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.

Coronavirus COVID-19 daily new and cumulative cases and deaths by country.

2019 Novel Coronavirus COVID-19 (2019-nCoV) Visual Dashboard and Map:
https://www.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6

• Confirmed Cases by Country/Region/Sovereignty
• Confirmed Cases by Province/State/Dependency
• Deaths
• Recovered

Downloadable data:
https://github.com/CSSEGISandData/COVID-19

Additional Information about the Visual Dashboard:
https://systems.jhu.edu/research/public-health/ncov

JHU Has Stopped Collecting Data As Of 03/10/2023

After three years of around-the-clock tracking of COVID-19 data from around the world, Johns Hopkins has discontinued the Coronavirus Resource Center’s operations.

The site’s two raw data repositories will remain accessible for information collected from 1/22/20 to 3/10/23 on cases, deaths, vaccines, testing and demographics.

Novel Corona Virus (COVID-19) epidemiological data since 22 January 2020. The data is compiled by the Johns Hopkins University Center for Systems Science and Engineering (JHU CCSE) from various sources including the World Health Organization (WHO), DXY.cn, BNO News, National Health Commission of the People’s Republic of China (NHC), China CDC (CCDC), Hong Kong Department of Health, Macau Government, Taiwan CDC, US CDC, Government of Canada, Australia Government Department of Health, European Centre for Disease Prevention and Control (ECDC), Ministry of Health Singapore (MOH), and others. JHU CCSE maintains the data on the 2019 Novel Coronavirus COVID-19 (2019-nCoV) Data Repository on Github.

Fields available in the data include Province/State, Country/Region, Last Update, Confirmed, Suspected, Recovered, Deaths.

On 23/03/2020, a new data structure was released. The current resources for the latest time series data are:

• time_series_covid19_confirmed_global.csv
• time_series_covid19_deaths_global.csv
• time_series_covid19_recovered_global.csv

---DEPRECATION WARNING---
The resources below ceased being updated on 22/03/2020 and were removed on 26/03/2020:

• time_series_19-covid-Confirmed.csv
• time_series_19-covid-Deaths.csv
• time_series_19-covid-Recovered.csv

Context

Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus. Most people infected with COVID-19 virus will experience mild to moderate respiratory illness and recover without requiring special treatment. Older people, and those with underlying medical problems like cardiovascular disease, diabetes, chronic respiratory disease, and cancer are more likely to develop serious illness. During the entire course of the pandemic, one of the main problems that healthcare providers have faced is the shortage of medical resources and a proper plan to efficiently distribute them. In these tough times, being able to predict what kind of resource an individual might require at the time of being tested positive or even before that will be of immense help to the authorities as they would be able to procure and arrange for the resources necessary to save the life of that patient.

The main goal of this project is to build a machine learning model that, given a Covid-19 patient's current symptom, status, and medical history, will predict whether the patient is in high risk or not.

content

The dataset was provided by the Mexican government (link). This dataset contains an enormous number of anonymized patient-related information including pre-conditions. The raw dataset consists of 21 unique features and 1,048,576 unique patients. In the Boolean features, 1 means "yes" and 2 means "no". values as 97 and 99 are missing data.

• sex: 1 for female and 2 for male.
• age: of the patient.
• classification: covid test findings. Values 1-3 mean that the patient was diagnosed with covid in different degrees. 4 or higher means that the patient is not a carrier of covid or that the test is inconclusive.
• patient type: type of care the patient received in the unit. 1 for returned home and 2 for hospitalization.
• pneumonia: whether the patient already have air sacs inflammation or not.
• pregnancy: whether the patient is pregnant or not.
• diabetes: whether the patient has diabetes or not.
• copd: Indicates whether the patient has Chronic obstructive pulmonary disease or not.
• asthma: whether the patient has asthma or not.
• inmsupr: whether the patient is immunosuppressed or not.
• hypertension: whether the patient has hypertension or not.
• cardiovascular: whether the patient has heart or blood vessels related disease.
• renal chronic: whether the patient has chronic renal disease or not.
• other disease: whether the patient has other disease or not.
• obesity: whether the patient is obese or not.
• tobacco: whether the patient is a tobacco user.
• usmr: Indicates whether the patient treated medical units of the first, second or third level.
• medical unit: type of institution of the National Health System that provided the care.
• intubed: whether the patient was connected to the ventilator.
• icu: Indicates whether the patient had been admitted to an Intensive Care Unit.
• date died: If the patient died indicate the date of death, and 9999-99-99 otherwise.

