Beginning March 1, 2022, the "COVID-19 Case Surveillance Public Use Data" will be updated on a monthly basis. This case surveillance public use dataset has 12 elements for all COVID-19 cases shared with CDC and includes demographics, any exposure history, disease severity indicators and outcomes, presence of any underlying medical conditions and risk behaviors, and no geographic data. CDC has three COVID-19 case surveillance datasets: COVID-19 Case Surveillance Public Use Data with Geography: Public use, patient-level dataset with clinical data (including symptoms), demographics, and county and state of residence. (19 data elements) COVID-19 Case Surveillance Public Use Data: Public use, patient-level dataset with clinical and symptom data and demographics, with no geographic data. (12 data elements) COVID-19 Case Surveillance Restricted Access Detailed Data: Restricted access, patient-level dataset with clinical and symptom data, demographics, and state and county of residence. Access requires a registration process and a data use agreement. (32 data elements) The following apply to all three datasets: 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 cells are suppressed to protect individual privacy. The 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 previously updated datasets. This 14-day lag allows case reporting to be stabilized and ensures that time-dependent outcome data are accurately captured. Datasets are updated monthly. Datasets are created using CDC’s operational 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://wwwn.cdc.gov/nndss/data-collection.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 (Interim-20-ID-01). CSTE updated the position statement on August 5, 2020 to clarify the interpretation of antigen detection tests and serologic test results within the case classification. The statement also recommended that all states and territories enact laws to make COVID-19 reportable in their jurisdiction, and that jurisdictions conducting surveillance should submit case notifications to CDC. COVID-19 case surveillance data are collected by jurisdictions and reported volun

The COVID-19 pandemic has had a significant impact on BHP's business and employees' health, as with many businesses worldwide. In the financial year ended June 30 2021, there were five thousand confirmed COVID-19 cases among the employees of the company, with three fatalities. Furthermore, the company conducted 467,261 COVID-19 tests, of which 440,000 tests were conducted in Minerals Americas operated assets.

Ratio of $\eta$ spectra from the PbSc to the combined spectra from figure 3f from 0-20% central Cu+Au collisions. Type...

Unlock the Insights: Dive into the Comprehensive COVID-19 Dataset and Uncover Key Patterns, Trends, and Impacts Worldwide. Empower Your Analysis with Rich, Reliable, and Up-to-Date Data.

The COVID-19 dataset provides a comprehensive collection of information related to the global pandemic. It encompasses various aspects such as the number of cases, deaths, recoveries, testing, and more. The dataset serves as a valuable resource for researchers, analysts, and individuals seeking to understand the impact and spread of the virus.

The dataset is compiled from reputable sources, including official government reports, health organizations, and reliable data repositories. It ensures the accuracy and reliability of the information, making it a trusted source for COVID-19 data analysis.

The dataset is inspired by the need for reliable and up-to-date information about the COVID-19 pandemic. It aims to provide a comprehensive resource that enables researchers, analysts, and individuals to gain insights, track trends, and make data-driven decisions to combat the global health crisis.

By leveraging this dataset, users can gain a deeper understanding of the pandemic's progression, identify patterns, and contribute to the ongoing efforts in managing and mitigating the impact of COVID-19.

Expected $95\%$ CL upper limit on the production cross section of gluinos in T5ttttZG model.

Siemens Healthineers' Atellica IM Sars-CoV-2 Total (COV2T) test has a sensitivity of 100 percent and a specificity of 99.8 percent. Specificity is the ability of a test to give a true negative test, that means that the person has not been exposed to SARS-CoV-2 and therefore not developed antibodies.

The COVID-19 pandemic has had a significant impact on the AngloGold Ashanti's business, as with many businesses worldwide. As of the end of March 2021, there were some 2,261 confirmed COVID-19 cases among the employees of the company, with 13 fatalities. The total spending of AngloGold Ashanti to tackle the direct impact of the pandemic on the business, and on community efforts, amounted to approximately 44 million U.S. dollars as of that date.

In past 24 hours, Lesotho, Africa had N/A new cases, N/A deaths and N/A recoveries.

