Katz Ingrid T, Thomson Dana Renee, Ravishankar Sindhu, Otwombe Kennedy, Macarayan Erlyn Rachelle, Novak Carissa, Schulte Alison R, Atwood Sidney, Woskie Liana Rosenkrantz, Siegel Zoe, Agins Bruce D, Dietrich Janan, Johnson Blair T, Stevens Erva-Jean, Butler Lisa M, Kavanagh Matthew
Mass General Brigham, Harvard Medical School, Cambridge, Massachusetts, USA
University of Twente Faculty of Geo-Information Science and Earth Observation, Enschede, Overijssel, The Netherlands.
BMJ Glob Health. 2025 Apr 9;10(4):e014750. doi: 10.1136/bmjgh-2023-014750.
To determine how the intersection of increased urban growth and poverty has impacted HIV incidence and prevalence, given growing HIV inequalities globally. Retrospective analysis using combined data from five publicly available, population-level datasets to determine city- and within-urban countrywide estimates of 95-95-95 treatment targets, prevalence and incidence rates from 2015 to 2019. For city-level estimates, we analysed combined data from: Fast-Track City (FTC), SINAN from Brazil and UNAIDS Naomi-Spectrum. Countrywide estimates of HIV prevalence in the urban slum versus non-slum since 2012 were compiled from Population-Based HIV Impact Assessment (PHIA) surveys in 12 countries and Demographic Health Surveys (DHS) in 28 countries. HIV prevalence is generally higher among the urban slum, compared to their non-slum counterparts, thus resulting in national HIV estimates masking nuances in HIV inequalities between the urban slum and non-slum. Specifically, national and city-level HIV estimates mask inequalities within and between cities, with secondary cities often having higher HIV prevalence and incidence rates than capital cities and large urban areas. The urban divide between slum and non-slum populations is a contributor to HIV inequality, often with poorer outcomes in smaller cities than their larger counterparts. Interventions tailored to cities, and particularly those considering local nuances in subpopulations (eg, different genders, ages, roles), are necessary to reduce HIV inequality. Focused HIV programming accounting for structural drivers of inequalities between urban slum and non-slum populations such as inequalities in wealth, education, employment and housing are crucial to closing gaps driving HIV inequalities globally.
鉴于全球范围内艾滋病病毒(HIV)不平等现象日益加剧,为确定城市增长加快与贫困交织如何影响HIV发病率和流行率,我们利用五个公开的人口层面数据集的合并数据进行回顾性分析,以确定2015年至2019年各城市及城市内部全国范围内95-95-95治疗目标、流行率和发病率的估计值。对于城市层面的估计,我们分析了以下合并数据:快速通道城市(FTC)、巴西的SINAN以及联合国艾滋病规划署的Naomi-Spectrum。2012年以来城市贫民窟与非贫民窟地区HIV流行率的全国估计值,是根据12个国家的基于人口的HIV影响评估(PHIA)调查和28个国家的人口与健康调查(DHS)汇编而成。与非贫民窟地区相比,城市贫民窟地区的HIV流行率通常更高,因此全国HIV估计值掩盖了城市贫民窟与非贫民窟之间HIV不平等的细微差别。具体而言,国家和城市层面的HIV估计值掩盖了城市内部和城市之间的不平等,二级城市的HIV流行率和发病率往往高于首都和大城市地区。贫民窟与非贫民窟人口之间的城市差距是导致HIV不平等的一个因素,小城市的情况往往比大城市更差。为减少HIV不平等,需要针对城市制定干预措施,尤其是那些考虑亚人群体(如不同性别、年龄、角色)当地细微差别的措施。针对城市贫民窟与非贫民窟人口之间不平等的结构性驱动因素(如财富、教育、就业和住房方面的不平等)制定有针对性的HIV规划,对于缩小导致全球HIV不平等的差距至关重要。
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