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  1. g

    Coronavirus (Covid-19) Data in the United States

    • github.com
    • openicpsr.org
    • +3altro
    csv
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    New York Times, Coronavirus (Covid-19) Data in the United States [Dataset]. https://github.com/nytimes/covid-19-data
    Esplora all'indirizzo:
    csvFormati di download disponibili
    Set di dati fornito da
    New York Times
    Licenza

    https://github.com/nytimes/covid-19-data/blob/master/LICENSEhttps://github.com/nytimes/covid-19-data/blob/master/LICENSE

    Descrizione

    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.

  2. i

    Coronavirus (COVID-19) Tweets Dataset

    • ieee-dataport.org
    • search.datacite.org
    • +1altro
    Ultimo aggiornamento: 26 ott 2020
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    Rabindra Lamsal (2020). Coronavirus (COVID-19) Tweets Dataset [Dataset]. http://doi.org/10.21227/781w-ef42
    Esplora all'indirizzo:
    Ultimo aggiornamento set di dati
    26 ott 2020
    Set di dati fornito da
    IEEE Dataport
    Autori
    Rabindra Lamsal
    Licenza

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    Le informazioni sulla licenza sono state recuperate automaticamente

    Descrizione

    This dataset (COV19Tweets) includes CSV files that contain IDs and sentiment scores of the tweets related to the COVID-19 pandemic. The real-time Twitter feed is monitored for coronavirus-related tweets using 90+ different keywords and hashtags that are commonly used while referencing the pandemic. The oldest tweets in this dataset date back to October 01, 2019. This dataset has been wholly re-designed on March 20, 2020, to comply with the content redistribution policy set by Twitter. Twitter's policy restricts the sharing of Twitter data other than IDs; therefore, only the tweet IDs are released through this dataset. You need to hydrate the tweet IDs in order to get complete data. For detailed instructions on the hydration of tweet IDs, please read this article.Announcements: We release CrisisTransformers (https://huggingface.co/crisistransformers), a family of pre-trained language models and sentence encoders introduced in the paper "CrisisTransformers: Pre-trained language models and sentence encoders for crisis-related social media texts". The models were trained based on the RoBERTa pre-training procedure on a massive corpus of over 15 billion word tokens sourced from tweets associated with 30+ crisis events such as disease outbreaks, natural disasters, conflicts, etc. CrisisTransformers were evaluated on 18 public crisis-specific datasets against strong baselines such as BERT, RoBERTa, BERTweet, etc. Our pre-trained models outperform the baselines across all 18 datasets in classification tasks, and our best-performing sentence-encoder outperforms the state-of-the-art by more than 17% in sentence encoding tasks. Please refer to the associated paper for more details.MegaGeoCOV Extended — an extended version of MegaGeoCOV has been released. The dataset is introduced in the paper "A Twitter narrative of the COVID-19 pandemic in Australia".We have released BillionCOV — a billion-scale COVID-19 tweets dataset for efficient hydration. Hydration takes time due to limits placed by Twitter on its tweet lookup endpoint. We re-hydrated the tweets present in this dataset (COV19Tweets) and found that more than 500 million tweet identifiers point to either deleted or protected tweets. If we avoid hydrating those tweet identifiers alone, it saves almost two months in a single hydration task. BillionCOV will receive quarterly updates, while this dataset (COV19Tweets) will continue to receive updates every day. Learn more