Reduction of antibiotic use and antibiotic resistance in commercial poultry

Use of antibiotics for companion animals and livestock in the Netherlands has reduced by more than 60% over the last 10 years (SDa 2019; MARAN-2019). This reduction is the result of a change in policy towards the use of antibiotics in veterinary practice and is characterized by a series of coherent political decisions which changed the playing field for farmers and veterinarians considerably. In the years before 2009 the Netherlands was a high consumer of antibiotics in veterinary practice (Grave et al., 2010). The ban of antimicrobial growth promoters (AGPs) did not result in a reduction in total use since in the Netherlands the AGPs were fully replaced by antibiotics licensed for therapy. The total sales of all antibiotics remained stable at around 600 tons from 2000 to 2009.This use pattern resulted in high levels of antimicrobial resistance in bacteria from livestock and food thereof and high prevalence of Livestock Associated MRSA and ESBL-producing E. coli and Salmonella (MARAN, 2019; RIVM, 2009). Specifically, ESBL-producing isolates in the food chain were considered a risk for public health and their high prevalences, predominantly but not solely in poultry and poultry meat products were the direct reason to initiate the change in policy towards antibiotic use in animals.In this manuscript the trends in antibiotic use in poultry will be explored in the context of total use in livestock and its effect on the occurrence and trends in ESBL-producers and antimicrobial resistance in other bacterial species from poultry

Monitoring of Farm-Level Antimicrobial Use to Guide Stewardship: Overview of Existing Systems and Analysis of Key Components and Processes

The acknowledgment of antimicrobial resistance (AMR) as a major health challenge in humans, animals and plants, has led to increased efforts to reduce antimicrobial use (AMU). To better understand factors influencing AMR and implement and evaluate stewardship measures for reducing AMU, it is important to have sufficiently detailed information on the quantity of AMU, preferably at the level of the user (farmer, veterinarian) and/or prescriber or provider (veterinarian, feed mill). Recently, several countries have established or are developing systems for monitoring AMU in animals. The aim of this publication is to provide an overview of known systems for monitoring AMU at farm-level, with a descriptive analysis of their key components and processes. As of March 2020, 38 active farm-level AMU monitoring systems from 16 countries were identified. These systems differ in many ways, including which data are collected, the type of analyses conducted and their respective output. At the same time, they share key components (data collection, analysis, benchmarking, and reporting), resulting in similar challenges to be faced with similar decisions to be made. Suggestions are provided with respect to the different components and important aspects of various data types and methods are discussed. This overview should provide support for establishing or working with such a system and could lead to a better implementation of stewardship actions and a more uniform communication about and understanding of AMU data at farm-level. Harmonization of methods and processes could lead to an improved comparability of outcomes and less confusion when interpreting results across systems. However, it is important to note that the development of systems also depends on specific local needs, resources and aims

Use of a new antimicrobial consumption monitoring system (Vet-AMNet): Application to Dutch dairy sector over a 9-year period

INTRODUCTION: The urgency of preventing the increase of antimicrobial resistance has been emphasized by international authorities such as the World Health Organization, European Medicines Agency, and World Organization for Animal Health. Monitoring systems capable of reporting antimicrobial consumption data are regarded as a crucial pillar of this fight. The Vet-AMNet system was developed to collect and analyze national antimicrobial consumption data in Portuguese dairy farms to support the veterinary authority in stewardship actions and to assist both veterinarians and farmers in daily decisions related to antimicrobials. METHODS: To evaluate the robustness of the system and other identified critical success factors, it was used to analyze antimicrobial consumption data available from the Dutch dairy cow sector over the period from 2012 to 2020. The data previously used for publications by the Netherlands Veterinary Medicines Institute (SDa) were imported and pre-processed by the Vet-AMNet system according to the SDa's standard operating procedure and the Dutch metrics to measure antimicrobial consumption were calculated. RESULTS: By comparing the outputs with the figures generated by the system established in the Netherlands, the Portuguese system was validated. Antimicrobial consumption data from the Dutch dairy sector during the 9-year period will be presented in unpublished graphs and tables, where each molecule's pharmaceutical formulation, pharmacotherapeutic group and line of choice will be related and discussed, illustrating the evolution of sectorial antimicrobial consumption against a background of a strong national antimicrobial policy initiated by public-private cooperation and supported by legislation

Predictors of Nonseroconversion to SARS-CoV-2 Vaccination in Kidney Transplant Recipients

