Utility of an in-line somatic cell count sensor for selecting cows for dry-cow therapy.

Minimizing the use of antimicrobials at the end of lactation (dry cow therapy, DCT) requires categorization of cows as likely infected or uninfected. While microbiology is the gold standard for such categorization, the costs of doing so mean that indirect tests such as somatic cell count (SCC) are commonly used. An in-line SCC sensor (SenseHub In Line Somatic Cell Count, in-line SCC) is commercially available but its utility to differentiate cows eligible for dry cow therapy has not been assessed. This prospective diagnostic accuracy study was undertaken to define the sensitivity (Se) and specificity (Sp) of SenseHub SCC against cow-composite milk samples submitted for conventional microbiology. A secondary objective was to assess the utility of SenseHub SCC compared with the maximum (max DHI SCC) or last (last DHI SCC) SCC determined from cow-composite milk samples collected as part of routine herd production recording at monthly intervals throughout lactation. Cows (n = 1,544) from 4 spring-calving, predominantly pasture-fed dairy herds from 3 regions of New Zealand had cow-composite milk samples collected following aseptic teat end preparation immediately before or after the final milking of lactation. These samples were submitted for routine microbiology. The microbiology data from approximately half the cows (n = 770; training data set) were randomly selected after blocking for intramammary infection (IMI) status within herd and these data were used to determine the optimal predictor for indicating IMI from the in-line SCC data by maximizing the area under the receiver operator curve (AUC). The average of the in-line SCC over the final 12 weeks of lactation (in-line 12wSCC) was found to be the best predictor and used for further analyses. The Se and Sp of the in-line SCC for any IMI or for a major pathogen IMI (defined as presence of Staphylococcus aureus, Streptococcus dysgalactiae or Streptococcus uberis) was calculated using the test data set (n = 774). The AUC for the maximum and last DHI SCC were compared with that of the in-line 12wSCC. The cow-level prevalence of any IMI or a major IMI across the entire population was 50.6% and 14.2%, respectively. At a cutpoint of 150,000 cells/mL, Se and Sp of the in-line 12wSCC for any IMI was 0.68 (95%CI 0.64-0.72) and 0.71 (95% CI 0.65-76), respectively, and the Se and Sp for a major pathogen IMI was 0.89 (95%CI 0.82-0.95) and 0.51 (95% CI 0.47-0.55), respectively. The AUC for a major pathogen IMI was 0.82 (95% CI 0.79-0.86), 0.82 (95% CI 0.78-0.86) and 0.84 (95% CI 0.90-0.97) for in-line 12wSCC, max DHI SCC and last DHI SCC, respectively. These AUC did not differ and the AUC for the in-line 12wSCC was non-inferior to that of the last and maximum HT SCC (both P < 0.001). It was concluded that the in-line 12wSCC had an AUC, Se and Sp not different from DHI SCC data and hence this test has utility in selecting cows for different dry cow therapy treatments.

Analysis of Uncertainty and Sensitivity in Tailings Dam Breach-Runout Numerical Modelling.

Tailings dam breaches (TDBs) and subsequent flows can pose significant risk to public safety, the environment, and the economy. Numerical runout models are used to simulate potential tailings flows and understand their downstream impacts. Due to the complex nature of the breach-runout processes, the mobility and downstream impacts of these types of failures are highly uncertain. We applied the first-order second-moment (FOSM) methodology to a database of 11 back-analyzed historical tailings flows to evaluate uncertainties in TDB runout modelling and conducted a sensitivity analysis to identify key factors contributing to the variability of the HEC-RAS model output, including at different locations along the runout path. The results indicate that prioritizing resources toward advancements in estimating the values of primary contributors to the sensitivity of the selected model outputs is necessary for more reliable model results. We found that the total released volume is among the top contributors to the sensitivity of modelled inundation area and maximum flow depth, while surface roughness is among the top contributors to the sensitivity of modelled maximum flow velocity and flow front arrival time. However, the primary contributors to the sensitivity of the model outputs varied depending on the case study; therefore, the selection of appropriate rheological models and consideration of site-specific conditions are crucial for accurate predictions. The study proposes and demonstrates the FOSM methodology as an approximate probabilistic approach to model-based tailings flow runout prediction, which can help improve the accuracy of risk assessments and emergency response plans. Supplementary Information: The online version contains supplementary material available at 10.1007/s10230-024-00970-w.