Daily updated dataset of all Coronavirus (COVID-19) Cases in all countries in the world. See the README file and the Codebook for more information including data dictionary.

• Confirmed cases and deaths: this data is collected from the World Health Organization Coronavirus Dashboard. The cases & deaths dataset is updated daily.
  • Note 1: Time/date stamps reflect when the data was last updated by WHO. Due to the time required to process and validate the incoming data, there is a delay between reporting to WHO and the update of the dashboard.
  • Note 2: Counts and corrections made after these times will be carried forward to the next reporting cycle for that specific region. Delayed reporting for any specific country, territory or area may result in pooled counts for multiple days being presented, with a retrospective update to counts on previous days to accurately reflect trends. Significant data errors detected or reported to WHO may be corrected at more frequent intervals.
• Hospitalizations and intensive care unit (ICU) admissions: our data is collected from official sources and collated by Our World in Data. The complete list of country-by-country sources is available here.
• Testing for COVID-19: this data is collected by the Our World in Data team from official reports; you can find further details in our post on COVID-19 testing, including our "https://ourworldindata.org/coronavirus-testing#our-checklist-for-covid-19-testing-data">checklist of questions to understand testing data, information on "https://ourworldindata.org/coronavirus-testing#which-countries-do-we-have-testing-data-for">geographical and temporal coverage, and "https://ourworldindata.org/coronavirus-testing#source-information-country-by-country">detailed country-by-country source information. On 23 June 2022, we stopped adding new datapoints to our COVID-19 testing dataset. You can read more here.
• Vaccinations against COVID-19: this data is collected by the Our World in Data team from official reports.
• Other variables: this data is collected from a variety of sources (United Nations, World Bank, Global Burden of Disease, Blavatnik School of Government, etc.). More information is available in our codebook.

2020

Content:

"Our World in Data" which in collaboration with The University of Oxford have developed a reliable repository of datasets about dozens of topics focusing on those big problems which affect the world. This is why since the beginning of COVID-19 outbreak several researchers have been collecting data from every country in the world about multiple indicators which can make us take better decisions, what is more amazing is the fact that this dataset offered is updated every day for all countries allowing people to keep track of it. In the following link you can find fascinating charts about the pandemic and obviously the World COVID-19 dataset (up to date) containing over 60 features which you can download for free:

https://ourworldindata.org/covid-vaccinations

Important to consider:

I will be updating this dataset every week according to the published data by the organization, if you found this dataset or the link given useful I would really appreciate your upvote!

Acknowledgements and Citation

Mathieu, E., Ritchie, H., Ortiz-Ospina, E. et al. A global database of COVID-19 vaccinations. Nat Hum Behav (2021)

