Recent studies have raised concerns about the potential reemergence of infectious diseases in Arctic regions associated with warming temperatures. Among these, particular attention has been devoted to anthrax, as a consequence of the outbreak that occurred in the Russian Yamalo-Nenets peninsula in 2016. Understanding how environmental change might influence the diffusion of this pathogen could allow informed decisions to prevent further zoonotic or epidemic episodes. To that end, the present study aims to identify and investigate the driving variables that may favor anthrax transmission within the Arctic, in order to build environmental niche maps describing the future suitability of these regions for the pathogen. To do so, we use the MaxEnt statistical learning tool informed by Arctic-specific variables, such as reindeer herd distribution and active-layer variation. Because of the relative lack of reliable georeferenced information in these regions, the resulting potential distribution maps are to be considered preliminary, but they can already provide a first assessment tool for local communities living in potential risk areas. They also indicate areas in which additional investigation is needed to improve the reliability of environmental niche modeling, hence the accuracy of risk mapping and the usefulness to Arctic communities.

Mapping environmental suitability for anthrax reemergence in the Arctic

Stella, Elisa;Gabrieli, Jacopo;Barbante, Carlo;Bertuzzo, Enrico
2021-01-01

Abstract

Recent studies have raised concerns about the potential reemergence of infectious diseases in Arctic regions associated with warming temperatures. Among these, particular attention has been devoted to anthrax, as a consequence of the outbreak that occurred in the Russian Yamalo-Nenets peninsula in 2016. Understanding how environmental change might influence the diffusion of this pathogen could allow informed decisions to prevent further zoonotic or epidemic episodes. To that end, the present study aims to identify and investigate the driving variables that may favor anthrax transmission within the Arctic, in order to build environmental niche maps describing the future suitability of these regions for the pathogen. To do so, we use the MaxEnt statistical learning tool informed by Arctic-specific variables, such as reindeer herd distribution and active-layer variation. Because of the relative lack of reliable georeferenced information in these regions, the resulting potential distribution maps are to be considered preliminary, but they can already provide a first assessment tool for local communities living in potential risk areas. They also indicate areas in which additional investigation is needed to improve the reliability of environmental niche modeling, hence the accuracy of risk mapping and the usefulness to Arctic communities.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10278/3746054
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