33 research outputs found
Manifestation of SARS-CoV-2 Infections in Mink Related to Host-, Virus- and Farm-Associated Factors, The Netherlands 2020
SARS-CoV-2 outbreaks on 69 Dutch mink farms in 2020 were studied to identify risk factors for virus introduction and transmission and to improve surveillance and containment measures. Clinical signs, laboratory test results, and epidemiological aspects were investigated, such as the date and reason of suspicion, housing, farm size and distances, human contact structure, biosecurity measures, and presence of wildlife, pets, pests, and manure management. On seven farms, extensive random sampling was performed, and age, coat color, sex, and clinical signs were recorded. Mild to severe respiratory signs and general diseases such as apathy, reduced feed intake, and increased mortality were detected on 62/69 farms. Throat swabs were more likely to result in virus detection than rectal swabs. Clinical signs differed between virus clusters and were more severe for dark-colored mink, males, and animals infected later during the year. Geographical clustering was found for one virus cluster. Shared personnel could explain some cases, but other transmission routes explaining farm-to-farm spread were not elucidated. An early warning surveillance system, strict biosecurity measures, and a (temporary) ban on mink farming and vaccinating animals and humans can contribute to reducing the risks of the virus spreading and acquisition of potential mutations relevant to human and animal health
Adaptation, spread and transmission of SARS-CoV-2 in farmed minks and associated humans in the Netherlands
In the first wave of the COVID-19 pandemic (April 2020), SARS-CoV-2 was detected in farmed minks and genomic sequencing was performed on mink farms and farm personnel. Here, we describe the outbreak and use sequence data with Bayesian phylodynamic methods to explore SARS-CoV-2 transmission in minks and humans on farms. High number of farm infections (68/126) in minks and farm workers (>50% of farms) were detected, with limited community spread. Three of five initial introductions of SARS-CoV-2 led to subsequent spread between mink farms until November 2020. Viruses belonging to the largest cluster acquired an amino acid substitution in the receptor binding domain of the Spike protein (position 486), evolved faster and spread longer and more widely. Movement of people and distance between farms were statistically significant predictors of virus dispersal between farms. Our study provides novel insights into SARS-CoV-2 transmission between mink farms and highlights the importance of combining genetic information with epidemiological information when investigating outbreaks at the animal-human interface
Adaptation, spread and transmission of SARS-CoV-2 in farmed minks and related humans in the Netherlands
In the first wave of the COVID-19 pandemic (April 2020), SARS-CoV-2 was detected in farmed minks and genomic sequencing was performed on mink farms and farm personnel. Here, we describe the outbreak and use sequence data with Bayesian phylodynamic methods to explore SARS-CoV-2 transmission in minks and related humans on farms. High number of farm infections (68/126) in minks and farm related personnel (>50% of farms) were detected, with limited spread to the general human population. Three of five initial introductions of SARS-CoV-2 lead to subsequent spread between mink farms until November 2020. The largest cluster acquired a mutation in the receptor binding domain of the Spike protein (position 486), evolved faster and spread more widely and longer. Movement of people and distance between farms were statistically significant predictors of virus dispersal between farms. Our study provides novel insights into SARS-CoV-2 transmission between mink farms and highlights the importance of combing genetic information with epidemiological information at the animal-human interface
Comparing Farm Biosecurity and Antimicrobial Use in High-Antimicrobial-Consuming Broiler and Pig Farms in the Belgian–Dutch Border Region
As antimicrobial resistance is a worldwide problem, threatening both livestock and public health, understanding the drivers for resistance in different settings and countries is essential. Therefore, 30 pig and 30 poultry farms with country-specific high antimicrobial use (AMU) were recruited in the Belgian–Dutch border region. Information regarding production parameters, farm characteristics, biosecurity, and AMU was collected. On average, more biosecurity measures were implemented on Dutch farms, compared to Belgian farms in both animal species. In addition, more opportunities were found to increase the level of internal biosecurity compared to external biosecurity in both countries. AMU, quantified as treatment incidence (TI), differed marginally significant between broiler farms in Belgium and the Netherlands (median BE: 8; NL: 3), whereas in weaned piglets (median BE: 45 and NL: 14) and finishing pigs (median BE: 5 and NL: 1), there was a substantial difference in AMU between farms from both countries. Overall, Dutch farms showed less between-farm variation in TI than did Belgian farms. In both poultry and pig production, the majority of antimicrobials used were extended-spectrum penicillins (BE: 32 and 40%; NL: 40 and 24% for poultry and pigs, respectively). Compared to Belgian farms, Dutch poultry farms used high amounts of (fluoro)quinolones (1 and 15% of total AMU, respectively). None of the production parameters between broiler farms differed significantly, but in pig production, weaning age in Belgian farms (median: 23) was lower than in Dutch farms (median: 27). These results indicate considerable room for improvement in both countries and animal species. Farm-specific preventive strategies can contribute to lowering the risk for animal disease and hence the need for AMU
Early Life Inoculation With Adult-Derived Microbiota Accelerates Maturation of Intestinal Microbiota and Enhances NK Cell Activation in Broiler Chickens
Association of wild bird densities around poultry farms with the risk of highly pathogenic avian influenza virus subtype H5N8 outbreaks in the Netherlands, 2016
Highly pathogenic (HP) avian influenza viruses (AIV) can spread globally through migratory birds and cause massive outbreaks in commercial poultry. AIV outbreaks have been associated with proximity to waterbodies, presence of waterfowl or wild bird cases near poultry farms. In this study, we compared densities of selected HPAI high‐risk wild bird species around 7 locations (H farms) infected with HPAIV H5N8 in the Netherlands in 2016–2017 to densities around 21 non‐infected reference farms. Nine reference farms were in low‐lying water‐rich areas (R‐W) and 12 in higher non‐water‐rich areas (R‐NW). Average monthly numbers/km2 of Eurasian wigeons, tufted ducks, Anatidae (ducks, geese and swans) and Laridae (gulls) were calculated between September and April in rings of 0–1, 1–3, 3–6 and 6–10 km around the farms. Linear mixed model analyses showed generally higher bird densities for H and R‐W compared to R‐NW farms between October and March. This was most striking for Eurasian wigeons, with in peak month December 105 (95% CI:17–642) and 40 (7–214) times higher densities around H and R‐W farms, respectively, compared to R‐NW farms. Increased densities around H farms for Eurasian wigeons and Anatidae were more pronounced for distances up to 10 km compared to 0–1 km that mostly consists of the farm yard, which is an unattractive habitat for waterfowl. This distance effect was not observed in gulls, nor in tufted ducks that live on large open waterbodies which are unlikely to be within 0–1 km of farms. This study provides insights into spatio‐temporal density dynamics of HPAI high‐risk birds around farms and their associations with poultry outbreaks. The outcomes indicate that knowledge of environmental and ecological drivers for wild bird presence and abundance may facilitate identification of priority areas for surveillance and biosecurity measures and decisions on establishments of poultry farms to reduce risk of HPAI outbreaks
ESBL-Producing, Carbapenem- and Ciprofloxacin-Resistant Escherichia coli in Belgian and Dutch Broiler and Pig Farms: A Cross-Sectional and Cross-Border Study
Background. The use of antibiotics in food production selects for resistant bacteria and may cause a threat to human and animal health. Belgium and the Netherlands have one of the highest densities of broilers and pigs in Europe, making active monitoring of antibiotic use and resistance in this region vital. Objectives. This study aimed to quantify ESBL-producing (ESBL-E. coli), carbapenem- and ciprofloxacin-resistant (CiproR) Escherichia coli in animal feces on broiler and pig farms with a history of high antibiotic use in Belgium and the Netherlands. Methods. A total of 779 broiler and 817 pig fecal samples, collected from 29 conventional broiler and 31 multiplier pig farms in the cross-border region of Belgium and the Netherlands, were screened for the presence of antibiotic-resistant E. coli using selective culturing. Results. Carbapenem-resistant E. coli were not detected. ESBL-E. coli were remarkably more prevalent in samples from Belgian than Dutch farms. However, CiproR-E. coli were highly prevalent in broilers of both countries. The percentage of samples with ESBL- and CiproR-E. coli was lower in pig compared to poultry farms and varied between farms. No clear association with the on-farm antibiotic use in the year preceding sampling was observed. Multidrug resistance was frequently observed in samples from both countries, but ESBL-production in combination with ciprofloxacin resistance was higher in samples from Belgium. Conclusions. This study demonstrated marked differences in antibiotic resistance between countries, farms and within farms. The observed variation cannot be explained straightforward by prior quantity of antibiotic use suggesting that it results from more complex interactions that warrant further investigation
