Beginning in 2003, highly pathogenic avian influenza (HPAI) H5N1 virus spread across Southeast Asia, causing unprecedented epidemics. Thailand was massively infected in 2004 and 2005 and continues today to experience sporadic outbreaks. While research findings suggest that the spread of HPAI H5N1 is influenced primarily by trade patterns, identifying the anthropogenic risk factors involved remains a challenge. In this study, we investigated which anthropogenic factors played a role in the risk of HPAI in Thailand using outbreak data from the “second wave” of the epidemic (3 July 2004 to 5 May 2005) in the country. We first performed a spatial analysis of the relative risk of HPAI H5N1 at the subdistrict level based on a hierarchical Bayesian model. We observed a strong spatial heterogeneity of the relative risk. We then tested a set of potential risk factors in a multivariable linear model. The results confirmed the role of free-grazing ducks and rice-cropping intensity but showed a weak association with fighting cock density. The results also revealed a set of anthropogenic factors significantly linked with the risk of HPAI. High risk was associated strongly with densely populated areas, short distances to a highway junction, and short distances to large cities. These findings highlight a new explanatory pattern for the risk of HPAI and indicate that, in addition to agro-environmental factors, anthropogenic factors play an important role in the spread of H5N1. To limit the spread of future outbreaks, efforts to control the movement of poultry products must be sustained.

In winter 2016–2017, Highly Pathogenic Avian Influenza (HPAI) H5N8 virus spread across Europe, causing unprecedented epizootics. France was massively affected, resulting in the culling of over 6 million poultry. Boosted regression tree (BRT) models were used to quantify the association between spatial risk factors and HPAI H5N8 infection in poultry holdings and to generate predictive maps for HPAI infection. Three datasets were combined to build the model: a dataset of the reported outbreaks in poultry, a dataset of the poultry holdings where the virus has not been reported and a set of relevant spatial risk factors, including poultry production and trade, and water bird habitat. Results identified key associations between the ‘foie gras’ production systems and HPAI H5N8 risk of occurrence and indicate that strengthening surveillance of fattening duck production systems and making the transportation of fattening ducks more secure would be key priority options for HPAI prevention and control.

Introduction: France 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.

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.

Antimicrobial stewardship (AMS) is a commonly advocated approach to address antimicrobial resistance. However, AMS is often defined in different ways depending on where it is applied, such that a range of definitions is now in use. These definitions may be functional and well-structured for a given context but are often ill-adapted for collaborative work, creating difficulties for intersectoral communication on AMS and complicating the design, implementation, and evaluation of AMS interventions from a One Health perspective. Using boundary object theory, we identified three key elements common to AMS in different settings in the human and animal health sectors—a sense of collective and temporal responsibility, flexibility in scale and scope, and contextual contingency. Based on these findings, we propose a definition for antimicrobial stewardship applicable to the human and animal health sectors, intended to facilitate intersectoral communication and cooperation. Further directions of this work could include the application of the definition to develop indicators for evaluating stewardship interventions and the extension of the definition to incorporate elements pertinent to plant and ecosystem health.