Modelling the effects of antimicrobial metaphylaxis and pen size on bovine respiratory disease in high and low risk fattening cattle

Contagious acquisition of antimicrobial resistance is critical for explaining emergence in western Canadian feedlots-insights from an agent-based modelling tool

Introduction

Antimicrobial resistance (AMR) is a growing threat to the efficacy of antimicrobials in humans and animals, including those used to control bovine respiratory disease (BRD) in high-risk calves entering western Canadian feedlots. Successful mitigation strategies require an improved understanding of the epidemiology of AMR. Specifically, the relative contributions of antimicrobial use (AMU) and contagious transmission to AMR emergence in animal populations are unknown.

Materials and methods

A stochastic, continuous-time agent-based model (ABM) was developed to explore the dynamics of population-level AMR in Mannheimia haemolytica in pens of high-risk cattle on a typical western Canadian feedlot. The model was directly informed and parameterized with proprietary data from partner veterinary practices and AMU/AMR surveillance data where possible. Hypotheses about how AMR emerges in the feedlot environment were represented by model configurations in which detectable AMR was impacted by (1) only selection arising from AMU; (2) only transmission between animals in the same pen; and (3) both AMU-linked selection and transmission. Automated calibration experiments were used to estimate unknown parameters of interest for select antimicrobial classes. Calibrated parameter values were used in a series of Monte Carlo experiments to generate simulated outputs at both the pen and feedlot levels. Key model outputs included the prevalence of AMR by class at multiple time points across the feeding period. This study compared the relative performances of these model configurations with respect to reproducing empirical AMR data.

Results

Across all antimicrobial classes of interest, model configurations which included the potential for contagious acquisition of AMR offered stronger fits to the empirical data. Notably, sensitivity analyses demonstrated that model outputs were more robust to changes in the assumptions underscoring AMU than to those affecting the likelihood of transmission.

Discussion

This study establishes a feedlot simulation tool that can be used to explore questions related to antimicrobial stewardship in the context of BRD management. The ABM stands out for its unique hierarchical depiction of AMR in a commercial feedlot and its grounding in robust epidemiological data. Future experiments will allow for both AMU-linked selection and transmission of AMR and can accommodate parameter modifications as required.

Determining the Effect of Varied Proportions of Cohort Administered Tulathromycin at Arrival on Nasopharyngeal Microbiota and Performance Characteristics in Yearling Steers in the First 56 Days on Feed

Metaphylaxis or treating the entire population of cattle at arrival with an antimicrobial has been studied extensively in the cattle industry; however, little information is available on the impacts of treating only a proportion of the population with antimicrobials at arrival. The study objective was to determine potential associations between the proportion of animals in a pen treated with antimicrobial therapy with pen performance and nasopharyngeal microbiome. Yearling steers (n = 160) were randomly allocated to study pens (n = 40) and pens were systematically randomized to one of two antimicrobial treatments (META: all four head received tulathromycin; MIXED: two of four head randomly selected to receive tulathromycin). The study was conducted in conjunction with an essential oil feeding trial. Deep nasal pharyngeal (DNP) swabs were collected from every steer at Days 0, 14, 28, and 56. All DNP swabs were individually cultured for Pasteurella multocida and Mannheimia haemolytica. Samples of DNA were extracted from DNP swabs, pooled by pen, and analyzed by metagenomic shotgun sequencing to compare nasopharyngeal microbiome composition and quantity of resistance genes between test groups. Neither antimicrobial nor essential oil treatment groups had any significant associations with performance or DNP microbiome. Sampling day was significantly associated with alpha and beta diversity at the species level. Shannon's diversity and Inverse Simpson diversity were significantly lower on Day 14 versus both Day 0 and Day 56. These data indicated a shift in microbial populations across study days; however, the microbiome diversity and relative abundance were not significantly different between antimicrobial treatment groups.

Harnessing uncertainty: A deep mechanistic approach for cautious diagnostic and forecast of Bovine Respiratory Disease

Bovine Respiratory Disease (BRD) is a prevalent infectious disease of respiratory tract in cattle, presenting challenges in accurate diagnosis and forecasting due to the complex interactions of multiple risk factors. Common methods, including mathematical epidemiological models and data-driven approaches such as machine learning models, face limitations such as difficult parameter estimation or the need for data across all potential outcomes, which is challenging given the scarcity and noise in observing BRD processes. In response to these challenges, we introduce a novel approach known as the Bayesian Deep Mechanistic method. This method couples a data-driven model with a mathematical epidemiological model while accounting for uncertainties within the processes. By utilising 265 lung ultrasound videos as sensor data from 163 animals across 9 farms in France, we trained a Bayesian deep learning model to predict the infection status (infected or non-infected) of an entire batch of 12 animals, also providing associated confidence levels. These predictions, coupled with their confidence levels, were used to filter out highly uncertain diagnoses and diffuse uncertainties into the parameterisation of a mathematical epidemiological model to forecast the progression of infected animals. Our findings highlight that considering the confidence levels (or uncertainties) of predictions enhances both the diagnosis and forecasting of BRD. Uncertainty-aware diagnosis reduced errors to 32 %, outperforming traditional automatic diagnosis. Forecast relying on veterinarian diagnoses, considered the most confident, had a 23 % error, whilst forecast taking into account diagnosis uncertainties had a close 27.2 % error. Building upon uncertainty-awareness, our future research could explore integrating multiple types of sensor data, such as video surveillance, audio recordings, and environmental parameters, to provide a comprehensive evaluation of animal health, employing multi-modal methods for processing this diverse data.

