Evolution of outcomes for patients hospitalised during the first 9 months of the SARS-CoV-2 pandemic in France: A retrospective national surveillance data analysis
Year: 2021
Type: article
Study design: Observational Study
Abstract: BACKGROUND: As SARS-CoV-2 continues to spread, a thorough characterisation of healthcare needs and patient outcomes, and how they have changed over time, is essential to inform planning. METHODS: We developed a probabilistic framework to analyse detailed patient trajectories from 198,846 hospitalisations in France during the first nine months of the pandemic. Our model accounts for the varying age- and sex- distribution of patients, and explore changes in outcome probabilities as well as length of stay. FINDINGS: We found that there were marked changes in the age and sex of hospitalisations over the study period. In particular, the proportion of hospitalised individuals that were >80y varied between 27% and 48% over the course of the epidemic, and was lowest during the inter-peak period. The probability of hospitalised patients entering ICU dropped from 0·25 (0·24-0·26) to 0·13 (0·12-0·14) over the four first months as case numbers fell, before rising to 0·19 (0·19-0·20) during the second wave. The probability of death followed a similar trajectory, falling from 0·25 (0·24-0·26) to 0·10 (0·09-0·11) after the first wave before increasing again during the second wave to 0·19 (0·18-0·19). Overall, we find both the probability of death and the probability of entering ICU were significantly correlated with COVID-19 ICU occupancy. INTERPRETATION: There are large scale trends in patients outcomes by age, sex and over time. These need to be considered in ongoing healthcare planning efforts. FUNDING: INCEPTION.
Institutions: Centre National de la Recherche Scientifique, Institut Pasteur, University of Cambridge, Génomique évolutive, modélisation et santé, Santé Publique France, Ministère des Solidarités et de la Santé, Inserm, Université Paris Cité, Assistance Publique – Hôpitaux de Paris, Hôpital Bichat-Claude-Bernard, Université Paris Diderot, Infection, Anti-microbiens, Modélisation, Evolution, Sorbonne Université, Institut Pierre Louis d‘Épidémiologie et de Santé Publique
Language: English
Subfield: Infectious Diseases
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,500
Awards: G1979782309, G221735260, G282427092, G434337789, G456987127, Rapid European SARS-CoV-2 Emergency research Response, Institut Convergences pour l’étude de l’Emergence des Pathologies au Travers des Individus et des populatiONs, Coupling dynamic population immunity profiles and host behaviours to arboviral spread, G5716161078, G6705547003, G7240651115, Integrative Biology of Emerging Infectious Diseases, G7916265299, G8670608220
OpenAlex ID: W3139345328