medical Examiner (OCME) or Department of Public Health (DPH) are included in the daily COVID-19 update. Data on Connecticut deaths were obtained from the Connecticut Deaths Registry maintained by the DPH Office of Vital Records. Cause of death was determined by a death certifier (e.g., physician, APRN, medical examiner) using their best clinical judgment. Additionally, all COVID-19 deaths, including suspected or related, are required to be reported to OCME. On April 4, 2020, CT DPH and OCME released a joint memo to providers and facilities within Connecticut providing guidelines for certifying deaths due to COVID-19 that were consistent with the CDC’s guidelines and a reminder of the required reporting to OCME.25,26 As of July 1, 2021, OCME had reviewed every case reported and performed additional investigation on about one-third of reported deaths to better ascertain if COVID-19 did or did not cause or contribute to the death. Some of these investigations resulted in the OCME performing postmortem swabs for PCR testing on individuals whose deaths were suspected to be due to COVID-19, but antemortem diagnosis was unable to be made.31 The OCME issued or re-issued about 10% of COVID-19 death certificates and, when appropriate, removed COVID-19 from the death certificate. For standardization and tabulation of mortality statistics, written cause of death statements made by the certifiers on death certificates are sent to the National Center for Health Statistics (NCHS) at the CDC which assigns cause of death codes according to the International Causes of Disease 10th Revision (ICD-10) classification system.25,26 COVID-19 deaths in this report are defined as those for which the death certificate has an ICD-10 code of U07.1 as either a primary (underlying) or a contributing cause of death. More information on COVID-19 mortality can be found at the following link: https://portal.ct.gov/DPH/Health-Information-Systems--Reporting/Mortality/Mortality-Statistics Data are reported daily, with timestamps indicated in the daily briefings posted at: portal.ct.gov/coronavirus. Data are subject to future revision as reporting changes. Starting in Ju

Note: This COVID-19 data set is no longer being updated as of December 1, 2023. Access current COVID-19 data on the CDPH respiratory virus dashboard (https://www.cdph.ca.gov/Programs/CID/DCDC/Pages/Respiratory-Viruses/RespiratoryDashboard.aspx) or in open data format (https://data.chhs.ca.gov/dataset/respiratory-virus-dashboard-metrics).

As of August 17, 2023, data is being updated each Friday.

For death data after December 31, 2022, California uses Provisional Deaths from the Center for Disease Control and Prevention’s National Center for Health Statistics (NCHS) National Vital Statistics System (NVSS). Prior to January 1, 2023, death data was sourced from the COVID-19 registry. The change in data source occurred in July 2023 and was applied retroactively to all 2023 data to provide a consistent source of death data for the year of 2023.

As of May 11, 2023, data on cases, deaths, and testing is being updated each Thursday. Metrics by report date have been removed, but previous versions of files with report date metrics are archived below.

All metrics include people in state and federal prisons, US Immigration and Customs Enforcement facilities, US Marshal detention facilities, and Department of State Hospitals facilities. Members of California's tribal communities are also included.

The "Total Tests" and "Positive Tests" columns show totals based on the collection date. There is a lag between when a specimen is collected and when it is reported in this dataset. As a result, the most recent dates on the table will temporarily show NONE in the "Total Tests" and "Positive Tests" columns. This should not be interpreted as no tests being conducted on these dates. Instead, these values will be updated with the number of tests conducted as data is received.

The New York Times is releasing a series of data files with cumulative counts of coronavirus cases in the United States, at the state and county level, over time. We are compiling this time series data from state and local governments and health departments in an attempt to provide a complete record of the ongoing outbreak.

Since the first reported coronavirus case in Washington State on Jan. 21, 2020, The Times has tracked cases of coronavirus in real time as they were identified after testing. Because of the widespread shortage of testing, however, the data is necessarily limited in the picture it presents of the outbreak.

We have used this data to power our maps and reporting tracking the outbreak, and it is now being made available to the public in response to requests from researchers, scientists and government officials who would like access to the data to better understand the outbreak.

The data begins with the first reported coronavirus case in Washington State on Jan. 21, 2020. We will publish regular updates to the data in this repository.

Read the associated blogpost for a detailed description of how this dataset was prepared; plus extra code for producing animated maps.

Context

The 2019 Novel Coronavirus (COVID-19) continues to spread in countries around the world. This dataset provides daily updated number of reported cases & deaths in Germany on the federal state (Bundesland) and county (Landkreis/Stadtkreis) level. In April 2021 I added a dataset on vaccination progress. In addition, I provide geospatial shape files and general state-level population demographics to aid the analysis.

