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International audience; The COVID-19 pandemic has spurred a large amount of experimental and observational studies reporting clear correlation between the risk of developing severe COVID-19 (or dying from it) and whether the individual is male or female. This paper is an attempt to explain the supposed male vulnerability to COVID-19 using a causal approach. We proceed by identifying a set of confounding and mediating factors, based on the review of epidemiological literature and analysis of sex-dis-aggregated data. Those factors are then taken into consideration to produce explainable and fair prediction and decision models from observational data. The paper outlines how non-causal models can motivate discriminatory policies such as biased allocation of the limited resources in intensive care units (ICUs). The objective is to anticipate and avoid disparate impact and discrimination, by considering causal knowledge and causalbased techniques to compliment the collection and analysis of observational big-data. The hope is to contribute to more careful use of health related information access systems for developing fair and robust predictive models.

International audience; Avec la Covid-19, les entreprises ont accéléré leur transformation digitale, en relevant souvent les défis à marche forcée. C’est le cas des PME, pour la plupart confrontées à des difficultés d’envergure lorsqu’il s’agit d’investir dans des outils technologiques coûteux, dont le déploiement implique un bouleversement du modèle d’affaires.Dans sa forme aboutie, la digitalisation combine plateforme, ensembles de données complexes, hyperautomatisation et expérience utilisateur. Mais les PME ont-elles la maturité digitale suffisante pour s’emparer de ces outils et nouvelles capacités ? Peuvent-elles s’aider d’un modèle de transformation adapté à leurs spécificités ?Cet ouvrage se penche sur la transformation digitale du business model des PME en s’adressant aux entrepreneurs qui sont en train de se transformer ou souhaitent le faire. En posant la question « Comment l’entrepreneur de PME peut-il digitaliser son modèle d’affaires ? », il développe un modèlede transformation : le Business Model Digital Dynamique (BMD²). Fondé sur l’analyse du contexte sociotechnique dans lequel s’ancre la digitalisation, le BMD² met l’entrepreneur au cœur de la dynamique de transformation. Le modèle est décliné en une méthode d’opérationnalisation DSIFAT actionnable sur le terrain des PME.L’ouvrage développe deux cas « d’échec » et de « réussite » de transformation digitale de deux PME du secteur tertiaire.

Several European countries were affected by severe floods in 2021. At the same time, despite the deployment of vaccines, Europe was the COVID-19 pandemic's epicenter several times during 2021. One research aim of this study is to identify socio-demographic groups vulnerable to floods and whether the groups vulnerable to floods and pandemics overlap or are disjoint. We ran a survey in four languages (English, French, German, and Spanish) and collected the judgment of 366 experts in disaster risk management and first-responders to find out how those people caring for “people in need” (be it operational or administratively) think about which persons are more at risk than others. Another research aim is to validate multi-hazard vulnerability factors by comparing judgment on groups vulnerable to the COVID-19 pandemic and to floods. The main findings are that experts think that socially vulnerable groups should be rescued or treated first. Treating everyone equally is less favored by comparison. Infrastructure losses, followed by economic losses, reveal better than deaths or psychological issues whether vulnerability played a role in a disaster. Regarding vulnerability characteristics, older, homeless people, and immigrants rank highest, and most factors can be used to explain both flood and COVID-19 vulnerability, while some differ; for example, mobility impairment is less important for COVID-19. There are major discrepancies between what respondents think should be done to prioritize help to certain groups and what they have experienced is being done on the field.

International audience

CNRS 2, FNEGE 2, HCERES A, ABS 3; International audience; The COVID-19 pandemic boosted the digital transformation of many services, including healthcare, and access to medical care using teleconsultation has increased rapidly. Thus, a growing number of online platforms have been developed to accommodate patients’ needs. This paper examines the factors that predict the intention to use medical teleconsultation by extending the unified theory of acceptance and use of technology (UTAUT2) with the three dimensions of trusting beliefs and self-efficacy. A survey was administered to patients who had used a teleconsultation platform during the pandemic period. As one of the largest studies to date, a sample of 1233 respondents was collected and analyzed using a partial least squares approach, often mobilized in the information systems (IS) domain. Furthermore, a deep analysis using all recommended metrics was performed. The results highlight the significance of trusting beliefs, and self-efficacy in the adoption of digital healthcare services. These findings contribute to both theory and practice in COVID-19 research.

International audience; Tiered social distancing policies have been adopted by many governments to mitigate the harmful consequences of COVID-19. Such policies have a number of well-established features i.e., they are short-term, adaptive (to the changing epidemiological conditions), and based on a multiplicity of indicators of the prevailing epidemic activity. Here, we use ideas from Behavioural Epidemiology to represent tiered policies in an SEIRS model by using a composite information index including multiple indicators of current and past epidemic activity mimicking those used by governments during the COVID-19 pandemic, such as transmission intensity, infection incidence and hospitals' occupancy. In its turn, the dynamics of the information index is assumed to endogenously inform the governmental social distancing interventions. The resulting model is described by a hereditary system showing a noteworthy property i.e., a dependency of the endemic levels of epidemiological variables from initial conditions. This is a consequence of the need to normalise the different indicators to pool them into a single index. Simulations suggest a rich spectrum of possible results. These include policy suggestions and identify pitfalls and undesired outcomes, such as a worsening of epidemic control, that can arise following such types of approaches to epidemic responses.

