Hospital emergency and SOS Médecins data on the COVID-19 epidemic in Île-de-FranceDonnées urgences hospitalières - SOS Médécins relatives à l'épidémie de COVID-19 en Île-de-France
Données urgences hospitalières - SOS Médécins relatives à l'épidémie de COVID-19 en Île-de-FranceHospital emergency and SOS Médecins data on the COVID-19 epidemic in Île-de-France
This dataset provides data on hospital emergency department visits and SOS Médecins consultations related to the COVID-19 epidemic in the Île-de-France region. It is published as part of the work of Santé publique France, the French national public health agency, whose mission is to improve and protect population health. During the health crisis, the agency monitored and analysed the epidemic's dynamics, anticipated possible scenarios, and supported public health decision-making. The data can be used to track the regional evolution of emergency healthcare demand linked to COVID-19 over time.Santé publique France a pour mission d'améliorer et de protéger la santé des populations. Durant la crise sanitaire liée à l'épidémie du COVID-19, Santé publique France se charge de surveiller et comprendre la dynamique de l'épidémie, d'anticiper les différents scénarii et de mettre en place des...
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Data schema (23 fields)
Click a field to see example values.
| Fill | Field | Type | Description |
|---|---|---|---|
| 100% | dep_codereg | text | Department code.Department code. |
| 100% | datedate_de_passage | date | Date of emergency room visit.Date of emergency room visit. |
| 100% | nb_pass_emgy_covidnbre_pass_corona | int | Number of emergency room visits for suspected COVID-19.Nombre de passages aux urgences pour suspicion de COVID-19 |
| 100% | tot_pass_emgynbre_pass_tot | int | Total number of emergency room visits.Nombre de passages aux urgences total |
| 100% | nb_ho_emgy_covidnbre_hospit_corona | int | Number of hospitalizations among COVID-19 suspected emergency visits.Nombre d'hospitalisations parmi les passages aux urgences pour suspicion de COVID-19 |
| 14.3% | nb_pass_emgy_covid_mnbre_pass_corona_h | int | Number of male emergency room visits for suspected COVID-19.Number of male emergency room visits for suspected COVID-19. |
| 14.3% | nb_pass_emgy_covid_fnbre_pass_corona_f | int | Number of female emergency room visits for suspected COVID-19.Number of female emergency room visits for suspected COVID-19. |
| 14.3% | tot_pass_emgy_mnbre_pass_tot_h | int | Total number of male emergency room visits.Total number of male emergency room visits. |
| 14.3% | tot_pass_emgy_fnbre_pass_tot_f | int | Total number of female emergency room visits.Total number of female emergency room visits. |
| 14.3% | nb_ho_emgy_covid_mnbre_hospit_corona_h | int | Number of male hospitalizations among suspected COVID-19 emergency visits.Number of male hospitalizations among suspected COVID-19 emergency visits. |
| 14.3% | nb_ho_emgy_covid_fnbre_hospit_corona_f | int | Number of female hospitalizations among suspected COVID-19 emergency visits.Number of female hospitalizations among suspected COVID-19 emergency visits. |
| 59.5% | nb_acte_sos_covidnbre_acte_corona | int | Number of SOS Médecins medical acts for suspected COVID-19.Nombres d'actes médicaux SOS Médecins pour suspicion de COVID-19 |
| 59.5% | tot_acte_sosnbre_acte_tot | int | Total number of SOS Médecins medical acts.Nombres d'actes médicaux SOS Médecins total |
| 8.5% | nb_sos_covid_mnbre_acte_corona_h | int | Number of male SOS Médecins acts for suspected COVID-19.Number of male SOS Médecins acts for suspected COVID-19. |
| 8.5% | nb_sos_covid_fnbre_acte_corona_f | int | Number of female SOS Médecins acts for suspected COVID-19.Number of female SOS Médecins acts for suspected COVID-19. |
| 8.5% | tot_sos_mnbre_acte_tot_h | int | Total number of male SOS Médecins medical acts.Total number of male SOS Médecins medical acts. |
| 8.5% | tot_sos_fnbre_acte_tot_f | int | Total number of female SOS Médecins medical acts.Total number of female SOS Médecins medical acts. |
| 100% | reg_codeCode de la région | int | Region code.Region code. |
| 100% | countrycode_iso_3166_1_alpha3Code ISO 3166 de la zone | text | ISO 3166-1 alpha-3 country code of the area.ISO 3166-1 alpha-3 country code of the area. |
| 100% | region_minNom région | text | Name of the region.Name of the region. |
| — | nom_dep_minNom du département | text | Name of the department.Name of the department. |
| — | age_labelLibellé tranches d'âge | text | Label of the age group.Label of the age group. |
| — | geo_point_2dCoordinates | geo_point_2d | Geographic coordinates of the area.Geographic coordinates of the area. |
Schema captured from opendatasoft 2 days ago.
Query the data
Pick columns and a sort, then fetch a live preview straight from the source. Choose an API-filterable column (marked ▾) under “Where” to pick from its list of values.
