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African swine fever (ASF) is a highly contagious viral disease in domestic pigs and wild boar that causes tremendous socioeconomic damage in related industries. In 2019, the virus emerged in South Korea, which has since reported 21 outbreaks in domestic pig farms and over 2,600 cases in wild boar. In this review, we synthesize the epidemiological knowledge generated on ASF in South Korea during the first three years of the epidemic (2019–2021). We searched four international and one domestic Korean database to identify scientific articles published since 2019 and describing ASF epidemiology in South Korea. Fourteen articles met our selection criteria and were used to synthesize the origin of ASF in South Korea, the risk factors of disease occurrence, the effectiveness of the surveillance and intervention measures that were implemented, and the viral transmission dynamics. We found that timely intensive surveillance and interventions on domestic pig farms successfully blocked between-farm transmission. However, in wild boar, the ASF virus has spread massively towards the south primarily along the mountain ranges despite ongoing fence erection and intensive depopulation efforts, endangering domestic pig farms across the country. The current devastating epidemic is suspected to be the consequence of an ASF control strategy unaligned to the epidemiological context, the challenging implementation of control measures hindered by topological complexities, and inappropriate biosecurity by field workers. To improve our understanding of ASF epidemiology in South Korea and enhance disease management, future research studies should specify the ecological drivers of disease distribution and spread and devise effective control strategies, particularly in relation to Korean topography, and the latent spread of the virus in wild boar populations. Additionally, research studies should explore the psychosocial factors for ASF management, and develop tools to support evidence-based decision-making for managing ASFV in wild boar. [ABSTRACT FROM AUTHOR]

The spread of highly pathogenic avian influenza (HPAI) viruses worldwide has serious consequences for animal health and a major economic impact on the poultry production sector. Since 2014, Europe has been severely hit by several HPAI epidemics, with France being the most affected country. Most recently, France was again affected by two devastating HPAI epidemics in 2020–21 and 2021–22. We conducted a descriptive analysis of the 2020–21 and 2021–22 epidemics, as a first step towards identifying the poultry sector's remaining vulnerabilities regarding HPAI viruses in France. We examined the spatio‐temporal distribution of outbreaks that occurred in France in 2020–21 and 2021–22, and we assessed the outbreaks' spatial distribution in relation to the 2016–17 epidemic and to the two 'high‐risk zones' recently incorporated into French legislation to strengthen HPAI prevention and control. There were 468 reported outbreaks during the 2020–21 epidemic and 1375 outbreaks during the 2021–22 epidemic. In both epidemics, the outbreaks' distribution matched extremely well that of 2016–17, and most outbreaks (80.6% and 68.4%) were located in the two high‐risk zones. The southwestern high‐risk zone was affected in both epidemics, while the western high‐risk zone was affected for the first time in 2021–22, explaining the extremely high number of outbreaks reported. As soon as the virus reached the high‐risk zones, it started to spread between farms at very high rates, with each infected farm infecting between two and three other farms at the peaks of transmission. We showed that the spatial distribution model used to create the two high‐risk zones was able to predict the location of outbreaks for the 2020–21 and 2021–22 epidemics. These zones were characterized by high poultry farm densities; future efforts should, therefore, focus on reducing the density of susceptible poultry in highly dense areas. [ABSTRACT FROM AUTHOR]

