Integrative One Health Approaches in Disease Prevention

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Auteur principal: Shete, Megha P.
Format: Recurso digital
Publié: Zenodo 2026
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author Shete, Megha P.
author_facet Shete, Megha P.
contents <p><strong><em><span>Abstract</span></em></strong></p> <p><em><span>The One Health approach provides a holistic framework that integrates human, animal, and environmental health to prevent, detect, and respond to emerging infectious diseases. This paper reviews recent advances in One Health strategies, highlighting the role of artificial intelligence (AI), Internet of Things (IoT), genomic epidemiology, and integrated surveillance systems in disease prevention. A novel integrative framework is proposed that combines cross-sector collaboration, real-time data integration, predictive modeling, and IoT-enabled monitoring to enhance early warning and proactive intervention. The paper also addresses implementation challenges, including data interoperability, privacy concerns, and resource limitations, and presents recent case studies illustrating successful One Health initiatives. These insights aim to guide policymakers, researchers, and public health practitioners in developing sustainable, technology-enabled disease prevention strategies.</span></em></p> <p> </p>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_18710293
institution Zenodo
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publishDate 2026
publisher Zenodo
record_format zenodo
spellingShingle Integrative One Health Approaches in Disease Prevention
Shete, Megha P.
Keywords— One Health, Disease Prevention, Integrated Surveillance, Artificial Intelligence, Internet of Things, Genomic Epidemiology, Predictive Modeling, Zoonotic Diseases.
<p><strong><em><span>Abstract</span></em></strong></p> <p><em><span>The One Health approach provides a holistic framework that integrates human, animal, and environmental health to prevent, detect, and respond to emerging infectious diseases. This paper reviews recent advances in One Health strategies, highlighting the role of artificial intelligence (AI), Internet of Things (IoT), genomic epidemiology, and integrated surveillance systems in disease prevention. A novel integrative framework is proposed that combines cross-sector collaboration, real-time data integration, predictive modeling, and IoT-enabled monitoring to enhance early warning and proactive intervention. The paper also addresses implementation challenges, including data interoperability, privacy concerns, and resource limitations, and presents recent case studies illustrating successful One Health initiatives. These insights aim to guide policymakers, researchers, and public health practitioners in developing sustainable, technology-enabled disease prevention strategies.</span></em></p> <p> </p>
title Integrative One Health Approaches in Disease Prevention
topic Keywords— One Health, Disease Prevention, Integrated Surveillance, Artificial Intelligence, Internet of Things, Genomic Epidemiology, Predictive Modeling, Zoonotic Diseases.
url https://doi.org/10.5281/zenodo.18710293