Sample data (5 records)
Record 1date: 2024-01-05 · dep_code: 77
{
"date": "2024-01-05",
"dep_code": "77",
"reg_code": 11,
"age_label": "0-4 ans",
"tot_sos_f": null,
"tot_sos_m": null,
"region_min": "Île-de-France",
"nom_dep_min": "Seine-et-Marne",
"geo_point_2d": {
"lat": 48.6281210472,
"lon": 2.93531969909
},
"tot_acte_sos": 70,
"tot_pass_emgy": 149,
"nb_sos_covid_f": null,
"nb_sos_covid_m": null,
"tot_pass_emgy_f": null,
"tot_pass_emgy_m": null,
"nb_ho_emgy_covid": 0,
"nb_acte_sos_covid": 0,
"nb_ho_emgy_covid_f": null,
"nb_ho_emgy_covid_m": null,
"nb_pass_emgy_covid": 1,
"nb_pass_emgy_covid_f": null,
"nb_pass_emgy_covid_m": null,
"countrycode_iso_3166_1_alpha3": "FRA"
}Record 2date: 2023-05-04 · dep_code: 91
{
"date": "2023-05-04",
"dep_code": "91",
"reg_code": 11,
"age_label": "5-14 ans",
"tot_sos_f": null,
"tot_sos_m": null,
"region_min": "Île-de-France",
"nom_dep_min": "Essonne",
"geo_point_2d": {
"lat": 48.5174587303,
"lon": 2.24865517666
},
"tot_acte_sos": 13,
"tot_pass_emgy": 110,
"nb_sos_covid_f": null,
"nb_sos_covid_m": null,
"tot_pass_emgy_f": null,
"tot_pass_emgy_m": null,
"nb_ho_emgy_covid": 0,
"nb_acte_sos_covid": 0,
"nb_ho_emgy_covid_f": null,
"nb_ho_emgy_covid_m": null,
"nb_pass_emgy_covid": 0,
"nb_pass_emgy_covid_f": null,
"nb_pass_emgy_covid_m": null,
"countrycode_iso_3166_1_alpha3": "FRA"
}Record 3date: 2024-10-27 · dep_code: 75
{
"date": "2024-10-27",
"dep_code": "75",
"reg_code": 11,
"age_label": "5-14 ans",
"tot_sos_f": null,
"tot_sos_m": null,
"region_min": "Île-de-France",
"nom_dep_min": "Paris",
"geo_point_2d": {
"lat": 48.8557954256,
"lon": 2.34411308321
},
"tot_acte_sos": 73,
"tot_pass_emgy": 137,
"nb_sos_covid_f": null,
"nb_sos_covid_m": null,
"tot_pass_emgy_f": null,
"tot_pass_emgy_m": null,
"nb_ho_emgy_covid": 0,
"nb_acte_sos_covid": 0,
"nb_ho_emgy_covid_f": null,
"nb_ho_emgy_covid_m": null,
"nb_pass_emgy_covid": 0,
"nb_pass_emgy_covid_f": null,
"nb_pass_emgy_covid_m": null,
"countrycode_iso_3166_1_alpha3": "FRA"
}Record 4date: 2023-01-18 · dep_code: 94
{
"date": "2023-01-18",
"dep_code": "94",
"reg_code": 11,
"age_label": "15-44 ans",
"tot_sos_f": null,
"tot_sos_m": null,
"region_min": "Île-de-France",
"nom_dep_min": "Val-de-Marne",
"geo_point_2d": {
"lat": 48.7692936982,
"lon": 2.47462077077
},
"tot_acte_sos": null,
"tot_pass_emgy": 494,
"nb_sos_covid_f": null,
"nb_sos_covid_m": null,
"tot_pass_emgy_f": null,
"tot_pass_emgy_m": null,
"nb_ho_emgy_covid": 0,
"nb_acte_sos_covid": null,
"nb_ho_emgy_covid_f": null,
"nb_ho_emgy_covid_m": null,
"nb_pass_emgy_covid": 2,
"nb_pass_emgy_covid_f": null,
"nb_pass_emgy_covid_m": null,
"countrycode_iso_3166_1_alpha3": "FRA"
}Record 5date: 2024-09-15 · dep_code: 91
{
"date": "2024-09-15",
"dep_code": "91",
"reg_code": 11,
"age_label": "tous âges",
"tot_sos_f": 78,
"tot_sos_m": 57,
"region_min": "Île-de-France",
"nom_dep_min": "Essonne",
"geo_point_2d": {
"lat": 48.5174587303,
"lon": 2.24865517666
},
"tot_acte_sos": 135,
"tot_pass_emgy": 647,
"nb_sos_covid_f": 2,
"nb_sos_covid_m": 1,
"tot_pass_emgy_f": 325,
"tot_pass_emgy_m": 322,
"nb_ho_emgy_covid": 0,
"nb_acte_sos_covid": 3,
"nb_ho_emgy_covid_f": 0,
"nb_ho_emgy_covid_m": 0,
"nb_pass_emgy_covid": 2,
"nb_pass_emgy_covid_f": 1,
"nb_pass_emgy_covid_m": 1,
"countrycode_iso_3166_1_alpha3": "FRA"
}Live sample captured at profiling time — values may have changed upstream.
Verification Status
Using the API
Configuration
- Base URL
- https://data.iledefrance.fr/api/explore/v2.1/catalog/datasets/donnees-urgences-hospitalieres-sos-medecins-relatives-a-lepidemie-de-covid-19-en
License
- ✓ Redistributable
- ✓ Attribution required
Query examples
curl -s 'https://data.iledefrance.fr/api/explore/v2.1/catalog/datasets/donnees-urgences-hospitalieres-sos-medecins-relatives-a-lepidemie-de-covid-19-en/records?limit=20' -H 'Accept: application/json'First 20 records of the dataset as JSON.
Uses the Opendatasoft Explore v2.1 syntax — supports select, where, group_by and order_by.
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