Digital Twin Technology in Precision Medicine and Public Health: Transforming Patient Care and Epidemiological Forecasting

Healthcare providers use digital twins to tailor health-related interventions to personal, genetic, lifestyle, and environmental factors as against the one-size-fits-all model. This is primarily because of its ability to facilitate individualized treatment plans while enhancing clinical decision-making. This study examines the role of digital twin in precision medicine and public health, with a focus on the revolutionizing capacity in patient care and epidemiological forecasting. Using multiple empirical and case studies, the impact of this technology on informing public health strategies and optimizing patient management will be assessed. Despite its transformative potential, the integration of digital twin technology presents challenges such as data interoperability issues and standardization concerns, which hinder effective implementation. Nonetheless, digital twin technology holds promise for improving public health outcomes as it continues to evolve.