Human mobility in West Africa is deeply embedded in socio-economic demands and environmental variability, yet existing studies often treat these drivers in isolation. This paper develops an integrated analytical model to examine the dynamic interplay between migration, social demand structures, and environmental change among the Frafra communities of Northern Ghana and the Biali communities of Northern Benin. Drawing upon a synthesis of established migration theories and empirical evidence from West African scholarship, the study conceptualizes migration as a multi-scalar adaptive strategy shaped by institutional, ecological, and socio-cultural pressures. A comparative modeling framework is proposed, combining demographic data, socio-economic indicators, and environmental stress variables to simulate migration decision-making processes. The findings indicate that migration is neither purely economically driven nor solely environmentally induced; rather, it emerges from a complex interaction of livelihood constraints, social obligations, and ecological risks. The study highlights the role of population pressure, land tenure transformations, and climate variability in restructuring migration patterns. It further identifies asymmetries in adaptive capacity between the two regions due to institutional and infrastructural differences. The research contributes to migration studies by offering a system-based framework that integrates environmental and social dimensions, providing a basis for policy interventions targeting sustainable livelihoods and climate resilience in West Africa.

Malignant mesothelioma remains a critical occupational and environmental health concern, traditionally associated with industrial asbestos exposure. However, emerging evidence indicates significant under-recognized risks in agricultural settings, particularly in regions with historical asbestos usage such as Lombardy, Italy. This study develops a comprehensive investigative framework to assess asbestos-related mesothelioma incidence among rural agricultural populations. The framework integrates epidemiological surveillance, occupational exposure reconstruction, environmental assessment, and cohort-based risk modeling. Drawing upon established studies of agricultural health cohorts and mesothelioma surveillance systems, this research identifies hidden exposure pathways including contaminated agricultural materials, secondary environmental exposure, and non-traditional occupational settings. The proposed methodology emphasizes longitudinal cohort analysis and spatial clustering techniques to quantify incidence patterns. Findings indicate that mesothelioma risk in agricultural communities is systematically underestimated due to fragmented exposure histories and insufficient surveillance coverage. The study contributes a structured, replicable model for identifying and analyzing asbestos-related disease in rural contexts, offering critical implications for public health policy, occupational safety regulation, and preventive interventions.