The Covid-19 pandemic strongly impacted the state of health in France. Furthermore, people among the French population were not impacted the same way. The virus indeed appeared more lethal depending one the age of people. The most vulnerable ones were elderly people. As of June 22, 2021, 73 percent of people aged 75 years and older were victims of the novel coronavirus (Covid-19) in France.

The novel coronavirus (COVID-19) caused a certain number of deaths within the French population. With 29,101 victims, the Paris Region, Île-de-France, recorded the highest number of deaths in France as of June 30, 2023. On the other hand, the regions of metropolitan France least affected were those of Brittany and Corsica. 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The dataset is no longer updated.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

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

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.

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.

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.

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.

The Coronavirus (SARS-CoV-2) outbreak, dubbed COVID-19, is first and foremost a human tragedy, affecting millions of people globally. The contagious Coronavirus, which broke out at the close of 2019, has led to a medical emergency across the world, with the World Health Organization officially declaring the novel Coronavirus a pandemic on March 11, 2020. Read More

COVID-19 data for France from 2020-01-23 to 2023-06-30, including cur_cas, cur_hospitalises, cur_reanimation, cur_tx_pos, tot_dc, tot_dc_esms, tot_dc_hosp

Files:

• ".pkl" Cache file backup
• Dataframe exported "PyCoa-DF.csv"
• Original database backup

Santé publique France's mission is to improve and protect the health of populations. During the health crisis linked to the COVID-19 epidemic, Public Health France is responsible for monitoring and understanding the dynamics of the epidemic, anticipating the different scenarios and implementing actions to prevent and limit the transmission of this virus on the national territory.

Daily hospital data relating to the COVID-19 epidemic by department and sex of the patient: number of hospitalized patients, number of people currently in intensive care or intensive care, cumulative number of people returned home, cumulative number of people who died.

For some patients, gender was not identified in the database. This can lead to a discrepancy between the H/F sum of an indicator and the total number of this indicator.

The region and iso 3166-1 codes of the zones have been added.

Warning: data under construction. May contain anomalies or missing data.

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

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.

Data and code to reproduce the analysis of our article.

# Contents

`code/`: Analysis code.
The main analysis file is `vaccination-indicators.Rmd`.
Some results are exported in `out*.RData` files.

`data/`: Data used for the analysis.
The data are treated by the `code/0_INSEE_predictors.R` script, and saved as `code/data_indicators.RData`, which is the file used for analysis.

`ms/`: Manuscript files; they are outdated (the ms was later modified with Word), but `ms.Rmd` contains code to reproduce the figures and some numerical values given in the text.

# Data Sources

- Vaccination data from Assurance Maladie:
- EPCI: <https://datavaccin-covid.ameli.fr/explore/dataset/donnees-devaccination-par-epci/>
- Paris, Marseille, Lyon: <https://datavaccin-covid.ameli.fr/explore/dataset/donnees-de-vaccination-parcommune/information/>

- Geographic information:
- EPCI: <https://datavaccin-covid.ameli.fr/explore/dataset/georef-france-epci/>
- Paris, Marseille, Lyon: <https://datavaccin-covid.ameli.fr/explore/dataset/georef-france-commune-arrondissement-municipal/>

- Socio-economic indicators from INSEE: <https://www.insee.fr/fr/statistiques/5359146#consulter>

- 2017 Presidential election:
- <https://www.data.gouv.fr/fr/datasets/election-presidentielle-des-23-avril-et-7-mai-2017-resultats-definitifs-du-1er-tour-par-communes/#resource-d282e53a-d273-425d-95bb-8a0d7632c79a-header>
https://www.data.gouv.fr/fr/datasets/election-presidentielle-des-23-avril-et-7-mai-2017-resultats-du-2eme-tour-2/
- Paris: <https://opendata.paris.fr/explore/dataset/elections-presidentielles-2017-1ertour/export/?disjunctive.id_bvote&disjunctive.num_circ&disjunctive.num_quartier&disjunctive.num_arrond&sort=-num_arrond>
- Marseille: <https://trouver.datasud.fr/dataset/82a6d91c-c81d-423c-9a4a-3f76d121c8ce/resource/03e2ef07-c2d0-41dd-b503-26910ecb15c3/download/marseille_presidentielles2017_tour1.csv>
- Lyon: <https://www.interieur.gouv.fr/Elections/Les-resultats/Presidentielles/elecresult_presidentielle-2017/(path)/presidentielle-2017/084/069/069L.html>

