We are releasing a Twitter dataset connected to our project Digital Narratives of Covid-19 (DHCOVID) that -among other goals- aims to explore during one year (May 2020-2021) the narratives behind data about the coronavirus pandemic.In this first version, we deliver a Twitter dataset organized as follows:

Each folder corresponds to daily data (one folder for each day): YEAR-MONTH-DAYIn every folder there are 9 different plain text files named with ""dhcovid"", followed by date (YEAR-MONTH-DAY), language (""en"" for English, and ""es"" for Spanish), and region abbreviation (""fl"", ""ar"", ""mx"", ""co"", ""pe"", ""ec"", ""es""):dhcovid_YEAR-MONTH-DAY_es_fl.txt: Dataset containing tweets geolocalized in South Florida. The geo-localization is tracked by tweet coordinates, by place, or by user information.dhcovid_YEAR-MONTH-DAY_en_fl.txt: We are gathering only tweets in English that refer to the area of Miami and South Florida. The reason behind this choice is that there are multiple projects harvesting English data, and, our project is particularly interested in this area because of our home institution (University of Miami) and because we aim to study public conversations from a bilingual (EN/ES) point of view.dhcovid_YEAR-MONTH-DAY_es_ar.txt: Dataset containing tweets from Argentina.dhcovid_YEAR-MONTH-DAY_es_mx.txt: Dataset containing tweets from Mexico.dhcovid_YEAR-MONTH-DAY_es_co.txt: Dataset containing tweets from Colombia.dhcovid_YEAR-MONTH-DAY_es_pe.txt: Dataset containing tweets from Perú.dhcovid_YEAR-MONTH-DAY_es_ec.txt: Dataset containing tweets from Ecuador.dhcovid_YEAR-MONTH-DAY_es_es.txt: Dataset containing tweets from Spain.dhcovid_YEAR-MONTH-DAY_es.txt: This dataset contains all tweets in Spanish, regardless of its geolocation.

For English, we collect all tweets with the following keywords and hashtags: covid, coronavirus, pandemic, quarantine, stayathome, outbreak, lockdown, socialdistancing. For Spanish, we search for: covid, coronavirus, pandemia, quarentena, confinamiento, quedateencasa, desescalada, distanciamiento social.The corpus of tweets consists of a list of Tweet Ids; to obtain the original tweets, you can use ""Twitter hydratator"" which takes the id and download for you all metadata in a csv file.We started collecting this Twitter dataset on April 24th, 2020 and we are adding daily data to our GitHub repository. There is a detected problem with file 2020-04-24/dhcovid_2020-04-24_es.txt, which we couldn't gather the data due to technical reasons.For more information about our project visit https://covid.dh.miami.edu/ For more updated datasets and detailed criteria, check our GitHub Repository: https://github.com/dh-miami/narratives_covid19/

This dataset contains tweets related to COVID-19. The dataset contains Twitter ids, from which you can download the original data directly from Twitter. Additionally, we include the date, keywords related to COVID-19 and the inferred geolocation. Check detailed information at http://twitterdata.covid19dataresources.org/index.

In the fight against COVID-19, various applications have been developed around the world to stop the spread of the virus in 2020. However, during the first lockdown, the application StopCovid did not meet the expected results that the government had hoped. The second time around, and with rising numbers of infections, the download rate of the new version of the app (called TousAntiCovid) had reached a higher share. But, when French people were asked about their readiness being tracked by a geolocation app in the fight against the crisis, about ** percent were reluctant to do so. About ** percent were ready to do so, if their privacy was guaranteed.

We present GeoCoV19

COVID-19 survey including geographical, behaviour, segmentation, health, conditions, medications and risk values

During the COVID-19 emergency in Italy many patients in need of care and consulting could not access health services the way they used to in the past. For this reason, the interest for telemedicine use to treat patients increased among doctors, in particular general practitioners. According to a survey conducted in June 2020 among general practitioners in Italy, 11 percent of respondents reported that they used telemedicine to conduct examinations before the COVID-19 emergency. However, the share of GPs that would be interest in carrying out tele-examinations reached 54 percent. The interest for the use of telemedicine in the future appeared to be generally high, especially when it involves consulting other colleagues and physicians, or monitoring patients' health status.

Descriptive statistics of the daily number of recordings in March 2019 and 2020 for each state on the weekends and weekdays.

Context

Amidst the COVID-19 outbreak, the world is facing great crisis in every way. The value and things we built as a human race are going through tremendous challenges. It is a very small effort to bring curated data set on Novel Corona Virus to accelerate the forecasting and analytical experiments to cope up with this critical situation. It will help to visualize the country level out break and to keep track on regularly added new incidents.

