As of November 24, 2024, France has reported over 39 million coronavirus cases and roughly 168,100 deaths. Like many countries in the world, France has been strongly impacted by the COVID-19 virus.For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

As of July 28, 2024, the French health authorities registered close to 39 million confirmed cases of COVID-19 in France. The first cases of the disease were recorded by the end of January 2020, with the highest increase in cases taking place between December 2021 and March 2022.

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

Context

COVID-19 has infected many people in France.

Content

The dataset is no longer updated. It contains almost all French metropolitan regions plus overseas regions, updated on March 09 2020. If you want to help updating this dataset, see contributions section below.

This dataset intention is to put all published information about COVID-19 patients in France in a csv file.

Acknowledgements

Source of data: Press releases of the French regional health agencies. Data transcripted in a csv by a GitHub community.

This work is inspired by a similar work made in South Korea: kaggle dataset.

Contributions

We need more contributors to build this dataset and keep it updated. Join us on GitHub.

Contributors: Lior Perez, Samia Drappeau, Manon Fourniol, Zoragna, Raphaël Presberg

France recorded 383768 Coronavirus Recovered since the epidemic began, according to the World Health Organization (WHO). In addition, France reported 127869 Coronavirus Deaths. This dataset includes a chart with historical data for France Coronavirus Recovered.

The number of COVID-19 vaccination doses administered in France rose to 154451978 as of Oct 27 2023. This dataset includes a chart with historical data for France Coronavirus Vaccination Total.

In past 24 hours, France, Europe had N/A new cases, N/A deaths and N/A recoveries.

Context

This are data useful to track and possibly predict the spread in France of 2019-nCoV, a highly contagious coronavirus that originated from Wuhan (Hubei province), Mainland China. France is a neighboring country of the second mainly infected at the time this database has been created, Italy

Content

Main dataset (France) is sourced from the governamental site:

https://www.data.gouv.fr/en/datasets/chiffres-cles-concernant-lepidemie-de-covid19-en-france/ or the daily updated repository https://github.com/opencovid19-fr

Data for China have been obtained from:

https://data.gov.hk/en-data/dataset/hk-dh-chpsebcddr-novel-infectious-agent

Those for Italy and Piedmont region are from the national website

http://www.protezionecivile.gov.it

Acknowledgements

Thanks to the French government that openly shares these important data to us.

France recorded 38989402 Coronavirus Cases since the epidemic began, according to the World Health Organization (WHO). In addition, France reported 163279 Coronavirus Deaths. This dataset includes a chart with historical data for France Coronavirus Cases.

Ce tableau de bord fournit une mise à jour quotidienne de la progression du Coronavirus COVID-19 en France (Métropole et DOM).Il se base sur les données publiées quotidiennement par Santé Publique France.Il comptabilise et représente :Le nombre de cas confirmés au niveau nationalLe nombre de décès au niveau nationalLe nombre de cas confirmés par région (sous forme de graphique et de carte par symboles proportionnels)La part des cas confirmés par rapport à la population, par région (sous forme de carte par dégradé de couleurs)L'évolution dans le temps du nombre de cas confirmés (sous forme de graphique) Il est optimisé pour être affiché sur un navigateur web (ordinateur ou tablette).Il fournit également un lien vers le tableau de bord national en version optimisée pour mobile.Visiter le site Esri France

Since the start of the COVID-19 pandemic in France, the level of concern towards the virus fluctuated a lot. While less than half of French people were not worried about the spread of the virus in January 2020, the share of worried people reached a peak (85 percent of respondents) during march 2020. Overall, there was a resurgence of concern about the COVID-19 virus with each announcement of a new lockdown by the French government.

The novel coronavirus (COVID-19)

Coronaviruses are a large family of viruses that cause illnesses ranging from a common cold to more severe conditions such as MERS or SARS. One of those viruses that have recently been identified is named COVID-19 or SARS-CoV-2. It was first detected in December 2019 in the Chinese city of Wuhan. According to the investigation of the Chinese authorities, people infected with the virus would have contracted it by consuming products (some of which are sold illegally) of animal origin from a large city market, the Huanan Seafood Wholesale Market (since closed). The transmission of this virus is likely to occur through the respiratory tract (exhalation, sneezing, coughing) and physical contact. The symptoms are similar to those of classic flu: fever, cough, breathing difficulties, muscle pain, and fatigue.

The pandemic situation in France

Although the data is changing daily, 5.7 million people infected by the COVID-19 virus have been identified in France since the beginning of the pandemic. Among them, more than 100,000 succumbed to this disease. As in many other countries, the French government is counting on its vaccination campaign to stop the epidemic.

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

This data package includes the underlying data and files to replicate the calculations, charts, and tables presented in When more delivers less: Comparing the US and French COVID-19 crisis responses, PIIE Policy Brief 20-9. If you use the data, please cite as: Cohen-Setton, Jérémie, and Jean Pisani-Ferry. (2020). When more delivers less: Comparing the US and French COVID-19 crisis responses. PIIE Policy Brief 20-9. Peterson Institute for International Economics.