This data set contains COVID-19 hospital incidence, temperature and human mobility and contact data recorded between 2020-03-24 and 2021-03-30 used in the paper:

Selinger et al. 2021: Predicting COVID-19 incidence in French hospitals using human contact network analytics. 10.1016/j.ijid.2021.08.029

See methods in the article for detailed descriptions and the data curation process.

1) cov_mob_tst_national.csv contains national-level data

The columns comprise:

incid_hosp: hospital admission incidence

incid_rea: ICU admission incidence

incid_dc: hospital death incidence

incid_rad: incidence of those returned home

within_departement_colocation_X%: X%-quantile of colocation probabilities with départements

between_departement_colocation_X%: X%-quantile of colocation probabilities between départements

fb_population_coverage_X%: X%-quantile of ratio of fb_population over census population in département

null_links_X%: X%-quantile of null links across départements

clustering_X%: X%-quantile of clustering coefficients across départements

ricci_X%: X%-quantile of curvature across départements

ricci_min_X%: X%-quantile of minimum curvature across départements

ricci_mean_X%: X%-quantile of average curvature across départements

ricci_max_X%: X%-quantile of maximum curvature across départements

strength_X%: X%-quantile of network strengths across départements

betweenness_centrality_X%: X%-quantile of betweenness_centrality scores across départements

positive_test_ratio_weekly: ratio of weekly cumulated positive tested over weekly cumulated tests

retail_and_recreation_percent_change_from_baseline: Google Mobility Reports

grocery_and_pharmacy_percent_change_from_baseline: Google Mobility Reports

parks_percent_change_from_baseline: Google Mobility Reports

transit_stations_percent_change_from_baseline: Google Mobility Reports

workplaces_percent_change_from_baseline: Google Mobility Reports

residential_percent_change_from_baseline: Google Mobility Reports

mean_temperature_X%: X% quantile of mean daily temperatures averaged over the week across départements

min_temperature_X%: X% quantile of minimum daily temperatures averaged over the week across départements

max_temperature_X%: X% quantile of maximum daily temperatures averaged over the week across départements

2) cov_mob_dep.csv contains département-level data

The columns comprise:

dep: département code

incid_hosp: hospital admission incidence

incid_rea: ICU admission incidence

incid_dc: hospital death incidence

incid_rad: incidence of those returned home

week: week (matched to colocation data recording usually on Tuesdays)

dep_name: name of the département

null_links: number of null links

betweenness_centrality: betweenness centrality

clustering: clustering coefficient

strength: network strength

ricci_mean: minimum curvature among all edges incident to a département

ricci_min: mean curvature across all edges incident to a département

ricci_X%: X%-quantile curvature among all edges incident to a département

fb_population: number of facebook users

facebook_colocation_within_dep: colocation probability within département

fb_population_coverage: ratio of fb_population over census population in département

facebook_colocation_between_dep_X%: X%-quantile of facebook colocation among all edges incident to the département

min_temperature: minimum daily temperature averaged over the week

max_temperature: maximum daily temperature averaged over the week

mean_temperature: mean daily temperature averaged over the week

incid_hosp_Y: incidence of hospital admission from Ynd most colocated département

incid_rea_Y: incidence of ICU admission from Ynd most colocated département

incid_dc_Y: incidence of hospital deaths from Ynd most colocated département

incid_rad_Y: incidence of returned home from Ynd most colocated département

GlobalData has revised downwards the forecast for the construction industry growth to -2%, with the high likelihood of further cuts if activity in the short-term is more severely disrupted than currently anticipated. Read More

