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A remarkable excess mortality has coincided with the COVID-19 pandemic in Europe. We present preliminary pooled estimates of all-cause mortality for 24 European countries/federal states participating in the European monitoring of excess mortality for public health action (EuroMOMO) network, for the period March-April 2020. Excess mortality particularly affected ≥ 65 year olds (91% of all excess deaths), but also 45-64 (8%) and 15-44 year olds (1%). No excess mortality was observed in 0-14 year olds. he EuroMOMO network has received financial support from the European Centre for Disease Prevention and Control (ECDC) and from the World Health Organization (WHO) Regional Office for Europe. We acknowledge all EuroMOMO partners for their contributions as well as the various National Offices of Statistics that are essential partners in ensuring the ongoing monitoring of mortality across Europe. Sí

International audience; Timely mortality surveillance in France is based on the monitoring of electronic death certificates to provide information to health authorities. This study aims at analyzing the performance of a rule-based and a supervised machine learning methods to classify medical causes of death into 60 mortality syndromic groups (MSGs). Performance was first measured on a test set. Then we compared the evolutions of the monthly numbers of deaths classified into MSGs from 2012 to 2016 using both methods. Among the 60 MSGs, 31 achieved recall and precision over 0.95 for either one or the other method on the test set. On the whole dataset, the correlation coefficient of the monthly numbers of deaths obtained by the two methods were close to 1 for 21 of 31 MSGs. This approach is useful to analyze a large number of categories or when the annotated resources are quite limited.

IntroductionLes causes médicales sont renseignées par les médecins sur les certificats de décès en texte libreavec une grande variété d'expressions. Les méthodes de traitement automatique des langues (TAL)permettent d'envisager leur exploitation dans des délais courts. Cet article décrit la démarcheretenue pour développer ces méthodes et illustre leur utilisation pour l'alerte sanitaire.MéthodesL'identification des méthodes performantes s'inscrit dans le cadre d'un challenge international. Celui-ci consiste à transmettre un corpus de données, comprenant le texte libre et les codes CIM10considérés comme le gold standard, aux équipes participantes pour développer leur outil deprédiction des codes CIM10 et à évaluer indépendamment les performances des outils sur un jeu detest.Certaines méthodes ont été utilisées pour la classification des causes en texte libre dans desregroupements pertinents pour la surveillance réactive de la mortalité.RésultatsLes meilleurs résultats ont été obtenus à l'aide de réseaux de neurones sur le corpus américain etavec des méthodes à base de règles sur le corpus français. Une méthode mixte incluant des règles etde la classification par SVM, ont produit des résultats meilleurs ou proches sur les deux corpus.L'analyse de l'évolution temporelle de quatre regroupements de causes pour la surveillance réactivede la mortalité a mis en évidence des évènements attendus (épidémies) et inhabituels.DiscussionL'expérience du challenge et l'application pour la surveillance à visée d'alerte montrent l'apport et laperformance des méthodes de TAL pour appuyer l'exploitation réactive des données de mortalitépour la santé publique.

