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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.

SARS-CoV-2 in infected patient mainly display pulmonary and oronasal tropism however, the presence of the virus has also been demonstrated in stools of patients and consequently in wastewater treatment plant effluents, questioning the potential risk of environmental contamination (such as seawater contamination) through inadequately treated wastewater spill-over into surface or coastal waters. The environmental detection of RNA alone does not substantiate risk of infection, and evidence of an effective transmission is not clear where empirical observations are lacking.Therefore, here, we decided to experimentally evaluate the persistence and infectious capacity of the Porcine epidemic diarrhea virus (PEDv), considered as a coronavirus representative model and SARS-CoV-2 surrogate, in the coastal environment of France. Coastal seawater was collected, sterile-filtered, and inoculated with PEDv before incubation for 0–4 weeks at four temperatures representative of those measured along the French coasts throughout the year (4, 8, 15, and 24°C). The decay rate of PEDv was determined using mathematical modeling and was used to determine the half-life of the virus along the French coast in accordance with temperatures from 2000 to 2021.We experimentally observed an inverse correlation between seawater temperature and the persistence of infectious viruses in seawater and confirm that the risk of transmission of infectious viruses from contaminated stool in wastewater to seawater during recreational practices is very limited. The present work represents a good model to assess the risk of transmission of not only SARS-CoV-2 but may also be used to model the risk of other coronaviruses, specifically enteric coronaviruses.ImportanceThis present work is a follow up addressing the question of the persistence of coronavirus in marine environment owing to the fact that SARS-CoV-2 is regularly detected in wastewater treating plan and the coastal environment is particularly at risk since it is subjected to increasing anthropogenic pressure and is the final receiver of surface waters and treated or sometimes insufficiently depurated waste waters. Our findings are of interest to researchers and authorities seeking to monitor SARS-CoV-2 and also enteric coronaviruses in the environment, either in tourist areas or in regions of the world, where centralized systems for wastewater treatment are not implemented, and more broadly, to the scientific community involved in “One Health” approaches.

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. ISSN:1865-1674 ISSN:1865-1682

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. ISSN:1865-1674 ISSN:1865-1682

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.

African Swine Fever (ASF) has been slowly but steadily increasing its endemic range throughout Europe, posing an imminent risk to the pig industry. ASF transmission among wild boar occurs mainly through wild boar population movements, hence wild boar presence and density are important risk factors for introducing, maintaining, and spreading the disease. The understanding of wild boar population dynamics and their role in ASF transmission and persistence remains limited. It is crucial to gain knowledge in this area to improve wildlife management while minimizing the risks for ASF introduction and spread. We adapted an individual-based spatio-temporal stochastic model developed by Halasa et al. (2019) and tailored it to two regions in France. The model assessed yearly hunting activity, the carcass persistence seasonality, and the specific landscape characteristics of the Franco-Belgian border region and the Pyrénées-Atlantiques department. Following the establishment of local population dynamics through preliminary runs of the model, the model was run 100 iterations over 8 years in the two study areas where ASF was randomly seeded after the 2nd year of simulation. For each scenario, the model was initiated with 500 wild boar groups randomly spread across the study areas. Hunting activities were included and excluded to assess the impact on population growth and ASF spread. Results showed an ever-growing wild boar population for all scenarios, which was balanced when hunting activities were included. When introducing ASF, the wild boar populations were dramatically impacted in both areas with a decrease of 63 % of the population at the Franco-Belgian border and 86 % in the Pyrénées-Atlantiques department. Habitat fragmentation and landscape connectivity were highlighted as important factors shaping ASF propagation. The Franco-Belgian border, which had the most fragmented habitat with unsuitable areas for wild boars, was shown to limit wild boar movements, reducing the probability, and spread of ASF across the landscape. The lack of connectivity was reflected in a less effective transmission and lower number of infected groups (406 versus 467). In contrast, the epidemic duration was lengthened in the fragmented habitat compared to the homogenous area (2.6 years vs 1.6 years). This study provided information on defining and implementing control measures in case of an ASF incursion, since delimitation of the area via fences artificially induces landscape fragmentation, which is important for controlling ASF outbreaks.