New deaths from Covid during a month in France, March, 2023 The most recent value is 717 new deaths from Covid as of March 2023, a decline compared to the previous value of 750 new deaths from Covid. Historically, the average for France from February 2020 to March 2023 is 4267 new deaths from Covid. The minimum of 2 new deaths from Covid was recorded in February 2020, while the maximum of 21037 new deaths from Covid was reached in April 2020. | TheGlobalEconomy.com

View daily updates and historical trends for France Coronavirus Full Vaccination Rate. Source: Our World in Data. Track economic data with YCharts analyti…

WHO: COVID-2019: Number of Patients: Confirmed: To-Date: France data was reported at 38,997,490.000 Person in 24 Dec 2023. This stayed constant from the previous number of 38,997,490.000 Person for 23 Dec 2023. WHO: COVID-2019: Number of Patients: Confirmed: To-Date: France data is updated daily, averaging 9,850,650.000 Person from Jan 2020 (Median) to 24 Dec 2023, with 1431 observations. The data reached an all-time high of 38,997,490.000 Person in 24 Dec 2023 and a record low of 0.000 Person in 25 Jan 2020. WHO: COVID-2019: Number of Patients: Confirmed: To-Date: France data remains active status in CEIC and is reported by World Health Organization. The data is categorized under High Frequency Database’s Disease Outbreaks – Table WHO.D002: World Health Organization: Coronavirus Disease 2019 (COVID-2019): by Country and Region (Discontinued). In 05 March 2020 report, the figures were reduced from prior situation reports due to separation of territories. Due to some inclusions and exclusions of cases that are not properly reflected in WHO report, which are the result of the retrospective adjustments of national authorities, some current day “To-date” figures will not tally to the sum of previous day “To-date” cases and current day new reported cases. Figures with excluded cases are relatively lower compared to the previous day.

Context

This dataset contains around 6k articles related to COVID-19 from 69 french-speaking news websites.

Content

• date_publish: Date of the publication. Some dates are inaccurate.
• title: Headline of the article.
• description: Short description of the article.
• maintext: Main content of the article. Some data are truncated because a subscription is required.
• url: URL of the article.
• labels: Categories of the article.

Acknowledgements

This dataset was collected from lemonde.fr, lefigaro.fr, liberation.fr, leparisien.fr, lesechos.fr, la-croix.com, lequipe.fr, slate.fr, latribune.fr, nouvelobs.com, lexpress.fr, marianne.net, francesoir.fr, leprogres.fr, lejdd.fr, linternaute.com, telerama.fr, bfmtv.com, lci.fr, francetvinfo.fr, boursorama.com, rtl.fr, clubic.com, huffingtonpost.fr, capital.fr, ledauphine.com, parismatch.com, europe1.fr, legorafi.fr, lalibre.be, lesoir.be, closermag.fr, elle.fr, esprit.presse.fr, sciencesetavenir.fr, politis.fr, caminteresse.fr, femmeactuelle.fr, nationalgeographic.fr, voici.fr, regards.fr, larecherche.fr, lhistoire.fr, journalmetro.com, dhnet.be, letemps.ch, levif.be, lesaffaires.com, lactualite.com, rtbf.be, franceinter.fr, lepetitjournal.com, lapresse.ca, futura-sciences.com, science-et-vie.com, pourlascience.fr, demotivateur.fr, buzzbeed.com, nordpresse.be, bopress.ma, secretnews.fr, letelegramme.fr, numerama.com, laprovence.com, ladepeche.fr, midilibre.fr, telestar.fr, courrierinternational.com and melty.fr.

Inspiration

• Study the media impact of COVID-19
• Analyze different writing styles
• Sentiment Analysis
• News generation

Citation

If you're using this dataset for research purposes, please use the following BibTex for citations:

@dataset{covidfrenchnews,
 author = {Gustave Cortal},
 year = {2021},
 month = {03},
 title = {COVID-19: French news dataset},
 url = {https://www.gustavecortal.com}

}

Total Covid deaths per million in France, March, 2023 The most recent value is 2506 total Covid deaths as of March 2023, an increase compared to the previous value of 2495 total Covid deaths. Historically, the average for France from February 2020 to March 2023 is 1562 total Covid deaths. The minimum of 0 total Covid deaths was recorded in February 2020, while the maximum of 2506 total Covid deaths was reached in March 2023. | TheGlobalEconomy.com

Data about CODIV-19 from Santé Publique France Website from 2020-02-28 until 2020-03-10 Unfortunately, from April, SPF don't provide data for each région (area). So I stop to use SPF source from April until now.

Because this website was changing every week, from html to PDF format, I had to start with scrapy directly on html data and finish with PDF files. Data was taken directly into HTML and PDF automatically.

