Common Gaps in Early Warning Systems and Frameworks of Surveillance Strategies for Emerging Infectious Diseases in Livestock Animals | ||
| Journal of Veterinary Medical Research | ||
| Articles in Press, Accepted Manuscript, Available Online from 28 June 2025 PDF (985.92 K) | ||
| Document Type: Review article | ||
| DOI: 10.21608/jvmr.2025.380569.1123 | ||
| Author | ||
| Asmaa N. Mohammed* | ||
| Department of Hygiene, Zoonoses and Epidemiology, Faculty of Veterinary Medicine, Beni-Suef University, Beni-Suef 62511, Egypt. | ||
| Abstract | ||
| Predicting the location of infection occurrence poses a challenge for the surveillance and prevention of Emerging Infectious Diseases (EIDs). Forecasting the individuals or species that will be affected is also a challenging aspect. Establishing surveillance and control programs for EIDs demands a substantial and long-term commitment of limited resources. This is in contrast with the countless potential zoonotic and non-zoonotic infectious diseases that may emerge, even within the scope of diseases involving livestock. Animal disease surveillance involves the methodical gathering of long-standing data on disease occurrences, risk influences, and other related parameters. The data is then analyzed in light of temporal and spatial features to draw conclusions that enable the implementation of the required preventive measures. A robust integrated surveillance system is essential for the early detection of emerging diseases. This review article highlighted the importance of aligning risk-based surveillance strategies with the fundamental mechanisms of disease emergence theory. Furthermore, it underscored the crucial role of flexibility in developing these strategies to ensure early detection of EIDs and address the common gaps in early warning systems, and establish frameworks of surveillance strategies and risk assessment of EIDs. | ||
| Keywords | ||
| Emerging infectious diseases; EIDs; Early warning systems; Prevention & control programs; Risk assessment; Surveillance system | ||
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