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 departements (French administrative regions) and the temporal dynamics of the effective viral population size (Ne) in each departement. Viral migration rates quantify viral spread between departements and Ne is a population genetic measure of the epidemic size and, in turn, is indicative of the within-departement 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 departements. No relationship was found between the viral spread and duck movements between departements. The within-departement transmission intensity was found to be weakly associated with the intensity of duck movements within departements. Together, these results indicated that the virus spread in short distances, either between adjacent departements or within departements. Results also suggested that the restrictions on duck transport within departements 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., Transboundary and Emerging Diseases, 69 (5), ISSN:1865-1674, ISSN:1865-1682

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 movement restrictions. Here we developed a nested multiscale model for the transmission of ASF, combining spatially explicit network model of animal movements with a deterministic compartmental model for the dynamics of two ASF strains within-pixels of 3 km × 3 km, amongst the pig population 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 modeling 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. This article is protected by copyright. All rights reserved.

Phylodynamic methods have successfully been used to describe viral spread history but their applications for assessing specific control measures are rare. In 2016-17, France experienced a devastating epidemic of a highly pathogenic avian influenza virus (H5N8 clade 2.3.4.4b). Using 196 viral genomes, we conducted a phylodynamic analysis combined with generalised linear model and showed that the large-scale preventive culling of ducks significantly reduced the viral spread between départements (French administrative division). We also found that the virus likely spread more frequently between départements that shared borders, but the spread was not linked to duck transport between départements. Duck transport within départements increased the within-département transmission intensity, although the association was weak. 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, by testing specific hypothesis related to different control measures, we demonstrated that phylodynamics methods are capable of investigating the impacts of control measures on viral spread.

The spread of African swine fever (ASF) poses a grave threat to the global swine industry. Understanding transmission dynamics, such as through mechanistic modeling, is critical for designing effective control strategies. Articles were examined across multiple epidemiological and model characteristics. Model filiation was determined through creation of a neighbor-joined tree using phylogenetic software. Of 34 four articles qualifying for inclusion, four main modelling objectives were identified: estimating transmission parameters (11 studies), assessing determinants of transmission (7), examining consequences of hypothetical outbreaks (5), and assessing alternative control strategies (11). Estimated transmission parameters varied widely as did parameter assumptions between models. Uncertainties on epidemiological and ecological parameters were usually accounted for to assess the impact on the modeled infection trajectory. Almost all models are host specific, being developed for either domestic pigs or wild boar despite the fact that spillover events between domestic pigs and wild boar are evidenced to play an important role in ASF outbreaks. The development of models incorporating such transmission routes is crucial. All compared control strategies were defined a priori, and future models should be built to identify optimal contributions across many control methods. Further, control strategies were examined in competition, opposed to how they would be synergistically implemented. While comparing strategies is beneficial for identifying a rank-order efficacy of control methods, this structure does not necessarily determine the most effective combination of all available strategies. In order for ASFV models to effectively support decision-making in controlling ASFV globally, these modelling limitations need to be addressed., 19 pages, 3 figures, 4 tables. Accepted to Preventive Veterinary Medicine. Revised from previous preprint to include models published through Dec 2020

This assessment was conducted by the ad hoc working group ‘ASF vectors’ of the French Agency for Food, Environmental and Occupational Health & Safety (Anses).; International audience; 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 (

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 movement restrictions. Here we developed a nested multiscale model for the transmission of ASF, combining spatially explicit network model of animal movements with a deterministic compartmental model for the dynamics of two ASF strains within-pixels of 3 km x 3 km, amongst the pig population 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 modeling 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.