African swine fever (ASF) represents the main threat to swine production, with heavy economic consequences for both farmers and the food industry. The spread of the virus that causes ASF through Europe raises the issues of identifying transmission routes and assessing their relative contributions in order to provide insights to stakeholders for adapted surveillance and control measures. A simulation model was developed to assess ASF spread over the commercial swine network in France. The model was designed from raw movement data and actual farm characteristics. A metapopulation approach was used, with transmission processes at the herd level potentially leading to external spread to epidemiologically connected herds. Three transmission routes were considered: local transmission (e.g. fomites, material exchange), movement of animals from infected to susceptible sites, and transit of trucks without physical animal exchange. Surveillance was represented by prevalence and mortality detection thresholds at herd level, which triggered control measures through movement ban for detected herds and epidemiologically related herds. The time from infection to detection varied between 8 and 21 days, depending on the detection criteria, but was also dependent on the types of herds in which the infection was introduced. Movement restrictions effectively reduced the transmission between herds, but local transmission was nevertheless observed in higher proportions highlighting the need of global awareness of all actors of the swine industry to mitigate the risk of local spread. Raw movement data were directly used to build a dynamic network on a realistic timescale. This approach allows for a rapid update of input data without any pre‐treatment, which could be important in terms of responsiveness, should an introduction occur. [ABSTRACT FROM AUTHOR]

In 2016–2017, France experienced a devastating epidemic of highly pathogenic avian influenza (HPAI) H5N8, with more than 400 outbreaks reported in poultry farms. We analyzed the spatiotemporal dynamics of the epidemic using a structured‐coalescent‐based phylodynamic approach that combined viral genomic data (n = 196; one viral genome per farm) and epidemiological data. In the process, we estimated viral migration rates between départements (French administrative regions) and the temporal dynamics of the effective viral population size (Ne) in each département. Viral migration rates quantify viral spread between départements and Ne is a population genetic measure of the epidemic size and, in turn, is indicative of the within‐département transmission intensity. We extended the phylodynamic analysis with a generalized linear model to assess the impact of multiple factors—including large‐scale preventive culling and live‐duck movement bans—on viral migration rates and Ne. We showed that the large‐scale culling of ducks that was initiated on 4 January 2017 significantly reduced the viral spread between départements. No relationship was found between the viral spread and duck movements between départements. The within‐département transmission intensity was found to be weakly associated with the intensity of duck movements within départements. Together, these results indicated that the virus spread in short distances, either between adjacent départements or within départements. Results also suggested that the restrictions on duck transport within départements might not have stopped the viral spread completely. Overall, we demonstrated the usefulness of phylodynamics in characterizing the dynamics of a HPAI epidemic and assessing control measures. This method can be adapted to investigate other epidemics of fast‐evolving livestock pathogens. [ABSTRACT FROM AUTHOR]

African swine fever (ASF) is considered the most impactful transboundary swine disease. In the absence of effective vaccines, control strategies are heavily dependent on mass depopulation and shipment restrictions. Here, we developed a nested multiscale model for the transmission of ASF, combining a spatially explicit network model of animal shipments with a deterministic compartmental model for the dynamics of two ASF strains within 3 km × 3 km pixels in one Brazilian state. The model outcomes are epidemic duration, number of secondary infected farms and pigs, and distance of ASF spread. The model also shows the spatial distribution of ASF epidemics. We analyzed quarantine‐based control interventions in the context of mortality trigger thresholds for the deployment of control strategies. The mean epidemic duration of a moderately virulent strain was 11.2 days, assuming the first infection is detected (best‐case scenario), and 15.9 days when detection is triggered at 10% mortality. For a highly virulent strain, the epidemic duration was 6.5 days and 13.1 days, respectively. The distance from the source to infected locations and the spatial distribution was not dependent on strain virulence. Under the best‐case scenario, we projected an average number of infected farms of 23.77 farms and 18.8 farms for the moderate and highly virulent strains, respectively. At 10% mortality‐trigger, the predicted number of infected farms was on average 46.27 farms and 42.96 farms, respectively. We also demonstrated that the establishment of ring quarantine zones regardless of size (i.e. 5 km, 15 km) was outperformed by backward animal movement tracking. The proposed modelling framework provides an evaluation of ASF epidemic potential, providing a ranking of quarantine‐based control strategies that could assist animal health authorities in planning the national preparedness and response plan. [ABSTRACT FROM AUTHOR]

