A combined methodological approach to characterize pig farming and its influence on the occurrence of interactions between wild boars and domestic pigs in Corsican micro-regions.

The pig sector in Corsica is based by a wide range of farming systems, mainly characterized on traditional extensive practices, which favor contacts between domestic and wild individuals. These contacts are suspected to influence the maintenance and the transmission of shared infectious diseases between both populations. Therefore, it is important to develop methods that allow to understand and anticipate their occurrence. Modeling these interactions requires accurate data on the presence, location and use of land on pig farms and farming practices, but such data are often unavailable, incomplete or outdated. In this study, we suggest a method to collect and analyze pig farming information that combines approaches from social sciences and epidemiology and enables a spatial representation of an index of potential interaction (IPI) between wild and domestic pigs at municipality level in the Corsican territory. As a first step of the process, interviews were conducted to gather information from 103 pig farms. Then, using hierarchical clustering, we identified five different clusters of pig farming practices which were evaluated and validated by local experts using participatory tools. The five pig farming clusters with their respective estimated levels of direct and indirect interactions with wild boars were combined in a linear equation with pig density to estimate a hypothetical index of potential interaction (IPI) in 155 municipalities. Our results revealed the diversity of pig farming practices across the island of Corsica and pointed out potential hotspots of interaction. Our method proved to be an effective way to collect and update information on the presence and typology of pig farms which has the potential to update official livestock production statistics. The spatial representation of an IPI between wild boars and domestic pigs in the Corsican territory could help design regional disease management strategies and policies to improve the control of certain shared pig pathogens in pig farms from Corsica.

The African swine fever modelling challenge: Model comparison and lessons learnt.

Robust epidemiological knowledge and predictive modelling tools are needed to address challenging objectives, such as: understanding epidemic drivers; forecasting epidemics; and prioritising control measures. Often, multiple modelling approaches can be used during an epidemic to support effective decision making in a timely manner. Modelling challenges contribute to understanding the pros and cons of different approaches and to fostering technical dialogue between modellers. In this paper, we present the results of the first modelling challenge in animal health - the ASF Challenge - which focused on a synthetic epidemic of African swine fever (ASF) on an island. The modelling approaches proposed by five independent international teams were compared. We assessed their ability to predict temporal and spatial epidemic expansion at the interface between domestic pigs and wild boar, and to prioritise a limited number of alternative interventions. We also compared their qualitative and quantitative spatio-temporal predictions over the first two one-month projection phases of the challenge. Top-performing models in predicting the ASF epidemic differed according to the challenge phase, host species, and in predicting spatial or temporal dynamics. Ensemble models built using all team-predictions outperformed any individual model in at least one phase. The ASF Challenge demonstrated that accounting for the interface between livestock and wildlife is key to increasing our effectiveness in controlling emerging animal diseases, and contributed to improving the readiness of the scientific community to face future ASF epidemics. Finally, we discuss the lessons learnt from model comparison to guide decision making.

A combination of probabilistic and mechanistic approaches for predicting the spread of African swine fever on Merry Island.

Over the last decade African swine fever virus, one of the most virulent pathogens known to affect pigs, has devastated pork industries and wild pig populations throughout the world. Despite a growing literature on specific aspects of African swine fever transmission dynamics, it remains unclear which methods and approaches are most effective for controlling the disease during a crisis. As a consequence, an international modelling challenge was organized in which teams analyzed and responded to a stream of data from an in silico outbreak in the fictive country of Merry Island. In response to this outbreak, we developed a modelling approach that aimed to predict the evolution of the epidemic and evaluate the impact of potential control measures. Two independent models were developed: a stochastic mechanistic space-time compartmental model for characterizing the dissemination of the virus among wild boar; and a deterministic probabilistic risk model for quantifying infection probabilities in domestic pig herds. The combined results of these two models provided valuable information for anticipating the main risks of dissemination and maintenance of the virus (speed and direction of African swine fever spread among wild boar populations, pig herds at greatest risk of infection, the size of the epidemic in the short and long terms), for evaluating the impact of different control measures and for providing specific recommendations concerning control interventions.

The Crimean-Congo haemorrhagic fever tick vector Hyalomma marginatum in the south of France: Modelling its distribution and determination of factors influencing its establishment in a newly invaded area.

