Choice of landscape discretisation method affects the inferred rate of spread in wildlife disease spread models.

Disease modelling at the livestock-wildlife interface is an important topic for which discrete-space models are used for the wildlife component. One prominent example is African Swine Fever, where wild boar play an influential role as reservoirs of disease spillover into domestic pig farms. In this paper, we present a simulation study that demonstrates the impact of seemingly arbitrary choices of landscape discretisation method on the inferred rate of spread within the model. We use an ordinary differential equation model to implement a simplified model of disease transmission between discrete groups of wild boar with spillover into domestic pig farms contained within a homogeneous landscape. We examine a range of scenarios whereby the landscape is discretised into wild boar patches of varying size and shape, and compare the rate of spread between domestic pig farms placed at fixed points on the landscape. Our results demonstrate a non-monotonic relationship between patch size and rate of spread, which is particularly unstable and unpredictable for square and triangular shaped patches. Discretisation of the landscape into hexagons appears to produce a more stable relationship between patch size and rate of spread for the three types of transmission kernel we investigated. Although the rate of disease spread does converge to a stable value, this occurs at patch sizes that are much smaller than would be used in practice for wild boar. We conclude that outputs of disease models containing a wildlife component should not be considered to be robust to arbitrary choices for patch size and placement, but rather as a source of uncertainty to be examined using sensitivity analysis. Furthermore, we strongly recommend the use of hexagons rather than squares or right triangles for landscape discretisation.

Emergence and spread of SARS-CoV-2 variants from farmed mink to humans and back during the epidemic in Denmark, June-November 2020.

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) not only caused the COVID-19 pandemic but also had a major impact on farmed mink production in several European countries. In Denmark, the entire population of farmed mink (over 15 million animals) was culled in late 2020. During the period of June to November 2020, mink on 290 farms (out of about 1100 in the country) were shown to be infected with SARS-CoV-2. Genome sequencing identified changes in the virus within the mink and it is estimated that about 4000 people in Denmark became infected with these mink virus variants. However, the routes of transmission of the virus to, and from, the mink have been unclear. Phylogenetic analysis revealed the generation of multiple clusters of the virus within the mink. Detailed analysis of changes in the virus during replication in mink and, in parallel, in the human population in Denmark, during the same time period, has been performed here. The majority of cases in mink involved variants with the Y453F substitution and the H69/V70 deletion within the Spike (S) protein; these changes emerged early in the outbreak. However, further introductions of the virus, by variants lacking these changes, from the human population into mink also occurred. Based on phylogenetic analysis of viral genome data, we estimate, using a conservative approach, that about 17 separate examples of mink to human transmission occurred in Denmark but up to 59 such events (90% credible interval: (39-77)) were identified using parsimony to count cross-species jumps on transmission trees inferred using Bayesian methods. Using the latter approach, 136 jumps (90% credible interval: (117-164)) from humans to mink were found, which may underlie the farm-to-farm spread. Thus, transmission of SARS-CoV-2 from humans to mink, mink to mink, from mink to humans and between humans were all observed.

Epidemiological analysis of African swine fever in the European Union during 2023.

In 2023, 14 Member States were affected by African swine fever (ASF), including Croatia and Sweden where ASF emerged (wild boar outbreaks only) and Greece where ASF re-emerged after being free since 2021. The number of ASF outbreaks among domestic pigs in the EU was five times higher than in 2022, reaching a similar magnitude to that in 2019. This was predominantly driven by the introduction and subsequent spread of ASF in Croatia and its resurgence in Romania, representing 96% of the EU outbreaks. ASF outbreaks in domestic pigs were clearly seasonal in all countries, with 88% of outbreaks reported between July and October. Most of the ASF outbreaks among domestic pigs were detected through clinical suspicion (94%), followed by tracing from affected establishments (3%), and the weekly testing of at least two dead pigs in establishments (3%). In wild boar, a 10% increase in the number of notified outbreaks was observed in the EU in comparison with 2022, with considerable variations between countries. A winter peak was observed only in Poland, Slovakia and Hungary. The epidemiological situation in wild boar improved in Germany and Hungary, as suggested by the decrease in the number of outbreaks and in the proportions of PCR-positive samples from dead wild boar. Overall, 31% of wild boar carcasses found during passive surveillance tested positive by PCR, representing 69% of the ASF outbreaks in wild boar in the EU. In contrast, 0.4% of hunted wild boar tested positive, representing 31% of the outbreaks. Despite the introduction of ASF into new countries and the increase in the number of outbreaks, the size of restricted zones in the EU remained stable, due to the highly clustered outbreaks in Croatia, and the reduction of restricted zones in Poland, Slovakia and Bulgaria (in domestic pigs), and Hungary (in wild boar).