Dataset no longer updated: Due to changes in the collection and availability of data on COVID-19, this dataset is no longer updated. Latest information about COVID-19 is available via the UKHSA data dashboard. The UK government publish daily data, updated weekly, on COVID-19 cases, vaccinations, hospital admissions and deaths. This note provides a summary of the key data for London from this release. Data are published through the UK Coronavirus Dashboard, last updated on 23 March 2023. This update contains: Data on the number of cases identified daily through Pillar 1 and Pillar 2 testing at the national, regional and local authority level Data on the number of people who have been vaccinated against COVID-19 Data on the number of COVID-19 patients in Hospital Data on the number of people who have died within 28 days of a COVID-19 diagnosis Data for London and London boroughs and data disaggregated by age group Data on weekly deaths related to COVID-19, published by the Office for National Statistics and NHS, is also available. Key Points On 23 March 2023 the daily number of people tested positive for COVID-19 in London was reported as 2,775 On 23 March 2023 it was newly reported that 94 people in London died within 28 days of a positive COVID-19 test The total number of COVID-19 cases identified in London to date is 3,146,752 comprising 15.2 percent of the England total of 20,714,868 cases In the most recent week of complete data (12 March 2023 - 18 March 2023) 2,951 new cases were identified in London, a rate of 33 cases per 100,000 population. This compares with 2,883 cases and a rate of 32 for the previous week In England as a whole, 29,426 new cases were identified in the most recent week of data, a rate of 52 cases per 100,000 population. This compares with 26,368 cases and a rate of 47 for the previous week Up to and including 22 March 2023 6,452,895 people in London had received the first dose of a COVID-19 vaccine and 6,068,578 had received two doses Up to and including 22 March 2023 4,435,586 people in London had received either a third vaccine dose or a booster dose On 22 March 2023 there were 1,370 COVID-19 patients in London hospitals. This compares with 1,426 patients on 15 March 2023. On 22 March 2023 there were 70 COVID-19 patients in mechanical ventilation beds in London hospitals. This compares with 72 patients on 15 March 2023. Update: From 1st July updates are weekly From Friday 1 July 2022, this page will be updated weekly rather than daily. This change results from a change to the UK government COVID-19 Dashboard which will move to weekly reporting. Weekly updates will be published every Thursday. Daily data up to the most recent available will continue to be added in each weekly update. Data summary Local authority data Demographics Notes on data sources Source: UK Coronavirus Dashboard. For more information see: Coronavirus (COVID-19) in the UK - About the Data. Cases Data UK Health Security Agency (UKHSA) reports new and cumulative cases identified by Pillar 1 and Pillar 2 testing. Pillar 1 testing relates to tests carried out in UKHSA laboratories or NHS Hospitals for those with clinical need, and health and care workers. Pillar 2 testing relates to tests carried out on the wider population in Lighthouse laboratories, public, private, and academic sector laboratories or using lateral flow devices. The cases data is published by day for Countries within the UK, and Regions, Upper Tier Local Authority (UTLA) and Lower Tier Local Authority (LTLA) within England. The data used here is taken from the regional and UTLA level cases data. Notice: Changes to COVID-19 case reporting As of 31 January 2022, UKHSA moved all COVID-19 case reporting in England to use an episode-based definition which includes possible reinfections. Those testing positive beyond 90 days of a previous infection are now counted as a separate infection episode (a possible reinfection episode). Previously people who tested positive for COVID-19 were only counted once in case numbers published on the daily dashboard, at the date of the first infection. Full details of the changes can be found here Changes to COVID-19 testing in England The availability of free COVID-19 tests in England changed on 1 April 2022. Information on who can access free tests has been published by UKHSA. Changes to patient testing in the NHS in England have also been published by NHS England. Deaths data Data on COVID-19 associated deaths in England are produced by UKHSA from multiple sources linked to confirmed case data. Deaths are only included if the deceased had a positive test for COVID-19 and died within 28 days of the first positive test. Postcode of residence for deaths is collected at the time of testing. This is supplemented, where available, with information from ONS mortality records, Health Protection Team reports and NHS Digital Patient Demographic Service records. Full details of the methodology are available in the technical summary of the PHE data series on deaths in people with COVID-19. Hospital admissions data UKHSA publish the daily total number of patients admitted to hospital, patients in hospital and patients in beds which can deliver mechanical ventilation with COVID-19. In England this includes COVID-19 patients being treated in NHS acute hospitals, mental health and learning disability trusts, and independent service providers commissioned by the NHS. Vaccination data UKHSA publish the number of people who have received a COVID-19 vaccination, by day on which the vaccine was administered. Data are reported daily and can be updated for historical dates as vaccinations given are recorded on the relevant system. Therefore, data for recent dates may be incomplete. Vaccinations that were carried out in England are reported in the National Immunisation Management Service which is the system of record for the vaccination programme in England. Only people aged 12 and over who have an NHS number and are currently alive are included. Age is defined as a person's age at 31 August 2021. The data includes counts of vaccinations by age band, dose, region, and local authority. Additional analysis of the vaccine roll out in London can be found here. ONS population estimates The counts of vaccines given has been converted to percentage of the population vaccinated using the ONS 2020 mid-year population estimates. This is a different population estimate to that used on the UK Coronavirus Dashboard for sub-national data. The UK Coronavirus Dashboard uses people aged 16 and over in the National Immunisation Management Service (NIMS), which is based on GP registrations. In more urban areas like London, NIMS is likely to give an overestimate of the population due to increased population mobility increasing the likelihood duplicate or out of date GP records. Due to the differences in population estimates the percentage of the population vaccinated given here will be higher than the figures included for London on the UK Coronavirus Dashboard.

