Association between location of out-of-hospital cardiac arrest, on-scene socioeconomic status, and accessibility to public automated defibrillators in two large metropolitan areas in Canada and France

International audienceAimTo compare walking access times to automated external defibrillators (AEDs) between area-level quintiles of socioeconomic status (SES) in out-of-hospital cardiac arrest (OHCA) cases occurring in 2 major urban regions of Canada and France.MethodsThis was an international, multicenter, retrospective cohort study of adult, non-traumatic OHCA cases in the metropolitan Vancouver (Canada) and Rhône County (France) regions that occurred between 2014 and 2018. We calculated area-level SES for each case, using quintiles of country-specific scores (Q5=most deprived). We identified AED locations from local registries. The primary outcome was the simulated walking time from the OHCA location to the closest AED (continuous and dichotomized by a 3-minute 1-way threshold). We fit multivariate models to analyze the association between OHCA-to-AED walking time and outcomes (Q5 vs. others).ResultsA total of 6,187 and 3,239 cases were included from the Metro Vancouver and Rhône County areas, respectively. In Metro Vancouver Q5 areas (vs. Q1-Q4), areas, AEDs were farther from (79% over 400m from case vs. 67%, p<0.001) and required longer walking times to (97% above 3min vs. 91%, p<0.001) cases. In Rhône Q5 areas, AEDs were closer than in other areas (43% over 400m from case vs. 50%, p=0.01), yet similarly poorly accessible (85% above 3min vs. 86%, p=0.79). In multivariate models, AED access time ≥ 3min was associated with decreased odds of survival at hospital discharge in Metro Vancouver (odds ratio 0.41, 95% CI [0.23-0.74], p=0.003).ConclusionsAccessibility of public AEDs was globally poor in Metro Vancouver and Rhône, and even poorer in Metro Vancouver’s socioeconomically deprived areas

Comprendre et surveiller l'évolution de l'épidémie de Covid-19 à partir des appels au numéro 15: l'exemple de l'agglomération parisienne

International audienceWe portray the evolution of the Covid-19 epidemic during the crisis ofMarch-April 2020 in the Paris area, by analyzing the medical emergencycalls received by the EMS of the four central departments of this area(Centre 15 of SAMU 75, 92, 93 and 94). Our study reveals strongdissimilarities between these departments. We show that the logarithmof each epidemic observable can be approximated by a piecewise linearfunction of time. This allows us to distinguish the different phasesof the epidemic, and to identify the delay between sanitary measuresand their influence on the load of EMS. This also leads to analgorithm, allowing one to detect epidemic resurgences. We rely on atransport PDE epidemiological model, and we use methods fromPerron-Frobenius theory and tropical geometry.Nous décrivons l'évolution de l'épidémie de Covid-19 dans l'agglomération parisienne, pendant la crise de Mars-Avril 2020, en analysant les appels d'urgence au numéro 15 traités par les SAMU des quatre départements centraux de l'agglomération (75, 92, 93 et 94). Notre étude révèle de fortes disparités entres ces départements. Nous montrons que le logarithme de toute observable épidémique peut être approché par une fonction du temps linéaire par morceaux. Cela nous permet d'identifier les différentes phases d'évolution de l'épidémie, et aussi d'évaluer le délai entre la prise de mesures sanitaires et leur effet sur la sollicitation de l'aide médicale urgente. Nous en déduisons un algorithme permettant de détecter une resurgence éventuelle de l'épidémie. Notre approche s'appuie sur un modèle d'EDP de transport de l'évolution épidémique, ainsi que sur des méthodes de théorie de Perron-Frobenius et de géométrie tropicale