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Major interregional differences in France of COVID-19 hospitalization and mortality from January to June 2020

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REVUE D EPIDEMIOLOGIE ET DE SANTE PUBLIQUE
卷 70, 期 6, 页码 265-276

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MASSON EDITEUR
DOI: 10.1016/j.respe.2022.08.008

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COVID-19; France; Cohort studies; Hospitals; Mortality

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This study provides a detailed description of the geographic and temporal evolution of COVID-19 in France, revealing significant interregional differences. The findings can help understand the dynamics of future epidemic waves.
Introduction. - Even though France was severely hit by the COVID-19 pandemic, few studies have addressed the dynamics of the first wave on an exhaustive, nationwide basis. We aimed to describe the geographic and temporal distribution of COVID-19 hospitalisations and in-hospital mortality in France during the first epi-demic wave, from January to June 2020.Methods. - This retrospective cohort study used the French national database for all acute care hospital admissions (PMSI). Contiguous stays were assembled into care sequences for analysis so as to limit bias when estimating incidence and mortality. The incidence rate and its evolution, mortality and hospitalized case fatality rates (HCFR) were compared between geographic areas. Correlations between incidence, mortal-ity, and HCFR were analyzed.Results. - During the first epidemic wave, 98,366 COVID-19 patients were hospitalized (incidence rate of 146.7/100,000 inhabitants), of whom 18.8% died. The median age was 71 years, the male/female ratio was 1.16, and 26.2% of patients required critical care. The Paris area and the North-East region were the first and most severely hit areas. A rapid increase of incidence and mortality within 4 weeks was followed by a slow decrease over 10 weeks. HCFRs decreased during the study period, and correlated positively with incidence and mortality rates.Discussion. - By detailing the geographical and temporal evolution of the COVID-19 epidemic in France, this study revealed major interregional differences, which were otherwise undetectable in global analyses. The precision afforded should help to understand the dynamics of future epidemic waves.(c) 2022 Elsevier Masson SAS. All rights reserved.

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