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Page No. : 78-95

ABSTRACT

Zoonotic diseases constitute significant threats to public health, food security, and global economies, necessitating advanced epidemiological tools and strategies. This review highlights a comprehensive array of descriptive, analytical, molecular, and experimental approaches within the One Health framework in veterinary epidemiology. Key methodologies include temporal and spatial analysis, molecular diagnostics like Polymerase chain reaction (PCR) and genomic sequencing, and statistical tools such as logistic regression and risk prediction models. These tools facilitate disease diagnosis, surveillance, pathogen characterization, and intervention planning, bridging human, animal, and environmental health. The review identifies critical gaps, including the limited cross-species compatibility of diagnostic tools and challenges in integrating environmental variables. Descriptive epidemiology, with Geographical Information System (GIS) mapping and epidemic curves, aids in identifying zoonotic hotspots, while molecular techniques enhance pathogen detection. Analytical methods, such as case-control and cohort studies, elucidate risk factors, and statistical tools optimize predictive modeling. Moreover, environmental monitoring and exposome analysis provide holistic insights into disease dynamics. Despite their transformative potential, barriers such as heterogeneous datasets and the complexity of multi-host systems persist. Future investigations should prioritize the development of universal diagnostic platforms and the integration of machine learning, and artificial intelligence in predictive modeling. This review underscores the critical role of veterinary epidemiology in mitigating zoonotic threats and fostering global health resilience through interdisciplinary approaches.

Keywords: Zoonotic diseases, One Health, Veterinary epidemiology, Epidemiological tools, Molecular diagnostics, Disease surveillance, Spatial analysis, GIS mapping, Pathogen detection, Environmental monitoring.