Risk factors for avian influenza in Danish poultry and wild birds during the epidemic from June 2020 to May 2021.

Exploring the risk factors of avian influenza (AI) occurrence helps us to monitor and control the disease. Since late 2020, the number of avian influenza outbreaks in domestic and wild birds has increased in most European countries, including Denmark. This study was conducted to identify potential risk factors for wild birds and poultry during the epidemic in 2020/2021 in Denmark. Using Danish AI surveillance data of actively surveyed poultry and passively surveyed wild birds from June 2020 to May 2021, we calculated geographical attributes for bird locations and assessed the potential risk factors of AI detections using logistic regression analyses. 4% of actively surveyed poultry and 39% of passively surveyed wild birds were detected with AI circulating or ongoing at the time. Of these, 10 and 99% tested positive for the H5/H7 AI subtypes, respectively. Our analyses did not find any statistically significant risk factors for actively surveyed poultry within the dataset. For passively surveyed wild birds, bird species belonging to the Anseriformes order had a higher risk of being AI virus positive than five other taxonomic bird orders, and Galliformes were of higher risk than two other taxonomic bird orders. Besides, every 1 km increase in the distance to wetlands was associated with a 5.18% decrease in the risk of being AI positive (OR (odds ratio) 0.95, 95% CI 0.91, 0.99), when all other variables were kept constant. Overall, bird orders and distance to wetlands were associated with the occurrence of AI. The findings may provide targets for surveillance strategies using limited resources and assist in risk-based surveillance during epidemics.

Are all avian influenza outbreaks in poultry the same? The predicted impact of poultry species and virus subtype.

AIMS: Outbreaks of avian influenza in poultry farms are currently increasing in frequency, with devastating consequences for animal welfare, farmers and supply chains. Some studies have documented the direct spread of the avian influenza virus between farms. Prevention of spread between farms relies on biosecurity surveillance and control measures. However, the evolution of an outbreak on a farm might vary depending on the virus strain and poultry species involved; this would have important implications for surveillance systems, epidemiological investigations and control measures. METHODS AND RESULTS: In this study, we utilized existing parameter estimates from the literature to evaluate the predicted course of an epidemic in a standard poultry flock with 10,000 birds. We used a stochastic SEIR simulation model to simulate outbreaks in different species and with different virus subtypes. The simulations predicted large differences in the duration and severity of outbreaks, depending on the virus subtypes. For both turkeys and chickens, outbreaks with HPAI were of shorter duration than outbreaks with LPAI. In outbreaks involving the infection of chickens with different virus subtypes, the shortest epidemic involved H7N7 and HPAIV H5N1 (median duration of 9 and 17 days, respectively) and the longest involved H5N2 (median duration of 68 days). The most severe outbreaks (number of chickens infected) were predicted for H5N1, H7N1 and H7N3 virus subtypes, and the least severe for H5N2 and H7N7, in which outbreaks for the latter subtype were predicted to develop most slowly. CONCLUSIONS: These simulation results suggest that surveillance of certain subtypes of avian influenza virus, in chicken flocks in particular, needs to be sensitive and timely if infection is to be detected with sufficient time to implement control measures. The variability in the predictions highlights that avian influenza outbreaks are different in severity, speed and duration, so surveillance and disease response need to be nuanced and fit the specific context of poultry species and virus subtypes.

Estimating the impact of low temperature on African swine fever virus transmission through contaminated environments.

African Swine Fever Virus (ASFV) is the cause of an infectious disease in pigs, which is difficult to control. Long viability of ASFV has been shown for several contaminated materials, especially under low temperature. Therefore, when pigs are exposed to a contaminated environment, new infections could occur without the presence of infectious individuals. For example, a contaminated, poorly washed, empty livestock vehicle poses a risk to the next load of pigs. A quantitative stochastic environmental transmission model was applied to simulate the change in environmental contamination levels over time and calculate the epidemic parameters through exposure-based estimation. Due to the lack of experimental data on environmental transmission at low temperatures, we performed a non-linear fit of the decay rate parameter with temperature based on a literature review. Eventually, 16 scenarios were constructed for different temperature (at 20 °C, 10 °C, 0 °C, or -10 °C) and duration of empty periods (1, 3, 5, or 7 days) after the environment had been contaminated. We quantified the variation in the contamination level of the environment over time and the probability of newly added recipients getting infected when exposed to the environment after the empty period. As a result, the transmission rate parameter for ASFV in pigs was estimated to be 1.53 (0.90, 2.45) day-1, the decay rate parameter to be 1.02 (0.73, 1.47) day-1 (at 21 °C), and the excretion rate parameter to be 2.70 (2.51, 3.02) day-1. Without washing and disinfecting, the environment required 9, 14, 24, 54 days to reach a low probability of causing at least one new case (<0.005) at 20 °C, 10 °C, 0 °C, -10 °C, respectively. In addition, the method proposed in this paper enables assessment of the effect of washing and disinfecting on ASFV environmental transmission. We conducted this study to better understand how the viability of ASFV at different temperatures could affect the infectivity in environmental transmission and to improve risk assessment and disease control strategies.