about BillionCOV on its page: https://dx.doi.org/10.21227/871g-yp65. Related publications:Rabindra Lamsal. (2021). Design and analysis of a large-scale COVID-19 tweets dataset. Applied Intelligence, 51(5), 2790-2804.Rabindra Lamsal, Aaron Harwood, Maria Rodriguez Read. (2022). Socially Enhanced Situation Awareness from Microblogs using Artificial Intelligence: A Survey. ACM Computing Surveys, 55(4), 1-38. (arXiv)Rabindra Lamsal, Aaron Harwood, Maria Rodriguez Read. (2022). Twitter conversations predict the daily confirmed COVID-19 cases. Applied Soft Computing, 129, 109603. (arXiv)Rabindra Lamsal, Aaron Harwood, Maria Rodriguez Read. (2022). Addressing the location A/B problem on Twitter: the next generation location inference research. In 2022 ACM SIGSPATIAL LocalRec (pp. 1-4).Rabindra Lamsal, Aaron Harwood, Maria Rodriguez Read. (2022). Where did you tweet from? Inferring the origin locations of tweets based on contextual information. In 2022 IEEE International Conference on Big Data (pp. 3935-3944). (arXiv)Rabindra Lamsal, Maria Rodriguez Read, Shanika Karunasekera. (2023). BillionCOV: An Enriched Billion-scale Collection of COVID-19 tweets for Efficient Hydration. Data in Brief, 48, 109229. (arXiv)Rabindra Lamsal, Maria Rodriguez Read, Shanika Karunasekera. (2023). A Twitter narrative of the COVID-19 pandemic in Australia. In 20th International ISCRAM Conference (pp. 353-370). (arXiv)Rabindra Lamsal, Maria Rodriguez Read, Shanika Karunasekera. (2024). CrisisTransformers: Pre-trained language models and sentence encoders for crisis-related social media texts. Knowledge-Based Systems, 296, 111916. (arXiv)Rabindra Lamsal, Maria Rodriguez Read, Shanika Karunasekera. (2024). Semantically Enriched Cross-Lingual Sentence Embeddings for Crisis-related Social Media Texts. In 21st International ISCRAM Conference (in press). (arXiv)An Open access Billion-scale COVID-19 Tweets Dataset (COV19Tweets)— Dataset name: COV19Tweets Dataset— Number of tweets : 2,263,729,117 tweets— Coverage : Global— Language : English (EN)— Dataset usage terms : By using this dataset, you agree to (i) use the content of this dataset and the data generated from the content of this dataset for non-commercial research only, (ii) remain in compliance with Twitter's Policy and (iii) cite the following paper:Lamsal, R. (2021). Design and analysis of a large-scale COVID-19 tweets dataset. Applied Intelligence, 51, 2790-2804. https://doi.org/10.1007/s10489-020-02029-zBibTeX entry:@article{lamsal2021design, title={Design and analysis of a large-scale COVID-19 tweets dataset}, author={Lamsal, Rabindra}, journal={Applied Intelligence}, volume={51}, number={5}, pages={2790--2804}, year={2021}, publisher={Springer} }— Geo-tagged Version: Coronavirus (COVID-19) Geo-tagged Tweets Dataset (GeoCOV19Tweets Dataset)— Dataset updates : Everyday— Active keywords and hashtags (archive: keywords.tsv) : corona, #corona, coronavirus, #coronavirus, covid, #covid, covid19, #covid19, covid-19, #covid-19, sarscov2, #sarscov2, sars cov2, sars cov 2, covid_19, #covid_19, #ncov, ncov, #ncov2019, ncov2019, 2019-ncov, #2019-ncov, pandemic, #pandemic #2019ncov, 2019ncov, quarantine, #quarantine, flatten the curve, flattening the curve, #flatteningthecurve, #flattenthecurve, hand sanitizer, #handsanitizer, #lockdown, lockdown, social distancing, #socialdistancing, work from home, #workfromhome, working from home, #workingfromhome, ppe, n95, #ppe, #n95, #covidiots, covidiots, herd immunity, #herdimmunity, pneumonia, #pneumonia, chinese virus, #chinesevirus, wuhan virus, #wuhanvirus, kung flu, #kungflu, wearamask, #wearamask, wear a mask, vaccine, vaccines, #vaccine, #vaccines, corona vaccine, corona vaccines, #coronavaccine, #coronavaccines, face shield, #faceshield, face shields, #faceshields, health worker, #healthworker, health workers, #healthworkers, #stayhomestaysafe, #coronaupdate, #frontlineheroes, #coronawarriors, #homeschool, #homeschooling, #hometasking, #masks4all, #wfh, wash ur hands, wash your hands, #washurhands, #washyourhands, #stayathome, #stayhome, #selfisolating, self isolating Important Notes:> Dataset files are published in chronological order.