Highlights • Maternally-derived neutralizing antibodies impair PRRS vaccination immune responses in piglets. • Maternally-derived neutralizing antibodies reduce PRRS vaccine efficacy in piglets. • IFNa may also interfere with PRRS vaccination., Modified live virus (MLV) vaccines are commonly used to reduce the impact of porcine reproductive and respiratory syndrome (PRRS) but limited efficacy is achieved in field conditions. Here, we evaluated the impact of maternally-derived neutralizing antibodies (MDNAs) on vaccine efficacy after PRRS virus (PRRSV) challenge. Piglets with low (A−) or high (A+) MDNA levels derived from a commercial pig herd were moved to experimental facilities to be vaccinated (V+) or not (V−) with a PRRSV-1 MLV vaccine at 3 weeks of age (woa). Because of unexpectedly low vaccine detection in A−V+ piglets post-vaccination (pv), all V+ piglets received a second vaccination at 4 woa. Five weeks (W5) pv, piglets were inoculated with a PRRSV-1 field strain to evaluate vaccine protection, and were mingled 24 h later with non-inoculated piglets of similar immune status to assess viral transmission. Vaccine strain was detected at W2 pv in 69% and 6% of A−V+ and A+V+ piglets, and at W5 pv in 50% and 25% of A−V+ and A+V+ piglets, respectively. At W5 pv, 94% of A−V+ and 44% of A+V+ piglets seroconverted, with a significant IFNg response induction in the A−V+ group only. After challenge, compared to the V− inoculated group, viremia was 100-fold lower at 10 days post-infection in A−V+ whereas viremia was not significantly reduced in A+V+ piglets. A lower transmission rate was estimated for the A−V+ group: 0.15 [0.07–0.29] versus 0.44 [0.18–1.76] and 0.32 [0.14–0.68] for the A+V+ and V− groups, respectively. Investigations about the low vaccine strain detection after the first vaccination suggested a relationship between IFNa levels and vaccine strain detection in A−V+ piglets. We showed that MDNAs impair vaccine efficacy against PRRSV both in inoculated and contact piglets, probably by reducing vaccine replication. IFNa may also interfere with PRRSV vaccination. These new data could help improving vaccination protocols.

Hepatitis E virus is a zoonotic pathogen for which pigs have been identified as the main reservoir in industrialised countries. HEV infection dynamics in pig herds and pigs are influenced by several factors, including herd practices and possibly co-infection with immunomodulating viruses. This study therefore investigates the impact of porcine circovirus type 2 (PCV2) on HEV infection and transmission through experimental HEV/PCV2 co-infection of specific-pathogen-free pigs. No statistical difference between HEV-only and HEV/PCV2-infected animals was found for either the infectious period or the quantity of HEV shed in faeces. The HEV latency period was shorter for HEV/PCV2 co-infected pigs than for HEV-only infected pigs (11.6 versus 12.3 days). Its direct transmission rate was three times higher in cases of HEV/PCV2 co-infection than in cases of HEV-only infection (0.12 versus 0.04). On the other hand, the HEV transmission rate through environmental accumulation was lower in cases of HEV/PCV2 co-infection (4.3.10(-6) versus 1.5.10(-5) g/RNA copies/day for HEV-only infected pigs). The time prior to HEV seroconversion was 1.9 times longer in HEV/PCV2 co-infected pigs (49.4 versus 25.6 days for HEV-only infected pigs). In conclusion, our study shows that PCV2 affects HEV infection and transmission in pigs under experimental conditions.

