Khayli Mounir, Lhor Youssef, Bengoumi Mohammed, Zro Khalil, El Harrak Mehdi, Bakkouri Abdenacer, Akrim Mohammed, Yaagoubi Reda, El Berbri Ikhlass, Kichou Faouzi, Berrada Jaouad, Bouslikhane Mohammed
National Office of Food Safety (ONSSA), Rabat-Instituts, Po. Box 6472, Rabat, Morocco.
FAO Subregional Office for North Africa, Po. Box 107, 1053, Tunisia.
Heliyon. 2021 Jan 25;7(1):e06019. doi: 10.1016/j.heliyon.2021.e06019. eCollection 2021 Jan.
This study aims to characterize the spatial distribution of animal rabies in Morocco in order to provide appropriate control approaches. Descriptive analyses of the epidemiological data show that the number of reported canine rabies cases greatly underestimates the true incidence of the disease. Underreporting subsequently affects the coherence of its spatial distribution. To perform accurate geographic distribution mapping of the disease based on interpolation methods, a data set was created using data between 2000 and 2018 to compare the derived disease cases with known true values in order to identify disease clusters. The subsequent interpolation was conducted using Ordinary Kriging regression methods and the semi variogram to focus on short distances and reduce uncertainty. The estimated clusters of rabies were evaluated using a cross validation step which revealed predicted cases close to the true values. To improve the precision of analysis, the authors displayed georeferenced dog and human rabies cases reported during the last three years, demonstrating reliable results that correspond to the estimated cluster areas similar to the true disease incidence on the field. This work highlights a strong correlation between infrastructure projects (i.e. railways, roads, facilities) and rabies epizootics for several specific locations. This study is the first attempt to use geostatistics to build upon the understanding of animal rabies in Morocco and shed light on the most appropriate strategies to sustainably reduce and mitigate the risk of rabies. There has been little literature on the use of kriging methods in animal health research. Thus, this study also aimed to explore a novel method in the veterinary sciences to establish kriging as a valid and coherent analysis tool to identify the extent to which the geostatistic area can objectively support understanding on animal rabies and saw it as being highly instrumental in coping with gaps in the data.
本研究旨在描述摩洛哥动物狂犬病的空间分布特征，以便提供适当的防控方法。对流行病学数据的描述性分析表明，报告的犬类狂犬病病例数量大大低估了该疾病的实际发病率。漏报随后影响了其空间分布的连贯性。为了基于插值方法进行该疾病准确的地理分布图绘制，利用2000年至2018年的数据创建了一个数据集，将得出的疾病病例与已知真实值进行比较，以识别疾病聚集区。随后使用普通克里格回归方法和半变异函数进行插值，重点关注短距离并减少不确定性。使用交叉验证步骤对估计的狂犬病聚集区进行评估，结果显示预测病例接近真实值。为提高分析精度，作者展示了过去三年报告的地理参考犬类和人类狂犬病病例，证明了可靠的结果，这些结果与估计的聚集区相对应，类似于实地的真实疾病发病率。这项工作突出了基础设施项目（即铁路、道路、设施）与几个特定地点狂犬病流行之间的强烈相关性。本研究是首次尝试利用地统计学来增进对摩洛哥动物狂犬病的了解，并阐明可持续降低和减轻狂犬病风险的最合适策略。在动物健康研究中使用克里格方法的文献很少。因此，本研究还旨在探索兽医学中的一种新方法，将克里格法确立为一种有效且连贯的分析工具，以确定地统计区域能够在多大程度上客观支持对动物狂犬病的理解，并认为它在应对数据缺口方面非常有用。