Content

The dataset consists of thre main csv files: covid_de.csv, demgraphics_de.csv, and covid_de_vaccines.csv. The geospatial shapes are included in the de_state.* files. See the column descriptions below for more detailed information.

• covid_de.csv: COVID-19 cases and deaths which will be updated daily. The original data are being collected by Germany's Robert Koch Institute and can be download through the National Platform for Geographic Data (the latter site also hosts an interactive dashboard). I reshaped and translated the data (using R tidyverse tools) to make it better accessible. This blogpost explains how I prepared the data, and describes how to produces animated maps.

• demographics_de.csv: General Demographic Data about Germany on the federal state level. Those have been downloaded from Germany's Federal Office for Statistics (Statistisches Bundesamt) through their Open Data platform GENESIS. The data reflect the (most recent available) estimates on 2018-12-31. You can find the corresponding table here.

• covid_de_vaccines.csv: In April 2021 I added this file that contains the Covid-19 vaccination progress for Germany as a whole. It details daily doses, broken down cumulatively by manufacturer, as well as the cumulative number of people having received their first and full vaccination. The earliest data are from 2020-12-27.

• de_state.*: Geospatial shape files for Germany's 16 federal states. Downloaded via Germany's Federal Agency for Cartography and Geodesy . Specifically, the shape file was obtained from this link.

Column Description

COVID-19 dataset covid_de.csv:

• state: Name of the German federal state. Germany has 16 federal states. I removed converted special characters from the original data.

• county: The name of the German Landkreis (LK) or Stadtkreis (SK), which correspond roughly to US counties.

• age_group: The COVID-19 data is being reported for 6 age groups: 0-4, 5-14, 15-34, 35-59, 60-79, and above 80 years old. As a shortcut the last category I'm using "80-99", but there might well be persons above 99 years old in this dataset. This column has a few NA entries.

• gender: Reported as male (M) or female (F). This column has a few NA entries.

• date: The calendar date of when a case or death were reported. There might be delays that will be corrected by retroactively assigning cases to earlier dates.

• cases: COVID-19 cases that have been confirmed through laboratory work. This and the following 2 columns are counts per day, not cumulative counts.

• deaths: COVID-19 related deaths.

• recovered: Recovered cases.

Demographic dataset demographics_de.csv:

• state, gender, age_group: same as above. The demographic data is available in higher age resolution, but I have binned it here to match the corresponding age groups in the covid_de.csv file.

• population: Population counts for the respective categories. These numbers reflect the (most recent available) estimates on 2018-12-31.

Vaccination progress dataset covid_de_vaccines.csv:

• date: calendar date of vaccination

• doses, doses_first, doses_second: Daily count of administered doses: total, 1st shot, 2nd shot.

• pfizer_cumul, moderna_cumul, astrazeneca_cumul: Daily cumulative number of administered vaccinations by manufacturer.

• persons_first_cumul, persons_full_cumul: Daily cumulative number of people having received their 1st shot and full vaccination, respectively.

Acknowledgements

All the data have been extracted from open data sources which are being gratefully acknowledged:

• The [Robert ...

Description:

This comprehensive dataset provides global information on both COVID-19 related deaths and vaccinations from January 5, 2020, to August 4, 2024. It consists of two parts: one tracking COVID-19 cases, deaths, and population statistics, and another monitoring vaccination progress worldwide. This dataset allows for an in-depth analysis of the pandemic’s spread, fatality rates, and the effectiveness of vaccination campaigns across various countries and regions.

Researchers and data analysts can use this dataset to study trends, compare countries, and evaluate public health responses throughout the COVID-19 pandemic.

Includes:

CovidDeaths Dataset: Records of total cases, deaths, and population.

CovidVaccinations Dataset: Records of daily vaccination counts and cumulative totals.

Use Cases:

Analyzing death rates relative to confirmed cases. Examining the percentage of population affected by COVID-19. Evaluating vaccination rates and coverage across different regions. This dataset is ideal for data exploration, statistical analysis, and visualizations related to the COVID-19 pandemic.

Note: The cumulative case count for some counties (with small population) is higher than expected due to the inclusion of non-permanent residents in COVID-19 case counts.

Reporting of Aggregate Case and Death Count data was discontinued on May 11, 2023, with the expiration of the COVID-19 public health emergency declaration. Although these data will continue to be publicly available, this dataset will no longer be updated.

