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The transmission of infectious diseases is intricately linked to spatiotemporal proximity. Spatial data used in veterinary epidemiology to depict the distribution of disease events typically encompasses pairwise distances between two locations. The Euclidean method is commonly employed to compute such distances. We have developed a tool capable of calculating pairwise distances, considering factors such as orography, the road network, or the land use, given a set of points representing farms or outbreak sites where samples have been collected. The outcome is a three dimensional object comprising six distinct pairwise matrix distances: Euclidean, Haversine, route, route with elevation, orographic/elevation and cost/friction. These distances offers opportunities for exploring novel approaches to integrating the spatial component into epidemiological applications.
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Cazzaro et al. (2024) studied this question.
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