International audience; How has the COVID-19 pandemic affected learning progress among school-age children? A growing number of studies address this question, but findings vary depending on context. We conduct a pre-registered systematic review, quality appraisal and meta-analysis of 42 studies across 15 countries to assess the magnitude of the effect of the pandemic on learning. We find a substantial overall learning deficit (Cohen’s d = –0.14, 95% c.i. –0.17, –0.10), which arose early in the pandemic and persists over time. Forgone learning is particularly large among children from low socio-economic backgrounds. It is also larger in math than in reading, and in middle-income countries, relative to high-income countries. There is a lack of evidence on learning progress during the pandemic in low-income countries. Future research should address this evidence gap and avoid the common risks of bias that we identify.; Comment la pandémie de COVID-19 a-t-elle affecté les progrès de l'apprentissage chez les enfants d'âge scolaire ? Un nombre croissant d'études se penchent sur cette question, mais les résultats varient en fonction du contexte. Nous réalisons une revue systématique pré-enregistrée, une évaluation de la qualité et une méta-analyse de 42 études dans 15 pays pour évaluer l'ampleur de l'effet de la pandémie sur l'apprentissage. Nous constatons un déficit d'apprentissage global substantiel (d de Cohen = -0,14, 95 % c.i. -0,17, -0,10), qui s'est manifesté au début de la pandémie et qui persiste au fil du temps. Le déficit d'apprentissage est particulièrement important chez les enfants issus de milieux socio-économiques défavorisés. Il est également plus important en mathématiques qu'en lecture, et dans les pays à revenu moyen, par rapport aux pays à revenu élevé. On manque de données sur les progrès de l'apprentissage pendant la pandémie dans les pays à faible revenu. Les recherches futures devraient combler ce manque de données probantes et éviter les risques communs de biais que nous avons identifiés.

BackgroundSurvivors of severe-to-critical COVID-19 may have functional impairment, radiological sequelae and persistent symptoms requiring prolonged follow-up. This pragmatic study aimed to describe their clinical follow-up and determine their respiratory recovery trajectories, and factors that could influence them and their health-related quality of life.MethodsAdults hospitalised for severe-to-critical COVID-19 were evaluated at 3 months and up to 12 months post-hospital discharge in this prospective, multicentre, cohort study.ResultsAmong 485 enrolled participants, 293 (60%) were reassessed at 6 months and 163 (35%) at 12 months; 89 (51%) and 47 (27%) of the 173 ones initially managed with standard oxygen were reassessed at 6 and 12 months, respectively. At 3 months, 34%, 70% and 56% of the participants had a restrictive lung defect, impaired DLCOand significant radiological sequelae, respectively. During extended follow-up, DLCOand FVC (% of predicted value) increased by means of +4 points at 6 months, and +6 points at 12 months. Sex, body mass index, chronic respiratory disease, immunosuppression, pneumonia extent or corticosteroid use during acute COVID-19 and prolonged invasive mechanical ventilation (IMV) were associated with DLCOat month 3, but not its trajectory thereafter. Among 475 (98%) patients with at least one chest computed-tomography scan during follow-up, 196 (41%) had significant sequelae on their last images.ConclusionAlthough pulmonary function and radiological abnormalities improved up to 1 year post-acute-COVID-19, high percentages of severe-to-critical disease survivors, including a notable proportion of those managed with standard oxygen, had significant lung sequelae and residual symptoms justifying prolonged follow-up.

Because SARS-CoV-2 constantly mutates to escape from the immune response, there is a reduction of neutralizing capacity of antibodies initially targeting the historical strain against emerging Variants of Concerns (VoC)s. That is why the measure of the protection conferred by vaccination cannot solely rely on the antibody levels, but also requires to measure their neutralization capacity. Here we used a mathematical model to follow the humoral response in 26 individuals that received up to three vaccination doses of Bnt162b2 vaccine, and for whom both anti-S IgG and neutralisation capacity was measured longitudinally against all main VoCs. Our model could identify two independent mechanisms that led to a marked increase in humoral response over the successive vaccination doses. In addition to the already known increase in IgG levels after each dose, we identified that the neutralization capacity was significantly increased after the third vaccine administration against all VoCs, despite large inter-individual variability. Consequently, the model projects that the mean duration of detectable neutralizing capacity against non-Omicron VoC is between 366 days (Beta variant, 95% Prediction Intervals PI [323; 366]) and 606 days (Alpha variant, 95% PI [555; 638]). Despite a very low protection after three doses, the mean duration of detectable neutralizing capacity against Omicron variants varies between 184 days (BA.5 variant, 95% PI [155; 215]) and 268 days (BA.1 variant, 95% PI [238; 302]). Our model shows the benefit of incorporating the neutralization capacity in the follow-up of patients to better inform on their level of protection against the different SARS-CoV-2 variants as well as their optimal timing of vaccine administration.

Many recent studies show that Europe has had a lower mortality inequality for most ages than the United States over the last thirty years. However, the evolution of the income gradient in mortality all along the twentieth century remains poorly understood. This article uses a unique dataset that gives the annual lifetables and fiscal income for the 90 administrative regions of mainland France from 1922 to 2020. The income gradients in mortality are computed across regions using a traditional method with calendar ages and, alternatively, with mortality milestones to control for the increase in life expectancy over time. The study reveals a systematic reversal of the gradient that occurred around the 1970s for both sexes and all ages or mortality groups when calculated at an aggregated level. Inequality in mortality amongst the oldest age groups has however returned to a level observed at least ten years earlier because of Covid-19, even after controlling for mortality improvements over the period.