COVID-19 Country Level Timeseries Dataset

This Dataset contains country wise public domain time series information on COVID-19 outbreak. The Data is sorted alphabetically on Country name and Date of Observation.

Column Descriptions

The data set contains the following columns:
ObservationDate: The date on which the incidents are observed country: Country of the Outbreak Confirmed: Number of confirmed cases till observation date Deaths: Number of death cases till observation date Recovered: Number of recovered cases till observation date New Confirmed: Number of new confirmed cases on observation date New Deaths: Number of New death cases on observation date New Recovered: Number of New recovered cases on observation date latitude: Latitude of the affected country longitude: Longitude of the affected country

Acknowledgements

This data set is a cleaner version of the https://www.kaggle.com/sudalairajkumar/novel-corona-virus-2019-dataset data set with added geo location information and regularly added incident counts. I would like to thank this great effort by SRK.

Original Data Source

Johns Hopkins University MoBS lab - https://www.mobs-lab.org/2019ncov.html World Health Organization (WHO): https://www.who.int/ DXY.cn. Pneumonia. 2020. http://3g.dxy.cn/newh5/view/pneumonia. BNO News: https://bnonews.com/index.php/2020/02/the-latest-coronavirus-cases/ National Health Commission of the People’s Republic of China (NHC): http://www.nhc.gov.cn/xcs/yqtb/list_gzbd.shtml China CDC (CCDC): http://weekly.chinacdc.cn/news/TrackingtheEpidemic.htm Hong Kong Department of Health: https://www.chp.gov.hk/en/features/102465.html Macau Government: https://www.ssm.gov.mo/portal/ Taiwan CDC: https://sites.google.com/cdc.gov.tw/2019ncov/taiwan?authuser=0 US CDC: https://www.cdc.gov/coronavirus/2019-ncov/index.html Government of Canada: https://www.canada.ca/en/public-health/services/diseases/coronavirus.html Australia Government Department of Health: https://www.health.gov.au/news/coronavirus-update-at-a-glance European Centre for Disease Prevention and Control (ECDC): https://www.ecdc.europa.eu/en/geographical-distribution-2019-ncov-cases Ministry of Health Singapore (MOH): https://www.moh.gov.sg/covid-19 Italy Ministry of Health: http://www.salute.gov.it/nuovocoronavirus

AnLoCOV is a large anonymized longitudinal GPS location dataset for studies spanning over pre- and post-COVID periods in Ecuador. This project contains data collected using the Global Positioning System (GPS) from mobile devices. This GPS data was acquired using the Google Location History, accessible in the Google Maps application. It includes data from 338 people over ten years (2012–2022). The dataset's goal is to promote studies on human mobility behavior and activity spaces using GPS data from mobile devices.

The vast majority of surveyed general practitioners in Hungary agreed that the coronavirus (COVID-19) would stay with us in the future and just like in the case of influenza, yearly revaccinations would be necessary in order to gain immunity against the new variants. Only eight percent of the respondents believed that the coronavirus (COVID-19) pandemic would be over within a year or two.

Descriptive statistics of the rank of the proportion of movement out of São Paulo capital city in the days of March 2019 and March 2020.

The data is for COVID-19 clinics.

From 20 October 2023, COVID-19 datasets will no longer be updated. Detailed information is available in the fortnightly NSW Respiratory Surveillance Report: https://www.health.nsw.gov.au/Infectious/covid-19/Pages/reports.aspx.
Latest national COVID-19 spread, vaccination and treatment metrics are available on the Australian Government Health website: https://www.health.gov.au/topics/covid-19/reporting?language=und

This dataset provides data on COVID-19 testing and assessment clinics by geolocation, address, contact details, services provided and opening hours.

This data is subject to change as clinic locations are changed.

The Government has obligations under the Privacy and Personal Information Protection Act 1998 and the Health Records and Information Privacy Act 2002 in relation to the collection, use and disclosure of the personal, including the health information, of individuals. Information about NSW Privacy laws is available here: https://data.nsw.gov.au/understand-key-data-legislation.

The information published about COVID-19 clinics does not include any information to directly identify individuals, such as their name, date of birth or address.

Other governments and private sector bodies also have legal obligations in relation to the protection of personal, including health, information. The Government does not authorise any reproduction or visualisation of the data on this website which includes any representation or suggestion in relation to the personal or health information of any individual. The Government does not endorse or control any third party websites including products and services offered by, from or through those websites or their content.