Las roturas de presas de relaves (TDBs) y los flujos subsiguientes pueden suponer un riesgo significativo para la seguridad pública, el medio ambiente y la economía. Los modelos numéricos de desbordamiento se utilizan para simular posibles flujos de relaves y comprender su impacto aguas abajo. Debido a la naturaleza compleja de los procesos de rotura-desbordamiento, la movilidad y los impactos aguas abajo de este tipo de fallos tienen mucha incertidumbre. Se aplicó la metodología del segundo-momento de primer-orden (FOSM) a una base de datos de 11 flujos históricos de relaves analizados retrospectivamente para evaluar las incertidumbres en la modelización del desbordamiento de TDB y se realizó un análisis de sensibilidad para identificar los factores clave que contribuyen a la variabilidad de los resultados del modelo HEC-RAS, incluso en diferentes ubicaciones a lo largo de la trayectoria de fuga. Los resultados indican que es necesario priorizar los recursos hacia avances en la estimación de los valores de los principales contribuyentes a la sensibilidad de los resultados del modelo seleccionado para obtener resultados más fiables del modelo. El volumen total liberado se encuentra entre los principales contribuyentes a la sensibilidad del área de inundación modelizada y la profundidad máxima del flujo, mientras que la rugosidad de la superficie se encuentra entre los principales contribuyentes a la sensibilidad de la velocidad máxima del flujo modelizado y el tiempo de llegada del frente de flujo. Sin embargo, los principales factores que contribuyen a la sensibilidad de los resultados del modelo varían dependiendo del caso de estudio; por lo tanto, la selección de modelos reológicos apropiados y la consideración de las condiciones específicas del emplazamiento son cruciales para obtener predicciones precisas. El estudio propone y muestra la metodología FOSM como un enfoque probabilístico aproximado para la predicción de la extensión de flujos de relaves basada en modelos, que puede ayudar a mejorar la precisión de las evaluaciones de riesgos y los planes de respuesta a emergencias.

Invited review: Selective treatment of clinical mastitis in dairy cattle.

Treatment of clinical mastitis (CM) and use of antimicrobials for dry cow therapy are responsible for the majority of animal-defined daily doses of antimicrobial use (AMU) on dairy farms. However, advancements made in the last decade have enabled excluding nonsevere CM cases from antimicrobial treatment that have a high probability of cure without antimicrobials (no bacterial causes or gram-negative, excluding Klebsiella spp.) and cases with a low bacteriological cure rate (chronic cases). These advancements include availability of rapid diagnostic tests and improved udder health management practices, which reduced the incidence and infection pressure of contagious CM pathogens. This review informed an evidence-based protocol for selective CM treatment decisions based on a combination of rapid diagnostic test results, review of somatic cell count and CM records, and elucidated consequences in terms of udder health, AMU, and farm economics. Relatively fast identification of the causative agent is the most important factor in selective CM treatment protocols. Many reported studies did not indicate detrimental udder health consequences (e.g., reduced clinical or bacteriological cures, increased somatic cell count, increased culling rate, or increased recurrence of CM later in lactation) after initiating selective CM treatment protocols using on-farm testing. The magnitude of AMU reduction following a selective CM treatment protocol implementation depended on the causal pathogen distribution and protocol characteristics. Uptake of selective treatment of nonsevere CM cases differs across regions and is dependent on management systems and adoption of udder health programs. No economic losses or animal welfare issues are expected when adopting a selective versus blanket CM treatment protocol. Therefore, selective CM treatment of nonsevere cases can be a practical tool to aid AMU reduction on dairy farms.

