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

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.

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.

2020

Our World in Data - COVID-19

▶ About Our World in Data 🏢

• Our World in Data website
• Our World in Data GitHub

▶ Similar Datasets 📄

• COVID-19 World Vaccination Progress
• The Our World in Data COVID Vaccination Data
• Data on COVID-19 (coronavirus)
• COVID-19 dataset by Our World in Data

▶ Context 📝

The complete COVID-19 dataset is a collection of the COVID-19 data maintained and provided by Our World in Data. Our World in Data team will update it daily throughout the duration of the COVID-19 pandemic.

▶ Content 📃

These are the following information that includes in the dataset: | Metrics | Source | Updated | Countries | | --- | --- | | Vaccinations | Official data collated by the Our World in Data team | Daily | 218 | | Tests & positivity | Official data collated by the Our World in Data team | Weekly | 139 | | Hospital & ICU | Official data collated by the Our World in Data team | Weekly | 39 | | Confirmed cases | JHU CSSE COVID-19 Data | Daily | 196 | | Confirmed deaths | JHU CSSE COVID-19 Data | Daily | 196 | | Reproduction rate | Arroyo-Marioli F, Bullano F, Kucinskas S, Rondón-Moreno C | Daily | 185 | | Policy responses | Oxford COVID-19 Government Response Tracker | Daily | 186 | | Other variables of interest | International organizations (UN, World Bank, OECD, IHME…) | Fixed |

Data dictionary is available below ⤵

▶ Acknowledgements 🙏

I'd like to clarify that I'm only making data about vaccines collected by Our World in Data available to Kaggle community. This dataset is gathered, integrated, and posted the new version on a daily basis, as maintained by Our World in Data on their GitHub repository.

▶ Inspiration 💭

• Forecasting daily new confirmed cases of COVID-19 in specific country.
• Perform data analysis/data visualization of COVID-19 cases/death/etc.

📷 Images by Fusion Medical Animation.

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.

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 latest trend plot. It covers China, Canada, Australia (at province/state level), and the rest of the world (at country level, represented by either the country centroids or their capitals)and the US at county-level. Data sources: WHO, CDC, ECDC, NHC, DXY, 1point3acres, Worldometers.info, BNO, state and national government health departments, and local media reports. . The China data is automatically updating at least once per hour, and non-China data is updating hourly. 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 and JHU Data Services. This layer is opened to the public and free to share. Contact us.

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.

As global communities responded to COVID-19, we heard from public health officials that the same type of aggregated, anonymized insights we use in products such as Google Maps would be helpful as they made critical decisions to combat COVID-19. These Community Mobility Reports aimed to provide insights into what changed in response to policies aimed at combating COVID-19. The reports charted movement trends over time by geography, across different categories of places such as retail and recreation, groceries and pharmacies, parks, transit stations, workplaces, and residential.

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/

Replaced by http://data.europa.eu/88u/dataset/covid-19-coronavirus-data-daily-up-to-14-december-2020

The current dataset contains Tweet IDs for tweets mentioning "COVID" (e.g., COVID-19, COVID19) and shared between March and July of 2020.Sampling Method: hourly requests sent to Twitter Search API using Social Feed Manager, an open source software that harvests social media data and related content from Twitter and other platforms.NOTE: 1) In accordance with Twitter API Terms, only Tweet IDs are provided as part of this dataset. 2) To recollect tweets based on the list of Tweet IDs contained in these datasets, you will need to use tweet 'rehydration' programs like Hydrator (https://github.com/DocNow/hydrator) or Python library Twarc (https://github.com/DocNow/twarc). 3) This dataset, like most datasets collected via the Twitter Search API, is a sample of the available tweets on this topic and is not meant to be comprehensive. Some COVID-related tweets might not be included in the dataset either because the tweets were collected using a standardized but intermittent (hourly) sampling protocol or because tweets used hashtags/keywords other than COVID (e.g., Coronavirus or #nCoV). 4) To broaden this sample, consider comparing/merging this dataset with other COVID-19 related public datasets such as: https://github.com/thepanacealab/covid19_twitter https://ieee-dataport.org/open-access/corona-virus-covid-19-tweets-dataset https://github.com/echen102/COVID-19-TweetIDs

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. Data and Resources phe_deaths_age_london.csv Source: https://coronavirus.data.gov.uk/ phe_deaths_london_boroughs.csv Source: https://coronavirus.data.gov.uk/ phe_vaccines_age_london_boroughs.csv

This repository contains spatiotemporal data from many official sources for 2019-Novel Coronavirus beginning 2019 in Hubei, China ("nCoV_2019") You may not use this data for commercial purposes. If there is a need for commercial use of the data, please contact Metabiota at info@metabiota.com to obtain a commercial use license. The incidence data are in a CSV file format. One row in an incidence file contains a piece of epidemiological data extracted from the specified source. The file contains data from multiple sources at multiple spatial resolutions in cumulative and non-cumulative formats by confirmation status. To select a single time series of case or death data, filter the incidence dataset by source, spatial resolution, location, confirmation status, and cumulative flag. Data are collected, structured, and validated by Metabiota’s digital surveillance experts. The data structuring process is designed to produce the most reliable estimates of reported cases and deaths over space and time. The data are cleaned and provided in a uniform format such that information can be compared across multiple sources. Data are collected at the time of publication in the highest geographic and temporal resolutions available in the original report. This repository is intended to provide a single access point for data from a wide range of data sources. Data will be updated periodically with the latest epidemiological data. Metabiota maintains a database of epidemiological information for over two thousand high-priority infectious disease events. Please contact us (info@metabiota.com) if you are interested in licensing the complete dataset.

On March 5, 2023, Estonia reported about 615.1 thousand confirmed cases of coronavirus (COVID-19). According to the country's Health Board, more than 2.9 thousand people died.

For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

This dataset tracks the updates made on the dataset "Coronavirus COVID-19 Global Cases Dashboard from Johns Hopkins University" as a repository for previous versions of the data and metadata.

This dataset illustrates uptake inequalities of fourth doses of the coronavirus (COVID-19) vaccine using 2021 Census-derived demographic and socio-economic characteristics: age. sex, ethnicity, religion, socio-economic status and self-reported disability and health status.

Vaccination data are produced using linked data from Deaths registrations and Census 2021, National Immunisation Management Service, Hospital Episode Statistics and General Practise Extraction Service data for Pandemic Planning and Research.

Data may differ from weekly administrative vaccination data published by NHS England.