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We analysed the interplay between palmiped farm density and the vulnerability of the poultry production system to highly pathogenic avian influenza (HPAI) H5N8. To do so, we used a spatially-explicit transmission model, which was calibrated to reproduce the observed spatio-temporal distribution of outbreaks in France during the 2016–2017 epidemic of HPAI. Six scenarios were investigated, in which the density of palmiped farms was decreased in the municipalities with the highest palmiped farm density. For each of the six scenarios, we first calculated the spatial distribution of the basic reproduction number (R0), i.e. the expected number of farms a particular farm would be likely to infect, should all other farms be susceptible. We also ran in silico simulations of the adjusted model for each scenario to estimate epidemic sizes and time-varying effective reproduction numbers. We showed that reducing palmiped farm density in the densest municipalities decreased substantially the size of the areas with high R0 values (> 1.5). In silico simulations suggested that reducing palmiped farm density, even slightly, in the densest municipalities was expected to decrease substantially the number of affected poultry farms and therefore provide benefits to the poultry sector as a whole. However, they also suggest that it would not have been sufficient, even in combination with the intervention measures implemented during the 2016–2017 epidemic, to completely prevent the virus from spreading. Therefore, the effectiveness of alternative structural preventive approaches now needs to be assessed, including flock size reduction and targeted vaccination. [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]

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]

Highly pathogenic avian influenza (HPAI) subtype H5N8 outbreaks occurred in poultry farms in France in 2016–2017, resulting in significant economic losses and disruption to the poultry industry. Current evidence on associations between actual on‐farm biosecurity risk factors and H5N8 occurrence is limited. Therefore, a retrospective matched case–control study was undertaken to investigate the inter‐relationships between on‐farm biosecurity practices and H5N8 infection status to provide new insights regarding promising targets for intervention. Data were collected on 133 case and 133 control duck farms (i.e. the most affected species) located in one area of the country that was mostly affected by the disease. Data were analysed using Additive Bayesian Networks which offer a rich modelling framework by graphically illustrating the dependencies between variables. Factors indirectly and directly positively associated with farm infection were inadequate management of vehicle movements (odds ratio [OR] 9.3, 95% credible interval [CI] 4.0–22.8) and inadequate delimitation of farm and units (OR 3.0, 95% CI 1.6–5.8), respectively. Inadequate disposal of dead birds was instead negatively associated with the outcome (OR 0.1, 95% CI 0.0–0.3). The findings highlight that reinforcing farm access control systems and reducing the number of visitors are key biosecurity measures to control farm vulnerability to H5N8 infection and could help setting priorities in biosecurity practices to prevent outbreaks' re‐occurrence. [ABSTRACT FROM AUTHOR]

The relative roles that movement and proximity networks play in the spread of highly pathogenic avian influenza (HPAI) viruses are often unknown during an epidemic, preventing effective control. We used network analysis to explore the devastating epidemic of HPAI A(H5N8) among poultry, in particular ducks, in France during 2016-2017 and to estimate the likely contribution of live-duck movements. Approximately 0.2% of live-duck movements could have been responsible for between-farm transmission events, mostly early during the epidemic. Results also suggest a transmission risk of 35.5% when an infected holding moves flocks to another holding within 14 days before detection. Finally, we found that densely connected groups of holdings with sparse connections between groups overlapped farmer organizations, which represents important knowledge for surveillance design. This study highlights the importance of movement bans in zones affected by HPAI and of understanding transmission routes to develop appropriate HPAI control strategies. [ABSTRACT FROM AUTHOR]