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 late January, 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.

United States Data

Data on cumulative coronavirus cases and deaths can be found in two files for states and counties.

Each row of data reports cumulative counts based on our best reporting up to the moment we publish an update. We do our best to revise earlier entries in the data when we receive new information.

Both files contain FIPS codes, a standard geographic identifier, to make it easier for an analyst to combine this data with other data sets like a map file or population data.

State-Level Data

State-level data can be found in the us-states.csv file.

date,state,fips,cases,deaths
2020-01-21,Washington,53,1,0
...

County-Level Data

County-level data can be found in the us-counties.csv file.

date,county,state,fips,cases,deaths
2020-01-21,Snohomish,Washington,53061,1,0
...

In some cases, the geographies where cases are reported do not map to standard county boundaries. See the list of geographic exceptions for more detail on these.

Github Repository

This dataset contains COVID-19 data for the United States of America made available by The New York Times on github at https://github.com/nytimes/covid-19-data

On March 10, 2023, the Johns Hopkins Coronavirus Resource Center ceased collecting and reporting of global COVID-19 data. For updated cases, deaths, and vaccine data please visit the following sources:Global: World Health Organization (WHO)U.S.: U.S. Centers for Disease Control and Prevention (CDC)For more information, visit the Johns Hopkins Coronavirus Resource Center.This feature layer contains the most up-to-date COVID-19 cases and the latest trend plot. It covers the US (county or state level), China, Canada, Australia (province/state level), and the rest of the world (country/region level, represented by either the country centroids or their capitals). Data sources are WHO, CDC, ECDC, NHC, DXY, 1point3acres, Worldometers.info, BNO, the COVID Tracking Project (testing and hospitalizations), state and national government health departments, and local media reports. This layer is created and maintained by the Center for Systems Science and Engineering (CSSE) at the Johns Hopkins University. This feature layer is supported by Esri Living Atlas team, JHU APL and JHU Data Services. This layer is opened to the public and free to share. Contact us.

On January 21, 2020, the U.S. Centers for Disease Control and Prevention (CDC) and Washington State Department of Health (DOH) announced the first case of 2019 Novel Coronavirus (COVID-19) in the United States, in Washington state. The link below provides access to DOH daily updates of confirmed Washington State COVID-19 cases and deaths, along with essential information about the virus and guidance on prevention and risk management. The link includes Frequently Asked Questions, as well as resources for specific groups such as parents, caregivers, employers, schools and health care providers.

Technical and methodological data from the Coronavirus (COVID-19) Infection Survey, England, Wales, Northern Ireland and Scotland.

The World Health Organization reported 766440796 Coronavirus Cases since the epidemic began. In addition, countries reported 6932591 Coronavirus Deaths. This dataset provides - World Coronavirus Cases- actual values, historical data, forecast, chart, statistics, economic calendar and news.

In 2025, China ranked first by revenue in the travel & tourism market among the 4 countries presented in the ranking. China's revenue amounted to 157.71 billion U.S. dollars, while the United States and Italy, the second and third countries, had records amounting to 43.90 billion U.S. dollars and 20.80 billion U.S. dollars, respectively.Further information about the methodology, more market segments, and metrics can be found on the dedicated Market Insights page on Travel & Tourism.

This dataset tracks the updates made on the dataset "Novel Coronavirus (COVID-19) Cases Data from JHU CCSE" as a repository for previous versions of the data and metadata.

Findings from the Coronavirus (COVID-19) Infection Survey for England.

Context

The 2019–20 coronavirus pandemic is an ongoing global pandemic of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The virus first emerged in Wuhan, Hubei, China, in December 2019. On 11 March 2020, the World Health Organization declared the outbreak a pandemic. As of 11 March 2020, over 126,000 cases have been confirmed in more than 110 countries and territories, with major outbreaks in mainland China, Italy, South Korea, and Iran. More than 4,600 have died from the disease and 67,000 have recovered.