For any further enquiries, please contact us at datansw@customerservice.nsw.gov.au

Several nations are currently experiencing a significant increase in coronavirus (COVID-19), including Indonesia. A total of 34,874,744 confirmed cases with 1,097,497 deaths (case fatality rate (CFR) 3.1%) were reported in 216 countries based on data from World Health Organization. COVID-19 remains public health problem around the world. It is possible the climate could affect the transmission of COVID-19. The wind is one of the climate factors besides temperature, humidity, and rainfall. Wind speed data can be used to study the spread of COVID-19 cases., The wind speed data was taken from the Meteorology, Climatology, and Geophysics Agency's data website (https://dataonline.bmkg. go.id/home). The wind speed (maximum and mean) in Jakarta from the pandemic inception, specifically between March and September 2020. These records were obtained from the website of the Jakarta Provincial Health Office and the website of the Indonesian Meteorology, Climatology, and Geophysics Agency. Subsequently, the general information was converted into 31-week documentation. Furthermore, a basic map of Jakarta with neighboring community boundaries was obtained using the GADM Map and Data site. Coordinates for the weather monitoring stations were accessed online from (https://www.gps-latitude-longitude.com/).,

Descriptive statistics of the rank of the proportion of movement out of Rio de Janeiro capital city in the days of March 2019 and March 2020.

According to a survey conducted in Australia, 67 percent of the general practitioners felt more positive toward using telehealth in their practice due to the coronavirus pandemic. In comparison, only 10 percent of the survey respondents held more negative opinions toward using telehealth in their practices.

During the COVID-19 emergency in Italy many patients in need of care and consulting could not access health services the way they used to in the past. For this reason, digital communication channels have become central in the interaction between patients and doctors, in particular general practitioners. According to a survey conducted in June 2020 among general practitioners in Italy, ** percent of respondents reported that they used emails to communicate with patients. This figure reached ** percent when including general practitioners interested in implementing this communication method. On the other hand, only **** percent of GPs said that they used collaboration platforms such as Skype. In this case, this figure reached ** percent when including also GPs who showed interested in the introduction of this kind of tools in the future.

Independent predictors of incident symptoms.

This dataset provides information on the sites where tests can be carried out: * Site identifiers * Location and geolocation of the site * Methods of sampling * The type of audience welcomed * The opening hours of the site * Whether or not you need to make an appointment * Telephone number and email address or website to make an appointment if necessary

Context

These data are collected through an online survey of public and private medical biology laboratories carrying out nasopharyngeal samples for analysis by RT-PCR known as PCR for SARS-CoV2 RNA.

Producer

The survey is set up by the DGS Health Crisis Centre. The technical implementation is carried out by the DREES health.

Data

This dataset provides information on the sites where virological testing (RT-PCR) can be performed: — Site identifiers — Location and geolocation of the site — The method of collection — Type of public welcomed — The opening hours of the site — Opening hours of the site for priority people — Whether or not to make an appointment — Telephone number and email address or website to make an appointment if necessary — The latest update date of one of the laboratories attached to the legal identifier

Point of attention on data

Please note that:

— The data are likely to evolve regularly when inaccuracies are identified or the laboratories modify, in agreement with the ARS, their public reception arrangements for carrying out naso-pharyngeal samples; — not all sampling sites welcome the general public. A table for restricted sites is offered separately. Please refer to the “public” column to inform you of the type of audience being welcomed.

Diffusion

The broadcast site general public sante.fr integrates this data daily.

About the data

By default, geographic coordinates are collected from the FINESS database of geolocated establishments.

Otherwise laboratories can enter the address manually, the input is based on the API address made available to Etalab.

When the geo API does not find the desired address, the lab places the marker on the map and checks the associated address using the reverse geocoding function (reverse) of the geo API.

Lexicon

— API = Application Programming Interface — Drees = Directorate of Research, Studies, Evaluation and Statistics at the Ministry of Solidarity and Health — DGS = Directorate-General for Health — Ars = Regional Health Agency

File columns

— ‘ID’: Identifier — ‘id_ej’: Legal Finess — ‘Finess’: Geographical Finess — ‘RS’: Company name — ‘address’: Address — ‘cpl_loc’: Complement localisation — ‘do_prel’: Performs RT-PCR test — ‘do_antigenic’: Performs antigenic test — ‘longitude’: Longitude — ‘latitude’: Latitude — ‘mod_prel’: Method of collection — ‘public’: Audiences welcomed — ‘time’: Schedule — ‘schedule_prio’: Priority persons schedule — ‘check_rdv’: With or without an appointment — ‘tel_rdv’: Phone made appointment — ‘web_rdv’: Website made an appointment — ‘modif_date’: Last update date

According to a survey conducted in Australia among general practitioners, around ** percent of respondents said they provided care to their patients using the telephone during the coronavirus pandemic in early 2020. Prior to the pandemic only ** percent of respondents had offered care using the telephone.