Using surveillance data for early warning modelling of highly pathogenic avian influenza in Europe reveals a seasonal shift in transmission, 2016-2022.

Avian influenza in wild birds and poultry flocks constitutes a problem for animal welfare, food security and public health. In recent years there have been increasing numbers of outbreaks in Europe, with many poultry flocks culled after being infected with highly pathogenic avian influenza (HPAI). Continuous monitoring is crucial to enable timely implementation of control to prevent HPAI spread from wild birds to poultry and between poultry flocks within a country. We here utilize readily available public surveillance data and time-series models to predict HPAI detections within European countries and show a seasonal shift that happened during 2021-2022. The output is models capable of monitoring the weekly risk of HPAI outbreaks, to support decision making.

Detection of African Swine Fever Virus and Blood Meals of Porcine Origin in Hematophagous Insects Collected Adjacent to a High-Biosecurity Pig Farm in Lithuania; A Smoking Gun?

A seasonal trend of African swine fever (ASF) outbreaks in domestic pig farms has been observed in affected regions of Eastern Europe. Most outbreaks have been observed during the warmer summer months, coinciding with the seasonal activity pattern of blood-feeding insects. These insects may offer a route for introduction of the ASF virus (ASFV) into domestic pig herds. In this study, insects (hematophagous flies) collected outside the buildings of a domestic pig farm, without ASFV-infected pigs, were analyzed for the presence of the virus. Using qPCR, ASFV DNA was detected in six insect pools; in four of these pools, DNA from suid blood was also identified. This detection coincided with ASFV being reported in the wild boar population within a 10 km radius of the pig farm. These findings show that blood from ASFV-infected suids was present within hematophagous flies on the premises of a pig farm without infected animals and support the hypothesis that blood-feeding insects can potentially transport the virus from wild boars into domestic pig farms.

Epidemiological analysis of African swine fever in the European Union during 2022.

This report presents the epidemiological analysis of African swine fever (ASF) during 2022 based on the surveillance and pig population data submitted by the European Union (EU) affected countries and one neighbouring country. Coinciding with regulatory changes and an important decrease in ASF outbreaks in 2022 in the EU, the number of domestic pig samples tested as part of active surveillance decreased by 80%, while the number of samples from passive surveillance almost doubled compared with 2021. Most outbreaks among domestic pigs in the EU were detected by testing clinical suspicions (93% of outbreaks), followed by tracing activities (5%) and weekly testing of the first two dead pigs per establishment (2%). Although most of the wild boar samples came from hunted animals, the probability of detecting PCR-positive animals was much higher in wild boar found dead. The ASF outbreaks among domestic pigs in the EU decreased by 79% while a decrease of 40% in the wild boar cases was observed in comparison with 2021. This was strongly marked in Romania, Poland and Bulgaria, with a reduction of 50-80% compared with 2021. In many countries, an important decrease in the number of pig establishments was observed, especially of small establishments with fewer than 100 pigs. The regional between farm incidence and proportion of pigs lost due to ASF in the EU was in general very low (average of 1%) apart from some regions in Romania. The impact of ASF on wild boar populations was variable, with a decline in wild boar abundance observed in certain countries versus a stable or even increased population after ASF introduction. This supports the negative relationship observed in this report between the proportion of the country with restricted zones due to ASF in wild boar and wild boar hunting bags.

Simulation of Foot-and-Mouth Disease Spread and Effects of Mitigation Strategies to Support Veterinary Contingency Planning in Denmark.