Aggregate Data Collection Process Since the beginning of the COVID-19 pandemic, data were reported through a robust process with the following steps:

• Aggregate county-level counts were obtained indirectly, via automated overnight web collection, or directly, via a data submission process.
• If more than one official county data source existed, CDC used a comprehensive data selection process comparing each official county data source to retrieve the highest case and death counts, unless otherwise specified by the state.
• A CDC data team reviewed counts for congruency prior to integration. CDC routinely compiled these data and post the finalized information on COVID Data Tracker.
• Cases and deaths are based on date of report and not on the date of symptom onset. CDC calculates rates in this data by using population estimates provided by the US Census Bureau Population Estimates Program (2019 Vintage).
• COVID-19 aggregate case and death data were organized in a time series that includes cumulative number of cases and deaths as reported by a jurisdiction on a given date. New case and death counts were calculated as the week-to-week change in reported cumulative cases and deaths (i.e., newly reported cases and deaths = cumulative number of cases/deaths reported this week minus the cumulative total reported the week before.

This process was collaborative, with CDC and jurisdictions working together to ensure the accuracy of COVID-19 case and death numbers. County counts provided the most up-to-date numbers on cases and deaths by report date. Throughout data collection, CDC retrospectively updated counts to correct known data quality issues. CDC also worked with jurisdictions after the end of the public health emergency declaration to finalize county data.

• Source: The weekly archived dataset is based on county-level aggregate count data
• Confirmed/Probable Cases/Death breakdown: Cumulative cases and deaths for each county are included. Total reported cases include probable and confirmed cases.
• Time Series Frequency: The weekly archived dataset contains weekly time series data (i.e., one record per week per county)

Important note: The counts reflected during a given time period in this dataset may not match the counts reflected for the same time period in the daily archived dataset noted above. Discrepancies may exist due to differences between county and state COVID-19 case surveillance and reconciliation efforts.

The surveillance case definition for COVID-19, a nationally notifiable disease, was first described in a position statement from the Council for State and Territorial Epidemiologists, which was later revised. However, there is some variation in how jurisdictions implement these case classifications. More information on how CDC collects COVID-19 case surveillance data can be found at FAQ: COVID-19 Data and Surveillance.

Confirmed and Probable Counts In this dataset, counts by jurisdiction are not displayed by confirmed or probable status. Instead, counts of confirmed and probable cases and deaths are included in the Total Cases and Total Deaths columns, when available. Not all jurisdictions report

Archived as of 3/16/22: Due to changing LTC reporting requirements, this dataset will no longer be updated after 3/16/2022. For data on Indiana's long term case facilities, please visit: https://data.cms.gov/covid-19/covid-19-nursing-home-data Number of verified COVID-19 related cases and deaths from Long-Term Care Facilities for residents and staff members. Historical case data are aggregated at the facility-level and are reported from 3/1/2020 and updated weekly. Facilities that are in non-compliance with historical case data reporting needs are denoted by "Facility has not submitted data" in the "Facility Submission Status" column. Facilities listed as non-compliant will be updated as necessary with any new submissions of their historical cases to the Indiana State Department of Health. Cases and deaths in this file include records reported by Long-Term Care Facilities and have been verified by ISDH through a positive COVID-19 diagnostic lab result. This data file was constructed to aggregate verified cases and deaths for LTC staff and residents at the facility level. Because residents and staff may be moved between facilities, calculating total verified counts from this data file is not advised. Users should refer to the ISDH LTC dashboard for total counts.

NOTE: 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.

A. SUMMARY This dataset shows San Francisco COVID-19 deaths by population characteristics. This data may not be immediately available for recently reported deaths. Data updates as more information becomes available. Because of this, death totals may increase or decrease.

Population characteristics are subgroups, or demographic cross-sections, like age, race, or gender. The City tracks how deaths have been distributed among different subgroups. This information can reveal trends and disparities among groups.

B. HOW THE DATASET IS CREATED As of January 1, 2023, COVID-19 deaths are defined as persons who had COVID-19 listed as a cause of death or a significant condition contributing to their death on their death certificate. This definition is in alignment with the California Department of Public Health and the national https://preparedness.cste.org/wp-content/uploads/2022/12/CSTE-Revised-Classification-of-COVID-19-associated-Deaths.Final_.11.22.22.pdf">Council of State and Territorial Epidemiologists. Death certificates are maintained by the California Department of Public Health.

Data on the population characteristics of COVID-19 deaths are from: *Case reports *Medical records *Electronic lab reports *Death certificates

Data are continually updated to maximize completeness of information and reporting on San Francisco COVID-19 deaths.

To protect resident privacy, we summarize COVID-19 data by only one population characteristic at a time. Data are not shown until cumulative citywide deaths reach five or more.

Data notes on select population characteristic types are listed below.

Race/ethnicity * We include all race/ethnicity categories that are collected for COVID-19 cases.