The website page was : https://www.santepubliquefrance.fr/maladies-et-traumatismes/maladies-et-infections-respiratoires/infection-a-coronavirus/articles/infection-au-nouveau-coronavirus-sars-cov-2-covid-19-france-et-monde

The kernel to see how to use PDF miner or Scrapy is there : https://www.kaggle.com/jeugregg/coronavirus-visualization-modeling

Since December 2019, a new agent, the SARS-Cov-2 coronavirus has been rapidly spreading from China to other countries causing an international outbreak of respiratory illnesses named COVID-19. In France, the first cases have been reported at the end of January with more than 60000 cases reported since then. A significant proportion (20-30%) of hospitalized COVID-19 patients will be admitted to intensive care unit. However, few data are available for this special population in France.

We conduct a large observational cohort of ICU suspected or proven COVID-19 patients that will enable to describe the initial management of COVID 19 patients admitted to ICU and to identify factors correlated to clinical outcome.

Context

Try to scrap data from official website of South Korea & France linked to COVID-19 confirmed cases and death in 2020

Content

Script to scrap data (France Publique Santé et South Korean KCDC) Results of scrapy : Data of COVID-19 confirmed cases & deaths Use direct link to differents sources : look at Acknowledgements

I use a very simple R0 model to try to evaluate what would happened without lock-down in Hubei, France, South-Korea, Italy in this https://www.kaggle.com/jeugregg/coronavirus-visualization-modeling

Acknowledgements

The world data is taken from https://github.com/CSSEGISandData/COVID-19 provided by JHU CSSE

South Korea areas data are retrieved with scrapy from online KCDC Press Release articles at https://www.cdc.go.kr/board/board.es?mid=a30402000000&bid=0030.

France areas data are taken with scrapy from online santepubliquefrance.fr Press articles at https://www.santepubliquefrance.fr/maladies-et-traumatismes/maladies-et-infections-respiratoires/infection-a-coronavirus/articles/infection-au-nouveau-coronavirus-sars-cov-2-covid-19-france-et-monde and https://www.worldometers.info/coronavirus/country/france/ but until 25th March 2020.

For Global France, data are from https://www.data.gouv.fr/fr/datasets/donnees-relatives-aux-resultats-des-tests-virologiques-covid-19/

For Global Italy, Germany, Hubei data are from https://www.worldometers.info/coronavirus/

Inspiration

What is the result of how each countries try to struggle this virus ?

Work in progress

This dataset comes from https://github.com/scrouzet/covid19-incrementality If you want to get a fresh data update, please go to this repo.

covid19-incrementalite

Study on incrementality of COVID-19 effect. Objective : quantify death increase due to COVID-19 in France at a department level.

References

• https://medium.com/@davidbessis/coronavirus-the-core-metrics-we-should-be-looking-at-2ca09a3dc4b1

Data sources

Death data form INSEE (French Statistic Agency) : https://www.data.gouv.fr/fr/datasets/fichier-des-personnes-decedees/

Geography referential (commune and departement) : https://geo.api.gouv.fr

Population data time serie from INSEE : https://www.insee.fr/fr/statistiques/1893198

Methodology

Data preparation :

• Collection and concatenation of yearly death data (1990=> 2019)
• Deleted " replaced with white space
• retreated dates : removed lines with invalid birth or death dates (0,72% of cases)
• fitler death dates> 1970
• join with geography referential to assiciate commune with department
• correction of department for specific geographies (Lyon, Paris, Marseille with arrondissement code instead of comune code in INSEE File)
• Grouping by death department, death date, sex, age, year of observation

Colonnes du fichier : data/INSEE_deces_2010_2019.zip

• year of observation (annee_comptabilisation) = year of the yearly file where the death has been accounted for. (2019 = deces_2019.txt). Please note that a yearly file contains death dates from previous yeras due to delay in data collection at insee. All files must be concatenated to get a complete view of death for a given year. Duplicate records are already removed.
• sexe : 1 = Male / 2 = Female
• age : age at death time
• departement_deces : department code of the commune where death happend. Note that some department are not valid in the repository : 1% death in "99" departement, non significative death cases in "98" department. The department name and associated region is provided in the geography referential
• date_deces : death_date
• nb_deces : count of deceased person, grouped by (anneee_comptabilisation, sex, age, departement_code, date_deces)

Modélisation

WORK IN PROGRESS - Modélisation par classe d'age et par département - Retraitement de la canicule 2003 - redressement des données hebdo de l'INSEE pour estimer l'effet de décallage dans la remontée des information (délai entre survenance du délai et comptabilisation par l'INSEE)

Preprocessing

The pickle files in 'preprocessed' directory have been generated with data from the 'data' directory. See original repo for preprocessing method.

How to contribute

1. Fork this repo
2. Commit your code in your forked repo
3. Do a pull-request on the main repo and ask for code reviewers
4. Take into account the comments

For contributors 1. Make a branch "feat-short_name_feature" 2. Commit your code in this branch 3. Do a pull-request on the main repo and ask for code reviewers 4. Take into account the comments