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Abstract Background There is a growing understanding of the role played by ‘neighbourhood’ in influencing health status. Various neighbourhood characteristics—such as socioeconomic environment, availability of amenities, and social cohesion, may be combined—and this could contribute to rising health inequalities. This study aims to combine a data-driven approach with clustering analysis techniques, to investigate neighbourhood characteristics that may explain the geographical distribution of the onset of myocardial infarction (MI) risk. Methods All MI events in patients aged 35–74 years occurring in the Strasbourg metropolitan area (SMA), from January 1, 2000 to December 31, 2007 were obtained from the Bas-Rhin coronary heart disease register. All cases were geocoded to the census block for the residential address. Each areal unit, characterized by contextual neighbourhood profile, included socioeconomic environment, availability of amenities (including leisure centres, libraries and parks, and transport) and psychosocial environment as well as specific annual rates standardized (per 100,000 inhabitants). A spatial scan statistic implemented in SaTScan was then used to identify statistically significant spatial clusters of high and low risk of MI. Result MI incidence was non-randomly spatially distributed, with a cluster of high risk of MI in the northern part of the SMA [relative risk (RR) = 1.70, p = 0.001] and a cluster of low risk of MI located in the first and second periphery of SMA (RR 0.04, p value = 0.001). Our findings suggest that the location of low MI risk is characterized by a high socioeconomic level and a low level of access to various amenities; conversely, the location of high MI risk is characterized by a high level of socioeconomic deprivation—despite the fact that inhabitants have good access to the local recreational and leisure infrastructure. Conclusion Our data-driven approach highlights how the different contextual dimensions were inter-combined in the SMA. Our spatial approach allowed us to identify the neighbourhood characteristics of inhabitants living within a cluster of high versus low MI risk. Therefore, spatial data-driven analyses of routinely-collected data georeferenced by various sources may serve to guide policymakers in defining and promoting targeted actions at fine spatial level.

BACKGROUND: Expanding access to antiretroviral therapy (ART) in sub-Saharan Africa requires implementation of alternative care delivery models to traditional physician-centered approaches. This longitudinal analysis compares outcomes of patients initiated on antiretroviral therapy (ART) by non-physician and physician providers. METHODS: Adults (≥15 years) initiating ART between September 2007 and March 2010, and with >1 follow-up visit were included and classified according to the proportion of clinical visits performed by nurses or by clinical officers (≥ 80% of visits). Multivariable Poisson models were used to compare 2-year program attrition (mortality and lost to follow-up) and mortality by type of provider. In sensitivity analyses only patients with less severe disease were included. RESULTS: A total of 10,112 patients contributed 14,012 person-years to the analysis: 3386 (33.5%) in the clinical officer group, 1901 (18.8%) in the nurse care group and 4825 (47.7%) in the mixed care group. Overall 2-year program retention was 81.8%. Attrition was lower in the mixed care and higher in the clinical officer group, compared to the nurse group (adjusted incidence rate ratio [aIRR]=0.54, 95%CI 0.45-0.65; and aIRR=3.03, 95%CI 2.56-3.59, respectively). While patients initiated on ART by clinical officers in the mixed care group had lower attrition (aIRR=0.36, 95%CI 0.29-0.44) than those in the overall nurse care group; no differences in attrition were found between patients initiated on ART by nurses in the mixed care group and those included in the nurse group (aIRR=1.18, 95%CI 0.95-1.47). Two-year mortality estimates were aIRR=0.72, 95%CI 0.49-1.09 and aIRR=5.04, 95%CI 3.56-7.15, respectively. Slightly higher estimates were observed when analyses were restricted to patients with less severe disease. CONCLUSION: The findings of this study support the use of a mixed care model with well trained and regularly supervised nurses and medical assistants to provide HIV care in countries with high HIV prevalence.

BackgroundThe French syndromic surveillance (SyS) system, SurSaUD®, was one of the systems used to monitor the COVID-19 outbreak.AimThis study described the epidemiological characteristics of COVID-19-related visits to both emergency departments (EDs) and the network of emergency general practitioners known as SOS Médecins (SOSMed) in France from 17 February to 28 June 2020.MethodsData on all visits to 634 EDs and 60 SOSMed associations were collected daily. COVID-19-related visits were identified using ICD-10 codes after coding recommendations were sent to all ED and SOSMed doctors. The time course of COVID-19-related visits was described by age group and region. During the lockdown period, the characteristics of ED and SOSMed visits and hospitalisations after visits were described by age group and gender. The most frequent diagnoses associated with COVID-19-related visits were analysed.ResultsCOVID-19 SyS was implemented on 29 February and 4 March for EDs and SOSMed, respectively. A total of 170,113 ED and 59,087 SOSMed visits relating to COVID-19 were recorded, representing 4.0% and 5.6% of the overall coded activity with a peak in late March representing 22.5% and 25% of all ED and SOSMed visits, respectively. COVID-19-related visits were most frequently reported for women and those aged 15-64 years, although patients who were subsequently hospitalised were more often men and persons aged 65 years and older.ConclusionSyS allowed for population health monitoring of the COVID-19 epidemic in France. As SyS has more than 15 years of historical data with high quality and reliability, it was considered sufficiently robust to contribute to defining the post-lockdown strategy.