Selective treatment of nonsevere clinical mastitis does not adversely affect cure, somatic cell count, milk yield, recurrence, or culling: A systematic review and meta-analysis.

Treatment of clinical mastitis (CM) contributes to antimicrobial use on dairy farms. Selective treatment of CM based on bacterial diagnosis can reduce antimicrobial use, as not all cases of CM will benefit from antimicrobial treatment, e.g., mild and moderate gram-negative infections. However, impacts of selective CM treatment on udder health and culling are not fully understood. A systematic search identified 13 studies that compared selective versus blanket CM treatment protocols. Reported outcomes were synthesized with random-effects models and presented as risk ratios or mean differences. Selective CM treatment protocol was not inferior to blanket CM treatment protocol for the outcome bacteriological cure. Noninferiority margins could not be established for the outcomes clinical cure, new intramammary infection, somatic cell count, milk yield, recurrence, or culling. However, no differences were detected between selective and blanket CM treatment protocols using traditional analyses, apart from a not clinically relevant increase in interval from treatment to clinical cure (0.4 d) in the selective group and higher proportion of clinical cure at 14 d in the selective group. The latter occurred in studies co-administering nonsteroidal anti-inflammatories only in the selective group. Bias could not be ruled out in most studies due to suboptimal randomization, although this would likely only affect subjective outcomes such as clinical cure. Hence, findings were supported by a high or moderate certainty of evidence for all outcome measures except clinical cure. In conclusion, this review supported the assertion that a selective CM treatment protocol can be adopted without adversely influencing bacteriological and clinical cure, somatic cell count, milk yield, and incidence of recurrence or culling.

Invited review: Selective use of antimicrobials in dairy cattle at drying-off.

Administering intramammary antimicrobials to all mammary quarters of dairy cows at drying-off [i.e., blanket dry cow therapy (BDCT)] has been a mainstay of mastitis prevention and control. However, as udder health has considerably improved over recent decades with reductions in intramammary infection prevalence at drying-off and the introduction of teat sealants, BDCT may no longer be necessary on all dairy farms, thereby supporting antimicrobial stewardship efforts. This narrative review summarizes available literature regarding current dry cow therapy practices and associated impacts of selective dry cow therapy (SDCT) on udder health, milk production, economics, antimicrobial use, and antimicrobial resistance. Various methods to identify infections at drying-off that could benefit from antimicrobial treatment are described for selecting cows or mammary quarters for treatment, including utilizing somatic cell count thresholds, pathogen identification, previous clinical mastitis history, or a combination of criteria. Selection methods may be enacted at the herd, cow, or quarter levels. Producers' and veterinarians' motivations for antimicrobial use are discussed. Based on review findings, SDCT can be adopted without negative consequences for udder health and milk production, and concurrent teat sealant use is recommended, especially in udder quarters receiving no intramammary antimicrobials. Furthermore, herd selection should be considered for SDCT implementation in addition to cow or quarter selection, as BDCT may still be temporarily necessary in some herds for optimal mastitis control. Costs and benefits of SDCT vary among herds, whereas impacts on antimicrobial resistance remain unclear. In summary, SDCT is a viable management option for maintaining udder health and milk production while improving antimicrobial stewardship in the dairy industry.

Streptococcus bovimastitidis sp. nov., isolated from a dairy cow with mastitis.