Announcement Beginning October 20, 2022, CDC will report and publish aggregate case and death data from jurisdictional and state partners on a weekly basis rather than daily. As a result, community transmission levels data reported on data.cdc.gov will be updated weekly on Thursdays, typically by 8 PM ET, instead of daily. This public use dataset has 7 data elements reflecting historical data for community transmission levels for all available counties. This dataset contains historical data for the county level of community transmission and includes updated data submitted by states and jurisdictions. Each day, the dataset is appended to contain the most recent day's data. This dataset includes data from January 1, 2021. Transmission level is set to low, moderate, substantial, or high using the calculation rules below. Currently, CDC provides the public with two versions of COVID-19 county-level community transmission level data: this dataset with the levels for each county from January 1, 2021 (Historical Changes dataset) and a dataset with the levels as originally posted (Originally Posted dataset), updated daily with the most recent day’s data. Methods for calculating county level of community transmission indicator The County Level of Community Transmission indicator uses two metrics: (1) total new COVID-19 cases per 100,000 persons in the last 7 days and (2) percentage of positive SARS-CoV-2 diagnostic nucleic acid amplification tests (NAAT) in the last 7 days. For each of these metrics, CDC classifies transmission values as low, moderate, substantial, or high (below and here). If the values for each of these two metrics differ (e.g., one indicates moderate and the other low), then the higher of the two should be used for decision-making. CDC core metrics of and thresholds for community transmission levels of SARS-CoV-2 Total New Case Rate Metric: "New cases per 100,000 persons in the past 7 days" is calculated by adding the number of new cases in the county (or other administrative level) in the last 7 days divided by the population in the county (or other administrative level) and multiplying by 100,000. "New cases per 100,000 persons in the past 7 days" is considered to have transmission level of Low (0-9.99); Moderate (10.00-49.99); Substantial (50.00-99.99); and High (greater than or equal to 100.00). Test Percent Positivity Metric: "Percentage of positive NAAT in the past 7 days" is calculated by dividing the number of positive tests in the county (or other administrative level) during the last 7 days by the total number of tests resulted over the last 7 days. "Percentage of positive NAAT in the past 7 days" is considered to have transmission level of Low (less than 5.00); Moderate (5.00-7.99); Substantial (8.00-9.99); and High (greater than or equal to 10.00). If the two metrics suggest different transmission levels, the higher level is selected. If one metric is missing, the other metric is used for the indicator. Transmission categories include: Low Transmission Threshold: Counties with fewer than 10 total cases per 100,000 population in the past 7 days, and a NAAT percent test positivity in the past 7 days below 5%; Moderate Transmission Threshold: Counties with 10-49 total cases per 100,000 population in the past 7 days or a NAAT test percent positivity in the past 7 days of 5.0-7.99%; Substantial Transmission Threshold: Counties with 50-99 total cases per 100,000 population in the past 7 days or a NAAT test percent positivity in the past 7 days of 8.0-9.99%; High Transmission Threshold: Counties with 100

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.

Count of COVID-19-associated deaths by date of death. Deaths reported to either the OCME or DPH are included in the COVID-19 data. COVID-19-associated deaths include persons who tested positive for COVID-19 around the time of death and persons who were not tested for COVID-19 whose death certificate lists COVID-19 disease as a cause of death or a significant condition contributing to death.

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

Note the counts in this dataset may vary from the death counts in the other COVID-19-related datasets published on data.ct.gov, where deaths are counted on the date reported rather than the date of death.

Starting in July 2020, this dataset will be updated every weekday. Data are subject to future revision as reporting changes.

The dataset contains a weekly situation update on COVID-19, the epidemiological curve and the global geographical distribution (EU/EEA and the UK, worldwide).

Since the beginning of the coronavirus pandemic, ECDC’s Epidemic Intelligence team has collected the number of COVID-19 cases and deaths, based on reports from health authorities worldwide. This comprehensive and systematic process was carried out on a daily basis until 14/12/2020. See the discontinued daily dataset: COVID-19 Coronavirus data - daily. ECDC’s decision to discontinue daily data collection is based on the fact that the daily number of cases reported or published by countries is frequently subject to retrospective corrections, delays in reporting and/or clustered reporting of data for several days. Therefore, the daily number of cases may not reflect the true number of cases at EU/EEA level at a given day of reporting. Consequently, day to day variations in the number of cases does not constitute a valid basis for policy decisions.