Kidney transplant recipients (KTRs) are still at risk of severe COVID-19 disease after SARS‑CoV‑2 vaccination, especially when they have limited antibody formation. Our aim was to understand the factors that may limit their humoral response. METHODS. Our data are derived from KTRs who were enrolled in the Dutch Renal Patients COVID-19 Vaccination consortium, using a discovery cohort and 2 external validation cohorts. Included in the discovery (N = 1804) and first validation (N = 288) cohorts were participants who received 2 doses of the mRNA-1273 vaccine. The second validation cohort consisted of KTRs who subsequently received a third dose of any SARS-CoV-2 vaccine (N = 1401). All participants had no history of SARS-CoV-2 infection. A multivariable logistic prediction model was built using stepwise backward regression analysis with nonseroconversion as the outcome. RESULTS. The discovery cohort comprised 836 (46.3%) KTRs, the first validation cohort 124 (43.1%) KTRs, and the second validation cohort 358 (25.6%) KTRs who did not seroconvert. In the final multivariable model‚ 12 factors remained predictive for nonseroconversion: use of mycophenolate mofetil/mycophenolic acid (MMF/MPA); chronic lung disease, heart failure, and diabetes; increased age; shorter time after transplantation; lower body mass index; lower kidney function; no alcohol consumption; ≥2 transplantations; and no use of mammalian target of rapamycin inhibitors or calcineurin inhibitors. The area under the curve was 0.77 (95% confidence interval [CI], 0.74-0.79) in the discovery cohort after adjustment for optimism, 0.81 (95% CI, 0.76-0.86) in the first validation cohort, and 0.67 (95% CI, 0.64-0.71) in the second validation cohort. The strongest predictor was the use of MMF/MPA, with a dose-dependent unfavorable effect, which remained after 3 vaccinations. CONCLUSIONS. In a large sample of KTRs, we identify a selection of KTRs at high risk of nonseroconversion after SARS-CoV-2 vaccination. Modulation of MMF/MPA treatment before vaccination may help to optimize vaccine response in these KTRs. This model contributes to future considerations on alternative vaccination strategies

Seasonality of antimicrobial use in Dutch food-producing animals

Due to globally increasing antimicrobial resistance (AMR), it is pivotal to understand factors contributing to antimicrobial use (AMU) to enable development and implementation of AMR-reducing interventions. Therefore, we explored seasonal variations of systemic AMU in food-producing animals in the Netherlands. Dutch surveillance data from January 2013 to December 2018 from cattle, pig, and broiler farms were used. AMU was expressed as the number of Defined Daily Dosages Animal per month (DDDA/animal-month) per farm by animal sector, antimicrobial line (first, second, and third), antimicrobial class, and farm type. Seasonality of AMU was analyzed using Generalized Additive Models (GAMs) with DDDA/animal-month as outcome variable, and year and month as independent variables. Year and month were modelled as smooth terms represented with penalized regression splines.Significant seasonality of AMU was found in the cattle and pig sectors, but not in broilers. Significant seasonality of AMU was found mainly for first-line antimicrobials. In the cattle sector, a significant increase during winter was found for the use of amphenicols (an increase of 23.8%) and long-acting macrolides (an increase of 3.4%). In the pig sector, seasonality of AMU was found for pleuromutilins (p < 0.001) with an increase of 20% in October-November. The seasonality of pleuromutilins was stronger in sows/piglets (an increase of 47%) than in fattening pigs (16% increase). Only in fattening pigs, the use of amphenicols showed a significant seasonality with an increase of 11% during winter (P < 0.001). AMU in cattle and pig sectors shows seasonal variations likely caused by seasonality of diseases. In broilers, no AMU seasonality was observed, possibly due to the controlled environment in Dutch farms. In the context of the one health concept, future studies are necessary to explore whether this seasonality is present in other populations and whether it has implications for antimicrobial resistance in humans through the food chain

Adherence to preventive measures after SARS-CoV-2 vaccination and after awareness of antibody response in kidney transplant recipients in the Netherlands:a nationwide questionnaire study