Here we describe a new species of the genus Streptococcus that was isolated from a dairy cow with mastitis in New Zealand. Strain NZ1587T was Gram-positive, coccus-shaped and arranged as chains, catalase and coagulase negative, γ-haemolytic and negative for Lancefield carbohydrates (A-D, F and G). The 16S rRNA sequence did not match sequences in the NCBI 16S rRNA or GreenGenes databases. Taxonomic classification of strain NZ1587T was investigated using 16S rRNA and core genome phylogeny, genome-wide average nucleotide identity (ANI) and predicted DNA-DNA hybridisation (DDH) analyses. Phylogeny based on 16S rRNA was unable to resolve the taxonomic position of strain NZ1587T, however NZ1587T shared 99.4 % identity at the 16S rRNA level with a distinct branch of S. pseudoporcinus. Importantly, core genome phylogeny demonstrated that NZ1587T grouped amongst the 'pyogenic' streptococcal species and formed a distinct branch supported by a 100 % bootstrap value. In addition, average nucleotide identity and inferred DNA-DNA hybridisation analyses showed that NZ1587T represents a novel species. Biochemical profiling using the rapid ID 32 strep identification test enabled differentiation of strain NZ1587T from closely related streptococcal species. In conclusion, strain NZ1587T can be classified as a novel species, and we propose a novel taxon named Streptococcus bovimastitidis sp. nov.; the type strain is NZ1587T. NZ1587T has been deposited in the Culture Collection University of Gothenburg (CCUG 69277T) and the Belgian Co-ordinated Collections of Micro-organisms/LMG (LMG 29747).

Addition of meloxicam to the treatment of bovine clinical mastitis results in a net economic benefit to the dairy farmer.

Recently, it has been shown that the addition of meloxicam to standard antimicrobial therapy for clinical mastitis (CM) improves the conception rate of dairy cows contracting CM in the first 120 d in milk. The objective of our study was to assess whether this improved reproduction through additional treatment with meloxicam would result in a positive net economic benefit for the farmer. We developed a stochastic bio-economic simulation model, in which a dairy cow with CM in the first 120 d in milk was simulated. Two scenarios were simulated in which CM cases were treated with meloxicam in conjunction with antimicrobial therapy or with antimicrobial therapy alone. The scenarios differed for conception rates (31% with meloxicam or 21% without meloxicam) and for the cost of CM treatment. Sensitivity analyses were undertaken for the biological and economic components of the model to assess the effects of a wide range of inputs on inferences about the cost effectiveness of meloxicam treatment. Model results showed an average net economic benefit of €42 per CM case per year in favor of the meloxicam scenario. Cows in the no-meloxicam treatment scenario had higher returns on milk production, lower costs upon calving, and reduced costs of treatment. However, these did not outweigh the savings associated with lower feed intake, reduced number of inseminations, and the reduced culling rate. The net economic benefit favoring meloxicam therapy was a consequence of the better reproductive performance in the meloxicam scenario in which cows had a shorter calving to conception interval (132 vs. 143 d), a shorter intercalving interval (405 vs. 416 d), and fewer inseminations per conception (2.9 vs. 3.7) compared with cows in the no-meloxicam treatment scenario. This resulted in a shorter lactation, hence a lower lactational milk production (8,441 vs. 8,517 kg per lactation) with lower feeding costs in the meloxicam group. A lower culling rate (12 vs. 25%) resulted in lower replacement costs in the meloxicam treatment scenario. All of the scenarios evaluated in the sensitivity analyses favored meloxicam treatment over no meloxicam. This study demonstrated that improvements in conception rate achieved by the use of meloxicam, as additional therapy for mild to moderate CM in the first 120 d in milk, have positive economic benefits. This inference remained true over a wide range of technical and economic inputs, demonstrating that use of meloxicam is likely to be cost effective across many production systems.

Identification of an immune modulation locus utilising a bovine mammary gland infection challenge model.