Gender * The City collects information on gender identity using these guidelines.

C. UPDATE PROCESS Updates automatically at 06:30 and 07:30 AM Pacific Time on Wednesday each week.

Dataset will not update on the business day following any federal holiday.

D. HOW TO USE THIS DATASET Population estimates are only available for age groups and race/ethnicity categories. San Francisco population estimates for race/ethnicity and age groups can be found in a dataset based on the San Francisco Population and Demographic Census dataset.These population estimates are from the 2018-2022 5-year American Community Survey (ACS).

This dataset includes several characteristic types. Filter the “Characteristic Type” column to explore a topic area. Then, the “Characteristic Group” column shows each group or category within that topic area and the number of cumulative deaths.

Cumulative deaths are the running total of all San Francisco COVID-19 deaths in that characteristic group up to the date listed.

To explore data on the total number of deaths, use the COVID-19 Deaths Over Time dataset.

E. CHANGE LOG

A. SUMMARY This dataset represents San Francisco COVID-19 related deaths by day. This data may not be immediately available for recently reported deaths. Data updates as more information becomes available. Because of this, death totals for previous days may increase or decrease. More recent data is less reliable.

B. HOW THE DATASET IS CREATED As of January 1, 2023, COVID-19 deaths are defined as persons who had COVID-19 listed as a cause of death or a significant condition contributing to their death on their death certificate. This definition is in alignment with the California Department of Public Health and the national https://preparedness.cste.org/wp-content/uploads/2022/12/CSTE-Revised-Classification-of-COVID-19-associated-Deaths.Final_.11.22.22.pdf">Council of State and Territorial Epidemiologists. Death data is provided by the California Department of Public Health.

It takes time to process this data. Because of this, death totals may increase or decrease over time.

Data are continually updated to maximize completeness of information and reporting on San Francisco COVID-19 deaths.

C. UPDATE PROCESS Updates automatically at 06:30 and 07:30 AM Pacific Time on Wednesday each week.

Dataset will not update on the business day following any federal holiday.

D. HOW TO USE THIS DATASET This dataset shows new deaths and cumulative deaths by date of death. New deaths are the count of deaths on that specific date. Cumulative deaths are the running total of all San Francisco COVID-19 deaths up to the date listed.

Use the Deaths by Population Characteristics Over Time dataset to see deaths by different subgroups including race/ethnicity, age, and gender.

E. CHANGE LOG

• 9/11/2023 – on this date, we began using an updated definition of a COVID-19 death to align with the California Department of Public Health. This change was applied to COVID-19 deaths retrospectively beginning on 1/1/2023. More information about the recommendation by the Council of State and Territorial Epidemiologists that motivated this change can be found https://preparedness.cste.org/wp-content/uploads/2022/12/CSTE-Revised-Classification-of-COVID-19-associated-Deaths.Final_.11.22.22.pdf">here.
• 4/6/2023 - the State implemented system updates to improve the integrity of historical data.
• 1/22/2022 - system updates to improve timeliness and accuracy of cases and deaths data were implemented.

This dataset provides values for CORONAVIRUS DEATHS reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Please see FAQ for latest information on COVID-19 Data Hub data flows: https://covid-19.geohive.ie/pages/helpfaqs.Notice:See the Technical Data Issues section in the FAQ for information about issues in data: https://covid-19.geohive.ie/pages/helpfaqs.Deaths: From 16th May 2022 onwards, reporting of Notified Deaths will be weekly (each Wednesday) with deaths notified since the previous Wednesday reported. This is based on the date on which a death was notified on CIDR, not the date on which the death occurred. Data on deaths by date of death is available on the new HPSC Epidemiology of COVID-19 Data Hub https://epi-covid-19-hpscireland.hub.arcgis.com/.Notice:

Please be advised that on 29th April 2021, the 'Aged65up' and 'HospitalisedAged65up' fields were removed from this table. The three fields 'Aged65to74', 'Aged75to84', and 'Aged85up' replace the 'Aged65up' field.The three fields 'HospitalisedAged65to74', 'HospitalisedAged75to84' and 'HospitalisedAged85up' replace the 'HospitalisedAged65up' field.Please be advised that on the week beginning 1st March 2021, the values in the following fields in this table were set to zero: 'CommunityTransmission' , 'CloseContact', 'TravelAbroad' and ‘ClustersNotified’. ----------------------------------------------------------------------This feature service contains the up to date Covid-19 Daily Statistics as well as the Profile of Covid-19 Daily Statistics for Ireland, as reported by the Health Protection Surveillance Centre.The Covid-19 Daily Statistics are updated once a week, each Wednesday, which includes data for the full time series. Data on deaths is updated once a week, each Wednesday, which includes data for the full time series.The further breakdown of these counts (age, gender, transmission, etc.) is part of a Daily Statistics Profile of Covid-19, to help identify patterns and trends.The primary Date applies to the following fields:ConfirmedCovidCases, TotalConfirmedCovidCases, ConfirmedCovidDeaths, TotalCovidDeaths, ConfirmedCovidRecovered,SevenDayAverageCases.The StatisticProfileDate applies to the following fields:CovidCasesConfirmed, HospitalisedCovidCases, RequiringICUCovidCases, HealthcareWorkersCovidCases,Clusters Notified,HospitalisedAged5,HospitalisedAged5to14,HospitalisedAged15to24,HospitalisedAged25to34,HospitalisedAged35to44,HospitalisedAged45to54,HospitalisedAged55to64,HospitalisedAged65to74,HospitalisedAged75to84,HospitalisedAged85up,Male, Female, Unknown,Aged1to4, Aged5to14, Aged15to24, Aged25to34, Aged35to44, Aged45to54, Aged55to64, Aged65to74,Aged75to84,Aged85up,MedianAgeCommunityTransmission, CloseContact, TravelAbroad, Total Deaths by Date of Death,Deaths by Date of Death.

As of July 2nd, 2024 the COVID-19 Deaths by Population Characteristics Over Time dataset has been retired. This dataset is archived and will no longer update. We will be publishing a cumulative deaths by population characteristics dataset that will update moving forward.

A. SUMMARY This dataset shows San Francisco COVID-19 deaths by population characteristics and by date. This data may not be immediately available for recently reported deaths. Data updates as more information becomes available. Because of this, death totals for previous days may increase or decrease. More recent data is less reliable.

Population characteristics are subgroups, or demographic cross-sections, like age, race, or gender. The City tracks how deaths have been distributed among different subgroups. This information can reveal trends and disparities among groups.

B. HOW THE DATASET IS CREATED As of January 1, 2023, COVID-19 deaths are defined as persons who had COVID-19 listed as a cause of death or a significant condition contributing to their death on their death certificate. This definition is in alignment with the California Department of Public Health and the national https://preparedness.cste.org/wp-content/uploads/2022/12/CSTE-Revised-Classification-of-COVID-19-associated-Deaths.Final_.11.22.22.pdf">Council of State and Territorial Epidemiologists. Death certificates are maintained by the California Department of Public Health.

Data on the population characteristics of COVID-19 deaths are from: *Case reports *Medical records *Electronic lab reports *Death certificates

Data are continually updated to maximize completeness of information and reporting on San Francisco COVID-19 deaths.

To protect resident privacy, we summarize COVID-19 data by only one characteristic at a time. Data are not shown until cumulative citywide deaths reach five or more.

Data notes on each population characteristic type is listed below.

Race/ethnicity * We include all race/ethnicity categories that are collected for COVID-19 cases.

Gender * The City collects information on gender identity using these guidelines.

C. UPDATE PROCESS Updates automatically at 06:30 and 07:30 AM Pacific Time on Wednesday each week.

Dataset will not update on the business day following any federal holiday.

D. HOW TO USE THIS DATASET Population estimates are only available for age groups and race/ethnicity categories. San Francisco population estimates for race/ethnicity and age groups 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 includes many different types of characteristics. Filter the “Characteristic Type” column to explore a topic area. Then, the “Characteristic Group” column shows each group or category within that topic area and the number of deaths on each date.

New deaths are the count of deaths within that characteristic group on that specific date. Cumulative deaths are the running total of all San Francisco COVID-19 deaths in that characteristic group up to the date listed.

This data may not be immediately available for more recent deaths. Data updates as more information becomes available.

To explore data on the total number of deaths, use the COVID-19 Deaths Over Time dataset.

E. CHANGE LOG

• 9/11/2023 - on this date, we began using an updated definition of a COVID-19 death to align with the California Department o

Reporting of Aggregate Case and Death Count data was discontinued on May 11, 2023, with the expiration of the COVID-19 public health emergency declaration. Although these data will continue to be publicly available, this dataset will no longer be updated.

The surveillance case definition for COVID-19, a nationally notifiable disease, was first described in a position statement from the Council for State and Territorial Epidemiologists, which was later revised. However, there is some variation in how jurisdictions implemented these case definitions. More information on how CDC collects COVID-19 case surveillance data can be found at FAQ: COVID-19 Data and Surveillance.