To forge a path towards livestock disease emergency preparedness in Denmark, 15 different strategies to mitigate foot-and-mouth disease (FMD) were examined by modelling epidemics initiated in cattle, pig or small ruminant herds across various production systems located in four different Danish regions (Scenario 1), or in one specific livestock production system within each of the three species geographically distributed throughout Denmark (Scenario 2). When additional mitigation strategies were implemented on top of basic control strategies in the European foot-and-mouth disease spread model (EuFMDiS), no significant benefits were predicted in terms of the number of infected farms, the epidemic control duration, and the total economic cost. Further, the model results indicated that the choice of index herd, the resources for outbreak control, and the detection time of FMD significantly influenced the course of an epidemic. The present study results emphasise the importance of basic mitigation strategies, including an effective back-and-forward traceability system, adequate resources for outbreak response, and a high level of awareness among farmers and veterinarians concerning the detection and reporting of FMD at an early stage of an outbreak for FMD control in Denmark.

SARS-CoV-2 in animals: susceptibility of animal species, risk for animal and public health, monitoring, prevention and control.

The epidemiological situation of SARS-CoV-2 in humans and animals is continually evolving. To date, animal species known to transmit SARS-CoV-2 are American mink, raccoon dog, cat, ferret, hamster, house mouse, Egyptian fruit bat, deer mouse and white-tailed deer. Among farmed animals, American mink have the highest likelihood to become infected from humans or animals and further transmit SARS-CoV-2. In the EU, 44 outbreaks were reported in 2021 in mink farms in seven MSs, while only six in 2022 in two MSs, thus representing a decreasing trend. The introduction of SARS-CoV-2 into mink farms is usually via infected humans; this can be controlled by systematically testing people entering farms and adequate biosecurity. The current most appropriate monitoring approach for mink is the outbreak confirmation based on suspicion, testing dead or clinically sick animals in case of increased mortality or positive farm personnel and the genomic surveillance of virus variants. The genomic analysis of SARS-CoV-2 showed mink-specific clusters with a potential to spill back into the human population. Among companion animals, cats, ferrets and hamsters are those at highest risk of SARS-CoV-2 infection, which most likely originates from an infected human, and which has no or very low impact on virus circulation in the human population. Among wild animals (including zoo animals), mostly carnivores, great apes and white-tailed deer have been reported to be naturally infected by SARS-CoV-2. In the EU, no cases of infected wildlife have been reported so far. Proper disposal of human waste is advised to reduce the risks of spill-over of SARS-CoV-2 to wildlife. Furthermore, contact with wildlife, especially if sick or dead, should be minimised. No specific monitoring for wildlife is recommended apart from testing hunter-harvested animals with clinical signs or found-dead. Bats should be monitored as a natural host of many coronaviruses.

Estimating transmission dynamics of African swine fever virus from experimental studies.

African swine fever virus (ASFV) continues to spread across the world, and currently, there are no treatments or vaccines available to combat this virus. Reliable estimates of transmission parameters for ASFV are therefore needed to establish effective contingency plans. This study used data from controlled ASFV inoculations of pigs to assess the transmission parameters. Three models were developed with (binary, piecewise-linear and exponential) time-dependent levels of infectiousness based on latency periods of 3-5 days derived from the analysis of 294 ethylenediamine tetraacetic acid-stabilized blood samples originating from 16 pigs with direct and 10 pigs with indirect contact to 8 inoculated pigs. The models were evaluated for three different discrete latency periods of infection. The likelihood ratio test showed that a binary model had an equally good fit for a latency period of 4 or 5 days as the piecewise-linear and exponential model. However, for a latency period of 3 days, the piecewise-linear and exponential models had the best fit. The modelling was done in discrete time as testing was conducted on specific days. The main contribution of this study is the estimation of ASFV genotype II transmission through the air in a confined space. The estimated transmission parameters via air are not much lower than for direct contact between pigs. The estimated parameters should be useful for future simulations of control measures against ASFV.

Epidemiological analyses of African swine fever in the European Union: (September 2020 to August 2021).

