Parker Craig, Mahlasi Craig, Govindasamy Tamara, Radebe Lebohang, Brink Nicholas Brian, Jack Christopher, Doumbia Madina, Kouakou Etienne, Chersich Matthew, Cissé Guéladio, Makhanya Sibusisiwe
Faculty of Health Sciences, Wits Planetary Health Research, University of the Witwatersrand, 7 York Road, Parktown, Johannesburg, 2193, South Africa.
IBM Research Africa, Johannesburg, South Africa.
Int J Biometeorol. 2025 Jul 2. doi: 10.1007/s00484-025-02971-y.
Urban populations face increasing vulnerability to extreme heat events, particularly in rapidly urbanising Global South cities where environmental exposure intersects with socioeconomic inequality and limited healthcare access. This study quantifies heat vulnerability across Johannesburg, South Africa, by integrating high-resolution environmental data with socio-economic and health metrics across 135 urban wards. We examine how historical urban development patterns influence contemporary vulnerability distributions using principal component analysis and spatial statistics. Environmental indicators (Land Surface Temperature (LST), vegetation indices, and thermal field variance) were combined with socioeconomic and health variables (including indicators on crowded dwellings and healthcare access, self-reporting of chronic diseases) in a comprehensive vulnerability assessment. Principal Component Analysis revealed three primary dimensions explaining 56.6% (95% CI: 52.4-60.8%) of the total variance: urban heat exposure (31.5%), health status (12.8%), and socio-economic conditions (12.3%). Built-up areas showed weak but significant correlations with heat indices (ρ = 0.28, p < 0.01), while higher poverty levels demonstrated moderate positive correlations with LST (ρ = 0.41, p < 0.001). The spatial analysis identified significant clustering of vulnerability (Global Moran's I = 0.42, p < 0.001), with distinct high-vulnerability clusters in historically disadvantaged areas. Alexandra Township showed the highest vulnerability(HVI score: 0.87, LST: 29.8 °C ± 0.4 °C, NDVI: 0.08 ± 0.02), with factors characterising the high vulnerability in that area including limited healthcare access and extreme heat exposure. Northern suburbs formed a significant low-vulnerability cluster (Mean HVI = 0.23 ± 0.07, p < 0.001), benefiting from greater vegetation coverage and better healthcare access. These findings demonstrate how historical planning decisions continue to shape contemporary environmental health risks, with vulnerability concentrated in areas of limited healthcare access and high extreme heat exposure. Results suggest the need for targeted interventions that address both environmental and social dimensions of heat vulnerability, particularly focusing on expanding healthcare access in identified hotspots and implementing community-scale green infrastructure in high-risk areas. This study provides an evidence-based framework for prioritising heat-resilience initiatives in rapidly urbanising Global South cities while highlighting the importance of addressing historical inequities in urban adaptation planning.
城市人口面临着越来越大的极端高温事件脆弱性,尤其是在快速城市化的全球南方城市,那里的环境暴露与社会经济不平等以及有限的医疗保健可及性相互交织。本研究通过将高分辨率环境数据与南非约翰内斯堡135个城市选区的社会经济和健康指标相结合,对该市的高温脆弱性进行了量化。我们使用主成分分析和空间统计方法,研究历史城市发展模式如何影响当代脆弱性分布。在一项全面的脆弱性评估中,将环境指标(地表温度(LST)、植被指数和热场方差)与社会经济和健康变量(包括关于拥挤居住和医疗保健可及性的指标、慢性病的自我报告)相结合。主成分分析揭示了三个主要维度,解释了总方差的56.6%(95%置信区间:52.4 - 60.8%):城市高温暴露(31.5%)、健康状况(12.8%)和社会经济条件(12.3%)。建成区与热指数显示出微弱但显著的相关性(ρ = 0.28,p < 0.01),而较高的贫困水平与地表温度显示出中等程度的正相关(ρ = 0.41,p < 0.001)。空间分析确定了脆弱性的显著聚类(全局莫兰指数I = 0.42,p < 0.001),在历史上处于不利地位的地区有明显的高脆弱性聚类。亚历山德拉镇显示出最高的脆弱性(高温脆弱性指数得分:0.87,地表温度:29.8°C ± 0.4°C,归一化植被指数:0.08 ± 0.02),该地区高脆弱性的特征因素包括有限的医疗保健可及性和极端高温暴露。北郊形成了一个显著的低脆弱性聚类(平均高温脆弱性指数 = 0.23 ± 0.07,p < 0.001),受益于更大的植被覆盖和更好的医疗保健可及性。这些发现表明历史规划决策如何继续塑造当代环境健康风险,脆弱性集中在医疗保健可及性有限和极端高温暴露高的地区。结果表明需要有针对性的干预措施,以解决高温脆弱性的环境和社会层面问题,特别是着重在已确定的热点地区扩大医疗保健可及性,并在高风险地区实施社区规模的绿色基础设施。本研究为在快速城市化的全球南方城市优先开展耐热性倡议提供了一个基于证据的框架,同时强调了在城市适应规划中解决历史不平等问题的重要性。