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.

African swine fever (ASF) is a serious global concern from an ecological and economic point of view. While it is well established that its main transmission routes comprise contact between infected and susceptible animals and transmission through contaminated carcasses, the specific mechanism leading to its long-term persistence is still not clear. Among others, a proposed mechanism involves the potential role of convalescent individuals, which would be able to shed the virus after the end of the acute infection. Using a spatially explicit, stochastic, individual-based model, we tested: (1) if ASF can persist when transmission occurs only through infected wild boars and infected carcasses; (2) if the animals that survive ASF can play a relevant role in increasing ASF persistence chances; (3) how hunting pressure can affect the ASF probability to persist. The scenario in which only direct and carcass-mediated transmission were contemplated had 52% probability of virus persistence 10 years after the initial outbreak. The inclusion of survivor-mediated transmission corresponded to slightly higher persistence probabilities (57%). ASF prevalence during the endemic phase was generally low, ranging 0.1–0.2%. The proportion of seropositive individuals gradually decreased with time and ranged 4.5–6.6%. Our results indicate that direct and carcass-mediated infection routes are sufficient to explain and justify the long-term persistence of ASF at low wild boar density and the ongoing geographic expansion of the disease front in the European continent. During the initial years of an ASF outbreak, hunting should be carefully evaluated as a management tool, in terms of potential benefits and negative side-effects, and combined with an intensive effort for the detection and removal of wild boar carcasses. During the endemic phase, further increasing hunting effort should not be considered as an effective strategy. Additional effort should be dedicated to finding and removing as many wild boar carcasses as possible.

African Swine Fever (ASF) is a highly lethal viral disease, which affects different species of wild and domestic suids. After its human-caused introduction in Georgia in 2007, the ASF virus has found a new ecological reservoir in the large and continuous wild boar (Sus scrofa) populations of Eurasia, spreading both eastward and westward. ASF has also breached into the intensive pork meat production system. Although the disease has no zoonotic potential, its consequences on wild boar populations and the economic losses for the pig industry have been dramatic. As no vaccine or effective medical treatment is available to reliably protect wild boar or domestic pigs against ASF, eradication efforts are mainly based on intensive wild boar hunting and on removing a significant portion of the infected wild boar carcasses, which are the main environmental virus reservoir. Both strategies have produced poor results, so far, and ASF is becoming endemic. We compared wild boar hunting and carcass removal as alternative and combined strategies for the eradication of ASF in its endemic state, using a spatially explicit individual-based model, which incorporated the demography and spatial dynamics of a wild boar population, the spatial epidemiology of ASF in its endemic phase, and a management system acting for the eradication of the disease from the population. When no eradication effort was simulated, ASF exhibited a clear and strong tendency to persist and remain endemic in the wild boar population. Both hunting and carcass removal, when used alone, provided either a low power to remove the virus from the population, or required unrealistic field effort. The best performing scenario corresponded to the combined use of a 30% annual hunting rate and of an intensive carcass removal, during a 2-month period in late winter (February-March). Eradicating ASF from wild boar populations remains a hard task. Managers should promote a drastic increase in the effort dedicated to systematically identify and remove as many infected wild boar carcasses as possible from the affected areas, with at least 5–15 carcasses removed for each 100 hunted wild boar.

African swine fever (ASF) is a contagious haemorrhagic fever that affects both domesticated and wild pigs. Since ASF reached Europe wild boar populations have been a reservoir for the virus. Collecting reliable data on infected individuals in wild populations is challenging, and this makes it difficult to deploy an effective eradication strategy. However, for diseases with high lethality rate, infected carcasses can be used as a proxy for the number of infected individuals at a certain time. Then R₀ parameter can be used to estimate the time distribution of the number of newly infected individuals for the outbreak. We estimated R₀ for two ASF outbreaks in wild boar, in Czech Republic and Belgium, using the exponential growth method. This allowed us to estimate both R₀ and the doubling time (T_d) for those infections. The results are R₀ = 1.95, T_d = 4.39 for Czech Republic and R₀ = 1.65, T_d = 6.43 for Belgium. We suggest that, if estimated as early as possible, R₀ and T_d can provide an expected course for the infection against which to compare the actual data collected in the field. This would help to assess if passive surveillance is properly implemented and hence to verify the efficacy of the applied control measures.

Estimating demographic parameters for wide‐ranging and elusive species living at low density is challenging, especially at the scale of an entire country. To produce wolf distribution and abundance estimates for the whole south‐central portion of the Italian wolf population, we developed an integrated spatial model, based on the data collected during a 7‐month sampling campaign in 2020–2021. Data collection comprised an extensive survey of wolf presence signs, and an intensive survey in 13 sampling areas, aimed at collecting non‐invasive genetic samples (NGS). The model comprised (i) a single‐season, multiple data‐source, multi‐event occupancy model and (ii) a spatially explicit capture‐recapture model. The information about species' absence was used to inform local density estimates. We also performed a simulation‐based assessment, to estimate the best conditions for optimizing sub‐sampling and population modelling in the future. The integrated spatial model estimated that 74.2% of the study area in south‐central Italy (95% CIs = 70.5% to 77.9%) was occupied by wolves, for a total extent of the wolf distribution of 108,534 km² (95% CIs = 103,200 to 114,000). The estimate of total population size for the Apennine wolf population was of 2557 individuals (SD = 171.5; 95% CIs = 2127 to 2844). Simulations suggested that the integrated spatial model was associated with an average tendency to slightly underestimate population size. Also, the main contribution of the integrated approach was to increase precision in the abundance estimates, whereas it did not affect accuracy significantly. In the future, the area subject to NGS should be increased to at least 30%, while at least a similar proportion should be sampled for presence‐absence data, to further improve the accuracy of population size estimates and avoid the risk of underestimation. This approach could be applied to other wide‐ranging species and in other geographical areas, but specific a priori evaluations of model requirements and expected performance should be made.