Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, St. Paul, MN, United States; Ahadi Veterinary Resource Center, P.O. Box 51002, 00200, Nairobi, Kenya.
Ahadi Veterinary Resource Center, P.O. Box 51002, 00200, Nairobi, Kenya; Veterinary Services Department, Kenya Wildlife Service, P.O. Box 40241, 00100, Nairobi, Kenya.
Prev Vet Med. 2021 Mar;188:105259. doi: 10.1016/j.prevetmed.2021.105259. Epub 2021 Jan 5.
Livestock movements are important drivers for infectious disease transmission. However, paucity of such data in pastoralist communities in rangeland ecosystems limits our understanding of their dynamics and hampers disease surveillance and control. The aim of this study was to investigate animal movement networks in a pastoralist community in Kenya, and assess network-based strategies for disease control. We used network analysis to characterize five types of between-village animal movement networks. We then evaluated implications of these networks for disease spread and control by quantifying topological changes in the network associated with targeted and random removal of nodes. To construct these networks, data were collected using standardized questionnaires (N = 165 households) from communities living within the Maasai Mara Ecosystem in southwestern Kenya. Our analyses show that the Maasai Mara National Reserve (MMNR), a protected wildlife area, was critical for maintaining village connectivity in the agistment network (dry season grazing), with MMNR-adjacent villages being highly utilized during the dry season. In terms of disease dynamics, the network-based basic reproduction number, R, was sufficient to allow disease invasion in all the five networks, and removal of villages based on degree or betweenness was not efficient in reducing R. However, we show that villages with high degree or betweenness may play an important role in maintaining network connectivity, which may not be captured by assessment of R alone. Such villages may function as potential "firebreaks." For example, targeted removal of highly connected village nodes was more effective at fragmenting each network than random removal of nodes, indicating that network-based targeting of interventions such as vaccination could potentially disrupt transmission pathways in the ecosystem. In conclusion, this work shows that animal movements have the potential to shape patterns of disease transmission in this ecosystem, with targeted interventions being a practical and efficient measure for disease control.
牲畜流动是传染病传播的重要驱动因素。然而,在草原生态系统中的牧民社区中,这种数据的缺乏限制了我们对其动态的理解,并阻碍了疾病监测和控制。本研究旨在调查肯尼亚一个牧民社区的动物流动网络,并评估基于网络的疾病控制策略。我们使用网络分析来描述五种类型的村庄间动物流动网络。然后,我们通过量化与有针对性和随机移除节点相关的网络拓扑变化,评估这些网络对疾病传播和控制的影响。为了构建这些网络,我们使用标准化问卷(N=165 户家庭)从肯尼亚西南部马赛马拉生态系统内的社区收集数据。我们的分析表明,马赛马拉国家保护区(MMNR)作为一个受保护的野生动物区,对维持放牧网络(旱季放牧)中的村庄连接性至关重要,在旱季,MMNR 附近的村庄被高度利用。就疾病动态而言,基于网络的基本繁殖数 R 足以允许五种网络中的所有网络发生疾病入侵,并且根据度或介数移除村庄并不能有效地降低 R。然而,我们表明,具有高度数或介数的村庄可能在维持网络连接性方面发挥重要作用,这可能无法通过单独评估 R 来捕捉。这些村庄可能是潜在的“防火带”。例如,有针对性地移除高度连接的村庄节点比随机移除节点更有效地使每个网络碎片化,这表明基于网络的干预措施,如疫苗接种,可能会潜在地破坏生态系统中的传播途径。总之,这项工作表明,动物流动有可能塑造该生态系统中疾病传播的模式,而有针对性的干预措施是疾病控制的一种实际有效的措施。