Using geostatistics to better understand the epidemiology of animal rabies in Morocco: what is the contribution of the predictive value?

Abstract

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.

The effects of geographical distributions of buildings and roads on the spatiotemporal spread of canine rabies: An individual-based modeling study

“…Although several modeling studies have investigated the influence of geographical features, such as rivers, roads, and buildings, on rabies spreading [ 7 , 17 , 19 , 33 , 35 ], none of these focused on the small scale of the spatial distribution of these features. Therefore, in this work, we constructed an individual-based epidemic model for canine rabies transmission incorporating the exact geographical distribution of buildings and road networks.…”

“…Geographical features are important determinants of distribution, density, and movement of host populations [ 17 , 33 – 35 ]. For example, natural barriers such as rivers and mountains can halt while roads can facilitate host movement and could affect the rabies transmission dynamics [ 13 , 17 , 33 , 36 , 37 ].…”

Spatial analysis of Varroa destructor and the relationship with surrounding landscape types in Southern Ontario

“…With advancements in communications and the low cost and absence of necessary technical tools to sample bees for Varroa mites, the collection of these data lends itself well to a citizen science approach (Thomas-Bachli et al, 2020;Khayli et al, 2021). With the implementation of citizen science and self-reported Varroa mite counts by beekeepers, agencies can achieve a greater number of observations per year, and cover a greater spatial area, without the need to increase inspector resources.…”

Spatial variability of Cu, Zn and Mn contents in Non-anthropized soils in the Santa Catarina state

“…To estimate the spatial variability of Cu, Mn and Zn, the lag size was previously established with the application of an empirical rule. The lag size corresponds to a distance vector, which must be equal to half of the largest interval between the sampled points (Ramos and Blanco, 2019;Khayli et al, 2021).…”