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Preliminary Study on the Development of a Transmission Model for Canine Distemper Virus in Wildlife Populations Using
Bryan Andrew Lazarus1, Muhammad Farris Mohd Sadali2, Farina Mustaffa Kamal2
1Department of Veterinary Preclinical Science, Faculty of Veterinary Medicine, University Putra Malaysia (UPM), Serdang 43400, Malaysia.
Canine Distemper Virus (CDV) spread in wildlife is poorly understood. This study models CDV transmission using heat maps and R0, identifying high-risk zones for conservation efforts.
Area of Science:
- Veterinary Epidemiology
- Wildlife Disease Ecology
- Conservation Biology
Background:
- Canine Distemper Virus (CDV) poses a significant threat to wildlife biodiversity and conservation.
- Understanding CDV transmission dynamics in wildlife, particularly in tropical ecosystems, is crucial but challenging due to data limitations.
- Current surveillance methods for wild animals are difficult to implement effectively.
Purpose of the Study:
- To develop a predictive model for estimating Canine Distemper Virus transmission potential in wildlife populations.
- To utilize spatial heat mapping and the basic reproduction number (R0) as key indicators for disease spread.
- To identify high-risk areas for CDV outbreaks to inform conservation and management strategies.
Main Methods:
- Integrated field observation data, environmental variables, and reported CDV cases.
- Generated predictive spatial heat maps to visualize potential disease transmission hotspots.
- Simulated CDV spread dynamics across various susceptible wildlife host populations.
- Employed the basic reproduction number (R0) to quantify transmission potential.
Main Results:
- Identified specific environmental factors and animal density hotspots as significant contributors to increased CDV transmission potential.
- Demonstrated that high-risk zones for CDV outbreaks can be delineated by analyzing overlapping wildlife movement corridors and human-wildlife interface areas.
- Preliminary findings highlight the utility of spatial modeling in pinpointing areas vulnerable to CDV spread.
Conclusions:
- The developed modeling approach provides a valuable tool for proactive wildlife disease management.
- Spatial heat mapping and R0 estimation can effectively guide targeted monitoring and early detection of CDV.
- This methodology supports the implementation of informed conservation strategies to mitigate CDV impacts on wildlife populations.
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