ECDC continues to monitor the situation. Every week between Monday and Wednesday, a team of epidemiologists screen up to 500 relevant sources to collect the latest figures for publication on Thursday. The data screening is followed by ECDC’s standard epidemic intelligence process for which every single data entry is validated and documented in an ECDC database. An extract of this database, complete with up-to-date figures and data visualisations, is then shared on the ECDC website, ensuring a maximum level of transparency.

ECDC receives regular updates from EU/EEA countries through the Early Warning and Response System (EWRS), The European Surveillance System (TESSy), the World Health Organization (WHO) and email exchanges with other international stakeholders. This information is complemented by screening up to 500 sources every day to collect COVID-19 figures from 196 countries. This includes websites of ministries of health (43% of the total number of sources), websites of public health institutes (9%), websites from other national authorities (ministries of social services and welfare, governments, prime minister cabinets, cabinets of ministries, websites on health statistics and official response teams) (6%), WHO websites and WHO situation reports (2%), and official dashboards and interactive maps from national and international institutions (10%). In addition, ECDC screens social media accounts maintained by national authorities on for example Twitter, Facebook, YouTube or Telegram accounts run by ministries of health (28%) and other official sources (e.g. official media outlets) (2%). Several media and social media sources are screened to gather additional information which can be validated with the official sources previously mentioned. Only cases and deaths reported by the national and regional competent authorities from the countries and territories listed are aggregated in our database.

Disclaimer: National updates are published at different times and in different time zones. This, and the time ECDC needs to process these data, might lead to discrepancies between the national numbers and the numbers published by ECDC. Users are advised to use all data with caution and awareness of their limitations. Data are subject to retrospective corrections; corrected datasets are released as soon as processing of updated national data has been completed.

If you reuse or enrich this dataset, please share it with us.

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 test results by date of specimen collection, including total, positive, negative, and indeterminate for molecular and antigen tests. Molecular tests reported include polymerase chain reaction (PCR) and nucleic acid amplicfication (NAAT) tests. Test results may be reported several days after the result. Data are incomplete for the most recent days. Data from previous dates are routinely updated. Records with a null date field summarize tests reported that were missing the date of collection. Starting in July 2020, this dataset will be updated every weekday.

The Underwater Acoustic Deterrent System is an experimental deterrent that utilizes underwater sounds to deter invasive carps. An experimental deployment and evaluation of a UADS is currently being conducted at Lock 19 on the Mississippi River, near Keokuk, Iowa. This dataset includes information derived from two telemetry arrays (i.e., 307 kHz HTI and 69 kHz VEMCO) deployed at and around Lock 19 to evaluate fish movement and response to the UADS in 2021 and 2022. Silver Carp, Bighead Carp, Grass Carp, and a variety of native fish species were tagged and monitored with the telemetry arrays.

In past 24 hours, Kazakhstan, Asia had N/A new cases, N/A deaths and N/A recoveries.

Please see FAQ for latest information on COVID-19 Data Hub Data Flows. https://covid-19.geohive.ie/pages/helpfaqs Category Field label Field Name Explanation

ExtractDate Extract Date Date the data is Extracted

Latitude Latitude

Longitude Longitude

VaccinationDate Vaccination Date Date the Vaccination occurred

Week Week Details of epidemiological weeks available here https://www.hpsc.ie/notifiablediseases/resources/epidemiologicalweeks/

TotalDailyVaccines Total Daily Vaccines

Gender Male

Female

NA

Dose Number Dose1 Dose 1

Dose2 Dose 2

SingleDose Single Dose

Vaccine Brand Moderna

Pfizer

Janssen

AstraZeneca

Age Group Partial_Age0to9 At Least One Dose Age 0 to 11 Dose 1 of Astrazenenca, MRNA or Single Dose Vaccine