Content

2019 Novel Coronavirus (2019-nCoV) is a virus (more specifically, a coronavirus) identified as the cause of an outbreak of respiratory illness first detected in Wuhan, China. Early on, many of the patients in the outbreak in Wuhan, China reportedly had some link to a large seafood and animal market, suggesting animal-to-person spread. However, a growing number of patients reportedly have not had exposure to animal markets, indicating person-to-person spread is occurring. At this time, it’s unclear how easily or sustainably this virus is spreading between people - CDC

This dataset has information on the number of affected cases, deaths and recovery from 2019 novel coronavirus. Please note that this data was scrapped from https://www.worldometers.info/coronavirus/.This data is solely for education purposes only.

Acknowledgements

This data is solely belongs to https://www.worldometers.info/coronavirus/. for licensing visit https://www.worldometers.info/licensing/

For English, see below

Nederland heeft voor het SARS-CoV-2 virus (coronavirus) een endemische fase bereikt en de GGD teststraten zijn per 17 maart 2023 gesloten. Daardoor wordt de data vanaf 1 april 2023 niet meer bijgewerkt.

Dit bestand bevat de volgende aantallen: - aantal nieuw gemelde positief geteste personen naar gemeente, per datum waarop de gegevens zijn gepubliceerd door het RIVM - aantal nieuw gemelde sterfgevallen naar gemeente, per datum waarop de gegevens zijn gepubliceerd door het RIVM weergegeven tot 1 januari 2023. De aantallen betreffen Covid-19 meldingen sinds de eerste melding in Nederland (27/02/2020).

Het bestand is als volgt opgebouwd: - Een set records per publicatiedatum met voor elke publicatiedatum:

Een record voor elke gemeente van Nederland, ook als voor de betreffende gemeente geen meldingen zijn. De aantallen zijn dan 0 (nul). Een record voor elke GGD, voor de aantallen meldingen waarbij de gemeente niet bekend is. Ook deze records worden altijd toegevoegd, dus ook als de aantallen 0 (nul) zijn. Ook zijn kolommen voor diverse regionale indelingen toegevoegd. In de beschrijving van de variabelen hieronder wordt per regio beschreven hoe deze zijn bepaald.

Beschrijving van de variabelen: Version: Versienummer van de dataset. Wanneer de inhoud van de dataset structureel wordt gewijzigd (dus niet de dagelijkse update of een correctie op record niveau), zal het versienummer aangepast worden (+1) en ook de corresponderende metadata in RIVMdata (https://data.rivm.nl). Versie 1 correctie update (16 juli 2021) - Door een correctie in de verwerking door het RIVM heeft een kleine set meldingen een herziene ziekenhuisopname publicatiedatum en overlijdens publicatiedatum gekregen per 16-07-2021 (betreft kolommen: Hospital_admission per Date_of_publication en Deceased per Date_of_publication). Versie 2 update (18 januari 2022): - In versie 2 van deze dataset is de variabele ‘hospital_admission’ niet meer beschikbaar. Voor het aantal ziekenhuisopnames wordt verwezen naar de geregistreerde ziekenhuisopnames van Stichting NICE (https://data.rivm.nl/covid-19/COVID-19_ziekenhuisopnames.html). Versie 3 update (20 januari 2022): - In versie 3 van deze dataset zijn records samengesteld volgens de gemeente herindeling van 1 januari 2022. Zie beschrijving van de variabele Municipality_code voor meer informatie. Versie 4 update (8 februari 2022) - Vanaf 8 februari 2022 worden de positieve SARS-CoV-2 testuitslagen rechtstreeks vanuit CoronIT aan het RIVM gemeld. Ook worden de testuitslagen van andere testaanbieders (zoals Testen voor Toegang) en zorginstellingen (zoals ziekenhuizen, verpleeghuizen en huisartsen) die hun positieve SARS-CoV-2 testuitslagen via het Meldportaal van GGD GHOR invoeren rechtstreeks aan het RIVM gemeld. Meldingen die onderdeel zijn van de bron- en contactonderzoek steekproef en positieve SARS-CoV-2 testuitslagen van zorginstellingen die via zorgmail aan de GGD worden gemeld worden wel via HPZone aan het RIVM gemeld. Versie 5 update (24 maart 2022): - In versie 5 van deze dataset zijn records samengesteld volgens de gemeente herindeling van 24 maart 2022. Zie beschrijving van de variabele Municipality_code voor meer informatie. Versie 6 update (1 september 2022): - Vanaf 1 september 2022 wordt de data niet meer iedere werkdag geüpdatet, maar op dinsdagen en vrijdagen. De data wordt op deze dagen met terugwerkende kracht bijgewerkt voor de andere dagen. - Vanaf 1 september 2022 is deze dataset opgesplitst in twee delen. Het eerste deel bevat de data vanaf het begin van de pandemie tot en met 3 oktober 2021 (week 39) en bevat ‘tm’ in de bestandsnaam. Deze data wordt niet meer geüpdatet. Het tweede deel bevat de data vanaf 4 oktober 2021 (week 40) en wordt iedere dinsdag en vrijdag geüpdatet. Versie 7 update (3 januari 2023): - In versie 7 van deze dataset zijn records samengesteld volgens de gemeente herindeling van 1 januari 2023. Deze gemeente herindeling is ook toegepast in het eerste deel van deze dataset dat ‘tm’ bevat in de bestandsnaam en de data bevat vanaf het begin van de pandemie tot en met 3 oktober 2021 (week 39). Zie beschrijving van de variabele Municipality_code voor meer informatie. - Per 1 januari 2023 verzamelt het RIVM geen aanvullende informatie meer. Dit heeft als gevolg dat we vanaf 1 januari 2023 geen overlijdens meer rapporteren en wordt en wordt de kolom [Deceased] op 9999 gezet.

