Abstract
African Swine Fever (ASF) is an infectious and highly fatal disease affecting wild and domestic swine. It is rapidly spreading worldwide and there is a pressing need for tools that help to identify areas to prioritize monitoring and prevention measures. In Europe, wild boars are the main driver of local spread, transmission, and maintenance of the disease in endemic areas, and also an introduction into ASF-free countries. Landscape connectivity studies are the main discipline to analyze wild species dispersal networks, and it can be an essential tool to predict dispersal wild boars’ movements and the associated potential ASF spread with holistic and successful disease management. In this study, we aimed to integrate structural and functional wild boar connectivity predictions with their population abundance and ASF notifications to calculate the impact of wild boars’ infection across Europe.
First, for the connectivity analyses we defined the available habitat patches, which represent the suitable areas of wild boar habitat. Second, the landscape surrounding the habitat patches was characterized by a resistance surface, measuring the difficulty level of moving through each land cover class of the landscape. Third, we estimated the most favorable routes or corridors of movement for wild boar between habitat patches with the least-cost path algorithm; obtaining the least accumulated resistance between each pair of habitat patches. Fourth, based on the probability of connectivity (PC) index used by the Conefor software (which measures the overall habitat connectivity of a landscape), we identify the most important areas to apply ASF spread control and surveillance measures using two risk indicators: the impact factor (how much the infection of each habitat patch and corridor would potentially affect the whole wild boar network), and the risk factor (the threat of infection of each habitat patch from already affected habitat patches). Furthermore, we tested the accuracy of the risk of infection comparing the results with the temporal distribution of ASF cases from 2019 to July 2022.
Our findings highlighted that the impact and risk factors were generally higher in Europe's central and eastern regions. Additionally, the impact factor was 31 times higher on habitat patches that actually were infected the next year, proving the utility of the proposed approach and the key role of wild boars’ movements in ASF spread. This early warning system tool and network analysis can aid to identify important areas for ASF management and locate the potential routes/corridors of the international spread of the disease to other countries by the natural movements of wild boar. Also, it is a useful tool to implement cost-effective active surveillance and preventive measures in the framework of the European wildlife health surveillance program for ASF disease.