BACKGROUND: Kidney transplant recipients (KTRs) were advised to tightly adhere to government recommendations to curb the spread of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) because of a high risk of morbidity and mortality and decreased immunogenicity after vaccination. The aim of this study was to analyse the change in adherence to preventive measures after vaccination and awareness of antibody response, and to evaluate its effectiveness.METHODS: In this large-scale, national questionnaire study, questionnaires were sent to 3531 KTRs enrolled in the Dutch RECOVAC studies, retrospectively asking for adherence to nine preventive measures on a 5-point Likert scale before and after SARS-CoV-2 vaccination and after awareness of antibody response. Blood samples were collected 28 days after the second vaccination. Antibody response was categorised as non-responder (≤50 BAU/mL), low-responder (&gt;50 ≤ 300 BAU/mL) or high-responder (&gt;300 BAU/mL), and shared with participants as a correlate of protection. Participants of whom demographics on sex and age, blood samples and completed questionnaires were available, were included. Our study took place between February 2021 and January 2022. The primary outcome of adherence before and after vaccination was assessed between August and October 2021 and compared via the Wilcoxon signed rank sum test. Logistic regression analysis was performed to estimate the association between antibody response and non-adherence, and adherence on acquiring SARS-CoV-2 infection. This study is registered at ClinicalTrials.gov (NCT04841785).FINDINGS: In 2939 KTRs (83%) who completed the first questionnaire on adherence to preventive measures, adherence was higher before than after vaccination (4.56, IQR 4.11-4.78 and 4.22, IQR 3.67-4.67, p &lt; 0.001). Adherence after awareness of antibody response was analysed in 2399 KTRs (82%) of whom also blood samples were available, containing 949 non-responders, 500 low-responders and 950 high-responders. Compared to non-responders, low- and high-responders reported higher non-adherence. Higher adherence was associated with lower infection rates before and after vaccination (OR 0.67 [0.51-0.91], p = 0.008 and OR 0.48 [0.28-0.86], p = 0.010).INTERPRETATION: Adherence decreased after SARS-CoV-2 vaccination and in KTRs who were aware of a subsequent antibody response compared with those without. Preventive measures in this vulnerable group seem to be effective, regardless of vaccination status. This study starts a debate on sharing antibody results with the patient and future studies should elucidate whether decreased adherence in antibody responders is justified, also in view of future pandemics.FUNDING: The Netherlands Organization for Health Research and Development and the Dutch Kidney Foundation.</p

Masking effect of anti-androgens on androgenic activity in European river sediment unveiled by effect-directed analysis

This study shows that the androgen receptor agonistic potency is clearly concealed by the effects of androgen receptor antagonists in a total sediment extract, demonstrating that toxicity screening of total extracts is not enough to evaluate the full in vitro endocrine disrupting potential of a complex chemical mixture, as encountered in the environment. The anti-androgenic compounds were masking the activity of androgenic compounds in the extract with relatively high anti-androgenic potency, equivalent to 200 nmol flutamide equivalents/g dry weight. A two-step serial liquid chromatography fractionation of the extract successfully separated anti-androgenic compounds from androgenic compounds, resulting in a total androgenic potency of 3,820 pmol dihydrotestosterone equivalents/g dry weight. The fractionation simplified the chemical identification analysis of the original complex sample matrix. Seventeen chemical structures were tentatively identified. Polyaromatic hydrocarbons, a technical mixture of nonylphenol and dibutyl phthalate were identified to contribute to the anti-androgenic potency observed in the river sediment sample. With the GC/MS screening method applied here, no compounds with AR agonistic disrupting potencies could be identified. Seventy-one unidentified peaks, which represent potentially new endocrine disrupters, have been added to a database for future investigation

Monitoring of Farm-Level Antimicrobial Use to Guide Stewardship: Overview of Existing Systems and Analysis of Key Components and Processes

peer-reviewedThe acknowledgment of antimicrobial resistance (AMR) as a major health challenge in humans, animals and plants, has led to increased efforts to reduce antimicrobial use (AMU). To better understand factors influencing AMR and implement and evaluate stewardship measures for reducing AMU, it is important to have sufficiently detailed information on the quantity of AMU, preferably at the level of the user (farmer, veterinarian) and/or prescriber or provider (veterinarian, feed mill). Recently, several countries have established or are developing systems for monitoring AMU in animals. The aim of this publication is to provide an overview of known systems for monitoring AMU at farm-level, with a descriptive analysis of their key components and processes. As of March 2020, 38 active farm-level AMU monitoring systems from 16 countries were identified. These systems differ in many ways, including which data are collected, the type of analyses conducted and their respective output. At the same time, they share key components (data collection, analysis, benchmarking, and reporting), resulting in similar challenges to be faced with similar decisions to be made. Suggestions are provided with respect to the different components and important aspects of various data types and methods are discussed. This overview should provide support for establishing or working with such a system and could lead to a better implementation of stewardship actions and a more uniform communication about and understanding of AMU data at farm-level. Harmonization of methods and processes could lead to an improved comparability of outcomes and less confusion when interpreting results across systems. However, it is important to note that the development of systems also depends on specific local needs, resources and aims

Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals

We conduct a genome-wide association study (GWAS) of educational attainment (EA) in a sample of ~3 million individuals and identify 3,952 approximately uncorrelated genome-wide-significant single-nucleotide polymorphisms (SNPs). A genome-wide polygenic predictor, or polygenic index (PGI), explains 12-16% of EA variance and contributes to risk prediction for ten diseases. Direct effects (i.e., controlling for parental PGIs) explain roughly half the PGI's magnitude of association with EA and other phenotypes. The correlation between mate-pair PGIs is far too large to be consistent with phenotypic assortment alone, implying additional assortment on PGI-associated factors. In an additional GWAS of dominance deviations from the additive model, we identify no genome-wide-significant SNPs, and a separate X-chromosome additive GWAS identifies 57