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CHARACTERIZING MOVEMENT PATTERNS OF NOMADIC PASTORALISTS AND THEIR EXPOSURE TO RIFT VALLEY FEVER IN KENYA
The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences ; XLVIII-M-1-2023:211-216, 2023.
Article in English | ProQuest Central | ID: covidwho-2300422
ABSTRACT
The role of animal movement in spreading infectious diseases is highly recognized by various legislations and institutions such as the World Organisation for Animal Health and the International Animal Health Code. The increased interactions at the nexus of human-animal-ecosystem interface have seen an unprecedented introduction and reintroduction of new zoonotic diseases with high socio-economic impacts such as the COVID-19 pandemic. Rift Valley fever (RVF) is a zoonotic disease that affects both humans and animals and is transmitted by Aedes mosquitoes or through contact with the body fluids of infected animals. This study seeks to characterize movement patterns of pastoralist and how this movement behaviour increases their susceptibility to RVF virus exposure. We levarage on a rapidly growing field of movement ecology to monitor five herds collared from 2013 – 2015 in an RVF endemic semi-arid region in Kenya. The herds were also sampled for RVF antibodies to assess their exposure to RVF virus during the rainy seasons. adehabitatLT package in R was used to analyze the trajectory data whereas the first passage time (FPT) analysis was used to measure the area utilized in grazing. Sedentary herds grazed within 15km radius while migrating herds presented restricted space use patterns during the dry seasons and transient movement during the start and end of the rainy season. Furthermore, RVF virus antibodies were generally low for sedentary herds whereas the migrating herds recorded high levels during their transition periods. This study can be used to identify RVF risk zones for timely and targeted management strategies.
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Full text: Available Collection: Databases of international organizations Database: ProQuest Central Language: English Journal: The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences Year: 2023 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: ProQuest Central Language: English Journal: The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences Year: 2023 Document Type: Article