Since African swine fever virus (ASFV) genotype II reached Europe in 2007 and has widely spread, causing important economic losses to the pig production sector. To guide policy and management actions, robust quantitative evidence about possible explanatory variables associated with ASF in domestic pigs and Eurasian wild boar (Sus scrofa) is needed. To this aim, a systematic literature review of the scientific evidence available on variables analysed through quantitative methods investigating their possible association with ASF occurrence was carried out in 2021 and updated in 2024. Information on article metadata, study settings, and details of the analysed variables were extracted from the identified articles. The variables were structured in categories and subcategories, and their frequencies were evaluated, as well as the proportions of the studied variables that proved significant in each subcategory. The literature search retrieved 569 articles, resulting in 48 inclusions in the review after application of the selection criteria. The categories of variables most often significantly associated with the occurrence of ASF in domestic pigs were related to the ASF virus infection pressure in the area, socio-economic factors (mainly human population density and poverty), the pig farming system (pig or farm density and certain biosecurity practises), and wild boar habitats. For wild boars, these were also variables related to ASFV infection pressure in the area, wild boar habitats (mainly climatic conditions, vegetation, waterbodies), and socio-economic factors (especially human population and poverty-related variables). Despite the many studies of variables possibly associated with ASF occurrence, the review identified a gap in quantitative observational studies focusing on manageable variables, i.e., those related to specific biosecurity measures applied to pig farms and during hunting. To allow for a meta-analysis of the results, these studies should be performed according to standardised protocols using harmonised data collections.

Iberian ibex (Caprapyrenaica) is an ecologically and economically relevant medium-sized emblematic mountain ungulate. Diseases participate in the population dynamics of the species as a regulating agent, but can also threaten the conservation and viability of vulnerable population units. Moreover, Iberian ibex can also be a carrier or even a reservoir of pathogens shared with domestic animals and/or humans, being therefore a concern for livestock and public health. The objective of this review is to compile the currently available knowledge on (1) diseases of Iberian ibex, presented according to their relevance on the health and demography of free-ranging populations; (2) diseases subjected to heath surveillance plans; (3) other diseases reported in the species; and (4) diseases with particular relevance in captive Iberian ibex populations. The systematic review of all the information on diseases affecting the species unveils unpublished reports, scientific communications in meetings, and scientific articles, allowing the first comprehensive compilation of Iberian ibex diseases. This review identifies the gaps in knowledge regarding pathogenesis, immune response, diagnostic methods, treatment, and management of diseases in Iberian ibex, providing a base for future research. Moreover, this challenges wildlife and livestock disease and wildlife population managers to assess the priorities and policies currently implemented in Iberian ibex health surveillance and monitoring and disease management.

The exposure of dairy cows to Coxiella burnetii using molecular and serological techniques was investigated in this study. Bulk tank milk and serum samples were collected from various farms in Greece (mainly northern Greece). DNA extraction was performed on milk samples, and qPCR targeting the IS1111 insertion sequence was performed to detect bacterial pathogens. An ELISA was used to detect specific antibodies in bulk milk and individual serum samples. Data on farms were collected in the field using handheld Global Positioning System Garmin units. The collected data were analyzed using an Ecological Niche Model within the framework of a geographic information system. The results indicated that in more than half of the dairy farms (35/60, 58.3%), C. burnetii is present in milk. Specific antibodies were also detected in almost all milk samples (57/60, 95.0%). At least one seropositive animal was identified using ELISA in the majority of the examined farms (25/28, 89.3%). C. burnetii PCR-positive farms were located in the low-altitude zone with a mean value of 97 m above sea level (range: 2–681). The environmental variable with the highest gain when used in isolation is precipitation in the wettest quarter (28.3% contribution), which therefore appears to have the most useful information by itself. The environmental variable that decreases the gain the most when omitted is the minimal temperature of the coldest month (6.9% contribution). The analysis demonstrated that a mild climate with low precipitation favors a positive status. The exposure of dairy cattle farms to C. burnetii is massive, raising significant concerns regarding livestock production and public health implications.

Urbanisation is reshaping ecosystems and increasing human–wildlife interactions. Wild boar (Sus scrofa), a highly adaptable species, is increasingly common in European cities, where it exploits natural and anthropogenic resources, often leading to conflict. Predicting when and where wild boars enter urban areas remains challenging, particularly using scalable tools such as remote sensing. Here, we show that temporal and spatial drivers of urban presence are decoupled in Barcelona over a 14-year period. Seasonal vegetation dynamics influenced the timing of urban incursions, with peaks in spring and late summer associated with changes in vegetation moisture and likely reinforced by increased energetic demands during reproduction and early lactation. However, remotely sensed vegetation indices captured these dynamics only partially, limiting their predictive power when used alone. Spatial variation in urban green area use was primarily explained by landscape structure, with proximity to streams and habitat fragmentation contributing similarly. Green areas near natural corridors were concentrated higher and had more variable presence, while heterogeneous landscapes likely facilitated repeated use by increasing access to foraging and refuge. Integrating remote sensing with landscape metrics can improve the anticipation and management of human–wildlife conflicts.

Urbanisation is reshaping ecosystems and increasing human–wildlife interactions. Wild boar (Sus scrofa), a highly adaptable species, is increasingly common in European cities, where it exploits natural and anthropogenic resources, often leading to conflict. Predicting when and where wild boar enters urban areas remains challenging, particularly using scalable tools such as remote sensing. Here we show that temporal and spatial drivers of urban presence are decoupled in Barcelona over a 14-year period. Seasonal vegetation dynamics influenced the timing of urban incursions, with peaks in spring and late summer associated with changes in vegetation moisture and likely reinforced by increased energetic demands during reproduction and early lactation. However, remotely sensed vegetation indices captured these dynamics only partially, limiting their predictive power when used alone. Spatial variation in urban green area use was primarily explained by landscape structure, with proximity to streams and habitat fragmentation contributing similarly. Green areas near natural corridors concentrated higher and more variable presence, while heterogeneous landscapes likely facilitated repeated use by increasing access to foraging and refuge. Integrating remote sensing with landscape metrics can improve anticipation and management of human–wildlife conflicts.