Aggregate Data Collection Process Since the beginning of the COVID-19 pandemic, data were reported from state and local health departments through a robust process with the following steps:

• Aggregate county-level counts were obtained indirectly, via automated overnight web collection, or directly, via a data submission process.
• If more than one official county data source existed, CDC used a comprehensive data selection process comparing each official county data source to retrieve the highest case and death counts, unless otherwise specified by the state.
• A CDC data team reviewed counts for congruency prior to integration and set up alerts to monitor for discrepancies in the data.
• CDC routinely compiled these data and post the finalized information on COVID Data Tracker.
• County level data were aggregated to obtain state- and territory- specific totals.
• Counting of cases and deaths is based on date of report and not on the date of symptom onset. CDC calculates rates in these data by using population estimates provided by the US Census Bureau Population Estimates Program (2019 Vintage).
• COVID-19 aggregate case and death data are organized in a time series that includes cumulative number of cases and deaths as reported by a jurisdiction on a given date. New case and death counts are calculated as the week-to-week change in cumulative counts of cases and deaths reported (i.e., newly reported cases and deaths = cumulative number of cases/deaths reported this week minus the cumulative total reported the prior week.

This process was collaborative, with CDC and jurisdictions working together to ensure the accuracy of COVID-19 case and death numbers. County counts provided the most up-to-date numbers on cases and deaths by report date. Throughout data collection, CDC retrospectively updated counts to correct known data quality issues.

Description This archived public use dataset focuses on the cumulative and weekly case and death rates per 100,000 persons within various sociodemographic factors across all states and their counties. All resulting data are expressed as rates calculated as the number of cases or deaths per 100,000 persons in counties meeting various classification criteria using the US Census Bureau Population Estimates Program (2019 Vintage).

Each county within jurisdictions is classified into multiple categories for each factor. All rates in this dataset are based on classification of counties by the characteristics of their population, not individual-level factors. This applies to each of the available factors observed in this dataset. Specific factors and their corresponding categories are detailed below.

Population-level factors Each unique population factor is detailed below. Please note that the “Classification” column describes each of the 12 factors in the dataset, including a data dict

This dataset reports the daily reported number of deaths involving COVID-19 by fatality type. Learn how the Government of Ontario is helping to keep Ontarians safe during the 2019 Novel Coronavirus outbreak. Effective November 14, 2024 this page will no longer be updated. Information about COVID-19 and other respiratory viruses is available on Public Health Ontario’s interactive respiratory virus tool: https://www.publichealthontario.ca/en/Data-and-Analysis/Infectious-Disease/Respiratory-Virus-Tool Data includes: * Date on which the death occurred * Total number of deaths involving COVID-19 * Number of deaths with “COVID-19 as the underlying cause of death” * Number of deaths with “COVID-19 contributed but not underlying cause” * Number of deaths where the “Cause of death unknown” or “Cause of death missing” ##Additional Notes The method used to count COVID-19 deaths has changed, effective December 1, 2022. Prior to December 1 2022, deaths were counted based on the date the death was updated in the public health unit’s system. Going forward, deaths are counted on the date they occurred. On November 30, 2023 the count of COVID-19 deaths was updated to include missing historical deaths from January 15, 2020 to March 31, 2023. CCM is a dynamic disease reporting system which allows ongoing update to data previously entered. As a result, data extracted from CCM represents a snapshot at the time of extraction and may differ from previous or subsequent results. Public Health Units continually clean up COVID-19 data, correcting for missing or overcounted cases and deaths. These corrections can result in data spikes and current totals being different from previously reported cases and deaths. Observed trends over time should be interpreted with caution for the most recent period due to reporting and/or data entry lags. As of December 1, 2022, data are based on the date on which the death occurred. This reporting method differs from the prior method which is based on net change in COVID-19 deaths reported day over day. Data are based on net change in COVID-19 deaths for which COVID-19 caused the death reported day over day. Deaths are not reported by the date on which death happened as reporting may include deaths that happened on previous dates. Spikes, negative numbers and other data anomalies: Due to ongoing data entry and data quality assurance activities in Case and Contact Management system (CCM) file, Public Health Units continually clean up COVID-19, correcting for missing or overcounted cases and deaths. These corrections can result in data spikes, negative numbers and current totals being different from previously reported case and death counts. Public Health Units report cause of death in the CCM based on information available to them at the time of reporting and in accordance with definitions provided by Public Health Ontario. The medical certificate of death is the official record and the cause of death could be different. Deaths are defined per the outcome field in CCM marked as “Fatal”. Deaths in COVID-19 cases identified as unrelated to COVID-19 are not included in the number of deaths involving COVID-19 reported. "_Cause of death unknown_" is the category of death for COVID-19 positive individuals with cause of death still under investigation, or for which the public health unit was unable to determine cause of death. The category may change later when the cause of death is confirmed either as “COVID-19 as the underlying cause of death”, “COVID-19 contributed but not underlying cause,” or “COVID-19 unrelated”. "_Cause of death missing_" is the category of death for COVID-19 positive individuals with the cause of death missing in CCM. Rates for the most recent days are subject to reporting lags All data reflects totals from 8 p.m. the previous day. This dataset is subject to change.

