Abstract

BackgroundThe first wave of the COVID-19 pandemic in France was associated with high excess mortality, and anecdotal evidence pointed to differing excess mortality patterns depending on social and environmental determinants. In this study we aimed to investigate the spatial distribution of excess mortality during the first wave of the COVID-19 pandemic in France and relate it at the subnational level to contextual determinants from various dimensions (socioeconomic, population density, overall health status, healthcare access etc.). We also explored whether the determinants identified at the national level varied depending on geographical location.MethodsWe used available national data on deaths in France to calculate excess mortality by department for three age groups: 0–49, 50–74 and > 74 yrs. between March 1st and April 27th, 2020. We selected 15 variables at the department level that represent four dimensions that may be related to overall mortality at the ecological level, two representing population-level vulnerabilities (morbidity, social deprivation) and two representing environmental-level vulnerabilities (primary healthcare supply, urbanization). We modelled excess mortality by age group for our contextual variables at the department level. We conducted both a global (i.e., country-wide) analysis and a multiscale geographically weighted regression (MGWR) model to account for the spatial variations in excess mortality.ResultsIn both age groups, excess all-cause mortality was significantly higher in departments where urbanization was higher (50–74 yrs.: β = 15.33, p < 0.001; > 74 yrs.: β = 18.24, p < 0.001) and the supply of primary healthcare providers lower (50–74 yrs.: β = − 8.10, p < 0.001; > 74 yrs.: β = − 8.27, p < 0.001). In the 50–74 yrs. age group, excess mortality was negatively associated with the supply of pharmacists (β = − 3.70, p < 0.02) and positively associated with work-related mobility (β = 4.62, p < 0.003); in the > 74 yrs. age group our measures of deprivation (β = 15.46, p < 0.05) and morbidity (β = 0.79, p < 0.008) were associated with excess mortality. Associations between excess mortality and contextual variables varied significantly across departments for both age groups.ConclusionsPublic health strategies aiming at mitigating the effects of future epidemics should consider all dimensions involved to develop efficient and locally tailored policies within the context of an evolving, socially and spatially complex situation.

Highlights

  • The first wave of the COVID-19 pandemic in France was associated with high excess mortality, and anecdotal evidence pointed to differing excess mortality patterns depending on social and environmental determinants

  • Over the study period, overall excess mortality for the 0–49 age group ranged from − 56.52 to + 114.29% at the national level

  • For all three age groups, there were departments with negative excess mortality, meaning that there had been a reduction in all-cause mortality over the study period

Read more

Summary

Introduction

The first wave of the COVID-19 pandemic in France was associated with high excess mortality, and anecdotal evidence pointed to differing excess mortality patterns depending on social and environmental determinants. Between March 1st and April 30th, mortality rates were much higher in the urban densely populated administrative region of Ile-de-France (i.e. Paris and surroundings, + 90%) and in the region where the largest outbreak of the disease occurred first (in northeastern France called Grand Est, + 55%) compared to the same period in the two preceding years [2] These variations in the overall spatial pattern of mortality during the first wave of the pandemic have been linked to specific events and/or known exacerbating factors in the dynamics of an infectious disease epidemic, but questions have been raised over environmental and social determinants beyond these [3, 4]. Understanding the spatial distribution of overall mortality may help us grasp the geographic scope of the contextual disease-specific determinants associated with COVID-19 mortality

Objectives
Methods
Results
Discussion
Conclusion
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.