This update on the African swine fever (ASF) outbreaks in the EU demonstrated that out of all tested wild boar found dead, the proportion of positive samples peaked in winter and summer. For domestic pigs only, a summer peak was evident. Despite the existence of several plausible factors that could result in the observed seasonality, there is no evidence to prove causality. Wild boar density was the most influential risk factor for the occurrence of ASF in wild boar. In the vast majority of introductions in domestic pig holdings, direct contact with infected domestic pigs or wild boar was excluded as the route of introduction. The implementation of emergency measures in the wild boar management zones following a focal ASF introduction was evaluated. As a sole control strategy, intensive hunting around the buffer area might not always be sufficient to eradicate ASF. However, the probability of eradication success is increased after adding quick and safe carcass removal. A wider buffer area leads to a higher success probability; however it implies a larger intensive hunting area and the need for more animals to be hunted. If carcass removal and intensive hunting are effectively implemented, fencing is more useful for delineating zones, rather than adding substantially to control efficacy. However, segments of fencing will be particularly useful in those areas where carcass removal or intensive hunting is difficult to implement. It was not possible to demonstrate an effect of natural barriers on ASF spread. Human‐mediated translocation may override any effect of natural barriers. Recommendations for ASF control in four different epidemiological scenarios are presented.

EFSA assisted four countries in the analysis of epidemiological data on African swine fever (ASF), collected until September 2017. The temporal analysis demonstrated that the average proportions of PCR and antibody-ELISA positive samples from the hunted wild boar remained below 3.9 and 6.6, respectively. A peak in the ASF incidence was observed 6 months after the first observed case, followed by a significant reduction of the number of cases and low levels of African swine fever virus (ASFV) circulation at the end of 38 months follow-up period at different spatial resolutions. The spatial analysis concluded that human-mediated spread of ASFV continues to play a critical role in the ASF epidemiology, despite all measures currently taken. 'Wild boar density', 'total road length' (as proxy for human activity) and 'average suitable wild boar habitat availability' were identified as predictors for the occurrence of ASF in Estonia by a Bayesian hierarchical model, whereas 'wild boar density' and 'density of pig farms' were predictors according to a generalised additive model. To evaluate the preventive strategies proposed in EFSA's Scientific Opinion (2015) to stop the spread of ASFV in the wild boar population, a simulation model, building on expert knowledge and literature was used. It was concluded that reduction of wild boar population and carcass removal to stop the spread of ASFV in the wild boar population are more effective when applied preventively in the infected area. Drastic depopulation, targeted hunting of female wild boar and carcass removal solely implemented as measures to control ASF in the wild boar population need to be implemented in a highly effective manner (at or beyond the limit of reported effectivity in wild boar management) to sustainably halt the spread of ASF.

African swine fever (ASF) infection is circulating in Eurasia since a decade within wild boar populations without a demonstrated vector host. Further the infection was recurrently translocated by spatio‐temporal dynamics that is incompatible with wild boar movement characteristics. Management actions are required in areas affected by ASF. Control measures address areas with recent focal introduction and areas with ASF circulating several seasons or endemic occurrence. In view of acknowledged gaps in understanding ecology and epidemiology of ASF in Eurasian wild boar, mechanistic modelling was applied. A comparative assessment of alternative control efforts in the focal situations was performed, considering pre‐emptive hunting, carcass detection and removal as well as fencing of selected zones. The individual‐based model was applied to test whether inclusion of natural barriers would affect the similarity with ADNS notification data when simulating the landscape scale spread in the Baltics and Poland. The tendency of barriers to improve the explicit space‐time predictions of the model could not be proven, more research is needed here. The comparative assessment revealed that in the focal scenario the increasing removal of carcasses will provide the greatest return on investment (given carcasses being involved in the transmission). Culling of the inner zones, usually with ASF detections, should be organised early if biosecurity standards could be guaranteed. Preventive hunting around the zones affected by ASF was an inevitable measure to cope with the risk of undetected release of the infection, although the measure alone was unable to terminate the spread. Fences assumed not wild boar proof contributed only marginally to the success but may act as demarcation of management zones in practice. The focal approach appears useful and practical to address ASF after local introductions.

This report provides an update of the epidemiology of African swine fever (ASF) in the European Union during the period November 2018 to October 2019. In this period, ASF has been confirmed in Slovakia, whereas Czechia became officially ASF-free in March 2019, bringing the number of affected countries in the EU to nine. The report provides a narrative update of the situation in the different countries and an analysis of the temporal and spatial patterns of the disease. There has been no increase in the proportion of seropositive hunted wild boar in the affected areas. In hunted animals, the proportions of wild boar testing polymerase chain reaction-positive and enzyme-linked immunosorbent assay-positive has remained low (< 0.05). In addition to the obvious seasonal peak in summer in domestic pigs, seasonality of ASF in wild boar was statistically confirmed. A network analysis demonstrated that the median velocity of the natural propagation of the disease in wild boar populations was between 2.9 and 11.7 km/year. Human-mediated spread, both in pigs and wild boar, however, remains important. Several wild boar-and domestic pig-related risk factors for ASF occurrence in non-commercial farms in Romania were identified with a case-control study. This report also updates an extensive literature review on control measures to stop the spread of the disease in wild boar and on measures to separate wild boar populations. Several new studies have been identified in this reporting period, but these did not alter the conclusions of the previous reporting period. Field experience with the use of fences as part of the control strategy deployed in the Belgian focal outbreak of ASF in wild boar is described. So far, the measures have proven effective to keep ASF virus inside the affected area. This strategy included a combination of different measures, namely zoning, carcass removal, a complete feeding ban, specific hunting regulations and depopulation actions depending on the zone, a partial ban of people and logging, and setting up a network of concentric fences.

Understanding host–pathogen dynamics requires realistic consideration of transmission events that, in the case of directly transmitted pathogens, result from contacts between susceptible and infected individuals. The corresponding contact rates are usually heterogeneous due to variation in individual movement patterns and the underlying landscape structure. However, in epidemiological models, the roles that explicit host movements and landscape structure play in shaping contact rates are often overlooked. We adapted an established agent‐based model of classical swine fever (CSF) in wild boar Sus scrofa to investigate how explicit representation of landscape heterogeneity and host movement between social groups affects invasion and persistence probabilities. We simulated individual movement both phenomenologically as a correlated random walk (CRW) and mechanistically by representing interactions of the moving individuals with the landscape and host population structure. The effect of landscape structure on the probability of invasion success and disease persistence depended remarkably on the way host movement is simulated and the case fatality ratio associated with the pathogen strain. The persistence probabilities were generally low with CRW which ignores feedbacks to external factors. Although the basic reproduction number R0, a measure of the contagiousness of an infectious disease, was kept constant, these probabilities were up to eight times higher under mechanistic movement rules, especially in heterogeneous landscapes. The increased persistence emerged due to important feedbacks of the directed movement on the spatial variation of host density, contact rates and transmission events to distant areas. Our findings underscore the importance of accounting for spatial context and group size structures in eco‐epidemiological models. Our study highlights that the simulation of explicit, mechanistic movement behaviour can reverse predictions of disease persistence in comparison to phenomenological rules such as random walk approaches. This can have severe consequences when predicting the probability of disease persistence and assessing control measures to prevent outbreaks.