Background: Although the poultry sector accounts for a major portion of global antimicrobial consumption, few studies have explored the factors which influence antimicrobial use (AMU) in poultry farms in Europe. We performed a matched case-control study in traditional free-range broiler farms in France during 2016 to evaluate the effect of technical factors and farmers' perceptions of health problems on the probability of AMU. In total, 52 cases (defined as flocks treated with antimicrobials when chickens were between 1 and 42 days old), were included. Another 208 controls (untreated flocks the same ages as the case flocks), were randomly selected and paired with a matching case (same farmer organization and placement date). On-farm questionnaires were administered. Multivariable logistic regression modeling was conducted; seven variables were significant in the final model. Results: Two factors were associated with a lower probability of AMU: the use of chicken paper topped with starter feed (OR = 0.3; 95% CI = [0.1; 0.9]) and the use of herbal drugs as a prophylaxis (OR = 0.1; 95% CI = [0.01; 0.5]). A higher probability of AMU was associated with farmers perceiving the cumulative mortality of chicks between 1 and 10 days old as normal (OR = 10.1; 95% CI = [1.7; 59]) or high (OR = 58.7; 95% CI = [9.6; 372.3]). A higher probability of AMU also was associated with farmers detecting a health problem (OR = 12.5, 95% CI = [4.2; 36.9]) and phone calls between farmers and their technicians (OR = 5.9; 95% CI = [2.3; 14.8]) when chicks are between 11 to 42 days old. Two additional factors (litter thickness and cleaning/disinfecting) were significant and highlighted the importance of technical factors such as biosecurity. Conclusions: Our results suggest that to reduce AMU, technical training should be provided to farmers to improve how farms are monitored and to reinforce preventive health measures. Training also should address how farmers assess warning criteria like daily mortality rates, which when overestimated often lead to antimicrobial treatment. [ABSTRACT FROM AUTHOR]

The severe impact of recently reported Highly Pathogenic Avian Influenza (HPAI) outbreaks have emphasized the need to better monitor biosecurity practices among the different French poultry production systems. Between October 2016 and September 2018, a large national cross-sectional study was carried out in France to assess biosecurity levels in high-risk poultry farms and identify farm biosecurity profiles, using Multiple Correspondence and Hierarchical Cluster Analyses. Results indicate that there is substantial room for improvement in cleaning and disinfection, anteroom management and delimitation of farm and production units for more than 50 % of the 1,004 analyzed farms. The farm biosecurity profile showing the highest level of biosecurity included commercial intensive poultry farms (gallinaceous poultry farms, in North-Western France), and those with a recent history of HPAI outbreak (duck farms, in South-Western France). The farms biosecurity profiles showing the lowest level of biosecurity included farms with multiple species (duck and gallinaceous poultry) or multiple production types (broilers and egg-layers), located in regions with a lower poultry density and without a recent history of HPAI outbreak. Outcomes provide support to adapt biosecurity improvement and inspection plans. [ABSTRACT FROM AUTHOR]

The emergence of clade 2.3.4.4b H5N1 highly pathogenic avian influenza (HPAI) viruses in 2021 has led to unprecedented epidemics in poultry, changing epidemiological patterns of year-round infections in resident wild avifauna and more frequent spill-over events to mammals. Given this situation, it is important that we recognise that traditional HPAI management strategies are no longer sufficient, and policy changes are required. Poultry vaccination has emerged as a crucial intervention in the current control of HPAI, as evidenced by France's nationwide campaign targeting domestic ducks. However, due to the logistical challenges and potential trade implications of vaccination, broader structural reforms appear also necessary. These include a shift from farm-level to territorial-level biosecurity approaches, putting into practice the concept of 'regional biosecurity'. Given the role duck farm density has played in successive HPAI epidemics in France, there is a need to think about the spatial distribution of poultry farms as a structural component of regional biosecurity and to consider the reduction of farm concentration as a measure to prevent viral spread. The integration of regional biosecurity and poultry vaccination into prevention strategies should impact the way poultry are produced and traded in the future.