This graph shows the impact of coronavirus (COVID-19) on the daily number of new car registrations in France during March 2020. During that month, daily registrations peaked at 6,403 new cars on March 10, before plummeting to around 300 daily registrations from March 14 onwards. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

Lockdown measures to limit the spread of Covid-19 in France in spring 2020 sharply reduced activities and lowered air-pollution concentrations. This study sought to determine the short- and long-term impacts on mortality in metropolitan France resulting from the temporary decrease in the population's exposure to air pollution. The reduction in exposure to air pollution was estimated by calculating the difference between modeled exposure of the population during the strict lockdown and the gradual lifting, and the simulated exposure that would have been observed in the absence of lockdown. A quantitative health impact assessment was used to estimate both the short-term impact of PM10 and NO2 reductions, and the long-term impact of PM2.5 and NO2 reductions on mortality. Reduced activities during the lockdown lowered NO2 and PM concentrations, resulting in about 2,300 deaths postponed for PM2.5 and nearly 1,200 for NO2, mainly due to avoided long-term effects. This study shows that, even in an unprecedented context that is certainly neither realistic nor desirable to improve air quality in the long run, public interventions appear to have a significant impact on health through reductions in air-pollution levels. In a long-term perspective, the study also reminds us that the total burden of air pollution on health remains a significant risk factor in France. Efforts to reduce ambient air pollution must thus be pursued sustainably for all sources of air pollution with suitably adapted but ambitious policies. Finally, the lockdown restrictions had other consequences, both positive and negative, on the population's health. These consequences highlight the need to conduct more integrated assessments of health impacts that include the multisectoral consequences of interventions, particularly in terms of population compliance with mitigating restrictions, behavior and mental health and, more broadly, climate change.

The statistic shows the activity of the sector-wide online commerce after the outbreak of the coronavirus (Covid-19) in France in March and April 2020, in terms of taffic rate development. Between the 24th of February and 26th of April 2020, travel and tourism websites showed the biggest fall of around 79 percent in terms of traffic, followed by the automobile industry with an approximate 60 percent downfall as of March 29th, compared to the week between February 6 and 16, 2020. Online pharmacies had the most increase in traffic, with almost 64 percent on March 15th. General retailers and mass distribution reported a rise of almost 200 percent in traffic rates on the 29th of March. For all sectors, the traffic increased and reached almost 10 percent up until the 22nd of March and almost 20 percent on March 29th 2020. Up until April 26th 2020, High-Tech and Marketplaces traffic rate increased by 26 percent. Banks and Insurances grew by around seven percent, compared to the week in January.

This statistic shows the number of confirmed COVID-19 (coronavirus) cases in France as of March 25, 2020, split down by region. On that day (2:00 pm), there were a total of 25,233 cases registered in all of France. With 7,660 cases, the Paris region (Ile-de-France) was the region most touched by the outbreak. The overseas regions registered a total of 313 cases.

SARS-CoV-2 coronavirus

Coronaviruses are a large family of viruses that cause illnesses ranging from a common cold to more severe conditions. But the virus in question here is a new coronavirus which causes a lung disease which has been named COVID-19 (Corona virus disease 2019). It made its first appearance back in December 2019 in the Chinese city of Wuhan. According to Chinese authorities, people infected with the virus could have contracted it by consuming products of animal origin from a large city market, the Huanan Seafood Wholesale Market. On March 11, the World Health Organization classified COVID-19 as a pandemic.

The situation in France

Although the number of confirmed cases is far less important than it is in China, France nevertheless features among the countries most affected by the outbreak. During a survey conducted in mid-March, 35 percent of French people stated being very worried about the spread of this new virus and 49 percent were rather worried. As of March 26, 1,333 people out of 25,600 infected had died from the virus and 3,907 had been listed as cured.

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