Inflammation of the mammary gland following bacterial infection, commonly known as mastitis, affects all mammalian species. Although the aetiology and epidemiology of mastitis in the dairy cow are well described, the genetic factors mediating resistance to mammary gland infection are not well known, due in part to the difficulty in obtaining robust phenotypic information from sufficiently large numbers of individuals. To address this problem, an experimental mammary gland infection experiment was undertaken, using a Friesian-Jersey cross breed F2 herd. A total of 604 animals received an intramammary infusion of Streptococcus uberis in one gland, and the clinical response over 13 milkings was used for linkage mapping and genome-wide association analysis. A quantitative trait locus (QTL) was detected on bovine chromosome 11 for clinical mastitis status using micro-satellite and Affymetrix 10 K SNP markers, and then exome and genome sequence data used from the six F1 sires of the experimental animals to examine this region in more detail. A total of 485 sequence variants were typed in the QTL interval, and association mapping using these and an additional 37 986 genome-wide markers from the Illumina SNP50 bovine SNP panel revealed association with markers encompassing the interleukin-1 gene cluster locus. This study highlights a region on bovine chromosome 11, consistent with earlier studies, as conferring resistance to experimentally induced mammary gland infection, and newly prioritises the IL1 gene cluster for further analysis in genetic resistance to mastitis.

Effect of exosomes from plasma of dairy cows with or without an infected uterus on prostaglandin production by endometrial cell lines.

A contributing factor to declining fertility in dairy cows is an activated inflammatory system associated with uterine infection. Detecting uterine disease using biomarkers may allow earlier diagnosis and intervention with resultant improvements in fertility. Exosomes are known to participate in intercellular communication, paracrine, and endocrine signaling. Exosomes carry a cargo of proteins, lipids, and nucleic acids that represent specific cellular sources. Prostaglandins are lipids that are critical determinants of bovine fertility. In this study exosomes were isolated from the plasma of cows before (d 0) and during (d 10) the study in healthy animals or those with an induced uterine infection in a 2 × 2 factorial design. Exosomes were characterized for size and number (nanoparticle tracking analysis), exosomal marker expression (Western blot), and morphology (transmission electron microscopy). No significant differences were observed in exosome size or number. The abundance of exosome-enriched markers was confirmed in noninfected and infected animals. Transmission electron microscopy confirmed the morphology of the exosomes. These exosomes were co-incubated with bovine endometrial epithelial and stromal cells. Exosomes from d-10-infected animal plasma decreased PGF2α production in endometrial epithelial but not stromal cells. For future research, the identification of effectors in the cargo may provide a useful basis for early diagnosis of uterine infection using an exosomal characterization approach.

Modulation of the immune system during postpartum uterine inflammation.

Postpartum uterine inflammation (endometritis) in the dairy cow is associated with lower fertility at both the time of infection and after the inflammation has resolved. We hypothesized that aberrant DNA methylation may be involved in the subfertility associated with uterine inflammation. The objective of this study was to characterize genome-wide DNA methylation and gene expression in the endometrium of dairy cows with subclinical endometritis (SCE). Endometrial tissues were obtained at 29 days postpartum (n = 12), and microarrays were used to characterize transcription and DNA methylation. Analyses revealed 1,856 probes differentially expressed in animals with SCE (n = 6) compared with controls (CON, n = 6, P < 0.05, Storey Multiple testing correction) and 2,976 probes with significant correlation between gene expression and bacteriology score. No significant associations among DNA methylation and gene expression were detected. Analysis of transcription data using the Database for Annotation, Visualization, and Integrated Discovery and Gene Set Enrichment Analysis identified several pathways and processes enriched in SCE cows, with the majority related to the immune response. Furthermore, the top ontology terms enriched in genes that had expression data correlated to bacteriology score were: Defense response, inflammatory response, and innate immune response. Gene expression profiles in cows with subclinical endometritis in this study indicate that the immune response is activated, potentially resulting in a local proinflammatory environment in the uterus. If this period of inflammation is prolonged it could result in tissue damage or failure to complete involution of the uterus, which may create a suboptimal environment for future pregnancy.

Minimum inhibitory concentrations of selected antimicrobials against Escherichia coli and Trueperella pyogenes of bovine uterine origin.

