Document Type : Original Articles
Authors
1
Tanzania Veterinary Laboratory Agency, Dar es Salaam, Tanzania.
2
Ministry of Livestock and Fisheries, Dodoma, Tanzania.
3
Boyd Orr Centre for Population and Ecosystem Health, School of Biodiversity, One Health & Veterinary Medicine, College of Medical, Veterinary & Life Sciences, University of Glasgow, Glasgow, England.
4
International Livestock Research Institute, Nairobi, Kenya.
5
International Livestock Research Institute, P.O. Box 30709, Nairobi 00100, Kenya
6
College of Veterinary Medicine, University of Minnesota, Saint Paul,United States.
7
College of Veterinary Medicine and Biomedical Sciences, Morogoro, Tanzania.
8
Food and Agriculture Organization of the United Nations, Rome, Italy.
9
SACIDS Africa Centre of Excellence for Infectious Diseases, SACIDS Foundation for One Health, Sokoine University of Agriculture (SUA), Morogoro, Tanzania.
10.32598/ARI.80.5.3402
Abstract
Introduction: Unregulated livestock movements pose a significant risk for the spread of diseases, threatening animal health and productivity. These movements have been cited as a potential driver of the spatial and temporal dynamics of disease spread in the country. However, a formal evaluation of peste des petits ruminants (PPR) spread linked to livestock migration is lacking. This study investigated the extent to which PPR spread can be attributed to livestock movement, while accounting for risk factors such as production system, livestock population, geographical location and season.
Materials & Methods: Data on livestock movement from Tanzania were collected to create network patterns illustrating the risk of PPR circulation across geographical areas and agroecological systems.
Results: Results demonstrate a notable variation in network structure. Compared to movement driven by seasonal variation, trade-related movement extended up to 600 km. Additionally, during the dry season, animals travel longer distances than in the wet season. The probability of contracting PPR infection was found to be half for households with outgoing livestock (outdegree), indicating a lower risk of infection compared to households with more incoming livestock (indegree). The network pattern shows scale-free properties, with negative and near- zero assortative mixing in pastoral and agropastoral societies, respectively.
Conclusion: These findings suggest that pastoral communities in northern Tanzania are prone to PPR infections, suggesting control methods targeting high-potential households in pastoral communities and districts with high livestock populations. The study suggests targeting the pastoral production system in these areas to impede PPR spread. Future research should emphasize dynamic modeling and targeted control interventions.
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