Abstract

African swine fever (ASF) is an infectious and highly fatal disease affecting wild and domestic swine, which is unstoppably spreading worldwide. In Europe, wild boars are one of the main drivers of spread, transmission, and maintenance of the disease. Landscape connectivity studies are the main discipline to analyze wild-species dispersal networks, and it can be an essential tool to predict dispersal-wild boar movement routes and probabilities and therefore the associated potential ASF spread through the suitable habitat. We aimed to integrate wild boar habitat connectivity predictions with their occurrence, population abundance, and ASF notifications to calculate the impact (i.e., the capacity of a landscape feature to favor ASF spread) and the risk (i.e., the likelihood of a habitat patch becoming infected) of wild boar infection across Europe. Furthermore, we tested the accuracy of the risk of infection by comparing the results with the temporal distribution of ASF cases. Our findings identified the areas with the highest impact and risk factors within Europe's central and Eastern regions where ASF is currently distributed. Additionally, the impact factor was 31 times higher on habitat patches that were infected vs non-infected, proving the utility of the proposed approach and the key role of wild boar movements in ASF-spread. All data and resulting maps are openly accessible and usable.

Details

Title
Landscape connectivity for predicting the spread of ASF in the European wild boar population
Author
Goicolea, Teresa 1 ; Cisneros-Araújo, Pablo 2 ; Vega, Cecilia Aguilar 3 ; Sánchez-Vizcaíno, Jose Manuel 3 ; Mateo-Sánchez, MCruz 2 ; Bosch, Jaime 3 

 Universidad Politécnica de Madrid, ETSI Montes, Forestal y del Medio Natural, Madrid, Spain (GRID:grid.5690.a) (ISNI:0000 0001 2151 2978); Universidad Autónoma de Madrid, Department of Biology (Botany), Madrid, Spain (GRID:grid.5515.4) (ISNI:0000 0001 1957 8126) 
 Universidad Politécnica de Madrid, ETSI Montes, Forestal y del Medio Natural, Madrid, Spain (GRID:grid.5690.a) (ISNI:0000 0001 2151 2978) 
 Universidad Complutense de Madrid, VISAVET Health Surveillance Center, Madrid, Spain (GRID:grid.4795.f) (ISNI:0000 0001 2157 7667); Universidad Complutense de Madrid, Department of Animal HealthFaculty of Veterinary, Madrid, Spain (GRID:grid.4795.f) (ISNI:0000 0001 2157 7667) 
Pages
3414
Publication year
2024
Publication date
2024
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2924578362
Copyright
© The Author(s) 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.