Following the emergence of highly pathogenic avian influenza (H5N8) in France in early December 2020, we used duck mortality data from the index farm to investigate within‐flock transmission dynamics. A stochastic epidemic model was fitted to the daily mortality data and model parameters were estimated using an approximate Bayesian computation sequential Monte Carlo (ABC‐SMC) algorithm. The model predicted that the first bird in the flock was infected 5 days (95% credible interval, CI: 3–6) prior to the day of suspicion and that the transmission rate was 4.1 new infections per day (95% CI: 2.8–5.8). On average, ducks became infectious 4.1 h (95% CI: 0.7–9.1) after infection and remained infectious for 4.3 days (95% CI: 2.8–5.7). The model also predicted that 34% (50% prediction interval: 8%–76%) of birds would already be infectious by the day of suspicion, emphasizing the substantial latent threat this virus could pose to other poultry farms and to neighbouring wild birds. This study illustrates how mechanistic models can help provide rapid relevant insights that contribute to the management of infectious disease outbreaks of farmed animals. These methods can be applied to future outbreaks and the resulting parameter estimates made available to veterinary services within a few hours. [ABSTRACT FROM AUTHOR]

African swine fever (ASF) represents a global threat with huge economic consequences for the swine industry. Even though direct contact is likely to be the main transmission route from infected to susceptible hosts, recent epidemiological investigations have raised questions regarding the role of haematophagous arthropods, in particular the stable fly (Stomoxys calcitrans). In this study, we developed a mechanistic vector‐borne transmission model for ASF virus (ASFV) within an outdoor domestic pig farm in order to assess the relative contribution of stable flies to the spread of the virus. The model was fitted to the ecology of the vector, its blood‐feeding behaviour and pig‐to‐pig transmission dynamic. Model outputs suggested that in a context of low abundance (<5 flies per pig), stable flies would play a minor role in the spread of ASFV, as they are expected to be responsible for around 10% of transmission events. However, with abundances of 20 and 50 stable flies per pig, the vector‐borne transmission would likely be responsible for almost 30% and 50% of transmission events, respectively. In these situations, time to reach a pig mortality of 10% would be reduced by around 26% and 40%, respectively. The sensitivity analysis emphasized that the expected relative contribution of stable flies was strongly dependent on the volume of blood they regurgitated and the infectious dose for pigs. This study identified crucial knowledge gaps that need to be filled in order to assess more precisely the potential contribution of stable flies to the spread of ASFV, including a quantitative description of the populations of haematophagous arthropods that could be found in pig farms, a better understanding of blood‐feeding behaviours of stable flies and the quantification of the probability that stable flies partially fed with infectious blood transmit the virus to a susceptible pig during a subsequent blood‐feeding attempt. [ABSTRACT FROM AUTHOR]

Hepatitis E virus (HEV) is a zoonotic pathogen, in particular genotype 3 HEV is mainly transmitted to humans through the consumption of contaminated pork products. This study aimed at describing HEV infection patterns in pig farms and at assessing the impact of immunomodulating co‐infections namely Porcine Reproductive and Respiratory Syndrome Virus (PRRSV) and Porcine Circovirus Type 2 (PCV2), as well as other individual factors such as piglets' immunity and litters' characteristics on HEV dynamics. A longitudinal follow‐up was conducted in three farrow‐to‐finish farms known to be HEV infected. Overall, 360 piglets were individually monitored from birth to slaughter with regular blood and faecal sampling as well as blood and liver samples collected at slaughterhouse. Virological and serological analyses were performed to detect HEV, PCV2 and PRRSV genome and antibodies. The links between 12 explanatory variables and four outcomes describing HEV dynamics were assessed using cox‐proportional hazard models and logistic regression. HEV infection dynamics was found highly variable between farms and in a lower magnitude between batches. HEV positive livers were more likely related to short time‐intervals between HEV infection and slaughter time (<40 days, OR = 4.1 [3.7–4.5]). In addition to an influence of piglets' sex and sows' parity, the sequence of co‐infections was strongly associated with different HEV dynamics: a PRRSV or PCV2/PRRSV pre‐ or co‐infection was associated with a higher age at HEV shedding (Hazard Ratio = 0.3 [0.2–0.5]), as well as a higher age at HEV seroconversion (HR = 0.5 [0.3–0.9] and HR = 0.4 [0.2–0.7] respectively). A PCV2/PRRSV pre‐ or co‐infection was associated with a longer duration of shedding (HR = 0.5 [0.3–0.8]). Consequently, a PRRSV or PCV2/PRRSV pre‐ or co‐infection was strongly associated with a higher risk of having positive livers at slaughter (OR = 4.1 [1.9–8.9] and OR = 6.5 [3.2–13.2] respectively). In conclusion, co‐infections with immunomodulating viruses were found to affect HEV dynamics in the farrow‐to‐finish pig farms that were followed in this study. [ABSTRACT FROM AUTHOR]