Date_of_report: Datum en tijd waarop het databestand is aangemaakt door het RIVM.

Date_of_publication: Dit betreft per dag het aantal meldingen dat nieuw binnengekomen is bij het RIVM. De tijdsperiode waarin de melding is doorgegeven loopt van 10.01 uur gisteren tot 10.00 uur vandaag. De publicatiedatum kan afwijken van de datum van de positieve testuitslag. Dit kan gebeuren als een melding van een positieve SARS-CoV-2 test later is doorgeven door een GGD aan het RIVM. Dit bestand bevat de meest actuele meldingen op basis van het bronbestand Osiris. Als er in Osiris correcties worden gedaan, dan worden deze correcties ook verwerkt in dit bestand.

Municipality_code: Gemeentecode. Gemeentelijke indeling gebaseerd op postcode van de woonplaats van de SARS-CoV-2 positief geteste persoon, gecodeerd volgens CBS. Sinds de eerste publicatiedatum van 13 maart 2020 tot de versie 3 update van 20 januari 2022, hebben 2 gemeentelijke herindelingen plaatsgevonden. Tot 7 januari 2021 is dit bestand volgens de gemeente indeling van 2020. Vanaf 7 januari 2021 t/m 19 januari 2022 is dit bestand samengesteld volgens de gemeente indeling van 1 januari 2021: Gemeenten Appingedam, Delfzijl en Loppersum zijn samengevoegd tot de nieuwe gemeente Eemsdelta Gr. De gemeente Haaren is opgegaan in de gemeenten Oisterwijk, Tilburg, Vught en Boxtel (https://www.cbs.nl/nl-nl/onze-diensten/methoden/classificaties/overig/gemeentelijke-indelingen-per-jaar/indeling-per-jaar/gemeentelijke-indeling-op-1-januari-2021). Met de opdeling van Haaren is de veiligheidsregio Midden- en West-Brabant iets groter geworden, ten koste van veiligheidsregio Brabant-Noord. Vanaf 20 januari 2022 t/m 23 maart 2022 is dit bestand samengesteld volgens de gemeente indeling van 1 januari 2022. Gemeente Beemster is opgegaan in gemeente Purmerend. De gemeenten Heerhugowaard en Langedijk zijn samengevoegd tot gemeente Dijk en Waard. Gemeente Landerd is met gemeente Uden samengevoegd tot gemeente Maashorst. De gemeenten Boxmeer, Cuijk, Grave, Mill en Sint Hubert en Sint Anthonis zijn samengevoegd tot de gemeente Land van Cuijk ((https://www.cbs.nl/nl-nl/onze-diensten/methoden/classificaties/overig/gemeentelijke-indelingen-per-jaar/indeling-per-jaar/gemeentelijke-indeling-op-1-januari-2021). Vanaf 24 maart 2022 t/m 31 december 2022 is dit bestand samengesteld volgens de gemeente indeling van 24 maart 2022. Gemeente Weesp is opgegaan in gemeente Amsterdam. Met deze indeling is de veiligheidsregio Gooi- en Vechtstreek kleiner geworden en de veiligheidsregio Amsterdam-Amstelland groter; GGD Amsterdam is groter geworden en GGD Gooi- en Vechtstreek is kleiner geworden ((https://www.cbs.nl/nl-nl/onze-diensten/methoden/classificaties/overig/gemeentelijke-indelingen-per-jaar/indeling-per-jaar/gemeentelijke-indeling-op-1-januari-2021). Vanaf 1 januari 2023 is dit bestand samengesteld volgens de gemeente indeling van 1 januari 2023. De gemeenten Brielle, Hellevoetsluis en Westvoorne zijn samen opgegaan in de nieuwe gemeente Voorne aan Zee (Gemeentelijke indeling op 1 januari 2023 (https://www.cbs.nl/nl-nl/onze-diensten/methoden/classificaties/overig/gemeentelijke-indelingen-per-jaar/indeling-per-jaar/gemeentelijke-indeling-op-1-januari-2023)).