International audience; This article summarizes influenza activity in France for the 2017-2018 season.Methods –This report is based on different sources of data collected in France: clinical influenza-like illness (ILI) in the community reported by the primary health care networks, virological data analysed by reference laboratories, emergency units visits and hospitalizations for clinical influenza, reporting of severe influenza cases hospitalised in intensive care units (ICU), reporting of acute respiratory infections (ARI) clusters in nursing homes, and mortality data.Results –In France, the 2017-18 season started early-December in mainland France, peaked on the last week of December and ended at the end of March, lasting 16 weeks. The epidemic was characterized by an atypical dynamics with two consecutive waves due to the circulation ofA(H1N1)pdm09 followed by B/Yamagata lineage viruses. Its impact was moderate in the community, but high numbers of hospitalizations (>9,700) and severe cases admitted to ICUs (>2,900) were recorded. During the epidemic, a marked excess mortality was observed, with 13,000 deaths attributed to influenza.Conclusion –The 2017-18 influenza epidemic started early and was unusually long, with an atypical dynamics and marked severity. The successive circulation of A(H1N1)pdm09 and B/Yamagata viruses, together with insufficient vaccine coverage and suboptimal vaccine effectiveness, have contributed to this severity. It confirms the high impact of the disease for the population at risk and strengthens the need for prevention especially higher vaccine coverage among people at risk, and the implementation of control measures to limit the spread of the virus around the cases, as well as the utility of early antiviral treatment for subjects at risk.; Cet article présente le bilan épidémiologique et virologique de l’épidémie grippale en France durant la saison 2017-2018.Méthode –Ce bilan s’appuie sur l’analyse descriptive des données de surveillance de la grippe ou des syndromes grippaux transmises par les réseaux de médecine ambulatoire, les analyses virologiques des laboratoires partenaires, la surveillance des passages aux urgences et des hospitalisations codées grippe, la surveillance des cas graves de grippe hospitalisés en services de réanimation, les signalements d’épisodes d’infections respiratoires aiguës (IRA) dans les collectivités de personnes âgées et les données de mortalité.Résultats –L’épidémie de grippe a débuté début décembre en France métropolitaine, a atteint son pic au cours de la dernière semaine de décembre et s’est terminée fin mars, soit 16 semaines d’épidémie. Elle a présenté une dynamique atypique, avec deux vagues successives dues à la circulation majoritaire du virus A(H1N1)pdm09 puis à celle du virus B Lignage Yamagata. L’épidémie a été d’intensité modérée en médecine ambulatoire mais elle a été caractérisée par un nombre élevé d’hospitalisations après recours aux urgences pour syndrome grippal (>9 700) et de cas graves admis en réanimation (>2 900). Cette épidémie a également été marquée par une surmortalité importante, avec 13 000 décès attribués à la grippe.Conclusion –L’épidémie de grippe 2017-2018, précoce et exceptionnellement longue, a été caractérisée par une dynamique atypique et une importante sévérité, liées à la circulation successive des virus A(H1N1)pdm09 et B/Yamagata, dans un contexte de couverture vaccinale insuffisante et d’efficacité vaccinale sous-optimale. Son impact important sur les hospitalisations et la mortalité rappelle la gravité de la maladie et l’intérêt de la prévention, à savoir la vaccination chez les personnes à risque, complétée de mesures barrières afin de limiter la diffusion du virus dans l’entourage des cas, ainsi que l’utilité d’un traitement antiviral précoce, particulièrement chez les sujets à risque.

International audience; This article summarizes the influenza activity in France for the 2016-17 season.Methods – This report is based on the descriptive analysis of different sources of data on influenza or influenza- like illness collected in mainland France: influenza clinical activity in the community reported by the primary health care network, virological data analysed by reference laboratories, emergency units visits and hospitali- zations for clinical influenza, reporting of acute respiratory infections (ARI) clusters in nursing homes, reporting of severe influenza cases hospitalised in intensive care units (ICU) and mortality data.Results – In mainland France, the 2016-17 season was characterized by a moderate influenza epidemic in the community which started in mid-December, peaked mid-January and lasted 10 weeks. Sub-type A(H3N2) viruses were the almost exclusive circulating influenza viruses. The impact of the influenza epidemic was espe- cially severe among the elderly (65 years old and more) with a high proportion of hospitalisations for influenza among outpatients presenting to emergency ward (16% of 40 000 outpatients) and a high proportion of patients aged above 65 years (69%) among hospitalized patients. This age group accounted for 67% of the 1,479 cases admitted to intensive care. During the epidemic wave, a marked excess mortality estimate at 14,400 deaths attributable to influenza was observed. Over 90% of this excess affected people 75 years old and more.Conclusion – The 2016-17 influenza epidemic was early, moderate, and particularly severe among the elderly. This severity is due to the almost exclusive circulation of A(H3N2) viruses in a context of low vaccine coverage and sub-optimal vaccine effectiveness. It confirms the severity of the disease for the population at risk and strengthens the need for prevention, especially a higher vaccine coverage among people at risk and the implementation of non-pharmaceutical control measures to limit the spread of the virus around cases.; Cet article présente le bilan épidémiologique et virologique de l’activité grippale en France durant la saison 2016-2017.Méthodes – Ce bilan s’appuie sur l’analyse descriptive des données de surveillance de la grippe ou des syndromes grippaux transmises par les réseaux de médecine ambulatoire, les analyses virologiques des laboratoires partenaires, les signalements d’épisodes d’infections respiratoires aiguës (IRA) dans les collec- tivités de personnes âgées, la surveillance des passages aux urgences et des hospitalisations codées grippe, la surveillance des cas graves de grippe hospitalisés en services de réanimation et les données de mortalité.Résultats – L’épidémie de grippe a débuté mi-décembre et a atteint son pic mi-janvier pour se terminer début février, soit une durée totale de 10 semaines. Due quasi-exclusivement au virus grippal de type A(H3N2), elle a été d’intensité modérée en milieu ambulatoire mais a eu un impact important chez les personnes âgées. Elle a été caractérisée par une part importante d’hospitalisations parmi les passages aux urgences pour syndrome grippal (16% des 40 000 passages) et par une proportion importante des 65 ans et plus parmi les patients hospitalisés (69%). Cette tranche d’âge a représenté 67% des 1 479 cas de grippe admis en réanimation. Cette épidémie a également été marquée par un excès de mortalité estimé à 14 400 décès attribuables à la grippe, dont plus de 90% chez les personnes de 75 ans et plus.Conclusion – L’épidémie de grippe 2016-2017, précoce et d’intensité modérée, s’est caractérisée par un impact particulièrement important chez les personnes âgées, lié à la circulation quasi-exclusive de virus A(H3N2) dans un contexte de couverture vaccinale insuffisante et d’efficacité vaccinale sub-optimale. Cette épidémie rappelle la gravité de la maladie et l’importance de la prévention, à savoir la vaccination chez les personnes à risque, qui doit être complétée de mesures barrières pour limiter la diffusion du virus dans l’entourage des cas.