Numerous viruses, mostly in mixed infections, have been associated worldwide with poult enteritis complex (PEC). In 2008 a coronavirus (Fr‐TCoV 080385d) was isolated in France from turkey poults exhibiting clinical signs compatible with this syndrome. In the present study, the median infectious dose (ID50), transmission kinetics and pathogenicity of Fr‐TCoV were investigated in 10‐day‐old SPF turkeys. Results revealed a titre of 104.88ID50/ml with 1 ID50/ml being beyond the limit of genome detection using a well‐characterized qRT‐PCR for avian coronaviruses. Horizontal transmission of the virus via the airborne route was not observed however, via the oro‐faecal route this proved to be extremely rapid (one infectious individual infecting another every 2.5 hr) and infectious virus was excreted for at least 6 weeks in several birds. Histological examination of different zones of the intestinal tract of the Fr‐TCoV‐infected turkeys showed that the virus had a preference for the lower part of the intestinal tract with an abundance of viral antigen being present in epithelial cells of the ileum, caecum and bursa of Fabricius. Viral antigen was also detected in dendritic cells, monocytes and macrophages in these areas, which may indicate a potential for Fr‐TCoV to replicate in antigen‐presenting cells. Together these results highlight the importance of good sanitary practices in turkey farms to avoid introducing minute amounts of virus that could suffice to initiate an outbreak, and the need to consider that infected individuals may still be infectious long after a clinical episode, to avoid virus dissemination through the movements of apparently recovered birds. [ABSTRACT FROM AUTHOR]

From the severe porcine epidemic diarrhoea (PED) epidemics that struck in 2013 in the United States of America and other countries of North and South America, two types of porcine epidemic diarrhoea virus (PEDV) were isolated, namely the InDel and the non‐InDel strains. They are differentiated by insertions/deletions in the S1 nucleotide sequence of the S gene, and differences in virulence were observed from the clinical cases. In 2014, a PED outbreak occurred in a pig farm in France, from which an InDel strain was isolated. This study aimed at comparing, under experimental conditions, the pathogenicity and the direct and indirect transmissions between a non‐InDel strain isolated from a PED‐affected piglet in 2014 in the USA and the French InDel strain. All infected pigs showed clinical signs with the non‐InDel strain although only the inoculated and direct contact pigs showed clinical signs in the InDel strain group. Although viral RNA was detected in air samples with both strains, the indirect contact pigs remained free from infection with the InDel strain in contrast to the non‐InDel group in which airborne transmission occurred in the indirect contact pigs. All infected pigs shed virus in faeces regardless of PEDV strain with 9 of 30 pigs showing intermittent faecal shedding. The transmission rate by direct contact was found to be 2.17‐fold higher than the non‐InDel strain compared with the InDel. In conclusion, the InDel strain was less pathogenic than the non‐InDel strain in our experimental conditions. The transmission route differed between the two strains. Direct contact was the main transmission route for the InDel strain, although the non‐InDel strain was transmitted through direct contact and indirectly through the air. [ABSTRACT FROM AUTHOR]