Live animal movements generate direct contacts (via the exchange of live animals) and indirect contacts (via the transit of transport vehicles) between farms, which can contribute to the spread of pathogens. However, most analyses focus solely on direct contacts and can therefore underestimate the contribution of live animal movements in the spread of infectious diseases. Here, we used French live duck movement data (2016–2018) from one of the largest transport companies to compare direct and indirect contact patterns between duck farms and evaluate how these patterns were associated with the French 2016–2017 epidemic of highly pathogenic avian influenza H5N8. A total number of 614 farms were included in the study, and two directed networks were generated: the animal introduction network (exchange of live ducks) and the transit network (transit of transport vehicles). Following descriptive analyses, these two networks were scrutinized in relation to farm infection status during the epidemic. Results showed that farms were substantially more connected in the transit network than in the animal introduction network and that the transit of transport vehicles generated more opportunities for transmission than the exchange of live animals. We also showed that animal introduction and transit networks’ statistics decreased substantially during the epidemic (January–March 2017) compared to non-epidemic periods (January-March 2016 and January-March 2018). We estimated a probability of 33.3 % that a farm exposed to the infection through either of the two live duck movement networks (i.e. that was in direct or indirect contact with a farm that was reported as infected in the following seven days) becomes infected within seven days after the contact. However, we also demonstrated that the level of exposure of farms by these two contact patterns was low, leading only to a handful of transmission events through these routes. As a consequence, we showed that live animal movement patterns are efficient transmission routes for HPAI but have been efficiently reduced to limit the spread during the French 2020–2021 epidemic. These results underpin the relevance of studying indirect contacts resulting from the movement of animals to understand their transmission potential and the importance of accounting for both routes when designing disease control strategies.

Following the emergence of highly pathogenic avian influenza (H5N8) in France in early December 2020, we used duck mortality data of the index case to investigate within-flock transmission dynamics. A stochastic epidemic model was adjusted to the daily mortality data and model parameters were estimated using an approximate Bayesian computation sequential Monte Carlo (ABC-SMC) algorithm. Results suggested that the virus was introduced 4 days (95% credible interval: 3 – 5) prior to the day suspicion was reported and that the transmission rate was 3.7 day-1 (95%CI: 2.6 – 5.3). On average, ducks started being infectious 3.1 hours (95%CI: 0.4 – 8.0) after infection and remained infectious for 4.4 days (95%CI: 3.1 – 5.6). Model outputs also suggested that the number of infectious ducks was already 3239 (95%CI: 26 – 3706) the day before suspicion, emphasising the substantial latent threat this virus could pose to other poultry farms and to neighbouring wildlife. These estimations can be applied to upcoming outbreaks and made available to veterinary services within few hours. This study illustrates how mechanistic models can provide rapid relevant insights to contribute to the management of infectious disease outbreaks of farmed animals.

Mathematical modelling is nowadays a pivotal tool for infectious diseases studies, completing regular biological investigations. The rapid growth of computer technology allowed for development of computational tools to address biological issues that could not be unravelled in the past. The global understanding of viral disease dynamics requires to account for all interactions at all levels, from within-host to between-herd, to have all the keys for development of control measures. A literature review was performed to disentangle modelling frameworks according to their major objectives and methodologies. One hundred and seventeen articles published between 1994 and 2020 were found to meet our inclusion criteria, which were defined to target papers representative of studies dealing with models of viral infection dynamics in pigs. A first descriptive analysis, using bibliometric indexes, permitted to identify keywords strongly related to the study scopes. Modelling studies were focused on particular infectious agents, with a shared objective: to better understand the viral dynamics for appropriate control measure adaptation. In a second step, selected papers were analysed to disentangle the modelling structures according to the objectives of the studies. The system representation was highly dependent on the nature of the pathogens. Enzootic viruses, such as swine influenza or porcine reproductive and respiratory syndrome, were generally investigated at the herd scale to analyse the impact of husbandry practices and prophylactic measures on infection dynamics. Epizootic agents (classical swine fever, foot-and-mouth disease or African swine fever viruses) were mostly studied using spatio-temporal simulation tools, to investigate the efficiency of surveillance and control protocols, which are predetermined for regulated diseases. A huge effort was made on model parameterization through the development of specific studies and methodologies insuring the robustness of parameter values to feed simulation tools.Integrative modelling frameworks, from within-host to spatio-temporal models, is clearly on the way. This would allow to capture the complexity of individual biological variabilities and to assess their consequences on the whole system at the population level. This would offer the opportunity to test and evaluate in silico the efficiency of possible control measures targeting specific epidemiological units, from hosts to herds, either individually or through their contact networks. Such decision support tools represent a strength for stakeholders to help mitigating infectious diseases dynamics and limiting economic consequences.