This report provides a descriptive analysis of the African swine fever (ASF) Genotype II epidemic in the affected Member States in the EU and two neighbouring countries for the period from 1 September 2020 to 31 August 2021. ASF continued to spread in wild boar in the EU, it entered Germany in September 2020, while Belgium became free from ASF in October 2020. No ASF outbreaks in domestic pigs nor cases in wild boar have been reported in Greece since February 2020. In the Baltic States, overall, there has been a declining trend in proportions of polymerase chain reaction (PCR)-positive samples from wild boar carcasses in the last few years. In the other countries, the proportions of PCR-positive wild boar carcasses remained high, indicating continuing spread of the disease. A systematic literature review revealed that the risk factors most frequently significantly associated with ASF in domestic pigs were pig density, low levels of biosecurity and socio-economic factors. For wild boar, most significant risk factors were related to habitat, socio-economic factors and wild boar management. The effectiveness of different control options in the so-named white zones, areas where wild boar densities have been drastically reduced to avoid further spread of ASF after a new introduction, was assessed with a stochastic model. Important findings were that establishing a white zone is much more challenging when the area of ASF incursion is adjacent to an area where limited control measures are in place. Very stringent wild boar population reduction measures in the white zone are key to success. The white zone needs to be far enough away from the affected core area so that the population can be reduced in time before the disease arrives and the timing of this will depend on the wild boar density and the required population reduction target in the white zone. Finally, establishing a proactive white zone along the demarcation line of an affected area requires higher culling efforts, but has a higher chance of success to stop the spread of the disease than establishing reactive white zones after the disease has already entered in the area.

A Multi-Laboratory Comparison of Methods for Detection and Quantification of African Swine Fever Virus.

African swine fever is a viral disease of the family Suidae. Methods to detect and quantify African swine fever virus (ASFV) include qPCR and virus infectivity assays. Individual laboratories often use in-house procedures for these assays, which can hamper the comparison of results. The objective of this study was to estimate the probability of ASFV detection using these assays, and to determine the inter-test correlations between results. This was achieved by testing a panel of 80 samples at three reference laboratories. Samples were analysed using nucleic acid extraction and qPCR, as well as virus infectivity assays. For qPCR, a very high probability (ranging from 0.96 to 1.0) of detecting ASFV DNA was observed for all tested systems. For virus infectivity assays in cells, the probability of detecting infectious ASFV varied from 0.68 to 0.90 and was highest using pulmonary alveolar macrophages, followed by MARC145 cells, peripheral blood monocytes, and finally wild boar lung cells. Intraclass correlation coefficient estimates of 0.97 (0.96-0.98) between qPCR methods, 0.80 (0.74-0.85) to 0.94 (0.92-0.96) between virus infectivity assays, and 0.77 (0.68-0.83) to 0.95 (0.93-0.96) between qPCR methods and virus infectivity assays were obtained. These findings show that qPCR gives the highest probability for the detection of ASFV.

SWOT analysis of risk factors associated with introduction of African Swine Fever through vehicles returning after export of pigs.

Denmark is a major pig exporter and applies a high level of biosecurity, with washing and disinfecting stations for returning livestock vehicles. The introduction of African Swine Fever (ASF) would have significant economic consequences related to loss of export of live pigs and products thereof. In this study, we focused on the role of empty livestock vehicles returning after exports of pigs for the introduction of ASF. Initially, the current components and measures related to export of livestock were described. Next, analyses of strengths, weaknesses, opportunities, and threats (SWOT) were conducted, covering the components and measures identified. Then, export of pigs was described either through assembly centers or directly from farms. Washing and disinfection, as required and undertaken at the designated stations, constitutes the most important among all risk-reducing measures identified. Recommendations are to: (1) ensure the quality of washing and disinfection through staff training; (2) find new, safe, and more efficient disinfectants; (3) ensure the required temperature, and therefore effect, of the disinfectant and water. It was impossible to assess, the influence of export through assembly centers compared to direct transport. However, through SWOT analyses we identified the strengths and weaknesses of the two pathways. Moreover, components/measures with risks of unknown sizes are also discussed, such as vehicles undertaking cabotage and the current vehicle quarantine periods.

Potential mosquito vector attraction to- and feeding preferences for pigs in Romanian backyard farms.

Introduction: Mosquitoes either biologically or mechanically transmit various vector-borne pathogens affecting pigs. Mosquito species display a wide variety of host preference, as well as host attraction and behaviours. Mosquito species attraction rates to- and feeding rates on pigs or other potential hosts, as well as the seasonal abundance of the mosquito species affects their pathogen transmission potential. Methods: We caught mosquitoes in experimental cages containing pigs situated in Romanian backyard farms. The host species of blood meals were identified with PCR and sequencing. Results: High feeding preferences for pigs were observed in Aedes vexans (90%), Anopheles maculipennis (80%) and Culiseta annulata (72.7%). However, due to a high abundance in the traps, Culex pipiens/torrentium were responsible for 37.9% of all mosquito bites on pigs in the Romanian backyards, despite low feeding rates on pigs in the cages (18.6%). We also found that other predominantly ornithophilic mosquito species, as well as mosquitoes that are already carrying a blood meal from a different (mammalian) host, were attracted to backyard pigs or their enclosure. Discussion: These results indicate that viraemic blood carrying, for instance, African swine fever virus, West-Nile virus or Japanese encephalitis virus could be introduced to these backyard pig farms and therefore cause an infection, either through subsequent feeding, via ingestion by the pig or by environmental contamination.