About Dataset: WHO COVID-19 Global Data

This dataset provides comprehensive information on the global COVID-19 pandemic as reported to the World Health Organization (WHO). The dataset is available in comma-separated values (CSV) format and includes the following fields:

Daily cases and deaths by date reported to WHO: WHO-COVID-19-global-data.csv

• Date_reported (Date): The date of reporting to WHO.
• Country_code (String): The ISO Alpha-2 country code.
• Country (String): The name of the country, territory, or area.
• WHO_region (String): The WHO regional office to which the country belongs. WHO Member States are grouped into six WHO regions, including AFRO (Regional Office for Africa), AMRO (Regional Office for the Americas), SEARO (Regional Office for South-East Asia), EURO (Regional Office for Europe), EMRO (Regional Office for the Eastern Mediterranean), and WPRO (Regional Office for the Western Pacific).
• New_cases (Integer): The number of new confirmed cases reported on a given day. This is calculated by subtracting the previous cumulative case count from the current cumulative case count.
• Cumulative_cases (Integer): The total cumulative confirmed cases reported to WHO up to the specified date.
• New_deaths (Integer): The number of new confirmed deaths reported on a given day. Similar to new cases, this is calculated by subtracting the previous cumulative death count from the current cumulative death count.- Cumulative_deaths (Integer): The total cumulative confirmed deaths reported to WHO up to the specified date.

In addition to the COVID-19 case and death data, this dataset also includes valuable information related to COVID-19 vaccinations. The vaccination data consists of the following fields:

Vaccination Data Fields: vaccination-data.csv

• COUNTRY (String): Country, territory, or area.
• ISO3 (String): ISO Alpha-3 country code.
• WHO_REGION (String): The WHO regional office to which the country belongs.
• DATA_SOURCE (String): Indicates the data source, which can be either "REPORTING" (Data reported by Member States or sourced from official reports) or "OWID" (Data sourced from Our World in Data COVID-19 Vaccinations).
• DATE_UPDATED (Date): Date of the last update.
• TOTAL_VACCINATIONS (Integer): Cumulative total vaccine doses administered.
• PERSONS_VACCINATED_1PLUS_DOSE (Decimal): Cumulative number of persons vaccinated with at least one dose.
• TOTAL_VACCINATIONS_PER100 (Integer): Cumulative total vaccine doses administered per 100 population.
• PERSONS_VACCINATED_1PLUS_DOSE_PER100 (Decimal): Cumulative persons vaccinated with at least one dose per 100 population.
• PERSONS_LAST_DOSE (Integer): Cumulative number of persons vaccinated with a complete primary series.
• PERSONS_LAST_DOSE_PER100 (Decimal): Cumulative number of persons vaccinated with a complete primary series per 100 population.
• VACCINES_USED (String): Combined short name of the vaccine in the format "Company - Product name."
• FIRST_VACCINE_DATE (Date): Date of the first vaccinations, equivalent to the start/launch date of the first vaccine administered in a country.
• NUMBER_VACCINES_TYPES_USED (Integer): Number of vaccine types used per country, territory, or area.
• PERSONS_BOOSTER_ADD_DOSE (Integer): Cumulative number of persons vaccinated with at least one booster or additional dose.
• PERSONS_BOOSTER_ADD_DOSE_PER100 (Decimal): Cumulative number of persons vaccinated with at least one booster or additional dose per 100 population.

In addition to the vaccination data, a separate dataset containing vaccination metadata is available, including information about vaccine names, product names, company names, authorization dates, start and end dates of vaccine rollout, and more.

Vaccination metadata Fields: vaccination-metadata.csv

• ISO3 (String): ISO Alpha-3 country code
• VACCINE_NAME (String): Combined short name of vaccine: "Company - Product name" (see below)
• PRODUCT_NAME (String): Name or label of vaccine product, or type of vaccine (if unnamed).
• COMPANY_NAME (String): Marketing authorization holder of vaccine product.
• FIRST_VACCINE_DATE (Date): Date of first vaccinations. Equivalent to start/launch date of the first vaccine administered in a country.
• AUTHORIZATION_DATE (Date): Date vaccine product was authorized for use in the country, territory, area.
• START_DATE (Date): Start/launch date of vaccination with vaccine type (excludes vaccinations during clinical trials).
• END_DATE (Date): End date of vaccine rollout
• COMMENT (String): Comments related to vaccine rollout
• DATA_SOURCE (String): Indicates data source - REPORTING: Data reported by Member States, or sourced from official re...