> Twitter's content redistribution policy restricts the sharing of tweet information other than tweet IDs and/or user IDs. Twitter wants researchers to always pull fresh data. It is because a user might delete a tweet or make his/her profile protected.> Retweets are excluded in the files corona_tweets_chi.csv and earlier.> Only the tweet IDs are available (sentiment scores are not available) for the tweets present in the files: corona_tweets_11b.csv, corona_tweets_223.csv, corona_tweets_297.csv, corona_tweets_395.csv and the files containing tweets from before March 20, 2020.> March 29, 2020 04:02 PM - March 30, 2020 02:00 PM -- Some technical fault has occurred. Preventive measures have been taken. Tweets for this session won't be available. [update: the tweets for this session are now available in the corona_tweets_11b.csv file; retweets are excluded though]> Please go through the Dataset Files section for specific notes.> There's a Combined_Files section (at the bottom of the dataset files list) if you want to download dataset files in bulk.> The naming convention for the later added CSVs (tweets from before March 20, 2020) will have a greek alphabet name instead of a numeric counter. I'll start with the last greek alphabet name "omega" and proceed up towards "alpha".> If you want access to tweets older than October 01, 2019, feel free to reach out to me at rlamsal [at] student.unimelb.edu.au using your academic/research institution email.Dataset Files (GMT+5:45)--------- tweets from before March 20, 2020 ---------corona_tweets_theta.csv: 418,625 tweets (October 01, 2019 12:00 AM - October 18, 2019, 07:51 AM)corona_tweets_iota.csv: 1,000,000 tweets (October 18, 2019, 07:51 AM - December 01, 2019 01:25 AM)corona_tweets_kappa.csv: 1,000,000 tweets (December 01, 2019 01:25 AM - January 09, 2020, 10:20 PM)corona_tweets_lambda.csv: 1,000,000 tweets (January 09, 2020, 10:20 PM - January 26, 2020, 05:14 PM)corona_tweets_mu.csv: 1,000,000 tweets (January 26, 2020, 05:14 PM - January 31, 2020, 07:18 AM)corona_tweets_nu.csv: 1,000,000 tweets (January 31, 2020, 07:18 AM - February 05, 2020 03:38 PM)corona_tweets_xi.csv: 4,003,032 tweets (February 05, 2020 03:38 PM - February 28, 2020 04:27 AM)corona_tweets_omicron.csv: 3,000,000 tweets (February 28, 2020 04:27 AM - March 04, 2020 03:36 PM)corona_tweets_pi.csv: 3,000,000 tweets (March 04, 2020 03:36 PM - March 09, 2020 07:58 AM)corona_tweets_rho.csv: 3,990,232 tweets (March 09, 2020 07:58 AM - March 12, 2020 12:01 PM)corona_tweets_sigma.csv: 3,000,000 tweets (March 12, 2020 12:01 PM - March 13, 2020 07:13 PM)corona_tweets_tau.csv: 3,000,000 tweets (March 13, 2020 07:13 PM - March 15, 2020 04:03 AM)corona_tweets_upsilon.csv: 3,999,408 tweets (March 15, 2020 04:03 AM - March 17, 2020 03:25 AM)corona_tweets_phi.csv: 3,000,000 tweets (March 17, 2020 03:25 AM - March 18, 2020 06:51 AM)corona_tweets_chi.csv: 3,000,000 tweets (March 18, 2020 06:51 AM - March 19, 2020 10:57 AM)corona_tweets_psi.csv: 3,878,586 tweets (March 19, 2020 10:57 AM - March 19, 2020 08:04 PM)corona_tweets_omega.csv: 4,000,000 tweets (March 19, 2020 08:04 PM - March 20, 2020 01:37 AM)----------------------------------corona_tweets_01.csv + corona_tweets_02.csv + corona_tweets_03.csv: 2,475,980 tweets (March 20, 2020 01:37 AM - March 21, 2020 09:25 AM)corona_tweets_04.csv: 1,233,340

