Actualités

L'ISSPAM organise la deuxième édition de son école d'été "Méthodes et Enjeux en Sciences de la Santé Publique" en format hybride, du 10 au 20 juin 2025 à Marseille lors de laquelle aura lieu un symposium ouvert à tous.

Privilégiant une approche interdisciplinaire, elle a pour objectif de former à la compréhension, l’analyse, l’interprétation de problèmes de santé publique du Nord et des Suds. Elle comprend des enseignements théoriques, pratiques et participatifs dans différents domaines mobilisant des méthodes quantitatives et qualitatives en sciences de la santé publique.

Plus d'informations et programme : https://url.univ-amu.fr/isspam-summer-school 

Dans le cadre de leur école d’été internationale respective, l’ISSPAM - Institut des Sciences de la Santé Publique d’Aix-Marseille Université et l’ISPED – Institut de Santé Publique, d’Epidémiologie et de Développement de l’Université de Bordeaux, organisent un webinaire conjoint.

Au travers de la présentation de résultats de travaux ou de travaux en cours, l’objectif est de sensibiliser les participants aux perspectives offertes par la réutilisation de données de santé, issues d’entrepôts de données de santé ou de bases médico-administratives, pour la recherche en santé publique et en santé.

Programme : 

• « Présentations des données de santé en France » par Julien Bezin (BPH/ U1219, ISPED) ;
• « PharmIAge : réutilisation de données hospitalière pour l’aide à validation pharmaceutique par la détection avancée des erreurs de prescription chez la personne âgée » par Jean-Charles Dufour (SESSTIM, ISSPAM) ;
• « Utilisation des transformers dans le SNDS : un cas d’usage du projet pilote de l’Espace Européen des Données de Santé » par Gayo Diallo (BPH / U1219, ISPED).

Inscription gratuite avant le 6 juin 2025 sur https://ngsurvey.credim.u-bordeaux.fr/s/B643FE46EBFC491D9B7E03CB9A0E85C8

Organisé dans le cadre de l'école d'été de l'ISSPAM, le symposium a pour objectif d’apporter un éclairage collectif sur différents enjeux de santé publique selon une approche de complémentarité des angles d’analyses dans une vision à 360 degrés.

Ce symposium mobilise 4 intervenants autour de 4 thèmes, proposés par chacun des 4 intervenants. Ainsi chaque intervenant porte en 18 minutes un thème qu’il présente et soumet à la réflexion, à l’analyse et à la vision des 3 autres intervenants, disposant chacun de 360 secondes pour cela. Cette table ronde est complétée par des débats entre les intervenants et avec les participants pour générer de l’intelligence collective et avoir cette vision à 360 degrés.

Intervenants

• Isabelle Richard - Professeure des universités et praticienne hospitalière, directrice de l’EHESP, Rennes, France
• Arnaud Chiolero - Epidemiologist, Professor of public health and Director of Population Health Laboratory,University of Fribourg, Switzerland, and Academic Co-Director, Swiss School of Public Health (SSPH+), Zürich, Switzerland
• Remy Slama - Directeur de recherche à l’Inserm, Professeur attaché à l’ENS-PSL, Institut de Biologie de l’ENS, PARSEC (Paris Recherche Santé Environnement Climat), Paris, France
• Nicholas Steel - Clinical Professor in Public Health, Head of Health Services and Primary Care Research Group, Norwich Medical School, University of East Anglian, Norwich, United Kingdom

Thème 1 | Planning healthcare human ressources - Pr. Isabelle Richard

Worldwide the shortage of human resources is threatening the development or the sustainability of healthcare systems. WHO estimates the number of missing professionals by 2030 to 13 million and advocates for the training of more than 40 million.

The objective remains to deliver healthcare to all and this requires solving a complex equation including the following terms: (1) estimating the health needs which depend on predictable variables such as demographic and epidemiological data, and on less predictable variables such as crisis, pandemics, climate change related disasters, (2) defining which professionals carry out which tasks in order to define the available “skill mix”, (3) estimating the level of activity of these professionals both per month and lifelong and there place of practice, (4) defining the structure and capacity of the training system at all levels. The presentation will show the difficulties in identifying these parameters, which are not mutually independent, through a set of examples in both high and low and middle income countries. We will show that improving human resources planning for the healthcare system requires both coordination between different stakeholders, among which the authorities in charge or health, public budgets and higher education, and flexibility if the actual behaviour of the different actors or the general context appear to diverge from the parameters included in the model. We will discuss the pros and cons of regulations aiming to submit practice authorisation to training requirements or influence the place of practice as well as the ethical issues of transnational cooperation and migration issues.

Thème 2 | Too much data? From infodemic to slow data - Pr. Arnaud Chiolero

In the age of the infodemic, it is not enough to have more data to provide useful information for health decision-making. In this presentation, we will highlight some of the problems associated with the use of “Big Data” for public health surveillance. In a “Slow Data” approach (https://pubmed.ncbi.nlm.nih.gov/37789225/), we will discuss the importance of identifying information needs and anticipating their dissemination, and of using high-quality population-based data processed by independent institutions with expertise in epidemiology and surveillance methods.

Thème 3 | Life expectancy and risk factors at local level - Pr. Nicholas Steel

AHealthy life expectancy (HLE) is a key national indicator of population health, which shows large geographic variations. Improving HLE and reducing these variations requires detailed knowledge of related morbidity and mortality risks in smaller geographic areas. In this presentation we will discuss an approach to assessing HLE and risk factors in small areas in England.

We will show how we used publicly available data to estimate HLE in 2011 and 2021 at birth and age 65 for males and females for 128 small areas in Norfolk, a county in England, used geospatial mapping, and analysed links between HLE and relevant risk factors.

We found that HLE at birth ranged from 52 to 73 years for men and 56 to 74 for women, with large variations between small areas in both HLE and exposure to risk factors. Lower HLE at area level was associated with lower weekly income, physical inactivity, air pollution, alcohol admissions, living alone as an older person and unhealthy diet.

We will discuss how this method could be used to monitor risks and inform targeted public health interventions at a local level. Stronger public health surveillance is needed to accurately monitor a wider variety local data on risks.

Thème 4 | To what extent is science considered in the management of environmental health issues? - Dr. Remy Slama

Summary to come and download on the programme link

Date limite d'inscription : 9 juin 2025

Tarifs, informations et inscription : https://institut-isspam.univ-amu.fr/fr/formation/ecole-ete/ecole-ete-20…

Meet the winner of the 2nd edition of the QuanTIM Webinar PhD Award !

This work advances Alzheimer's disease (AD) diagnostics by investigating signs of vascular damage like white matter hyperintensities (WMHs) as potential biomarkers. Initially, it focused on optimizing the automatic segmentation pipelines for WMHs by validating a harmonization strategy for reliable segmentation across multiple datasets and scanners. Then, it explored Quantitative Susceptibility Mapping's contribution to WMH detection, finding significant improvements when incorporated into the imaging protocol. Finally, it used deep learning (DL) models for AD classification across multiple populations, employing explainability techniques to compare WMHs' relevance against healthy tissues and established AD biomarkers.

Remarkably, WMHs demonstrated higher relevance than both normal-appearing white matter and medial temporal loberegions. This finding remained consistent across DL learning architectures and explainability approaches. Our results strongly support including WMHs in AD diagnostic criteria, potentially enhancing early detection and treatment efficacy.

Keywords. White Matter Hyperintensities, Alzheimer's Disease Diagnosis, Imaging Biomarkers, Artificial Intelligence