Effects of vaccination timing and target pathogens on performances and antimicrobial use in long-transported Charolais beef cattle from France to Italy - A retrospective study

Antimicrobial use (AMU) in the livestock sector is a major driver of antimicrobial resistance. Italian beef industry strongly relies on the import of young cattle from France, which are commingled in sorting facilities before transportation to Italy. Both commingling and transportation are stressors for animals and lead to higher risk of bovine respiratory disease (BRD), which in turn increases the risk of AMU. This study aimed to investigate how the timing of first BRD vaccination and the different vaccination target pathogens affect AMU and performance of young Charolais beef cattle imported from France to Italy. Information on animal performance, antimicrobial treatments, and vaccinations was available for 60,726 Charolais cattle belonging to 1449 batches in 33 Italian specialised fattening farms between January 2016 and December 2021. Antimicrobial use was estimated using the treatment incidence 100 adapted for Italy (TI100it). A mixed linear model was used to quantify the effects of the vaccination and the time of first administration on slaughter age, carcase weight, and average daily carcase gain. Similarly, a generalised linear mixed model was used to analyse the TI100it. The vaccination programme was usually applied the first day after the animals' arrival to the Italian fattening farms. Most animals were vaccinated with a polyvalent vaccine against infectious bovine rhinotracheitis (IBR), bovine parainfluenza type 3 virus (PI-3), bovine viral diarrhoea virus type 1 and 2 (BVDV), and bovine respiratory syncytial virus (BRSV). The most used class of antimicrobials to treat BRD were the macrolides, followed by aminoglycosides, amphenicols, tetracyclines, aminopenicillins, and fluoroquinolones. Animals that got vaccinated against any of the considered BRD pathogens upon arrival had significantly lower TI100it, greater average daily carcase gain, and reached slaughter age earlier than animals that got vaccinated later. Animals that received the vaccination against BVDV had lower TI100it and greater average daily carcase gain, and animals that received the vaccination against BRSV were younger at slaughter than unvaccinated animals. The vaccination against Mannheimia haemolytica significantly decreased the slaughter age and increased the carcase weight and average daily carcase gain, and the vaccination against PI-3 and Histophilus somni significantly increased the slaughter age. Thus, even if the vaccination programme is essential to tackle BRD, this practice is questionable if applied at arrival to the Italian fattening farms and it is advisable that the vaccination programme is planned before the commingling procedure in France.

Modeling the effects of farming practices on bovine respiratory disease in a multi-batch cattle fattening farm

Bovine Respiratory Disease (BRD) affects young bulls, causing animal welfare and health concerns as well as economical costs. BRD is caused by an array of viruses and bacteria and also by environmental and abiotic factors. How farming practices influence the spread of these causal pathogens remains unclear. Our goal was to assess the impact of zootechnical practices on the spread of three causal agents of BRD, namely the bovine respiratory syncytial virus (BRSV), Mannheimia haemolytica and Mycoplasma bovis. In that extent, we used an individual based stochastic mechanistic model monitoring risk factors, infectious processes, detection and treatment in a farm possibly featuring several batches simultaneously. The model was calibrated with three sets of parameters relative to each of the three pathogens using data extracted from literature. Separated batches were found to be more effective than a unique large one for reducing the spread of pathogens, especially for BRSV and M.bovis. Moreover, it was found that allocating high risk and low risk individuals into separated batches participated in reducing cumulative incidence, epidemic peaks and antimicrobial usage, especially for M. bovis. Theses findings rise interrogations on the optimal farming practices in order to limit BRD occurrence and pave the way to models featuring coinfections and collective treatments p { line-height: 115%; margin-bottom: 0.25 cm; background: transparent}a:link { color: #000080; text-decoration: underline}a.cjk:link { so-language: zxx}a.ctl:link { solanguage: zxx}.

Impact of Water Sources and Shared Fence Lines on Bovine Respiratory Disease Incidence in the First 45 Days on Feed

Bovine respiratory disease (BRD) is a frequent disease in feedlot cattle, but little is known on the role of pen housing conditions. The objective of this research is to use a retrospective analysis with data from 10 U.S. feedlots to determine potential associations between BRD risk during the first 45 days after arrival with pen-level management factors including the number of water sources, shared water sources, and shared fence lines. Generalized linear mixed models were used to evaluate associations between management factors, cattle demographics, and BRD incidence. The effect of shared water sources on BRD risk was modified by arrival weight and cohort size (p < 0.05). Cattle with two water sources had lower BRD morbidity (5.55% ± 0.98) compared to cattle with one water source (8.80% ± 1.50) when arrival weight was 227 kg to 272 kg, while there were few differences in heavier weight cattle. Cattle with two water sources had lower BRD morbidity (3.11% ± 0.56) compared to one water (5.50% ± 0.10) when cohort size was 100−175 head, but there were no BRD morbidity differences when bigger or smaller cohorts were evaluated. Shared fence lines and water sources were associated with BRD risk; however, no biologically meaningful results were identified. The number of water sources was associated with BRD risk, and effects were modified by cohort size and arrival weight.