Partial_Age10to19 At Least One Dose Age 12 to 19

Partial_Age20to29 At Least One Dose Age 20 to 29

Partial_Age30to39 At Least One Dose Age 30 to 39

Partial_Age40to49 At Least One Dose Age 40 to 49

Partial_Age50to59 At Least One Dose Age 50 to 59

Partial_Age60to69 At Least One Dose Age 60 to 69

Partial_Age70to79 At Least One Dose Age 70 to 79

Partial_Age80+ At Least One Dose Age80+

Partial_NA At Least One Dose Not Assigned

Age Group Cumulative ParCum_Age0to9 Cumulative Age 0 to 11 Cumulative At least One Dose Age 0 to 11

ParCum_Age10to19 Cumulative Age 12 to 19 Cumulative At least One Dose Age 12 to 19

ParCum_Age20to29 Cumulative Age 20 to 29 Cumulative At least One Dose Age 20 to 29

ParCum_Age30to39 Cumulative Age 30 to 39 Cumulative At least One Dose Age 30 to 39

ParCum_Age40to49 Cumulative Age 40 to 49 Cumulative At least One Dose Age 40 to 49

ParCum_Age50to59 Cumulative Age50 to 59 Cumulative At least One Dose Age 50 to 59

ParCum_Age60to69 Cumulative Age 60 to 69 Cumulative At least One Dose Age 60 to 69

ParCum_Age70to79 Cumulative Age 70 to 79 Cumulative At least One Dose Age 70 to 79

ParCum_80+ Cumulative Age 80+ Cumulative At least One Dose Age 80+

Age Group Cumulative Percent ParCum_NA Cumulative Age Not Assigned Cumulative At least One Dose Age Not Assigned

ParPer_Age0to9 At Least One Dose Percent Age 0 to 11 Cumulative At least One Dose Age cohort/ Age cohort population

ParPer_Age10to19 At Least One Dose Percent Age 12 to 19

ParPer_Age20to29 At Least One Dose Percent Age 20 to 29

ParPer_Age30to39 At Least One Dose Percent Age 30 to 39

ParPer_Age40to49 At Least One Dose Percent Age 40 to 49

ParPer_Age50to59 At Least One Dose Percent Age 50 to 59

ParPer_Age60to69 At Least One Dose Percent Age 60 to 69

ParPer_Age70to79 At Least One Dose Percent Age 70 to 79

ParPer_80+ At Least One Dose Percent 80+

ParPer_NA At Least One Dose Percent Not Assigned

Age Group Fully_Age0to9 Fully vaccinated Age 0 to 11 Dose 2 of An MRNA or AztraZeneca Vaccine or a single dose vaccine of a Janssen

Fully_Age10to19 Fully vaccinated Age 12 to 19

Fully_Age20to29 Fully vaccinated Age 20 to 29

Fully_Age30to39 Fully vaccinated Age 30 to 39

Fully_Age40to49 Fully vaccinated Age 40 to 49

Fully_Age50to59 Fully vaccinated Age 50 to 59

Fully_Age60to69 Fully vaccinated Age 60 to 69

Fully_Age70to79 Fully vaccinated Age 70 to 79

Fully_Age80+ Fully vaccinated Age 80+

Fully_NA Fully vaccinated Age Not Available

Age Group Cumulative FullyCum_Age0to9 Cumulative Fully vaccinated Age 0 to 11

FullyCum_Age10to19 Cumulative Fully vaccinated Age 12 to 19

FullyCum_Age20to29 Cumulative Fully vaccinated Age 20 to 29

FullyCum_Age30to39 Cumulative Fully vaccinated Age 30 to 39

FullyCum_Age40to49 Cumulative Fully vaccinated Age 40 to 49

FullyCum_Age50to59 Cumulative Fully vaccinated Age 50 to 59

FullyCum_Age60to69 Cumulative Fully vaccinated Age 60 to 69

FullyCum_Age70to79 Cumulative Fully vaccinated Age 70 to 79

FullyCum_80+ Cumulative Fully vaccinated Age 80+

Age Group Cumulative Percent FullyCum_NA Cumulative Fully vaccinated Age Not Available