  3. H

    Novel Coronavirus (COVID-19) Cases Data

    • data.humdata.org
    csv
    Ultimo aggiornamento: 4 feb 2025
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    Johns Hopkins University Center for Systems Science and Engineering (2025). Novel Coronavirus (COVID-19) Cases Data [Dataset]. https://data.humdata.org/dataset/novel-coronavirus-2019-ncov-cases
    Esplora all'indirizzo:
    csvFormati di download disponibili
    Ultimo aggiornamento set di dati
    4 feb 2025
    Set di dati fornito da
    Johns Hopkins University Center for Systems Science and Engineering
    Licenza

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    Le informazioni sulla licenza sono state recuperate automaticamente

    Descrizione
    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
  4. Coronavirus (Covid-19) Data in the United States

    • openicpsr.org
    Ultimo aggiornamento: 7 dic 2020
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    New York Times (2020). Coronavirus (Covid-19) Data in the United States [Dataset]. http://doi.org/10.3886/E128303V1
    Esplora all'indirizzo:
    Identificatore univoco
    https://doi.org/10.3886/E128303V1
    Ultimo aggiornamento set di dati
    7 dic 2020
    Set di dati fornito da
    The New York Timeshttp://nytimes.com/
    Autori
    New York Times
    Periodo di tempo coperto
    21 gen 2020 - 22 nov 2020
    Area coperta
    United States
    Descrizione

    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. This time series data is being compiled from state and local governments and health departments in an attempt to provide a complete record of the ongoing outbreak. This deposit contains live data from three geographic levels: U.S., states and counties. ICPSR staff scraped these data on 11/22/2020. For the most current data, please visit https://github.com/nytimes/covid-19-data.

  5. g

    Coronavirus COVID-19 Global Cases by the Center for Systems Science and...

    • github.com
    • systems.jhu.edu
    • +1altro
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    Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE), Coronavirus COVID-19 Global Cases by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU) [Dataset]. https://github.com/CSSEGISandData/COVID-19
    Esplora all'indirizzo:
    Set di dati fornito da
    Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE)
    Area coperta
    Globale
    Descrizione

    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

  6. Coronavirus COVID-19 Global Cases

    • redivis.com
    application/jsonl +7
    Ultimo aggiornamento: 13 lug 2020
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    Stanford Center for Population Health Sciences (2020). Coronavirus COVID-19 Global Cases [Dataset]. http://doi.org/10.57761/pyf5-4e40
    Esplora all'indirizzo:
    application/jsonl, parquet, csv, stata, avro, spss, sas, arrowFormati di download disponibili
    Ultimo aggiornamento set di dati
    13 lug 2020
    Set di dati fornito da
    Redivis Inc.
    Autori
    Stanford Center for Population Health Sciences
    Periodo di tempo coperto
    22 gen 2020 - 12 lug 2020
    Descrizione

    Abstract

    JHU Coronavirus COVID-19 Global Cases, by country

    Documentation

    PHS is updating the Coronavirus Global Cases dataset weekly, Monday, Wednesday and Friday from Cloud Marketplace.

    This data comes from the data repository for the 2019 Novel Coronavirus Visual Dashboard operated by the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE). This database was created in response to the Coronavirus public health emergency to track reported cases in real-time. The data include the location and number of confirmed COVID-19 cases, deaths, and recoveries for all affected countries, aggregated at the appropriate province or state. It was developed to enable researchers, public health authorities and the general public to track the outbreak as it unfolds. Additional information is available in the blog post.

    Visual Dashboard (desktop): https://www.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6

    Section 2

    Included Data Sources are:

    %3C!-- --%3E

    Section 3

    **Terms of Use: **

    This GitHub repo and its contents herein, including all data, mapping, and analysis, copyright 2020 Johns Hopkins University, all rights reserved, is provided to the public strictly for educational and academic research purposes. The Website relies upon publicly available data from multiple sources, that do not always agree. The Johns Hopkins University hereby disclaims any and all representations and warranties with respect to the Website, including accuracy, fitness for use, and merchantability. Reliance on the Website for medical guidance or use of the Website in commerce is strictly prohibited.

    Section 4

    **U.S. county-level characteristics relevant to COVID-19 **

    Chin, Kahn, Krieger, Buckee, Balsari and Kiang (forthcoming) show that counties differ significantly in biological, demographic and socioeconomic factors that are associated with COVID-19 vulnerability. A range of publicly available county-specific data identifying these key factors, guided by international experiences and consideration of epidemiological parameters of importance, have been combined by the authors and are available for use:

    https://github.com/mkiang/county_preparedness/

  7. d

    Data from: Novel Coronavirus 2019

    • datahub.io
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    Novel Coronavirus 2019 [Dataset]. https://datahub.io/core/covid-19
    Esplora all'indirizzo:
    Licenza

    ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
    Le informazioni sulla licenza sono state recuperate automaticamente

    Descrizione

    Coronavirus disease 2019 (COVID-19) time series listing confirmed cases, reported deaths and reported recoveries. Data is disaggregated by country (and sometimes subregion). Coronavirus disease (COV...