Development of the in vitro Cecal Chicken ALIMEntary tRact mOdel-2 to Study Microbiota Composition and Function
The digestive system of the chicken plays an important role in metabolism, immunity, and chicken health and production performance. The chicken ceca harbor a diverse microbial community and play a crucial role in the microbial fermentation and production of energy-rich short-chain fatty acids (SCFA). For humans, dogs, and piglets in vitro digestive system models have been developed and are used to study the microbiota composition and metabolism after intervention studies. For chickens, most research on the cecal microbiota has been performed in in vivo experiments or in static in vitro models that may not accurately resemble the in vivo situations. This paper introduces an optimized digestive system model that simulates the conditions in the ceca of the chicken, i.e., the Chicken ALIMEntary tRact mOdel-2 (CALIMERO-2). The system is based on the well-validated TNO in vitro model of the colon-2 (TIM-2) and is the first dynamic in vitro digestion model for chickens species. To validate this model, the pH, temperature, and different types of microbial feeding were compared and analyzed, to best mimic the conditions in the chicken ceca. The bacterial composition, as well as the metabolite production at 72 h, showed no significant difference between the different microbial feedings. Moreover, we compared the CALIMERO-2 digestive samples to the original inoculum and found some significant shifts in bacterial composition after the fermentation started. Over time the bacterial diversity increased and became more similar to the original inoculum. We can conclude that CALIMERO-2 is reproducible and can be used as a digestive system model for the chicken ceca, in which the microbial composition and activity can be maintained and shows similar results to the in vivo cecum. CALIMERO-2 can be used to study effects on composition and activity of the chicken cecum microbiota in response to in-feed interventions
The ADKAR® change management model for farmer profiling with regard to antimicrobial stewardship in livestock production
Antimicrobial stewardship in veterinary practice and animal production is important from a One Health perspective. The ADKAR® change management model is a well-known strategy to implement behavioral change in people and small businesses. The objective of this study was to adapt the existing ADKAR® change management model to enable herd veterinarians to profile farmers with regard to antimicrobial stewardship. Therefore, an antimicrobial stewardship related scoring scale was defined. Subsequently, ADKAR® profiles of 26 poultry and 28 pig farmers from Belgium and the Netherlands were determined. For 57% of the farmers, perception and/or motivation were expected to limit successful change. For 70% of the farmers, knowledge and for 52% of the farmers, a lack of ability were the limiting factor. The ADKAR® model proved useful for identifying the key elements that prevent successful behavioral change in farmers to reduce the use of antibiotics in farm animals
Coaching Belgian and Dutch Broiler Farmers Aimed at Antimicrobial Stewardship and Disease Prevention
A reduction in antimicrobial use (AMU) is needed to curb the increase in antimicrobial resistance in broiler production. Improvements in biosecurity can contribute to a lower incidence of disease and thereby lower the need for AMU. However, veterinary advice related to AMU reduction or biosecurity is often not complied with, and this has been linked to the attitudes of farmers. Behavior change promoted by coaching may facilitate uptake and compliance regarding veterinary advice. Thirty broiler farms in Belgium and the Netherlands with high AMU were included in this study for 13 months. For each farmer, the attitude towards AMU reduction was quantified using an adjusted Awareness, Desire, Knowledge, Ability, and Reinforcement (ADKAR®) change management model, and farm biosecurity was assessed with the Biocheck.UGent™ tool. Subsequently, farmers were coached to improve disease prevention and antimicrobial stewardship. After the individual coaching of farmers, there was a change in their attitudes regarding AMU, reflected by an increase in ADKAR® scores. Biosecurity levels improved by around 6% on average, and AMU was reduced by 7% on average without negative effects on performance parameters. Despite these improvements, no significant association could be found between higher ADKAR® scores and lower AMU. Further investigation into sociological models is needed as a tool to reduce AMU in livestock production