We developed a correlative model at high resolution for predicting the distribution of one of the main vectors of Crimean-Congo haemorrhagic fever virus (CCHFV), Hyalomma marginatum, in a recently colonised area, namely southern France. About 931 H. marginatum adult ticks were sampled on horses from 2016 to 2019 and 2021 in 14 southern French departments, which resulted in the first H. marginatum detection map on a large portion of the national territory. Such updated presence/absence data, as well as the mean number of H. marginatum per examined animal (mean parasitic load) as a proxy of tick abundance, were correlated to multiple parameters describing the climate and habitats characterising each collection site, as well as movements of horses as possible factors influencing tick exposure. In southern France, H. marginatum was likely detected in areas characterised by year-long warm temperatures and low precipitation, especially in summer and mostly concentrated in autumn, as well as moderate annual humidity, compared to other sampled areas. It confirms that even in newly invaded areas this tick remains exclusively Mediterranean and cannot expand outside this climatic range. Regarding the environment, a predominance of open natural habitats, such as sclerophyllous vegetated and sparsely vegetated areas, were also identified as a favourable factor, in opposition to urban or peri-urban and humid habitats, such as continuous urban areas and inland marshes, respectively, which were revealed to be unsuitable. Based on this model, we predicted the areas currently suitable for the establishment of the tick H. marginatum in the South of France, with relatively good accuracy using internal (AUC = 0.66) and external validation methods (AUC = 0.76 and 0.83). Concerning tick abundance, some correlative relationships were similar to the occurrence model, as well as the type of horse movements being highlighted as an important factor explaining mean parasitic load. However, the limitations of estimating and modelling H. marginatum abundance in a correlative model are discussed.

Implementation of zoning to guide management of foot and mouth disease in Tunisia.

The World Organisation for Animal Health advocates the zoning approach for the surveillance and monitoring of foot and mouth disease (FMD), a highly contagious animal disease. Our purpose is to implement the zoning approach in Tunisia by identifying existing natural and artificial barriers to the movement of live animals. A Geographic Information System (GIS)-based MultiCriteria Evaluation approach was developed. Eight national and international experts were asked to identify the barriers and prioritize them, characterized by a percentage weight between 0 and 100. These barriers were mapped and combined, taking into account their relative importance, to create a friction map that makes it possible to visualize areas where animal movements are restricted. Uncertainty analysis was performed to assess the robustness of the model. The results showed that the selected barriers were in order of decreasing importance: maritime borders with a weight of 33.5%, rivers (13.8%), slopes equal to or greater than 10% (13.8%), wetlands (13.3%), forests (7.7%), land borders (7.7%), railway networks (5%) and main roads (4.9%). The Cap Bon zone is the only favourable zoning area for the control of FMD in Tunisia. A regional approach resulting from this work could be a major asset in identifying regions suitable for zoning in North Africa.

Research perspectives on animal health in the era of artificial intelligence.

Leveraging artificial intelligence (AI) approaches in animal health (AH) makes it possible to address highly complex issues such as those encountered in quantitative and predictive epidemiology, animal/human precision-based medicine, or to study host × pathogen interactions. AI may contribute (i) to diagnosis and disease case detection, (ii) to more reliable predictions and reduced errors, (iii) to representing more realistically complex biological systems and rendering computing codes more readable to non-computer scientists, (iv) to speeding-up decisions and improving accuracy in risk analyses, and (v) to better targeted interventions and anticipated negative effects. In turn, challenges in AH may stimulate AI research due to specificity of AH systems, data, constraints, and analytical objectives. Based on a literature review of scientific papers at the interface between AI and AH covering the period 2009-2019, and interviews with French researchers positioned at this interface, the present study explains the main AH areas where various AI approaches are currently mobilised, how it may contribute to renew AH research issues and remove methodological or conceptual barriers. After presenting the possible obstacles and levers, we propose several recommendations to better grasp the challenge represented by the AH/AI interface. With the development of several recent concepts promoting a global and multisectoral perspective in the field of health, AI should contribute to defract the different disciplines in AH towards more transversal and integrative research.

Using a participatory qualitative risk assessment to estimate the risk of introduction and spread of transboundary animal diseases in scarce-data environments: A Spatial Qualitative Risk Analysis applied to foot-and-mouth disease in Tunisia 2014-2019.

