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La Revue économique (1950-2025), une perspective quantitative
No full textCet article analyse l’évolution de la Revue économique depuis sa création en 1950 jusqu’en 2025. Nous retraçons son histoire, sa place centrale dans la recherche économique française et les transformations de son contenu éditorial. Notre étude repose sur un probabilistic topic model, un modèle d’apprentissage automatique par classification non supervisée que nous appliquons aux textes entiers de la Revue économique. Initialement positionnée entre une approche réformatrice et une ouverture aux autres sciences sociales, la revue s’est progressivement standardisée autour des méthodes quantitatives avec une importance centrale pour la macroéconomie. Nous montrons ensuite un glissement vers une approche plus appliquée et empirique à la fin du XXe siècle. Au-delà des sujets traités, nous discutons dans une dernière partie le pluralisme au sein de la revue ainsi que l’influence de l’internationalisation et de la féminisation de la discipline
Crush, sexting et identités sexuelles comment ils réinventent les codes de l’amour
No full textOn les dit manipulés par le porno, passionnés d’échanges numériques plutôt que de relations physiques, militants invétérés du consentement et de la cause LGBTQI+. À quoi ressemble la révolution sexuelle de la « gen Z »
Les composantes naturelles et migratoires. Une variété de configurations géographiques qui résultent des trajectoires individuelles
No full textHospitalisation for acute heart failure and in-hospital mortality before, during, and after the COVID-19 pandemic in France: A Nationwide cohort study from 2013 to 2024
No full textIntroduction: Healthcare systems were reorganised in 2020 to manage the COVID-19 pandemic. Despite their urgent status, hospital admissions for acute heart failure (AHF) were reported to decline from 9% to 66% worldwide between 2020 and 2021, with divergent findings regarding in-hospital mortality. This study aimed to investigate in detail the evolution of AHF hospitalisations and in-hospital mortality in France from 2013 to 2024.
Methods: Based on the 2.9 million AHF hospitalisations recorded in France from 2013 to 2024, yearly numbers of hospitalisations and deaths expected in years 2020 to 2024 were estimated using a Poisson regression model, with 2013–2019 as the reference period. The differences between observed and expected event counts in the years 2020 to 2024 were used to quantify the disruptions that occurred since the emergence of the pandemic.
Results: A total deficit of −222,913 [−223,908; −221,926] (mean [95% CI]) AHF hospitalisations was estimated for the 2020-2024 years, corresponding to a 16.1% decrease compared to pre-pandemic trends. The yearly reduction in AHF hospitalisations worsened over time, from −39,268 [−39,685; − 38,847] fewer cases in 2020 to −55,521 [−55,984; −55,051] in 2024. In parallel with the decline in AHF hospitalisations, estimated excess in-hospital deaths were 828 [729; 928], 1,625 [1,517; 1,731], 2,427 [2,323; 2,531], 1,739 [1,634; 1,844], and 1,175 [1,068; 1,281] for the years 2020 to 2024, respectively. These correspond to relative increases in in-hospital mortality ranging from 4.4% to 13.2% compared to expected values. The disruptions in both hospital admissions and in-hospital mortality affected more females than males.
Conclusions: The apparent long-lasting changes in the management of AHF patients in France observed since the COVID-19 pandemic emergence, particularly among females, suggest improving the preparedness for future crises and require addressing the current sustained disruptions.
