Faculty of Forest and Environment, University for Sustainable Development Eberswalde, Schicklerstraße 5, 16225 Eberswalde, Germany; School of Biological and Environmental Sciences, Faculty of Science, Liverpool John Moores University, Byrom Street, Liverpool L3 3AF, UK; Department of Wildlife and Aquatic Resources Management, College of Veterinary Medicine and Agriculture, University of Rwanda, P.O. Box: 57, Nyagatare, Rwanda.
School of Biological and Environmental Sciences, Faculty of Science, Liverpool John Moores University, Byrom Street, Liverpool L3 3AF, UK; Department of Wildlife and Aquatic Resources Management, College of Veterinary Medicine and Agriculture, University of Rwanda, P.O. Box: 57, Nyagatare, Rwanda.
Vet Parasitol Reg Stud Reports. 2020 Dec;22:100488. doi: 10.1016/j.vprsr.2020.100488. Epub 2020 Nov 2.
In recent decades, remote sensing (RS) technology and geographical information systems (GIS) were increasingly used as tools for epidemiological studies and the control of zoonotic diseases. Fasciolosis, a zoonotic disease caused by a trematode parasite (Fasciola spp.), is a good candidate for the application of RS and GIS in epidemiology because it is strongly influenced by the environment, i.e. the habitat of the intermediate host. In this study, we examined variables which may increase the fasciolosis risk of Ankole cattle in the degraded and overgrazed Mutara rangelands of north-eastern Rwanda. The risk variables considered included three environmental variables (normalized difference vegetation index, NDVI; normalized difference moisture index, NDMI; normalized difference water index, NDWI), two landscape metric variables (rangeland proportion, building density), two geological variables (poorly-drained soil proportion, elevation) and three animal husbandry variables (herd size, adult proportion and the body condition score). Fasciola spp. prevalence was used as the dependent variable, sampling season as a fixed factor and four principal components (PCs, condensed from the ten risk variables) as covariates in a univariate General Linear Model. Fasciola spp. prevalence was positively correlated to rangeland proportion, cattle herd size in rural areas, adult proportion and individual body condition. Moreover, high Fasciola spp. prevalence was found in densely vegetated areas with high moisture (high values of NDVI and NDMI), in combination with large proportions of poorly-drained soil at low elevations. Future investigations should focus on increased sampling across the Mutara rangelands to prepare a predictive, spatial fasciolosis risk map that would help to further improve sustainable land-use management.
近几十年来，遥感 (RS) 技术和地理信息系统 (GIS) 越来越多地被用作流行病学研究和动物源性疾病控制的工具。由吸虫寄生虫（Fasciola 属）引起的人畜共患病肝片吸虫病是 RS 和 GIS 在流行病学中应用的一个很好的候选疾病，因为它强烈受到环境的影响，即中间宿主的栖息地。在这项研究中，我们检查了可能增加卢旺达东北部退化和过度放牧的 Mutara 牧场中安科勒牛肝片吸虫病风险的变量。考虑的风险变量包括三个环境变量（归一化差异植被指数 NDVI；归一化差异水分指数 NDMI；归一化差异水指数 NDWI）、两个景观度量变量（牧场比例、建筑密度）、两个地质变量（排水不良土壤比例、海拔）和三个畜牧业变量（畜群规模、成年比例和身体状况评分）。Fasciola 属的流行率被用作因变量，采样季节作为固定因素，以及从十个风险变量中提取的四个主成分（PC）作为协变量，用于单变量通用线性模型。Fasciola 属的流行率与牧场比例、农村地区的牛群规模、成年比例和个体身体状况呈正相关。此外，在植被茂密、水分含量高（高 NDVI 和 NDMI 值）的地区，以及低海拔地区排水不良土壤比例较高的地区，发现 Fasciola 属的高流行率。未来的调查应集中在增加对 Mutara 牧场的采样，以准备一个预测性的、空间的肝片吸虫病风险图，这将有助于进一步改善可持续土地利用管理。