Minimum inhibitory concentrations (MIC) of 9 antimicrobials for isolates of 2 common bovine intrauterine bacterial pathogens, Escherichia coli (n=209) and Trueperella pyogenes (n=35), were determined using broth microdilution methodology. The isolates were recovered from dairy cows from 7 herds postpartum using the cytobrush technique. The pathogens were initially identified using phenotypic techniques. Additionally, PCR was used to confirm the identity of T. pyogenes isolates and to categorize the E. coli isolates into phylogenetic groups A, B1, B2, and D. Minimum inhibitory concentrations in excess of published cut-points or bimodal distributions of MIC indicated potential antimicrobial resistance to ampicillin, cefuroxime, cephapirin, and oxytetracycline for E. coli, and to oxytetracycline for T. pyogenes. Of the antimicrobials tested, ticarcillin/clavulanic acid, ceftiofur, and enrofloxacin had the lowest MIC for these 2 pathogens. Differences in MIC of some antimicrobials were found between herds, age, breeds, and E. coli phylogenetic groups. Isolation of E. coli with an MIC ≥8µg/mL of oxytetracycline at 23d postpartum was associated with a lower probability of pregnancy within 6wk of commencement of breeding compared with those isolates with an MIC <8µg/mL (relative risk=0.66). Minimum inhibitory concentrations for uterine pathogens were determined for isolates from New Zealand dairy cows. However, in the absence of either epidemiological or clinical interpretive criteria, the interpretation of these MIC remains unclear. Further studies are required to define interpretative criteria, including determination of pharmacokinetic and pharmacodynamic profiles for antimicrobials.

An Assessment of the Epidemiology and Herd-Level Impact of the Fractured Humerus Epidemic in New Zealand Dairy Cattle, 2007-2015: Results from Four Studies.

A multi-method approach integrating data from four independent sources was used to describe some key features of the epidemiology and estimate the herd and within-herd incidence of fractured humeri in New Zealand dairy cattle for the period 2007-2015. The first dataset was from a national case series where cases of humeral fractures in dairy cattle were identified by veterinarians across New Zealand between the 2007/2008 and 2011/2012 lactation seasons. The second dataset was from a pet food company based in the Waikato region, which collated the number of casualty first- and second-lactation cows found to have a fractured humerus post-slaughter in the 2014/2015 lactation season, and the third dataset was a case series conducted by veterinarians employed in a Waikato veterinary business, also from the 2014/2015 lactation season. For the final dataset, 505 randomly selected New Zealand dairy farmers completed a phone survey on the incidence of non-responsive, non-weight-bearing forelimb lameness in first- and second-lactation cows in the 2014/2015 lactation season. Using the telephone survey results, the within-herd and herd-level incidence of cases for first- and second-lactation dairy animals was calculated. The national case series reported 149 cases of humeral fractures in 22 dairy herds; the pet food case series identified 61 cases from 41 farms; and the practice-based case series found 14 cases from 10 farms. Humeral fractures exclusively affected first- and second-lactation dairy cows and had a peak incidence between calving and early mating. The national telephone survey found that non-weight-bearing forelimb lameness requiring euthanasia of first- or second-lactation cows occurred in 11.7% of herds, with a mean within-herd incidence of 2.6% for first lactation cows and 2.8% for second-lactation cows for affected herds. These combined datasets demonstrate that humeral fractures in young, lactating dairy cattle are more common than previously suspected and that they occur nationally and over multiple years on some farms. Further work on this condition is urgently required in New Zealand to establish cost-effective management practices that will reduce unnecessary animal suffering and waste.

A scoping review of antimicrobial resistance in the Australian dairy cattle industry.