This article presents a participative and iterative qualitative risk assessment framework that can be used to evaluate the spatial variation of the risk of infectious animal disease introduction and spread on a national scale. The framework was developed through regional training action workshops and field activities. The active involvement of national animal health services enabled the identification, collection and hierarchization of risk factors. Quantitative data were collected in the field, and expert knowledge was integrated to adjust the available data at regional level. Experts categorized and combined the risk factors into ordinal levels of risk per epidemiological unit to ease implementation of risk-based surveillance in the field. The framework was used to perform a qualitative assessment of the risk of introduction and spread of foot-and-mouth disease (FMD) in Tunisia as part of a series of workshops held between 2015 and 2018. The experts in attendance combined risk factors such as epidemiological status, transboundary movements, proximity to the borders and accessibility to assess the risk of FMD outbreaks in Tunisia. Out of the 2,075 Tunisian imadas, 23 were at a very high risk of FMD introduction, mainly at the borders; and 59 were at a very high risk of FMD spread. To validate the model, the results were compared to the FMD outbreaks notified by Tunisia during the 2014 FMD epizootic. Using a spatial Poisson model, a significant alignment between the very high and high-risk categories of spread and the occurrence of FMD outbreaks was shown. The relative risk of FMD occurrence was thus 3.2 higher for imadas in the very high and high spread risk categories than for imadas in the low and negligible spread risk categories. Our results show that the qualitative risk assessment framework can be a useful decision support tool for risk-based disease surveillance and control, in particular in scarce-data environments.

Favorable Conditions for Genomic Evaluation to Outperform Classical Pedigree Evaluation Highlighted by a Proof-of-Concept Study in Poplar.

Forest trees like poplar are particular in many ways compared to other domesticated species. They have long juvenile phases, ongoing crop-wild gene flow, extensive outcrossing, and slow growth. All these particularities tend to make the conduction of breeding programs and evaluation stages costly both in time and resources. Perennials like trees are therefore good candidates for the implementation of genomic selection (GS) which is a good way to accelerate the breeding process, by unchaining selection from phenotypic evaluation without affecting precision. In this study, we tried to compare GS to pedigree-based traditional evaluation, and evaluated under which conditions genomic evaluation outperforms classical pedigree evaluation. Several conditions were evaluated as the constitution of the training population by cross-validation, the implementation of multi-trait, single trait, additive and non-additive models with different estimation methods (G-BLUP or weighted G-BLUP). Finally, the impact of the marker densification was tested through four marker density sets. The population under study corresponds to a pedigree of 24 parents and 1,011 offspring, structured into 35 full-sib families. Four evaluation batches were planted in the same location and seven traits were evaluated on 1 and 2 years old trees. The quality of prediction was reported by the accuracy, the Spearman rank correlation and prediction bias and tested with a cross-validation and an independent individual test set. Our results show that genomic evaluation performance could be comparable to the already well-optimized pedigree-based evaluation under certain conditions. Genomic evaluation appeared to be advantageous when using an independent test set and a set of less precise phenotypes. Genome-based methods showed advantages over pedigree counterparts when ranking candidates at the within-family levels, for most of the families. Our study also showed that looking at ranking criteria as Spearman rank correlation can reveal benefits to genomic selection hidden by biased predictions.

Seroprevalence and molecular characterization of foot-and-mouth disease virus in Chad.

This study aimed at determining the seroprevalence of foot-and-mouth disease (FMD) in domestic ruminants and at characterizing the virus strains circulating in four areas of Chad (East Batha, West Batha, Wadi Fira and West Ennedi). The study was carried out between October and November 2016. A total of 1,520 sera samples (928 cattle, 216 goats, 254 sheep and 122 dromedaries) were collected randomly for FMD serological analyses. Nine epithelial tissue samples were also collected from cattle showing clinical signs, for FMDV isolation and characterization. Serological results showed an overall NSP seroprevalence of 40% (375/928) in cattle in our sample (95% CrI [19-63]). However, seroprevalences of 84% (27/32), 78% (35/45) and 84% (21/25) were estimated in cattle over 5 years of age in East Batha, West Batha and Wadi Fira, respectively. In cattle under 1 year of age, 67% (18/27) seroprevalence was estimated in Wadi Fira, 64% (14/22) in East Batha and 59% (13/22) in West Batha. It was found that the high seroprevalences have been obtained in areas where pastures are shared by several different herds but also in farms where two to three species (bovine, caprine and ovine) are raised together. ELISA PrioCHECK® FMDV types O and A and in-house solid phase competition ELISA serotyping results showed that the four O, A, SAT1 and SAT2 serotypes have circulated in Chad in 2016. However, the type SAT2 dominated with an overall seroprevalence of 43% (29/67) and was present in the four areas investigated. The phylogenetic analyses of the VP1 coding sequence allowed determining the serotype SAT2 topotype VII, close to viral strains found in Cameroon in 2015 with a similarity of 98.60%.