Recent climate change is a consequence of the greenhouse effect and human activity, and is directly responsible for extreme events such as heatwaves (see report of the French Academie des Sciences). Human thermoregulation depends more on behavior than on biology Air conditioning and building structure play an essential role. The 2003 heatwave was not a unique event. Preventive measures reduced mortality during subsequent heatwaves. Most deaths were due to heat stroke associated with dehydration. During strenuous exercise, especially during military training, heat stroke requires specific treatment. Temperature/ global mortality and temperature/cardiovascular mortality curves are both U-shaped. Usually, global mortality increases winter and is linked to temperature. During summer, global mortality increases only when heatwaves occur. Climate change participates in the spread of infectious diseases. Nevertheless, in continental France, for the moment, climate change is not a major factor in the incidence of infectious diseases, despite the fact that several bacteria, viruses and vectors are temperature-sensitive. The situation in Reunion, French Polynesia and French Departments of America is more complicated, due to their geographic heterogeneity. Some areas are more exposed to the climatic risk and could act as a gateway for new infections and mutations. The dramatic loss of biodiversity is partly a consequence of climate change. It increases the transmissibility of some pathogens and can also potentially lead to an increase in autoimmune diseases and obesity. Climate change plays a important role in allergic diseases, through changes in the diffusion and composition of pollens. These modifications are being monitored by several observatories. Six different veterinary diseases, including several zoonoses, are of particular concern.

International audience; BACKGROUND: Declared cases of exposures related to potential toxic agents are reported through a national database, the French Network of Poison Centers, and account on average for 200,000 cases per year, including 75,000 to 80,000 symptomatic cases. These data are currently used to investigate signals from local, national or international institutional partners (such as hospitals, local health authorities, and the Rapid Alert System for Food and Feed). Our objective is to complete this classical toxicovigilance activity through the automated detection of unexpected or unusual events in order to identify precociously signals representing potential threats for public health. To reach this objective, the inventory of surveillance and detection methods of unexpected events is necessary.METHODS: A literature review was conducted via Scopus(®) and Pubmed(®) databases, completed with grey literature and data available on worldwide vigilance systems' websites.RESULTS: The most commonly used methods are disproportional measures in the field of pharmacovigilance, some of which are subject to a routine detection at regular time intervals. Criteria of signal generation differ from one system to another, which have implemented data filtering strategies before or after analysis, in order to decrease the number of generated signals and improve their priority level. These signals are then transmitted to an experts committee for a clinical and epidemiological evaluation, and at times, for informing the patient's medical records. We also notice an interest in other approaches such as surveillance methods of temporal series or symbolic methods for associative rules extraction between one or more drugs and one or more adverse effects, with the possibility to include other types of variables, such a demographic data. The developments of probabilistic-based algorithms have also been recently developed, opening new opportunities.CONCLUSION: These surveillance and detection methods are of high interest for the automated detection of signals from the French toxicovigilance network. The initial step to developing these methods consists in studying the statistical quality of data and targeting the needs and expectations of the toxicovigilance network for what we want and what we can detect.