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 hematophagous 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 (

Hepatitis E virus (HEV) is a zoonotic agent with pigs as the main reservoir in industrialised countries. Recent studies conducted on pig farms, in experimental conditions or through modelling approaches, have led to a better understanding of the spread of HEV on pig farms. The findings have also made it possible to define a set of measures to reduce HEV prevalence and the risk of marketing contaminated products. The objective of this study was to assess the feasibility of a set of HEV control strategies on pig farms. Individual semi-structured interviews were conducted with farmers, veterinarians and farming advisors to collect general data, their level of knowledge of HEV, their opinion on the technical feasibility of certain changes in practices, their perception of the respective responsibilities of the different stakeholders, and their feelings about the importance of the issue, following the framework of the Theory of Planned Behaviour. The interviews made it possible to highlight potential barriers and preferred motivators for the implementation of on-farm risk mitigation strategies. Barriers included lack of knowledge, scientific gaps, perceived inability to control HEV, and low perception of the importance of the issue. Motivators included professional satisfaction, family recognition, and the opportunity to achieve higher quality standards. Three clusters of stakeholders were also identified, with a group of leaders who could help unlock reluctance and disseminate innovations. This type of behavioural approach appeared useful to help risk managers facilitate zoonotic control on pig farms.

International audience; Abstract African swine fever (ASF) has affected Romania since July 2017, with considerable economic and social consequences, despite the implementation of control measures mainly based on stamping out of infected pig populations. On the basis of the 2973 cumulative recorded cases up to September 2019 among wild boars and domestic pigs, analysis of the epidemiological characteristics could help to identify the factors favoring the persistence and spread of ASF. A statistical framework, based on a random forest methodology, was therefore developed to assess the spatiotemporal features of the epidemics and their relationships with environmental, human, and agricultural factors. The landscape of Romania was associated with the infection dynamics, particularly concerning forested and wetland areas. Waterways were also identified as a pivotal factor, raising questions about possible waterborne transmission since these waterways are often used as a water supply for backyard holdings. However, human activity was clearly identified as the main risk factor for the spread of ASF. Although the situation in Romania cannot be directly transposed to intensive pig farming countries, the findings of this study highlight the need for strict biosecurity measures on farms, and during transportation, to avoid ASF transmission at large geographic and temporal scales.

Modelling in epidemiology can be used for parameter estimation, understanding infectious process or control strategies evaluation, and is based on a mathematical model representing the infectious process derived from the SIR model (susceptible-infectious-removed). This model is further adapted to the disease under study with additional health statuses to represent more precisely the characteristics of the infectious agent and to couple the infection dynamics with the population dynamics of the studied system. This adaptation is documented by descriptive and analytic epidemiological studies to obtain a model representing the infectious process in a realistic way. Risk assessment and/or evaluation of control strategies can be proposed by the model simulation. The use of a modelling approach to understand the determinisms of a viral infectious process within a structured animal population is further illustrated by the example of swine influenza A viruses persistence in pig farms. The model set up to this aim is used to better understand the mechanisms related to viruses persistence within the herd and identify potential control measures that could be applied in farm conditions.

Co-infection by a type 1 modified live vaccine-like strain (MLV1-like) of porcine reproductive and respiratory syndrome virus (PRRSV) and a type 2 porcine circovirus (PCV2) was identified on a French pig farm with post-weaning multisystemic wasting syndrome (PMWS). An in vivo experiment was set up to characterize the virulence level of the MLV1-like strain compared with the parental MLV1 strain, and to assess the impact of PCV2 co-infection on the pathogenicity of both PRRSV strains. Six groups of six pigs each were inoculated only with either one of the two PRRSV strains or with PCV2, or co-inoculated with PCV2 and MLV1 or PCV2 and MLV1-like strains. Six contact pigs were added to each inoculated group to assess viral transmission. The animals were monitored daily for 35 days post-inoculation for clinical symptoms. Blood and nasal swabs were sampled twice a week, and tissue samples were collected during necropsy for viral quantification. Compared to MLV1-infected pigs, animals infected with the MLV1-like strain had increased PRRSV viremia and nasal shedding, a higher viral load in the tonsils, and lymph node hypertrophy at microscopic level. PCV2 co-infection did not influence clinical, virologic or transmission parameters for MLV1, but co-infected MLV1-like/PCV2 pigs had the most severe lung lesions, the highest viremia in contact animals and the highest transmission rate. Our study demonstrated that the MLV1 strain tested was safe when co-inoculated with PCV2 in piglets. However, co-infection by the MLV1-like strain and PCV2 resulted in increased virulence compared with that due to a single infection.

