Integrative One Health Approaches in Disease Prevention
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| Format: | Recurso digital |
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Zenodo
2026
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| _version_ | 1866901936672866304 |
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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 |
| language | |
| 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 |