African swine fever (ASF) is one of the most severe diseases of pigs; it has a drastic impact on the pig industry, causing serious socio-economic consequences to pig farmers and pork producers. In Europe, there are currently two main clusters of infection; one in Sardinia caused by strains of African swine fever virus (ASFV) belonging to genotype I and another in Eastern Europe caused by strains of ASFV belonging to genotype II. The latter is inducing an acute form of ASF and it represents a serious threat to the pig sector. ASF is a disease for which there is no effective vaccine; therefore, prevention has a pivotal role in the control strategy of the disease. This review describes the main preventive measures to adopt to mitigate the risk of ASF spread in pig farming systems.

African swine fever (ASF) is a notifiable viral disease of pigs and wild boars that could lead to serious economic losses for the entire European pork industry. As no effective treatment or vaccination is available, disease prevention and control rely on strictly enforced biosecurity measures tailored to the specific risk factors of ASF introduction within domestic pig populations. Here, we present a review addressing the risk factors associated with different European pig farming systems in the context of the actual epidemiological scenario. A list of keywords was combined into a Boolean query, “African swine fever” AND (“Risk factors” OR “Transmission” OR “Spread” OR “Pig farming” OR “Pigs” OR “Wild boars”); was run on 4 databases; and resulted in 52 documents of interest being reviewed. Based on our review, each farming system has its own peculiar risk factors: commercial farms, where best practices are already in place, may suffer from unintentional breaches in biosecurity, while backyard and outdoor farms may suffer from poor ASF awareness, sociocultural factors, and contact with wild boars. In the literature selected for our review, human-related activities and behaviours are presented as the main risks, but we also stress the need to implement biosecurity measures also tailored to risks factors that are specific for the different pig farming practices in the European Union (EU).

African swine fever (ASF) is one of the most severe diseases of pigs and has a drastic impact on pig industry. Wild boar populations play the role of ASF genotype II virus epidemiological reservoir. Disease surveillance in wild boar is carried out either by testing all the wild boar found sick or dead for virus detection (passive surveillance) or by testing for virus (and antibodies) all hunted wild boar (active surveillance). When virus prevalence and wild boar density are low as it happens close to eradication, the question on which kind of surveillance is more efficient in detecting the virus is still open. We built a simulation model to mimic the evolution of the host-parasite interaction in the European wild boar and to assess the efficiency of different surveillance strategies. We constructed a deterministic SIR model, which estimated the probability to detect the virus during the 8 years following its introduction, using both passive and active surveillance. Overall, passive surveillance provided a much larger number of ASF detections than active surveillance during the first year. During subsequent years, both active and passive surveillance exhibited a decrease in their probability to detect ASF. Such decrease, though, was more pronounced for passive surveillance. Under the assumption of 50% of carcasses detection, active surveillance became the best detection method when the endemic disease prevalence was lower than 1.5%, when hunting rate was >60% and when population density was lower than 0.1 individuals/km². In such a situation, though, the absolute probability to detect the disease was very low with both methods, and finding almost every carcass is the only way to ensure virus detection. The sensitivity analysis shows that carcass search effort is the sole parameter that increases proportionally the chance of ASF virus detection. Therefore, an effort should be made to promote active search of dead wild boar also in endemic areas, since reporting wild boar carcasses is crucial to understand the epidemiological situation in any of the different phases of ASF infection at any wild boar density.

The complex health problem of antimicrobial resistance (AMR) involves many host species, numerous bacteria and several routes of transmission. Extended-spectrum β-lactamase and AmpC (ESBL/AmpC)-producing Escherichia coli are among the most important strains. Moreover, wildlife hosts are of interest as they are likely antibiotics free and are assumed as environmental indicators of AMR contamination. Particularly, wild boar (Sus scrofa) deserves attention because of its increased population densities, with consequent health risks at the wildlife–domestic–human interface, and the limited data available on AMR. Here, 1504 wild boar fecal samples were microbiologically and molecularly analyzed to investigate ESBL/AmpC-producing E. coli and, through generalized linear models, the effects of host-related factors and of human population density on their spread. A prevalence of 15.96% of ESBL/AmpC-producing E. coli, supported by bla_CTX-M (12.3%), bla_TEM (6.98%), bla_CMY (0.86%) and bla_SHV (0.47%) gene detection, emerged. Young animals were more colonized by ESBL/AmpC strains than older subjects, as observed in domestic animals. Increased human population density leads to increased bla_TEM prevalence in wild boar, suggesting that spatial overlap may favor this transmission. Our results show a high level of AMR contamination in the study area that should be further investigated. However, a role of wild boar as a maintenance host of AMR strains emerged.

A semi-quantitative risk assessment was developed to classify pig farms in terms of the probability of introduction of African swine fever virus (ASFV). Following on-farm data collection via a specific checklist, we applied a modified failure mode and effect analysis (FMEA) to calculate the risk priority codes (RPC's), indicating increasing risk levels ranging from 1 to 5. The importance of biosecurity measures was attributed by experts. To consider geographic risk factors, we classified pig farms based on local density of farmed pigs, and on the estimated wild boar population density. The combination of RPC's with geographical risk factors resulted into a final ranking of pig farms in terms of the risk of ASFV introduction. Furthermore, the estimation of frequency and levels of non-compliance with biosecurity measures was used to identify weak points in risk prevention at farm level. The outcome of the risk assessment was affected by choices in assigning non-compliance scores and importance to specific components of biosecurity. The method was applied in 60 commercial farms in major pig production areas in Italy. Furthermore, we applied a reduced version of our checklist in 12 non-commercial/small commercial (≤20 pigs) farms in the northern Apennines. In commercial farms, highest RPC's were obtained for biosecurity measures associated with personnel practices and farm buildings/planimetry. Intervention should be addressed to training of personnel on biosecurity and ASF, to avoid contacts with other pig herds, and to improve practices in the entrance into the farm. Sharing trucks with other farms, and loading/unloading of pigs were other weak points. Fencing was classified as insufficient in 70% of the commercial farms. Among these farms, breeding units were characterised by the lowest risk of ASFV introduction (although differences among median ranks were not statistically significant: P-value = 0.07; Kruskal–Wallis test), and increasing herd size was not significantly correlated with a higher risk (Kendall's τ = −0.13; P-value = 0.14). Density of farmed pig was greatest in the main pig production area in northern Italy. Conversely, exposure to wild boars was greatest for non-commercial/small commercial farms on the Apennines, which were also characterised by non-compliance with critical biosecurity measures.