  8. [DEPRECATED] Données relatives au coronavirus COVID-19

    • data.europa.eu
    csv, excel xlsx, html +3
    Ultimo aggiornamento: 14 dic 2020
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    European Centre for Disease Prevention and Control (2020). [DEPRECATED] Données relatives au coronavirus COVID-19 [Dataset]. https://data.europa.eu/data/datasets/covid-19-coronavirus-data?locale=fr
    Esplora all'indirizzo:
    json, excel xlsx, rss feed, html, xml, csvFormati di download disponibili
    Ultimo aggiornamento set di dati
    14 dic 2020
    Set di dati fornito da
    European Centre for Disease Prevention and Control (ECDC)http://ecdc.europa.eu/
    Autori
    European Centre for Disease Prevention and Control
    Licenza

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    Le informazioni sulla licenza sono state recuperate automaticamente

    Descrizione
  9. a

    COVID-19 US Confirmed Cases

    • hub.arcgis.com
    • disaster-amerigeoss.opendata.arcgis.com
    Ultimo aggiornamento: 11 apr 2020
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    CivicImpactJHU (2020). COVID-19 US Confirmed Cases [Dataset]. https://hub.arcgis.com/maps/c477155f93d940d0ba01828900a7ff7d
    Esplora all'indirizzo:
    Ultimo aggiornamento set di dati
    11 apr 2020
    Set di dati creato e fornito da
    CivicImpactJHU
    Area coperta
    Descrizione

    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 web map contains the most up-to-date information on confirmed cases of the coronavirus COVID-19 in the US. Data is pulled from the Coronavirus COVID-19 Global Cases by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University, the Red Cross, the Census American Community Survey, and the Bureau of Labor and Statistics, and aggregated at the US county level. This web map created and maintained by the Centers for Civic Impact at the Johns Hopkins University, and is supported by the Esri Living Atlas team and JHU Data Services. It is used in the COVID-19 United States Cases by County dashboard. For more information on Johns Hopkins University’s response to COVID-19, visit the Johns Hopkins Coronavirus Resource Center where our experts help to advance understanding of the virus, inform the public, and brief policymakers in order to guide a response, improve care, and save lives.

  10. d

    Fighting Coronavirus/COVID-19 with Public Health Data

    • catalog.data.gov
    • data.amerigeoss.org
    Ultimo aggiornamento: 18 mar 2023
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    City of Tempe (2023). Fighting Coronavirus/COVID-19 with Public Health Data [Dataset]. https://catalog.data.gov/dataset/fighting-coronavirus-covid-19-with-public-health-data-1cf8a
    Esplora all'indirizzo:
    Ultimo aggiornamento set di dati
    18 mar 2023
    Set di dati fornito da
    City of Tempe
    Descrizione

    This story map explores the partnership between the City of Tempe and Arizona State University to study city wastewater for Coronavirus/COVID-19. Featured sections include:What is Coronavirus/COVID-19Analyzing Wastewater DataData-Driven Decision MakingWhat You Can DoFrequently Asked Questions Important ContactsPlease also see the Spanish language version.

  11. o

    Novel Coronavirus (COVID-19) Cases Data - Dataset - Data Catalog Armenia

    • data.opendata.am
    Ultimo aggiornamento: 31 mag 2023
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    (2023). Novel Coronavirus (COVID-19) Cases Data - Dataset - Data Catalog Armenia [Dataset]. https://data.opendata.am/dataset/novel-coronavirus-covid-19-cases-data
    Esplora all'indirizzo:
    Ultimo aggiornamento set di dati
    31 mag 2023
    Licenza

    Attribution-ShareAlike 4.0 (CC BY-SA 4.0)https://creativecommons.org/licenses/by-sa/4.0/
    Le informazioni sulla licenza sono state recuperate automaticamente

    Descrizione

    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 has Stopped collecting data as of 10 March 2023.

