The Scientific Committee (SC) reconfirms that the benchmark dose (BMD) approach is a scientifically more advanced method compared to the NOAEL approach for deriving a Reference Point (RP). Most of the modifications made to the SC guidance of 2009 concern the section providing guidance on how to apply the BMD approach. Model averaging is recommended as the preferred method for calculating the BMD confidence interval, while acknowledging that the respective tools are still under development and may not be easily accessible to all. Therefore, selecting or rejecting models is still considered as a suboptimal alternative. The set of default models to be used for BMD analysis has been reviewed, and the Akaike information criterion (AIC) has been introduced instead of the log-likelihood to characterise the goodness of fit of different mathematical models to a dose-response data set. A flowchart has also been inserted in this update to guide the reader step-by-step when performing a BMD analysis, as well as a chapter on the distributional part of dose-response models and a template for reporting a BMD analysis in a complete and transparent manner. Finally, it is recommended to always report the BMD confidence interval rather than the value of the BMD. The lower bound (BMDL) is needed as a potential RP, and the upper bound (BMDU) is needed for establishing the BMDU/BMDL per ratio reflecting the uncertainty in the BMD estimate. This updated guidance does not call for a general re-evaluation of previous assessments where the NOAEL approach or the BMD approach as described in the 2009 SC guidance was used, in particular when the exposure is clearly smaller (e.g. more than one order of magnitude) than the health-based guidance value. Finally, the SC firmly reiterates to reconsider test guidelines given the expected wide application of the BMD approach.

EFSA was asked to update the 2015 EFSA risk assessment on Xylella fastidiosa for the territory of the EU. In particular, EFSA was asked to focus on potential establishment, short-and long-range spread, the length of the asymptomatic period, the impact of X. fastidiosa and an update on risk reduction options. EFSA was asked to take into account the different subspecies and Sequence Types of X. fastidiosa. This was attempted throughout the scientific opinion but several issues with data availability meant that this could only be partially achieved. Models for risk of establishment showed most of the EU territory may be potentially suitable for X. fastidiosa although southern EU is most at risk. Differences in estimated areas of potential establishment were evident among X. fastidiosa subspecies, particularly X. fastidiosa subsp. multiplex which demonstrated areas of potential establishment further north in the EU. The model of establishment could be used to develop targeted surveys by Member States. The asymptomatic period of X. fastidiosa varied significantly for different host and pathogen subspecies combinations, for example from a median of approximately 1 month in ornamental plants and up to 10 months in olive, for pauca. This variable and long asymptomatic period is a considerable limitation to successful detection and control, particularly where surveillance is based on visual inspection. Modelling suggested that local eradication (e.g. within orchards) is possible, providing sampling intensity is sufficient for early detection and effective control measures are implemented swiftly (e.g. within 30 days). Modelling of long-range spread (e.g. regional scale) demonstrated the important role of long-range dispersal and the need to better understand this. Reducing buffer zone width in both containment and eradication scenarios increased the area infected. Intensive surveillance for early detection, and consequent plant removal, of new outbreaks is crucial for both successful eradication and containment at the regional scale, in addition to effective vector control. The assessment of impacts indicated that almond and Citrus spp. were at lower impact on yield compared to olive. Although the lowest impact was estimated for grapevine, and the highest for olive, this was based on several assumptions including that the assessment considered only Philaenus spumarius as a vector. If other xylem-feeding insects act as vectors the impact could be different. Since the Scientific Opinion published in 2015, there are still no risk reduction options that can remove the bacterium from the plant in open field conditions. Short-and long-range spread modelling showed that an early detection and rapid application of phytosanitary measures, consisting among others of plant removal and vector control, are essential to prevent further spread of the pathogen to new areas. Further data collection will allow a reduction in uncertainty and facilitate more tailored and effective control given the intraspecific diversity of X. fastidiosa an...

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.

African swine fever (ASF) entered Georgia in 2007 and the EU in 2014. In the EU, the virus primarily spread in wild boar (Sus scrofa) in the period from 2014-2018. However, from the summer 2018, numerous domestic pig farms in Romania were affected by ASF. In contrast to the existing knowledge on ASF transmission routes, the understanding of risk factors and the importance of different transmission routes is still limited. In the period from May to September 2019, 655 Romanian pig farms were included in a matched case-control study investigating possible risk factors for ASF incursion in commercial and backyard pig farms. The results showed that close proximity to outbreaks in domestic farms was a risk factor in commercial as well as backyard farms. Furthermore, in backyard farms, herd size, wild boar abundance around the farm, number of domestic outbreaks within 2 km around farms, short distance to wild boar cases and visits of professionals working on farms were statistically significant risk factors. Additionally, growing crops around the farm, which could potentially attract wild boar, and feeding forage from ASF affected areas to the pigs were risk factors for ASF incursion in backyard farms. In 2007, African swine fever (ASF) spread from the African continent, where the disease is endemic, into Georgia then on through Eastern Europe, reaching the European Union in 2014. During the first years of the epidemic in the EU (2014-early 2017), the disease mainly affected wild boar, with sporadic spill-over to domestic pigs 1. In 2017, ASF spread to Romania, initially resulting in a small number of outbreaks in domestic pig farms in the county of Satu Mare, which neighbours Hungary and Ukraine. In July 2018, ASF occurred in two counties neighbouring Satu Mare, but also in five counties around the Danube delta close to the Black Sea in the South East part of Romania. In July 2018, 334 outbreaks were detected, mostly in domestic farms, predominantly in the South East. From then on, ASF spread widely in Romania with outbreaks in more than 1,000 domestic pig farms in 2018 and about 2,500 in 2019 (Animal Disease Notification System of the European Commission (ADNS)).

The European Commission requested EFSA to compare the reliability of wild boar density estimates across the EU and to provide guidance to improve data collection methods. Currently, the only EU‐wide available data are hunting data. Their collection methods should be harmonised to be comparable and to improve predictive models for wild boar density. These models could be validated by more precise density data, collected at local level e.g. by camera trapping. Based on practical and theoretical considerations, it is currently not possible to establish wild boar density thresholds that do not allow sustaining African swine fever (ASF). There are many drivers determining if ASF can be sustained or not, including heterogeneous population structures and human‐mediated spread and there are still unknowns on the importance of different transmission modes in the epidemiology. Based on extensive literature reviews and observations from affected Member States, the efficacy of different wild boar population reduction and separation methods is evaluated. Different wild boar management strategies at different stages of the epidemic are suggested. Preventive measures to reduce and stabilise wild boar density, before ASF introduction, will be beneficial both in reducing the probability of exposure of the population to ASF and the efforts needed for potential emergency actions (i.e. less carcass removal) if an ASF incursion were to occur. Passive surveillance is the most effective and efficient method of surveillance for early detection of ASF in free areas. Following focal ASF introduction, the wild boar populations should be kept undisturbed for a short period (e.g. hunting ban on all species, leave crops unharvested to provide food and shelter within the affected area) and drastic reduction of the wild boar population may be performed only ahead of the ASF advance front, in the free populations. Following the decline in the epidemic, as demonstrated through passive surveillance, active population management should be reconsidered.