Authors : Ronke V. Olatunde; Millicent Y. Gyasiwaa; Ayange S. Ayangeakaa; Mutiyat A. Usman; Timothy O. Olorundare; Ome Valentina Akpughe

Volume/Issue : Volume 10 - 2025, Issue 6 - June

Google Scholar : https://tinyurl.com/tc5a7pe3

DOI : https://doi.org/10.38124/ijisrt/25jun719

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : 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.

Keywords : Digital Twin, Digital Twin Technology, Precision Medicine, Public Health, Patient Care, Epidemiological Forecasting.

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