  12. COVID-19 cases worldwide as of May 2, 2023, by country or territory

    • statista.com
    • flwrdeptvarieties.store
    Ultimo aggiornamento: 29 ago 2023
    altre # versioni
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    Statista (2023). COVID-19 cases worldwide as of May 2, 2023, by country or territory [Dataset]. https://www.statista.com/statistics/1043366/novel-coronavirus-2019ncov-cases-worldwide-by-country/
    Esplora all'indirizzo:
    Ultimo aggiornamento set di dati
    29 ago 2023
    Set di dati creato e fornito da
    Statistahttp://statista.com/
    Area coperta
    World
    Descrizione

    As of May 2, 2023, the outbreak of the coronavirus disease (COVID-19) had been confirmed in almost every country in the world. The virus had infected over 687 million people worldwide, and the number of deaths had reached almost 6.87 million. The most severely affected countries include the U.S., India, and Brazil.

    COVID-19: background information COVID-19 is a novel coronavirus that had not previously been identified in humans. The first case was detected in the Hubei province of China at the end of December 2019. The virus is highly transmissible and coughing and sneezing are the most common forms of transmission, which is similar to the outbreak of the SARS coronavirus that began in 2002 and was thought to have spread via cough and sneeze droplets expelled into the air by infected persons.

    Naming the coronavirus disease Coronaviruses are a group of viruses that can be transmitted between animals and people, causing illnesses that may range from the common cold to more severe respiratory syndromes. In February 2020, the International Committee on Taxonomy of Viruses and the World Health Organization announced official names for both the virus and the disease it causes: SARS-CoV-2 and COVID-19, respectively. The name of the disease is derived from the words corona, virus, and disease, while the number 19 represents the year that it emerged.

  13. d

    Washington State Novel Coronavirus (COVID-19) Cases

    • catalog.data.gov
    • data.wa.gov
    Ultimo aggiornamento: 14 mar 2025
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    data.wa.gov (2025). Washington State Novel Coronavirus (COVID-19) Cases [Dataset]. https://catalog.data.gov/dataset/washington-state-novel-coronavirus-covid-19-cases
    Esplora all'indirizzo:
    Ultimo aggiornamento set di dati
    14 mar 2025
    Set di dati fornito da
    data.wa.gov
    Area coperta
    Washington
    Descrizione

    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.

  14. Total number of U.S. COVID-19 cases and deaths April 26, 2023

    • statista.com
    Ultimo aggiornamento: 15 mag 2024
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    Statista (2024). Total number of U.S. COVID-19 cases and deaths April 26, 2023 [Dataset]. https://www.statista.com/statistics/1101932/coronavirus-covid19-cases-and-deaths-number-us-americans/
    Esplora all'indirizzo:
    Ultimo aggiornamento set di dati
    15 mag 2024
    Set di dati creato e fornito da
    Statistahttp://statista.com/
    Area coperta
    United States
    Descrizione

    As of April 26, 2023, the number of both confirmed and presumptive positive cases of the COVID-19 disease reported in the United States had reached over 104 million with over 1.1 million deaths reported among these cases.

    Coronavirus deaths by age in the U.S. Daily new cases of COVID-19 hit record highs in the United States at the beginning of 2022. Underlying health conditions can worsen cases of coronavirus, and case fatality rates among confirmed COVID-19 patients increase with age. The highest number of deaths from COVID-19 have been among those aged 85 years and older, with this age group accounting for over 300 thousand deaths.

    Where has this coronavirus come from? Coronaviruses are a large group of viruses transmitted between animals and people that cause illnesses ranging from the common cold to more severe diseases. The novel coronavirus that is currently infecting humans was already circulating among certain animal species. The first human case of this new coronavirus strain was reported in China at the end of December 2019. The coronavirus was named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and its associated disease is known as COVID-19.

  15. Coronavirus (COVID-19) Infection Survey: technical data

    • ons.gov.uk
    • cy.ons.gov.uk
    xlsx
    Ultimo aggiornamento: 10 mar 2023
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    Office for National Statistics (2023). Coronavirus (COVID-19) Infection Survey: technical data [Dataset]. https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/conditionsanddiseases/datasets/covid19infectionsurveytechnicaldata
    Esplora all'indirizzo:
    xlsxFormati di download disponibili
    Ultimo aggiornamento set di dati
    10 mar 2023
    Set di dati fornito da
    Office for National Statisticshttp://www.ons.gov.uk/
    Licenza

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    Le informazioni sulla licenza sono state recuperate automaticamente