Hepatitis E virus is a zoonotic pathogen for which pigs are recognized as the major reservoir in industrialised countries. A multiscale model was developed to assess the HEV transmission and persistence pattern in the pig production sector through an integrative approach taking into account within-farm dynamics and animal movements based on actual data. Within-farm dynamics included both demographic and epidemiological processes. Direct contact and environmental transmission routes were considered along with the possible co-infection with immunomodulating viruses (IMVs) known to modify HEV infection dynamics. Movements were limited to 3,017 herds forming the largest community on the swine commercial network in France and data from the national pig movement database were used to build the contact matrix. Between-herd transmission was modelled by coupling within-herd and network dynamics using the SimInf package. Different introduction scenarios were tested as well as a decrease in the prevalence of IMV-infected farms. After introduction of a single infected gilt, the model showed that the transmission pathway as well as the prevalence of HEV-infected pigs at slaughter age were affected by the type of the index farm, the health status of the population and the type of the infected farms. These outcomes could help design HEV control strategies at a territorial scale based on the assessment of the farms' and network's risk.

International audience; 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.

Maternally-derived antibodies (MDA) reduce piglet susceptibility to swine influenza A virus, but interfere with post-infectious immune responses, raising questions about protection after waning of passive immunity. We therefore analysed the impact of different levels of residual MDA on virus excretion and immune responses in piglets born to vaccinated sows (MDA+) and infected with H1N1 at 5, 7 or 11 weeks of age, in comparison to piglets born to unvaccinated sows (MDA-). Subsequent protection against a second homologous infection occurring 4 weeks after the primo-infection was also investigated. MDA- pigs showed clinical signs, shed the virus, and developed specific immune responses despite some age-dependent differences: 7-week-old pigs were less affected clinically, showed a 2-day delayed excretion peak and excreted less virus than younger pigs. In MDA+ animals, clinical signs increased together with the decrease of MDA levels related to the age at infection-time. Virus shedding was not prevented and genome quantification profiles were similar to those obtained in MDA- piglets. However, viral particles excreted by 5-week-old MDA+ piglets appeared to be less infectious than those shed by MDA- piglets at the same age. Humoral response was affected by MDA as illustrated by the absence of HI and neutralizing response regardless the infection age, but anti-NP/M responses were less affected. Proliferative T cell responses were slightly delayed by high MDA levels. Nevertheless, MDA+ animals were all protected from a second infection, like MDA- piglets. In conclusion, responses of pigs to H1N1 were affected by both the physiological development of animals at infection and the MDA level.

Highlights • A method is proposed to explore the role of pig movements on pathogen epidemiology. • Pig farm centrality in the network is associated with higher HEV seroprevalence. • Some local areas are more at risk for HEV due to incoming pig movements. • Animal movements should be included in risk-based surveillance strategies., Animal movements between farms are a major route of pathogen spread in the pig production sector. This study aimed to pair network analysis and epidemiological data in order to evaluate the impact of animal movements on pathogen prevalence in farms and assess the risk of local areas being exposed to diseases due to incoming movements. Our methodology was applied to hepatitis E virus (HEV), an emerging foodborne zoonotic agent of concern that is highly prevalent in pig farms. Firstly, the pig movement network in France (data recorded in 2013) and the results of a nation-wide seroprevalence study (data collected in 178 farms in 2009) were modelled and analysed. The link between network centrality measures of farms and HEV seroprevalence levels was explored using a generalised linear model. The in-degree and ingoing closeness of farms were found to be statistically associated with high HEV within-farm seroprevalence (p