Effective September 27, 2023, this dataset will no longer be updated. Similar data are accessible from wonder.cdc.gov.

Estimates of excess deaths can provide information about the burden of mortality potentially related to COVID-19, beyond the number of deaths that are directly attributed to COVID-19. Excess deaths are typically defined as the difference between observed numbers of deaths and expected numbers. This visualization provides weekly data on excess deaths by jurisdiction of occurrence. Counts of deaths in more recent weeks are compared with historical trends to determine whether the number of deaths is significantly higher than expected.

Estimates of excess deaths can be calculated in a variety of ways, and will vary depending on the methodology and assumptions about how many deaths are expected to occur. Estimates of excess deaths presented in this webpage were calculated using Farrington surveillance algorithms (1). For each jurisdiction, a model is used to generate a set of expected counts, and the upper bound of the 95% Confidence Intervals (95% CI) of these expected counts is used as a threshold to estimate excess deaths. Observed counts are compared to these upper bound estimates to determine whether a significant increase in deaths has occurred. Provisional counts are weighted to account for potential underreporting in the most recent weeks. However, data for the most recent week(s) are still likely to be incomplete. Only about 60% of deaths are reported within 10 days of the date of death, and there is considerable variation by jurisdiction. More detail about the methods, weighting, data, and limitations can be found in the Technical Notes.

Note: Reporting of new COVID-19 Case Surveillance data will be discontinued July 1, 2024, to align with the process of removing SARS-CoV-2 infections (COVID-19 cases) from the list of nationally notifiable diseases. Although these data will continue to be publicly available, the dataset will no longer be updated.

Authorizations to collect certain public health data expired at the end of the U.S. public health emergency declaration on May 11, 2023. The following jurisdictions discontinued COVID-19 case notifications to CDC: Iowa (11/8/21), Kansas (5/12/23), Kentucky (1/1/24), Louisiana (10/31/23), New Hampshire (5/23/23), and Oklahoma (5/2/23). Please note that these jurisdictions will not routinely send new case data after the dates indicated. As of 7/13/23, case notifications from Oregon will only include pediatric cases resulting in death.

This case surveillance public use dataset has 19 elements for all COVID-19 cases shared with CDC and includes demographics, geography (county and state of residence), any exposure history, disease severity indicators and outcomes, and presence of any underlying medical conditions and risk behaviors.

Currently, CDC provides the public with three versions of COVID-19 case surveillance line-listed data: this 19 data element dataset with geography, a 12 data element public use dataset, and a 33 data element restricted access dataset.

The following apply to the public use datasets and the restricted access dataset:

• Data elements can be found on the COVID-19 case report form located at www.cdc.gov/coronavirus/2019-ncov/downloads/pui-form.pdf.
• Data are considered provisional by CDC and are subject to change until the data are reconciled and verified with the state and territorial data providers.
• Some data are suppressed to protect individual privacy.
• Datasets will include all cases with the earliest date available in each record (date received by CDC or date related to illness/specimen collection) at least 14 days prior to the creation of the current datasets. This 14-day lag allows case reporting to be stabilized and ensure that time-dependent outcome data are accurately captured.
• Datasets are updated monthly.
• Datasets are created using CDC’s Policy on Public Health Research and Nonresearch Data Management and Access and include protections designed to protect individual privacy.
• For more information about data collection and reporting, please see https://www.cdc.gov/coronavirus/2019-ncov/covid-data/about-us-cases-deaths.html.
• For more information about the COVID-19 case surveillance data, please see https://www.cdc.gov/coronavirus/2019-ncov/covid-data/faq-surveillance.html
  

Overview

The COVID-19 case surveillance database includes individual-level data reported to U.S. states and autonomous reporting entities, including New York City and the District of Columbia (D.C.), as well as U.S. territories and affiliates. On April 5, 2020, COVID-19 was added to the Nationally Notifiable Condition List and classified as “immediately notifiable, urgent (within 24 hours)” by a Council of State and Territorial Epidemiologists (CSTE) Interim Position Statement (<a href="https://cdn.ymaws.com/www.cste.org/resource/resmgr/ps/positionstatement2020/Interim-20-ID-01_COVID