    Descrizione

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

  16. H

    Data from: Coronavirus (COVID-19) Vaccinations

    • data.humdata.org
    csv
    Ultimo aggiornamento: 2 mar 2022
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    HDX (2022). Coronavirus (COVID-19) Vaccinations [Dataset]. https://data.humdata.org/dataset/abd3f359-6fe5-45c4-984c-f0f23f520a7e
    Esplora all'indirizzo:
    csvFormati di download disponibili
    Ultimo aggiornamento set di dati
    2 mar 2022
    Set di dati fornito da
    HDX
    Licenza

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    Le informazioni sulla licenza sono state recuperate automaticamente

    Descrizione

    The map and chart below show the number of COVID-19 vaccination doses administered per 100 people within a given population. Note that this does not measure the total number of people that have been vaccinated (which is usually two doses).

  17. Cumulative cases of COVID-19 worldwide from Jan. 22, 2020 to Jun. 13, 2023,...

    • statista.com
    Ultimo aggiornamento: 15 giu 2022
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    Statista (2022). Cumulative cases of COVID-19 worldwide from Jan. 22, 2020 to Jun. 13, 2023, by day [Dataset]. https://www.statista.com/statistics/1103040/cumulative-coronavirus-covid19-cases-number-worldwide-by-day/
    Esplora all'indirizzo:
    Ultimo aggiornamento set di dati
    15 giu 2022
    Set di dati creato e fornito da
    Statistahttp://statista.com/
    Periodo di tempo coperto
    22 gen 2020 - 13 giu 2023
    Area coperta
    Worldwide
    Descrizione

    As of June 13, 2023, there have been almost 768 million cases of coronavirus (COVID-19) worldwide. The disease has impacted almost every country and territory in the world, with the United States confirming around 16 percent of all global cases.

    COVID-19: An unprecedented crisis Health systems around the world were initially overwhelmed by the number of coronavirus cases, and even the richest and most prepared countries struggled. In the most vulnerable countries, millions of people lacked access to critical life-saving supplies, such as test kits, face masks, and respirators. However, several vaccines have been approved for use, and more than 13 billion vaccine doses had already been administered worldwide as of March 2023.

    The coronavirus in the United Kingdom Over 202 thousand people have died from COVID-19 in the UK, which is the highest number in Europe. The tireless work of the National Health Service (NHS) has been applauded, but the country’s response to the crisis has drawn criticism. The UK was slow to start widespread testing, and the launch of a COVID-19 contact tracing app was delayed by months. However, the UK’s rapid vaccine rollout has been a success story, and around 53.7 million people had received at least one vaccine dose as of July 13, 2022.

  18. Coronavirus (COVID-19) dataset

    • kaggle.com
    Ultimo aggiornamento: 29 apr 2020
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    Balaaje (2020). Coronavirus (COVID-19) dataset [Dataset]. https://www.kaggle.com/balaaje/coronavirus-covid19-dataset/tasks
    Esplora all'indirizzo:
    CroissantCroissant è un formato per i set di dati di machine learning. Scopri di più all'indirizzo mlcommons.org/croissant.
    Ultimo aggiornamento set di dati
    29 apr 2020
    Set di dati fornito da
    Kagglehttp://kaggle.com/
    Autori
    Balaaje
    Descrizione

    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/

  19. COVID-19 cases and deaths per million in 210 countries as of July 13, 2022

    • statista.com
    Ultimo aggiornamento: 25 nov 2024
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    Statista (2024). COVID-19 cases and deaths per million in 210 countries as of July 13, 2022 [Dataset]. https://www.statista.com/statistics/1104709/coronavirus-deaths-worldwide-per-million-inhabitants/
    Esplora all'indirizzo:
    Ultimo aggiornamento set di dati
    25 nov 2024
    Set di dati creato e fornito da
    Statistahttp://statista.com/
    Area coperta
    Worldwide
    Descrizione

    Based on a comparison of coronavirus deaths in 210 countries relative to their population, Peru had the most losses to COVID-19 up until July 13, 2022. As of the same date, the virus had infected over 557.8 million people worldwide, and the number of deaths had totaled more than 6.3 million. Note, however, that COVID-19 test rates can vary per country. Additionally, big differences show up between countries when combining the number of deaths against confirmed COVID-19 cases. The source seemingly does not differentiate between "the Wuhan strain" (2019-nCOV) of COVID-19, "the Kent mutation" (B.1.1.7) that appeared in the UK in late 2020, the 2021 Delta variant (B.1.617.2) from India or the Omicron variant (B.1.1.529) from South Africa.