Municipality_name: Naam van de gemeente.

Province: Naam van de provincie. Indien gemeente niet bekend is, is de provincie afgeleid van de meldende GGD zodat provincie voor elk record gevuld is.

Security_region_code: Veiligheidsregiocode. Veiligheidsregio gebaseerd op de woonplaats van de patiënt. Indien de woonplaats niet bekend is, wordt Veiligheidsregio gebaseerd op de GGD die de melding heeft gedaan, behalve voor Veiligheidsregio Midden- en West-Brabant en Brabant-Noord aangezien voor deze regio’s GGD en Veiligheidsregio niet vergelijkbaar zijn. Zie ook: https://www.cbs.nl/nl-nl/cijfers/detail/84721NED?q=Veiligheid Security_region_name: Naam van de veiligheidsregio Dit is de naam van de veiligheidregios zoals tot dusver gebruikt in diverse rapportages en verslagen van het RIVM, en kan iets afwijken van de naamgeving zoals aangegeven in de codelijst van CBS (zie link hierboven bij variabele Security_region_code). Zie ook: https://www.rijksoverheid.nl/onderwerpen/veiligheidsregios-en-crisisbeheersing/veiligheidsregios Municipal_health_service: Naam van de GGD. GGD op basis van gemeente (woonplaats van de patiënt). Indien deze niet bekend is wordt hier de GGD die de melding heeft gedaan ingevuld. Zie ook: https://www.ggd.nl ROAZ_region: Naam van de ROAZ-regio. ROAZ-regio op basis van de woonplaats van de patiënt. Indien de woonplaats niet bekend is op basis van meldende GGD (alleen wanneer een GGD geografisch kan worden gematched met een ROAZ-regio). Zie ook: https://www.lnaz.nl/acute-zorg Total_reported: Het aantal nieuwe aan de GGD gemelde personen die positief zijn getest voor SARS-CoV-2 dat op [Date_of_publication] is gepubliceerd door het RIVM. Sinds het begin van de COVID-19 epidemie in Nederland is het testbeleid gelijdelijk veranderd. Het huidige testbeleid is hier te vinden (https://www.rijksoverheid.nl/onderwerpen/coronavirus-covid-19/testen/testbeleid/wijzigingen-testen-vanaf-11-april-2022). Niet alle met SARS-CoV-2 besmette personen worden getest. De werkelijke aantallen in Nederland zijn daarom hoger dan de aantallen die hier genoemd worden.

Deceased: Het aantal aan de GGD’en gemelde overleden personen die positief zijn getest voor SARS-CoV-2 en op [Date_of_publication] is gepubliceerd door het RIVM. Het werkelijke aantal overleden personen positief

United States recorded 16306656 Coronavirus Recovered since the epidemic began, according to the World Health Organization (WHO). In addition, United States reported 797346 Coronavirus Deaths. This dataset includes a chart with historical data for the United States Coronavirus Recovered.