Typological analysis of public-private partnerships in the veterinary domain.

Public-Private Partnerships (PPPs) are defined as a collaborative approach in which the public and private sector share resources, responsibilities and risks to achieve common objectives and mutual benefits in a sustainable manner. PPPs are identified as a key solution to reinforce Veterinary Services. However only limited information is available on the scope, added value and enabling factors of PPPs in this sector. The aims of this study were to develop a typology of PPPs in the veterinary field and to identify key success factors and obstacles to their implementation. A structured questionnaire was sent to all 181 World Organisation for Animal Health (OIE) Member Countries and to 47 private contacts. 36 different variables characterizing PPP initiatives were collected. 97 examples of PPPs were retrieved from 76 countries. Dimensionality reduction techniques were combined with clustering and discrimination methods to establish a typology of PPPs and to derive a set of simple rules to classify new instances of PPPs. Three clusters were identified, separated according to two main variables: the type of private partners and the type of interaction. Cluster 1, transactional PPPs, represented the traditional understanding of PPPs by Veterinary Services, initiated and funded by the public sector, giving service delivery accreditation to mostly private veterinarians; cluster 2, collaborative PPPs, included partnerships between producer associations and public Veterinary Services, driven by trade interests; cluster 3, transformational PPPs, represented joint programs initiated and funded by private companies and initially driven by business development objectives. Specific success factors and key obstacles affecting the performances and sustainability of these initiatives were identified for each cluster. This study represents the first practical attempt to develop a meaningful typology of PPPs in the field of animal health and to identify fundamental obstacles currently inhibiting the development of PPPs, and suggests ways to support national Veterinary Services in overcoming these obstacles.

Modeling Culicoides abundance in mainland France: implications for surveillance.

BACKGROUND: Biting midges of the genus Culicoides Latreille (Diptera: Ceratopogonidae) are involved in the transmission of several viruses affecting humans and livestock, particularly bluetongue (BTV). Over the last decade, Culicoides surveillance has been conducted discontinuously and at various temporal and spatial scales in mainland France following the BTV epizootics in 2008-2009 and its reemergence and continuous circulation since 2015. The ability to predict seasonal dynamics and spatial abundance of Culicoides spp. is a key element in identifying periods and areas at high risk of transmission in order to strengthen surveillance for early detection and to establish seasonally disease-free zones. The objective of this study was to model the abundance of Culicoides spp. using surveillance data. METHODS: A mixed-effect Poisson model, adjusted for overdispersion and taking into account temperature data at each trap location, was used to model the weekly relative abundance of Culicoides spp. over a year in 24 vector zones, based on surveillance data collected during 2009-2012. Vector zones are the spatial units used for Culicoides surveillance since 2016 in mainland France. RESULTS: The curves of the predicted annual abundance of Culicoides spp. in vector zones showed three different shapes: unimodal, bimodal or plateau, reflecting the temporal variability of the observed counts between zones. For each vector zone, the model enabled to identify periods of vector activity ranging from 25 to 51 weeks. CONCLUSIONS: Although the data were collected for surveillance purposes, our modeling approach integrating vector data with daily temperatures, which are known to be major drivers of Culicoides spp. activity, provided areas-specific predictions of Culicoides spp. abundance. Our findings provide decisions makers with essential information to identify risk periods in each vector zone and guide the allocation of resources for surveillance and control. Knowledge of Culicoides spp. dynamics is also of primary importance for modeling the risk of establishment and spread of midge-borne diseases in mainland France.

Culicoides Latreille in the sun: faunistic inventory of Culicoides species (Diptera: Ceratopogonidae) in Mayotte (Comoros Archipelago, Indian Ocean).