    The difficulties of death figures

    This table aims to provide a complete picture on the topic, but it very much relies on data that has become more difficult to compare. As the coronavirus pandemic developed across the world, countries already used different methods to count fatalities, and they sometimes changed them during the course of the pandemic. On April 16, for example, the Chinese city of Wuhan added a 50 percent increase in their death figures to account for community deaths. These deaths occurred outside of hospitals and went unaccounted for so far. The state of New York did something similar two days before, revising their figures with 3,700 new deaths as they started to include “assumed” coronavirus victims. The United Kingdom started counting deaths in care homes and private households on April 29, adjusting their number with about 5,000 new deaths (which were corrected lowered again by the same amount on August 18). This makes an already difficult comparison even more difficult. Belgium, for example, counts suspected coronavirus deaths in their figures, whereas other countries have not done that (yet). This means two things. First, it could have a big impact on both current as well as future figures. On April 16 already, UK health experts stated that if their numbers were corrected for community deaths like in Wuhan, the UK number would change from 205 to “above 300”. This is exactly what happened two weeks later. Second, it is difficult to pinpoint exactly which countries already have “revised” numbers (like Belgium, Wuhan or New York) and which ones do not. One work-around could be to look at (freely accessible) timelines that track the reported daily increase of deaths in certain countries. Several of these are available on our platform, such as for Belgium, Italy and Sweden. A sudden large increase might be an indicator that the domestic sources changed their methodology.

    Where are these numbers coming from?

    The numbers shown here were collected by Johns Hopkins University, a source that manually checks the data with domestic health authorities. For the majority of countries, this is from national authorities. In some cases, like China, the United States, Canada or Australia, city reports or other various state authorities were consulted. In this statistic, these separately reported numbers were put together. For more information or other freely accessible content, please visit our dedicated Facts and Figures page.

  20. Cumulative cases of COVID-19 in the U.S. from Jan. 20, 2020 - Nov. 11, 2022,...

    • statista.com
    Ultimo aggiornamento: 17 nov 2022
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    Cumulative cases of COVID-19 in the U.S. from Jan. 20, 2020 - Nov. 11, 2022, by week [Dataset]. https://www.statista.com/statistics/1103185/cumulative-coronavirus-covid19-cases-number-us-by-day/
    Esplora all'indirizzo:
    Ultimo aggiornamento set di dati
    17 nov 2022
    Set di dati creato e fornito da
    Statistahttp://statista.com/
    Periodo di tempo coperto
    20 gen 2020 - 11 nov 2022
    Area coperta
    United States
    Descrizione

    As of November 11, 2022, almost 96.8 million confirmed cases of COVID-19 had been reported by the World Health Organization (WHO) for the United States. The pandemic has impacted all 50 states, with vast numbers of cases recorded in California, Texas, and Florida.

    The coronavirus in the U.S. The coronavirus hit the United States in mid-March 2020, and cases started to soar at an alarming rate. The country has performed a high number of COVID-19 tests, which is a necessary step to manage the outbreak, but new coronavirus cases in the U.S. have spiked several times since the pandemic began, most notably at the end of 2022. However, restrictions in many states have been eased as new cases have declined.

    The origin of the coronavirus In December 2019, officials in Wuhan, China, were the first to report cases of pneumonia with an unknown cause. A new human coronavirus – SARS-CoV-2 – has since been discovered, and COVID-19 is the infectious disease it causes. All available evidence to date suggests that COVID-19 is a zoonotic disease, which means it can spread from animals to humans. The WHO says transmission is likely to have happened through an animal that is handled by humans. Researchers do not support the theory that the virus was developed in a laboratory.

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New York Times, Coronavirus (Covid-19) Data in the United States [Dataset]. https://github.com/nytimes/covid-19-data

Coronavirus (Covid-19) Data in the United States

Esplora all'indirizzo:
csvFormati di download disponibili
Set di dati fornito da
New York Times
Licenza

https://github.com/nytimes/covid-19-data/blob/master/LICENSEhttps://github.com/nytimes/covid-19-data/blob/master/LICENSE

Descrizione

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.