A methodological framework to characterize the wildlife-livestock interface: The case of wild boar in mainland Spain.

BACKGROUND: The representation of wildlife-livestock interface (WLI) at an accurate spatial resolution poses several challenges. Furthermore, there is a lack of published material providing detailed descriptions of geospatial techniques for the purpose of producing visual results that are interpretable and contrastable for epidemiological analysis. OBJECTIVES: Our aim is to develop a standardized, applicable, and scalable methodological framework for describing and characterizing the WLI across a large spatial extent. Subsequently, we aim to employ this framework to depict specific WLI based on different epidemiological scenarios determined by the abundance of wild boar (Sus scrofa) and domestic ungulates as an illustrative case, specifically focusing on mainland Spain. METHODS: To establish a methodological framework, we merged data from both wild and domestic sources into a hexagonal grid. We utilized data on wild boar hunting and the locations of pig, cattle, sheep, and goat farms in mainland Spain. New variables were derived from this combined dataset to illustrate the overlapping abundance between wild boar and domestic species. Finally, a cluster analysis of the generated variables was carried out, with the aim of distinguishing and characterizing various scenarios of the wild boar-domestic ungulate interface in mainland Spain. RESULTS: The hexagonal grid proved appropriate to represent and evaluate the WLI at fine spatial resolution over such broad extent. Despite the inability to ascribe a dominant livestock type and production system to a specific region, we were able to identify fifteen main areas of interest in terms of overlap. As for extensive livestock, normally at the highest risk of interaction with wild boar, the primary regions in Spain were those with dehesa agroecosystem and the Atlantic areas. Certain scenarios were particularly relevant in terms of risk for interaction and subsequent transmission of disease, namely, the case of extensive pig production in south western Spain (dehesa agroecosystem), which is especially concerned about the potential introduction of African Swine fever (ASF) in the Country. DISCUSSION AND CONCLUSIONS: We provide a basis for visualizing and understanding of different WLI scenarios, which is extensible to other regions and interfaces, and automatable where precise source of data from wildlife and livestock are available. This spatial statistics framework enables the utilization of high-resolution data, ensuring consistency on uniform grids. This aligns with the needs of high-resolution disease dissemination models based on wildlife behaviour. Such aspects are crucial for developing risk assessment and improving strategies for the prevention, control, and eradication of shared priority emerging diseases at national and international levels, such as ASF.

Determinants of Crimean-Congo haemorrhagic fever virus exposure dynamics in Mediterranean environments.

Crimean-Congo haemorrhagic fever (CCHF) is an emerging tick-borne human disease in Spain. Understanding the spatiotemporal dynamics and exposure risk determinants of CCHF virus (CCHFV) in animal models is essential to predict the time and areas of highest transmission risk. With this goal, we designed a longitudinal survey of two wild ungulate species, the red deer (Cervus elaphus) and the Eurasian wild boar (Sus scrofa), in Doñana National Park, a protected Mediterranean biodiversity hotspot with high ungulate and CCHFV vector abundance, and which is also one of the main stopover sites for migratory birds between Africa and western Europe. Both ungulates are hosts to the principal CCHFV vector in Spain, Hyalomma lusitanicum. We sampled wild ungulates annually from 2005 to 2020 and analysed the frequency of exposure to CCHFV by a double-antigen ELISA. The annual exposure risk was modelled as a function of environmental traits in an approach to understanding exposure risk determinants that allow us to predict the most likely places and years for CCHFV transmission. The main findings show that H. lusitanicum abundance is a fundamental driver of the fine-scale spatial CCHFV transmission risk, while inter-annual risk variation is conditioned by virus/vector hosts, host community structure and weather variations. The most relevant conclusion of the study is that the emergence of CCHF in Spain might be associated with recent wild ungulate population changes promoting higher vector abundance. This work provides relevant insights into the transmission dynamics of CCHFV in enzootic scenarios that would allow deepening the understanding of the ecology of CCHFV and its major determinants.

Environmental factors driving fine-scale ixodid tick abundance patterns.

Tick abundance is an essential demographic parameter to infer tick-borne pathogen transmission risks. Spatiotemporal patterns of tick abundance are heterogeneous, so its determinants at small spatial scales need to be understood to reduce their negative effects on hosts. Current knowledge of these determinants is scarce, especially in Mediterranean environments, limiting the possibilities for designing efficient tick control strategies. With the goal of unravelling tick abundance determinants and informing new tick management strategies, we estimated tick burdens on 1965 wild ungulates in Doñana National Park, Spain, annually between 2010 and 2020. Under the hypothesis of a predominant host influence on tick abundance, we modelled the burdens of Rhipicephalus annulatus, Hyalomma lusitanicum, and Ixodes ricinus with relevant predictors grouped into four factors: i) environment; ii) host population; iii) host individual; and iv) land-use. Generalized linear mixed models with a zero-inflated negative binomial distribution were built. Additionally, we analysed the differential contribution to abundance of each factor by deviance partitioning. We finally estimated the similarity in the environmental space of tick species by analysing their niche overlap with the environmental principal component analysis method. Our work hypothesis was confirmed for R. annulatus and H. lusitanicum, but we found that tick abundance at a fine spatial scale is jointly driven by multiple drivers, including all four factors considered in this study. This result points out that understanding the demography of ticks is a complex multifactorial issue, even at small spatial scales. We found no niche differences between the three tick species at the study spatial scale, thus showing similar host and environmental dependencies. Overall results identify that host aggregation areas displaying environmentally favourable traits for ticks are relevant tick and vector-borne pathogen transmission hotspots. Our findings will facilitate the design of new strategies to reduce the negative effects of tick parasitism.