BACKGROUND: The south-west insular territories of the Indian Ocean have recently received attention concerning the diversity of arthropods of medical or veterinary interest. While a recent study highlighted the circulation of Culicoides-borne viruses, namely bluetongue and epizootic hemorrhagic disease, with clinical cases in Mayotte (comprising two islands, Petite-Terre and Grand-Terre), Comoros Archipelago, no data have been published concerning the species diversity of Culicoides present on the two islands. RESULTS: A total of 194,734 biting midges were collected in 18 sites, covering two collection sessions (April and June) in Mayotte. Our study reports for the first time livestock-associated Culicoides species and recorded at least 17 described Afrotropical species and one undescribed species. The most abundant species during the April collection session were C. trifasciellus (84.1%), C. bolitinos (5.4%), C. enderleini (3.9%), C. leucostictus (3.3%) and C. rhizophorensis (2.1%). All other species including C. imicola represented less than 1% of the total collection. Abundance ranged between 126-78,842 females with a mean and median abundance of 14,338 and 5111 individuals/night/site, respectively. During the June collection, the abundance per night was low, ranging between 6-475 individuals. Despite low abundance, C. trifasciellus and C. bolitinos were still the most abundant species. Culicoides sp. #50 is recorded for the first time outside South Africa. CONCLUSIONS: Our study reports for the first time the Culicoides species list for Mayotte, Comoros Archipelago, Indian Ocean. The low abundance and rare occurrence of C. imicola, which is usually considered the most abundant species in the Afrotropical region, is unexpected. The most abundant and frequent species is C. trifasciellus, which is not considered as a vector species so far, but its role needs further investigation. Further work is needed to describe Culicoides sp. #50 and to carry on faunistic investigations on the other islands of the archipelago as well as in neighboring countries.

Accounting for preferential sampling in species distribution models.

Species distribution models (SDMs) are now being widely used in ecology for management and conservation purposes across terrestrial, freshwater, and marine realms. The increasing interest in SDMs has drawn the attention of ecologists to spatial models and, in particular, to geostatistical models, which are used to associate observations of species occurrence or abundance with environmental covariates in a finite number of locations in order to predict where (and how much of) a species is likely to be present in unsampled locations. Standard geostatistical methodology assumes that the choice of sampling locations is independent of the values of the variable of interest. However, in natural environments, due to practical limitations related to time and financial constraints, this theoretical assumption is often violated. In fact, data commonly derive from opportunistic sampling (e.g., whale or bird watching), in which observers tend to look for a specific species in areas where they expect to find it. These are examples of what is referred to as preferential sampling, which can lead to biased predictions of the distribution of the species. The aim of this study is to discuss a SDM that addresses this problem and that it is more computationally efficient than existing MCMC methods. From a statistical point of view, we interpret the data as a marked point pattern, where the sampling locations form a point pattern and the measurements taken in those locations (i.e., species abundance or occurrence) are the associated marks. Inference and prediction of species distribution is performed using a Bayesian approach, and integrated nested Laplace approximation (INLA) methodology and software are used for model fitting to minimize the computational burden. We show that abundance is highly overestimated at low abundance locations when preferential sampling effects not accounted for, in both a simulated example and a practical application using fishery data. This highlights that ecologists should be aware of the potential bias resulting from preferential sampling and account for it in a model when a survey is based on non-randomized and/or non-systematic sampling.

Deciphering Hybrid Larch Reaction Norms Using Random Regression.

The link between phenotypic plasticity and heterosis is a broad fundamental question, with stakes in breeding. We report a case-study evaluating temporal series of wood ring traits of hybrid larch (Larix decidua × L. kaempferi and reciprocal) in relation to soil water availability. Growth rings record the tree plastic responses to past environmental conditions, and we used random regressions to estimate the reaction norms of ring width and wood density with respect to water availability. We investigated the role of phenotypic plasticity on the construction of hybrid larch heterosis and on the expression of its quantitative genetic parameters. The data came from an intra-/interspecific diallel mating design between both parental species. Progenies were grown in two environmentally contrasted sites, in France. Ring width plasticity with respect to water availability was confirmed, as all three taxa produced narrower rings under the lowest water availability. Hybrid larch appeared to be the most plastic taxon as its superiority over its parental species increased with increasing water availability. Despite the low heritabilities of the investigated traits, we found that the expression of a reliable negative correlation between them was conditional to the water availability environment. Finally, by means of a complementary simulation, we demonstrated that random regression can be applied to model the reaction norms of non-repeated records of phenotypic plasticity bound by a family structure. Random regression is a powerful tool for the modeling of reaction norms in various contexts, especially perennial species.

Advanced spectroscopy-based phenotyping offers a potential solution to the ash dieback epidemic.