What is already known on this topic In 2020 and 2021, hospitalisations for acute heart failure were reported to decline worldwide following the onset of the COVID-19 pandemic. However, findings on concomitant in-hospital mortality have remained unclear, and little is known about whether these disruptions persisted through 2022 to 2024.What this study adds Analyses of exhaustive French national data indicate that the decline in admissions observed in 2020 persisted and even worsened through 2024, with an overall decrease of 16.1%. In parallel, in-hospital mortality was estimated in each year from 2020 to 2024, and the resulting excess corresponded to a cumulative increase of 8.4%. Females were more impacted than males by both disruptions.How this study might affect research, practice or policy This study highlights critical warnings on ongoing disruptions affecting patients hospitalised for acute heart failure in France and identifies the subpopulations most impacted. These findings might contribute to guide targeted mitigation strategies and to enhance the preparedness of national health systems for future health crises
Revisiting the link between COVID-19 incidence and infection fatality rate during the first pandemic wave
No full textSeveral studies found an association between COVID-19 incidence, cumulated over the first pandemic wave, and the risk of death for infected individuals. They attributed this association to hospital overload. We studied this association across the French departments using 82,467 serological samples and a hierarchical Bayesian model with spatial smoothing. In high-incidence areas, we hypothesized that hospital overload would increase infection fatality rate (IFR) without increasing infection hospitalization rate (IHR). The analyses were adjusted for intensive care beds per capita, age of the population, and diabetes prevalence (as a surrogate for obesity). We found that increasing departmental incidence from 3 to 9% rose IFR from 0.42 to 1.14% (difference 0.72%, 95% CI 0.49–1.01%), and IHR from 1.66 to 3.61% (difference 1.94%, 95% CI 1.18–2.80%). An increase in incidence from 6 to 12% in people under 60 was associated with an increased proportion of people over 60 among those infected, from 11.6 to 17.4% (difference 5.8%, 95% CI 2.9–8.8%). Higher incidence increased the risk of death for infected individuals and their risk of hospitalization by the same magnitude. These findings could be explained by a higher age among infected individuals in high-incidence areas, rather by than hospital overload
The 2025 report of the Lancet Countdown to 2030 for women's, children's, and adolescents' health: tracking progress on health and nutrition
No full textIn line with previous progress reports by Countdown to 2030 for Women's, Children's, and Adolescents' Health, this report analyses global and regional trends and inequalities in health determinants, survival, nutritional status, intervention coverage, and quality of care in reproductive, maternal, newborn, child and adolescent health (RMNCAH) and nutrition, as well as country health systems, policies, financing, and prioritisation. The focus is on low-income and middle-income countries (LMICs) where 99% of maternal deaths and 98% of child and adolescent deaths (individuals aged 0–19 years) occur, with special attention to sub-Saharan Africa and South Asia
Evaluating the effectiveness of two Milan’s congestion limitation policies: Charge increase and vehicle type limitation
No full textCongestion pricing, also referred to as road pricing, is a form of Pigouvian taxation designed to limit or reduce vehicular traffic within a specific area. These systems aim to encourage changes in driving behavior and the choice of transportation mode. An example of a congestion pricing system is the Milan Area C charging zone, which operates on a fixed-rate basis. In recent years, two changes to the system have been introduced: (i) restrictions on the vehicle types allowed to enter the zone, and (ii) a 50 percent increase in the congestion charge. This study introduces a novel and replicable approach to evaluate the effectiveness of these policy changes, by studying the ratio of vehicles entering Area C to the total number of unique individuals within it, leveraging mobile phone data on user presence. Using fixed-effects models to control for unobserved heterogeneity across time, this study analyzes the impact of these two policy changes in the Area C congestion pricing system. The findings indicate that both policy changes influenced individuals’ choice of transportation mode, with vehicle type restrictions having a greater impact than price increases. This shows the effectiveness of the two types of measures, offering insights for policymakers on how to enhance congestion charging system effectiveness through refined pricing strategies and vehicle limitations. Additionally, demographic characteristics of users present in the area, as captured through mobile phone data, such as the proportion of women and elderly individuals, significantly influence transportation choices. Recognizing these factors is essential for policymakers, as it highlights the need for equitable policies that improve acceptance and effectiveness among vulnerable groups. Additionally, demographic characteristics of users present in the area, as captured through mobile phone data—such as the proportion of women and elderly individuals—significantly influence transportation choices
Health and Inequality in Under-Five Mortality Rates: A Longitudinal Multilevel Analysis in South America (2000-2020)
No full textThis study investigates the connection between health and inequality variables, and under-five infant mortality rates in ten South American countries (Argentina, Bolivia, Brazil, Chile, Colombia, Ecuador, Paraguay, Peru, Venezuela, and Uruguay). For this purpose, we conducted a longitudinal multilevel model where the dependent variable was Under-5 Mortality Rate (U5MR). To address the health factors and inequalities in the study of U5MR, we selected the following indicators: (i) -a- immunization coverage for diphtheria and -b- immunization coverage for measles in children under 1 year old, (ii) prevalence levels of anemia in women of childbearing age, (iii) undernourishment levels in the population, (iv) the percentage of urban population, and (v) the ratio between per capita health expenditure and GDP per capita. We obtained the indicators from three data sources: The World Bank, the World Health Organization, and the Food and Agriculture Organization of the United Nations. The selected variables were measured over 21 time-steps (2000-2020) for the ten South American countries. We compared three hierarchical linear models, finding that the model incorporating time as a predictor provided the best fit for explaining mortality. This model suggests that factors like increased undernourishment and anemia are associated with higher infant mortality, while a higher urban population correlates with lower mortality, alongside a general global decline over time