Biosecurity is crucial for infectious disease prevention, more importantly in the absence of vaccination. The need for improving the implementation of biosecurity practices was highlighted in French duck farms following the 2016-2017 H5N8 Highly Pathogenic Avian Influenza (HPAI) epidemic. Farmers have multiple reasons for not implementing biosecurity practices: external (time, money) and internal (socio-psychological). The purpose of this study was to determine how sets of socio-psychological factors (i.e. knowledge on biosecurity and avian influenza transmission, attitudes, personality traits, social background) affect the adoption of on-farm biosecurity practices. Biosecurity practices and socio-psychological determinants were assessed during 127 duck farm visits, in South West France, using both questionnaires and on-farm observations. Factorial analysis of mixed data (FAMD) and hierarchical clustering analysis (HCA) identified three groups of farmers with different socio-psychological profiles: the first group was characterized by minimal knowledge, negative attitudes towards biosecurity, little social pressure and a low level of conscientiousness. The second group was characterized by more extensive experience in poultry production, higher stress and social pressure. The third group was characterized by less experience in poultry production, better knowledge and positive attitudes towards biosecurity, increased self-confidence and orientation towards action. The first group had a significantly lower adoption of biosecurity measures than the two other groups. A better understanding of the factors involved in farmers' decision-making could improve the efficiency of interventions aiming at improving and maintaining the level of on-farm biosecurity in the duck industry., (© 2020 Blackwell Verlag GmbH.)

In the winter 2016-2017 the largest epidemic of highly pathogenic avian influenza (HPAI) ever recorded in the European Union spread to all 28 member states. France was hit particularly hard and reported a total of 484 infected premises (IPs) by March 2017. We developed a mathematical model to analyze the spatiotemporal evolution of the epidemic and evaluate the impact of control strategies. We estimated that farms rearing ducks were on average 2.5 times more infectious and 5.0 times more susceptible to HPAI than farms rearing other avian species. The implementation of surveillance zones around IPs reduced transmission by a factor of 1.8 on average. Compared to the strengthening of pre-emptive culling measures enforced by French authorities in February 2017, we found that a faster depopulation of diagnosed IPs would have had a larger impact on the total number of infections. For example, halving the time delay from detection to slaughter of infected animals would have reduced the total number of IPs by 52% and total cull numbers by 50% on average. This study showcases the possible contribution of modeling to inform and optimize control strategies during an outbreak., (Copyright © 2019 The Authors. Published by Elsevier B.V. All rights reserved.)

IntroductionFrance is one of Europe's foremost poultry producers and the world's fifth largest producer of poultry meat. In November 2016, highly pathogenic avian influenza (HPAI) virus subtype H5N8 emerged in poultry in the country. As of 23 March 2017, a total of 484 confirmed outbreaks were reported, with consequences on animal health and socio-economic impacts for producers. Methods: We examined the spatio-temporal distribution of outbreaks that occurred in France between November 2016 and March 2017, using the space-time K-function and space-time permutation model of the scan statistic test. Results : Most outbreaks affected duck flocks in south-west France. A significant space-time interaction of outbreaks was present at the beginning of the epidemic within a window of 8 km and 13 days. This interaction disappeared towards the epidemic end. Five spatio-temporal outbreak clusters were identified in the main poultry producing areas, moving sequentially from east to west. The average spread rate of the epidemic front wave was estimated to be 5.5 km/week. It increased from February 2017 and was negatively associated with the duck holding density. Conclusion : HPAI-H5N8 infections varied over time and space in France. Intense transmission events occurred at the early stages of the epidemic, followed by long-range jumps in the disease spread towards its end. Findings support strict control strategies in poultry production as well as the maintenance of high biosecurity standards for poultry holdings. Factors and mechanisms driving HPAI spread need to be further investigated.

To assess environmental and horse-level risk factors associated with West Nile Virus (WNV) circulation in Camargue, Southern France, a serosurvey was conducted on non-vaccinated horses (n = 1159 from 134 stables) in 2007 and 2008. Fifteen Landsat images were examined to quantify areas with open water and flooded vegetation around sampled horses. Mean percentages of areas of open water and flooded vegetation, as well as variations in these percentages between 3 periods (November to February = NOT, March to July = END and August to October = EPI), were calculated for buffers of 2 km radius around the stables. Results of the final logistic regression showed that the risk of WNV seropositivity in horses decreased with their date of acquisition and age. Results also demonstrated the significant role of environmental variables. Horse serological status was associated with variations of open water areas between the NOT (November to February) and END (March to July) periods, as well as between END and EPI (August to October). WNV spillover was found more intense in areas where water level decreased strongly from winter to spring and from spring to summer.