Risk factors for antimicrobial use in Dutch pig farms: A cross-sectional study.

BACKGROUND: Antimicrobial use (AMU) has decreased significantly in Dutch pig farms since 2009. However, this decrease has stagnated recently, with relatively high AMU levels persisting mainly among weaners. The aim of this study was to identify farm-level characteristics associated with: i) total AMU and ii) use of specific antimicrobial classes. METHODS: In 2020, cross-sectional data from 154 Dutch pig farms were collected, including information on AMU and farm characteristics. A mixed-effects conditional Random Forest analysis was applied to select the subset of features that was best associated with AMU. RESULTS: The main risk factors for total AMU in weaners were vaccination for PRRS in sucklings, being a conventional farm (vs. not), high within-farm density, and early weaning. The main protective factors for total AMU in sows/sucklings were E. coli vaccination in sows and having boars for estrus detection from own production. Regarding antimicrobial class-specific outcomes, several risk factors overlapped for weaners and sows/sucklings, such as farmer's non-tertiary education, not having free-sow systems during lactation, and conventional farming. An additional risk factor for weaners was having fully slatted floors. For fatteners, the main risk factor for total AMU was PRRS vaccination in sucklings. CONCLUSIONS: Several factors found here to be associated with AMU. Some were known but others were novel, such as farmer's tertiary education, low pig aggression and free-sow systems which were all associated with lower AMU. These factors provide targets for developing tailor-made interventions, as well as an evidence-based selection of features for further causal assessment and mediation analysis.

Assessing potential determinants of the stagnating trend in Salmonella Enteritidis human infections in Europe and options for intervention: A multi-criteria decision analysis.

Background: After years of significant decline, the incidence of Salmonella enterica serotype Enteritidis (SE) human infections in Europe has started stagnating in recent years. The reasons for this stagnation remain largely unclear and are possibly multifactorial and interconnected in nature. We assessed and ranked several potential determinants of the stagnating SE trend in Europe, as well as different options for intervention at the level of poultry health and production, public health (infra)structure, and pathogen biology. Methods: A Multi-Criteria Decision-Analysis (MCDA) approach based on the Analytical Hierarchy Process was used. Through two separate surveys, a European panel of Salmonella experts first provided weights for several pre-defined criteria and subsequently scored different potential determinants and options for intervention (i.e. alternatives) against the criteria, during 2020-21. The weighting and scoring were based on Saaty's pairwise comparisons. The final ranking of the alternatives was derived from the summation of the products of each criterion weight with the score of the corresponding alternative. Sensitivity analyses were performed to assess the impact of different methodological choices, including European regions, and domains of expertise on the ranking of the determinants and options for intervention. Results: The first and second-ranked determinants of the stagnated trend in human SE infections were related to poultry health and production, namely "inadequacies of sampling programmes" and "premature relaxation of control measures". This ranking agreed with the ranking of the options for intervention, which were also those at the poultry health and production level, specifically "stricter biosecurity", "improving sampling", and "better/increased vaccination". Differences in rankings were observed among European regions and domains of expertise. Conclusions: The rankings of potential determinants and options for intervention for the stagnating SE trend in Europe pointed to the level of poultry health and production. Salmonella-control activities in poultry in Europe are harmonized across countries since many years, but the results of this study suggest that further improvements may be necessary for some countries. A multidisciplinary collaboration among veterinarians, public health professionals, and microbiologists is needed to further understand the origins of the stagnating SE trend and to identify effective interventions in order to reverse the trend, contextually in a given country, following a One Health approach.

Biosecurity and antimicrobial use in broiler farms across nine European countries: toward identifying farm-specific options for reducing antimicrobial usage.

Broiler chickens are among the main livestock sectors worldwide. With individual treatments being inapplicable, contrary to many other animal species, the need for antimicrobial use (AMU) is relatively high. AMU in animals is known to drive the emergence and spread of antimicrobial resistance (AMR). High farm biosecurity is a cornerstone for animal health and welfare, as well as food safety, as it protects animals from the introduction and spread of pathogens and therefore the need for AMU. The goal of this study was to identify the main biosecurity practices associated with AMU in broiler farms and to develop a statistical model that produces customised recommendations as to which biosecurity measures could be implemented on a farm to reduce its AMU, including a cost-effectiveness analysis of the recommended measures. AMU and biosecurity data were obtained cross-sectionally in 2014 from 181 broiler farms across nine European countries (Belgium, Bulgaria, Denmark, France, Germany, Italy, the Netherlands, Poland and Spain). Using mixed-effects random forest analysis (Mix-RF), recursive feature elimination was implemented to determine the biosecurity measures that best predicted AMU at the farm level. Subsequently, an algorithm was developed to generate AMU reduction scenarios based on the implementation of these measures. In the final Mix-RF model, 21 factors were present: 10 about internal biosecurity, 8 about external biosecurity and 3 about farm size and productivity, with the latter showing the largest (Gini) importance. Other AMU predictors, in order of importance, were the number of depopulation steps, compliance with a vaccination protocol for non-officially controlled diseases, and requiring visitors to check in before entering the farm. K-means clustering on the proximity matrix of the final Mix-RF model revealed that several measures interacted with each other, indicating that high AMU levels can arise for various reasons depending on the situation. The algorithm utilised the AMU predictive power of biosecurity measures while accounting also for their interactions, representing a first step toward aiding the decision-making process of veterinarians and farmers who are in need of implementing on-farm biosecurity measures to reduce their AMU.

Factors associated with antimicrobial use in pig and veal calf farms in the Netherlands: A multi-method longitudinal data analysis.

Minimizing antimicrobial use (AMU) in livestock is needed to control antimicrobial resistance (AMR). In the Netherlands, the livestock sector reduced AMU by almost 70 % since 2009, but this reduction stagnated in recent years. With only therapeutic AMU allowed, it is clear that besides socio-economic and behavioral factors, also the farm technical characteristics influence the conditions under which farmers need AMU. These characteristics pertain to farm management, including biosecurity, vaccination schemes, nutrition, micro-climate and husbandry practices. Identifying farm-related risk factors for AMU is needed to control AMR in a sustainable and pragmatic way. This need, often concerns the overall contribution of seemingly related (rather than individualized) factors. Here, risk factors for AMU in pig and calf farms were determined using two approaches: a typical risk factor analysis based on generalized estimating equations (GEEs) or hierarchical mixed-effects models and a multiblock partial least-squares regression analysis. These methods were applied to longitudinal data from two previous studies, i.e. a panel study and an intervention study involving 36 multiplier pig farms and 51 veal calf farms in the Netherlands, respectively. The multiblock analysis allowed us to quantify the importance of each factor and their respective block (i.e. farm management domain). For pigs, factors related to internal biosecurity had the highest impact on AMU, while for calves, these were mainly related to micro-climate. Structural characteristics, such as farm size and production type, followed in importance for both sectors. While both methods provided similar outcomes, the multiblock approach provided further insights by grouping and comparing factors believed to be inter-related.