Natural and urban forests worldwide are increasingly threatened by global change resulting from human-mediated factors, including invasions by lethal exotic pathogens. Ash dieback (ADB), incited by the alien invasive fungus Hymenoscyphus fraxineus, has caused large-scale population decline of European ash (Fraxinus excelsior) across Europe, and is threatening to functionally extirpate this tree species. Genetically controlled host resistance is a key element to ensure European ash survival and to restore this keystone species where it has been decimated. We know that a low proportion of the natural population of European ash expresses heritable, quantitative resistance that is stable across environments. To exploit this resource for breeding and restoration efforts, tools that allow for effective and efficient, rapid identification and deployment of superior genotypes are now sorely needed. Here we show that Fourier-transform infrared (FT-IR) spectroscopy of phenolic extracts from uninfected bark tissue, coupled with a model based on soft independent modelling of class analogy (SIMCA), can robustly discriminate between ADB-resistant and susceptible European ash. The model was validated with populations of European ash grown across six European countries. Our work demonstrates that this approach can efficiently advance the effort to save such fundamental forest resource in Europe and elsewhere.

Genomic-based multiple-trait evaluation in Eucalyptus grandis using dominant DArT markers.

We investigated the impact of combining the pedigree- and genomic-based relationship matrices in a multiple-trait individual-tree mixed model (a.k.a., multiple-trait combined approach) on the estimates of heritability and on the genomic correlations between growth and stem straightness in an open-pollinated Eucalyptus grandis population. Additionally, the added advantage of incorporating genomic information on the theoretical accuracies of parents and offspring breeding values was evaluated. Our results suggested that the use of the combined approach for estimating heritabilities and additive genetic correlations in multiple-trait evaluations is advantageous and including genomic information increases the expected accuracy of breeding values. Furthermore, the multiple-trait combined approach was proven to be superior to the single-trait combined approach in predicting breeding values, in particular for low-heritability traits. Finally, our results advocate the use of the combined approach in forest tree progeny testing trials, specifically when a multiple-trait individual-tree mixed model is considered.

Rising Out of the Ashes: Additive Genetic Variation for Crown and Collar Resistance to Hymenoscyphus fraxineus in Fraxinus excelsior.

Since the early 1990s, ash dieback due to the invasive ascomycete Hymenoscyphus fraxineus is threatening Fraxinus excelsior in most of its natural range. Previous studies reported significant levels of genetic variability in susceptibility in F. excelsior either in field or inoculation experiments. The present study was based on a field experiment planted in 1995, 15 years before onset of the disease. Crown and collar status were monitored on 777 trees from 23 open-pollinated progenies originating from three French provenances. Health status was modeled using a Bayesian approach where spatiotemporal effects were explicitly taken into account. Moderate narrow-sense heritability was found for crown dieback (h2 = 0.42). This study is first to show that resistance at the collar level is also heritable (h2 = 0.49 for collar lesions prevalence and h2 = 0.42 for their severity) and that there is significant genetic correlation (r = 0.40) between the severities of crown and collar symptoms. There was no evidence for differences between provenances. Family effects were detected, but computing individual breeding values showed that most of the genetic variation lies within families. In agreement with previous reports, early flushing correlates with healthier crown. Implications of these results in disease management and breeding are discussed.

Bovine paramphistomosis in Galicia (Spain): prevalence, intensity, aetiology and geospatial distribution of the infection.

The present study explored various basic aspects of the epidemiology of paramphistomosis in Galicia, the main cattle producing region in Spain. In total, 589 cows from different farms located across the region were selected at random in the slaughterhouse for examination of the rumens and reticula for the presence of Paramphistomidae flukes. Paramphistomes were found in 111 of 589 necropsied cows (18.8%; 95% CI: 15.7-21.9%), with higher prevalences of infection in beef cows than in dairy cows (29.2% vs 13.9%). Although the number of flukes per animal was generally low (median=266 flukes), some cows harboured large parasite burdens (up to 11,895 flukes), which may have harmful effects on their health or productivity. Cows with higher parasite burdens also excreted greater numbers of fluke eggs in their faeces, which suggests that heavily parasitized mature cows play an important role in the transmission of paramphistomosis. This role may be particularly important in Galicia, where the roe deer, which is the only wild ruminant in the study area, was found not to be a reservoir for the infection. The use of morpho-anatomical and molecular techniques applied to a large number of fluke specimens provided reliable confirmation that Calicophoron daubneyi is the only species of the family Paramphistomidae that parasitizes cattle in Galicia. The environmental data from the farms of origin of the necropsied cows were used in Bayesian geostatistical models to predict the probability of infection by C. daubneyi throughout the region. The results revealed the role of environmental risk factors in explaining the geographical heterogeneity in the probability of infection in beef and dairy cattle. These explanatory factors were used to construct predictive maps showing the areas with the highest predicted risk of infection as well as the uncertainty associated with the predictions.