The Digital–Health Nexus: A Bayesian Deep Learning Analysis of Technology, E‐Governance, and Environmental Impacts on Life Expectancy

ABSTRACT This study investigates the relationships between carbon emissions, natural resource dependence, information and communication technology (ICT) diffusion, economic development, and e‐government development in shaping life expectancy across 29 African countries over the period 2013–2022. Grounded in the Health Production Model, the study employs a comprehensive methodological framework combining Kernel Regularized Least Squares (KRLS) and Bayesian Neural Network (BNN) analysis to capture both direct and moderating effects. To ensure robustness, the findings are validated using advanced panel estimators, including the Augmented Mean Group (AMG) and Common Correlated Effects Mean Group (CCEMG) approaches, which account for cross‐sectional dependence and heterogeneity. The empirical results show that carbon emissions and natural resource rents significantly reduce life expectancy, while ICT diffusion and economic development exert positive and significant effects on longevity. Importantly, e‐government development emerges as a critical moderating factor, strengthening the positive contributions of ICT diffusion and economic development while mitigating the adverse effects of carbon emissions and resource dependence. By identifying the mechanisms through which environmental, economic, and technological factors interact with governance institutions, the study extends the Health Production Model. The study provides new insights into the digital–health nexus. The findings offer important policy implications, suggesting that strengthening digital governance systems can enhance the effectiveness of development drivers and support integrated strategies that align environmental sustainability, digital transformation, and public health objectives within the Sustainable Development Goals (SDGs) framework.