Healthcare system and social trust in the fight against COVID-19: the case of France
| Autor: | Nadine Levratto, Giuseppe Arcuri, Mounir Amdaoud |
|---|---|
| Přispěvatelé: | EconomiX, Université Paris Nanterre (UPN)-Centre National de la Recherche Scientifique (CNRS) |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Disease
Trust 050105 experimental psychology Spillover effect 0502 economics and business Development economics Pandemic Health care Humans 0501 psychology and cognitive sciences 050207 economics Pandemics Socioeconomic status SARS-CoV-2 business.industry 05 social sciences Public Health Environmental and Occupational Health COVID-19 [SHS.ECO]Humanities and Social Sciences/Economics and Finance 3. Good health Metropolitan France Econometric model Geography [No keyword available] France business Delivery of Health Care Social capital |
| Zdroj: | European Journal of Public Health European Journal of Public Health, Oxford University Press (OUP): Policy B-Oxford Open Option D, 2021, 31 (4), pp.895-900. ⟨10.1093/eurpub/ckab112⟩ European Journal of Public Health, Oxford University Press (OUP): Policy B-Oxford Open Option D, 2021 European Journal of Public Health, 2021, 31 (4), pp.895-900. ⟨10.1093/eurpub/ckab112⟩ |
| ISSN: | 1101-1262 1464-360X |
| DOI: | 10.1093/eurpub/ckab112⟩ |
| Popis: | BackgroundCOVID-19, like all pandemics, has territorial specificities that need to be considered: the impact of the COVID-19 crisis strongly differs not only across countries, but also across regions, districts and municipalities within countries. There are several factors that, potentially, can contribute to the differentiated impact of COVID-19, and explain the disparities seen among areas. This study aims to contribute to this debate by analyzing the role of health system and social trust in lessening the impact of the COVID-19 pandemic in French ‘départements’.MethodsThe data used in this study have been provided by the INSEE and the French Ministry of Health. Database is made up of the 96 ‘départements’ of metropolitan France. We use spatial analysis techniques to identify the groups of areas that are particularly affected, and to test the influence of local socio-economic factors on the spread of the epidemic.ResultsOur exploratory spatial analysis reveals the heterogeneity and spatial autocorrelation of the disease. The use of spatial econometric models, then, allows us to highlight the impact of emergency services, and social capital in reducing the exposition to COVID-19. Our results also report on the role of spillover effects between neighbouring areas.ConclusionsThis research shows that, although individual characteristics are important factors in explaining the probability of contracting COVID-19 disease, health care services and social trust factors also play a significant role in curbing the epidemic’s outbreak. These findings should have an interest for policy makers in the prevention of future waves of COVID-19 pandemic. |
| Databáze: | OpenAIRE |
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