Publications

Journal Article Ahead of print 1 citation

PubMed: 42532401 DOI: 10.1016/j.ijid.2026.109013

Social Deprivation and Remoteness as Determinant of COVID-19 Hospitalisations and Severity: an Area-Level Analysis in South-Eastern France.

Int J Infect Dis

Authors: Pierre Garneret, Guillaume Gaubert, Steve Nauleau, Florian Franke, Stanislas Rebaudet, Emilie Mosnier, Luka Canton, Pierre Schalkwijk, Pascal Chaud, Sabira Smaïli, Stéphanie Vandentorren, Michael Huart, Marc-Karim Bendiane, Jordi Landier, Jean Gaudart

Affiliations

  • Aix Marseille Univ, IRD, INSERM, SESSTIM, Aix Marseille Institute of Public Health, ISSPAM, Marseille, France.
  • Aix Marseille Univ, IRD, INSERM, SESSTIM, Aix Marseille Institute of Public Health, ISSPAM, Marseille, France.
  • Agence Régionale de Santé Provence Alpes Côte d'Azur, Marseille, France.
  • Santé Publique France, Paris, France.
  • Hôpital Européen Marseille, France; Aix Marseille Univ, IRD, INSERM, SESSTIM, Aix Marseille Institute of Public Health, ISSPAM, Marseille, France.
  • Aix Marseille Univ, IRD, INSERM, SESSTIM, Aix Marseille Institute of Public Health, ISSPAM, Marseille, France; Infectious and Tropical Diseases Unit, University Hospital of La Réunion, Saint Pierre, La Réunion, France.
  • Agence Régionale de Santé Occitanie, Montpellier, France.

Abstract

BACKGROUND

Since the onset of COVID-19 pandemic, multiple individual-level factors, including socioeconomic determinants have been associated with infection risk and disease severity. However, public health policies implemented at national level did not consider social determinants at territorial and community levels. In collaboration with the Regional Health Agency of Provence-Alpes-Côte d'Azur (PACA) in France, we analysed COVID-19 hospitalisations together with incidence and testing data, at a fine geographical scale, in order to contextualise the epidemic, and assess the impact of area-level socioeconomic and demographic characteristics on disease severity.

METHODS

We conducted a fine scale ecological study of COVID-19 hospitalisation rates in the PACA region, during the second and third epidemic waves (September 2020-June 2021). French census areas (IRIS), the smallest spatial units available for socioeconomic and population-based analysis, were classified into six socio-demographic profiles. We characterized COVID-19 with indicators of incidence and severity relative to total population (incidence and hospitalisation rates) and proportional to tests or cases (proportion of positive tests and proportion of hospitalised cases). Associations between these profiles and COVID-19 indicators were assessed using generalised additive models, adjusting for testing rates, healthcare access, retirement home presence and population age structure. Spatial autocorrelation between areas was accounted for in the models.

RESULTS

The most socially deprived IRIS had the highest COVID-19 incidence and hospitalisation rates both in conventional settings and in intensive care units (ICU). Decreasing social deprivation was associated with a gradient of decreasing incidence and hospitalisation rates. Complementary models examining proportion of hospitalisation among confirmed cases indicated that excess hospitalisation in very socially deprived area reflected both higher incidence and greater severity of the disease. IRIS profiles corresponding to remote, rural areas displayed an isolated increase in conventional hospitalisation ratios without a corresponding rise in ICU hospitalisation ratios.

CONCLUSION

Socioeconomic deprivation was strongly associated with both higher infection spread and greater severity of COVID-19 at the territorial level, underscoring the need to prioritize prevention efforts in socially deprived areas to mitigate future health crisis. Remote areas also exhibited higher conventional hospitalisation rates, possibly reflecting clinical decisions influenced by remoteness rather than increased disease severity.

MeSH

Research Design, Incidence, Covid-19, Intensive Care Units, Communicable Diseases, Epidemics, Demography, Infections