Landscape effects and spatial patterns of avian influenza virus in Danish wild birds, 2006-2020.

Avian influenza (AI) is a contagious disease of birds with zoonotic potential. AI virus (AIV) can infect most bird species, but clinical signs and mortality vary. Assessing the distribution and factors affecting AI presence can direct targeted surveillance to areas at risk of disease outbreaks, or help identify disease hotspots or areas with inadequate surveillance. Using virus surveillance data from passive and active AIV wild bird surveillance, 2006-2020, we investigated the association between the presence of AIV and a range of landscape factors and game bird release. Furthermore, we assessed potential bias in the passive AIV surveillance data submitted by the public, via factors related to public accessibility. Lastly, we tested the AIV data for possible hot- and cold spots within Denmark. The passive surveillance data was biased regarding accessibility to areas (distance to roads, cities and coast) compared to random locations within Denmark. For both the passive and active AIV surveillance data, we found significant (p < .01) associations with variables related to coast, wetlands and cities, but not game bird release. We used these variables to predict the risk of AIV presence throughout Denmark, and found high-risk areas concentrated along the coast and fjords. For both passive and active surveillance data, low-risk clusters were mainly seen in Jutland and northern Zealand, whereas high-risk clusters were found in Jutland, Zealand, Funen and the southern Isles such as Lolland and Falster. Our results suggest that landscape affects AIV presence, as coastal areas and wetlands attract waterfowl and migrating birds and therefore might increase the potential for AIV transmission. Our findings have enabled us to create risk maps of AIV presence in wild birds and pinpoint high-risk clusters within Denmark. This will aid targeted surveillance efforts within Denmark and potentially aid in planning the location of future poultry farms.

Infection, recovery and re-infection of farmed mink with SARS-CoV-2.

Mink, on a farm with about 15,000 animals, became infected with SARS-CoV-2. Over 75% of tested animals were positive for SARS-CoV-2 RNA in throat swabs and 100% of tested animals were seropositive. The virus responsible had a deletion of nucleotides encoding residues H69 and V70 within the spike protein gene as well as the A22920T mutation, resulting in the Y453F substitution within this protein, seen previously in mink. The infected mink recovered and after free-testing of 300 mink (a level giving 93% confidence of detecting a 1% prevalence), the animals remained seropositive. During further follow-up studies, after a period of more than 2 months without any virus detection, over 75% of tested animals again scored positive for SARS-CoV-2 RNA. Whole genome sequencing showed that the viruses circulating during this re-infection were most closely related to those identified in the first outbreak on this farm but additional sequence changes had occurred. Animals had much higher levels of anti-SARS-CoV-2 antibodies in serum samples after the second round of infection than at free-testing or during recovery from initial infection, consistent with a boosted immune response. Thus, it was concluded that following recovery from an initial infection, seropositive mink were readily re-infected by SARS-CoV-2.

Research priorities to fill knowledge gaps in wild boar management measures that could improve the control of African swine fever in wild boar populations.

The European Commission asked EFSA to provide study designs for the investigation of four research domains (RDs) according to major gaps in knowledge identified by EFSA in a report published in 2019: (RD 1) African swine fever (ASF) epidemiology in wild boar; (RD 2) ASF transmission by vectors; (RD 3) African swine fever virus (ASFV) survival in the environment, and (RD 4) the patterns of seasonality of ASF in wild boar and domestic pigs in the EU. In this Scientific Opinion, the second RD on ASF epidemiology in wild boar is addressed. Twenty-nine research objectives were proposed by the working group and broader ASF expert networks and 23 of these research objectives met a prespecified inclusion criterion. Fourteen of these 23 research objectives met the predefined threshold for selection and so were prioritised based on the following set of criteria: (1) the impact on ASF management; (2) the feasibility or practicality to carry out the study; (3) the potential implementation of study results in practice; (4) a possible short time-frame study (< 1 year); (5) the novelty of the study; and (6) if it was a priority for risk managers. Finally, after further elimination of three of the proposed research objectives due to overlapping scope of studies published during the development of this opinion, 11 research priorities were elaborated into short research proposals, considering the potential impact on ASF management and the period of one year for the research activities.