FullyPer_Age0to9 Cumulative Percent Fully vaccinated Age 0 to 11 Cumulative Fully Vaccinated Age cohort/ Age cohort population

FullyPer_Age10to19 Cumulative Percent Fully vaccinated Age 12 to 19

FullyPer_Age20to29 Cumulative Percent Fully vaccinated Age 20 to 29

FullyPer_Age30to39 Cumulative Percent Fully vaccinated Age 30 to 39

FullyPer_Age40to49 Cumulative Percent Fully vaccinated Age 40 to 49

FullyPer_Age50to59 Cumulative Percent Fully vaccinated Age 50 to 59

FullyPer_Age60to69 Cumulative Percent Fully vaccinated Age 60 to 69

FullyPer_Age70to79 Cumulative Percent Fully vaccinated Age 70 to 79

FullyPer_80+ Cumulative Percent Fully vaccinated Age 80+

FullyPer_NA Cumulative Percent Fully vaccinated Age Not Available

The coronavirus (COVID-19) has led to over 183,000 deaths in Germany, as of 2024. When looking at the distribution of deaths by age, based on the figures currently available, most death occurred in the age group 80 years and older at approximately 118,938 deaths.

Feature service with the current Covid-19 infections per 100,000 inhabitants on the German federal states. The service is updated daily with the current case numbers of the Robert Koch Institute.

Data source: Robert Koch Institute Terms of Use: Robert Koch Institute; German Federal Agency for Cartography and Geodesy Source note: Robert Koch-Institute (RKI), dl-en/by-2-0 Disclaimer: "The content made available on the Internet pages of the Robert Koch-Institute is intended solely for the general information of the public, primarily the specialist public". Data protection declaration: "The use of the RKI website is generally possible without disclosing personal data".

The official information on the spread of the epidemic in France is rather fragmented, and is almost never structured in the form of data. The objective of this dataset is to consolidate the official information, and make it available in open and easily reusable formats (JSON, CSV...). ### Granularity The data are proposed according to several granularities: world, country (France), region and department. The data at the department’s mesh are currently very fragmentary. ### Sources used — Public health France — Prefectures — Regional health agencies — Ministry of Solidarity and Health ### Source code and outputs Link to the data collection project. Report data issues and errors by creating exits at the following address: https://github.com/opencovid19-fr/data

This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found

Context

These datasets are from Our World in Data. Their complete COVID-19 dataset is a collection of the COVID-19 data maintained by Our World in Data. It is updated daily and includes data on confirmed cases, deaths, hospitalizations, testing, and vaccinations as well as other variables of potential interest.

Content

Confirmed cases and deaths:

our data comes from the COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU). We discuss how and when JHU collects and publishes this data. The cases & deaths dataset is updated daily. Note: the number of cases or deaths reported by any institution—including JHU, the WHO, the ECDC, and others—on a given day does not necessarily represent the actual number on that date. This is because of the long reporting chain that exists between a new case/death and its inclusion in statistics. This also means that negative values in cases and deaths can sometimes appear when a country corrects historical data because it had previously overestimated the number of cases/deaths. Alternatively, large changes can sometimes (although rarely) be made to a country's entire time series if JHU decides (and has access to the necessary data) to correct values retrospectively.

Hospitalizations and intensive care unit (ICU) admissions:

our data comes from the European Centre for Disease Prevention and Control (ECDC) for a select number of European countries; the government of the United Kingdom; the Department of Health & Human Services for the United States; the COVID-19 Tracker for Canada. Unfortunately, we are unable to provide data on hospitalizations for other countries: there is currently no global, aggregated database on COVID-19 hospitalization, and our team at Our World in Data does not have the capacity to build such a dataset.

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 checklist of questions to understand testing data, information on geographical and temporal coverage, and detailed country-by-country source information. The testing dataset is updated around twice a week.

Acknowledgements

Our World in Data GitHub repository for covid-19.

Inspiration

All we love data, cause we love to go inside it and discover the truth that's the main inspiration I have.