North African cities are increasingly exposed to overlapping climatic and urban pressures. Intensifying heatwaves, persistent water scarcity, growing cooling demand, pressures on urban infrastructure, and widening socioeconomic disparities are reshaping conditions of urban life. Although investment in climate adaptation has increased, urban decision-making frequently remains fragmented. Climate risk, health vulnerability, characteristics of the built environment, infrastructure performance, and social conditions are often addressed separately, limiting the capacity to guide coordinated interventions. Existing approaches to resilience assessment also face constraints, particularly where evaluation remains static or narrowly sectoral, reducing their ability to support predictive and spatially informed planning. This project proposes the development of the Urban Health Resilience Intelligence Platform (UHRIP), conceived as an AI-assisted decision-support system for urban climate and health planning in North African cities. At its core, the platform incorporates a multidimensional Urban Health Resilience Index (UHRI) while extending beyond index-based assessment through the integration of geographic information systems, urban climate analysis, predictive modeling, and scenario evaluation. Resilience is examined through several interrelated dimensions, including thermal exposure, pressures associated with water availability, patterns of energy performance, public health vulnerability, socioeconomic conditions, urban form, ecological infrastructure, and institutional preparedness. The platform is intended to produce spatial assessments of resilience, identify areas of heightened vulnerability, and support prioritization of urban interventions through adaptive planning scenarios. Municipal authorities, planning agencies, ministries, and development institutions constitute the principal target users. A pilot application is proposed in Sfax, Tunisia, where exposure to heat stress, water scarcity, coastal pressures, and urban growth creates a relevant context for testing. Over time, the initiative is intended to provide a framework that can be adapted across cities in North Africa.
Ali et al. (2026) studied this question.