INTRODUCTION: Quantification of antimicrobial resistance (AMR) is beneficial to inform policies and direct prudent antimicrobial use. AIM: This study aimed to assess the current published evidence of AMR from passive and active ad hoc surveillance activities within the Australian dairy cattle industry. METHODS: Following a scoping review framework 373 articles published before January 2023 were retrieved using the keyword search function from two online databases (PubMed® and Web of Science™ Core Collection). The duplicate articles were removed and the title, abstract, and full text of the remaining articles were reviewed following the study objectives and inclusion criteria (location, subject/theme, and data). Data from the remaining articles were extracted, summarised, interpreted and the study quality assessed using the Grades of Recommendations, Assessment, Development, and Evaluation guidelines. RESULTS: A total of 29 articles dating from the 1960 s until 2022 were identified to meet the study criteria (passive: n = 15; active: n = 14). Study characteristics such as sampling type, sampling method, and AMR assessment were all common characteristics from both passive and active surveillance articles, being milk samples, individual sampling, and phenotypic assessment respectively. Passive surveillance articles had a wider range in both the type of bacteria and the number of antimicrobials investigated, while active surveillance articles included a higher number of bacterial isolates and sampling from healthy populations. There was an overall low level of clinical AMR across all articles. Higher prevalence of non-wildtype Escherichia coli, Salmonella spp., and Staphylococcus spp., although limited in data, was suggested for commonly used Australian veterinary antimicrobials for these bacteria. The prevalence of phenotypic AMR varied due to the health and age status of the sampled animals. The articles reviewed in this study suggest the prevalence of AMR genes was higher for commonly used antimicrobials, although genes were not always related to the phenotypic AMR profile. CONCLUSIONS: Published evidence of AMR in the Australian dairy cattle industry is limited as demonstrated by only 29 articles included in this review following selection criteria screening. However, collectively these articles provide insight on industry AMR prevalence. For example, the suggestion of non-wildtype bacteria within the Australian dairy cattle indicating a risk of emerging or increasing industry AMR. Therefore, further surveillance is required to monitor the development of future AMR risk within the industry. Additionally, evidence suggesting that animals varying in health and age differ in prevalence of AMR imply a requirement for further research into animal population demographics to reduce potential bias in data collated in both national and global surveillance activities.

Steps towards operationalizing One Health approaches.

One Health recognizes the health of humans, agriculture, wildlife, and the environment are interrelated. The concept has been embraced by international health and environmental authorities such as WHO, WOAH, FAO, and UNEP, but One Health approaches have been more practiced by researchers than national or international authorities. To identify priorities for operationalizing One Health beyond research contexts, we conducted 41 semi-structured interviews with professionals across One Health sectors (public health, environment, agriculture, wildlife) and institutional contexts, who focus on national-scale and international applications. We identify important challenges, solutions, and priorities for delivering the One Health agenda through government action. Participants said One Health has made progress with motivating stakeholders to attempt One Health approaches, but achieving implementation needs more guidance (action plans for how to leverage or change current government infrastructure to accommodate cross-sector policy and strategic mission planning) and facilitation (behavioral change, dedicated personnel, new training model).

Molecular epidemiology of mastitis pathogens of dairy cattle and comparative relevance to humans.

Mastitis, inflammation of the mammary gland, can be caused by a wide range of organisms, including gram-negative and gram-positive bacteria, mycoplasmas and algae. Many microbial species that are common causes of bovine mastitis, such as Escherichia coli, Klebsiella pneumoniae, Streptococcus agalactiae and Staphylococcus aureus also occur as commensals or pathogens of humans whereas other causative species, such as Streptococcus uberis, Streptococcus dysgalactiae subsp. dysgalactiae or Staphylococcus chromogenes, are almost exclusively found in animals. A wide range of molecular typing methods have been used in the past two decades to investigate the epidemiology of bovine mastitis at the subspecies level. These include comparative typing methods that are based on electrophoretic banding patterns, library typing methods that are based on the sequence of selected genes, virulence gene arrays and whole genome sequencing projects. The strain distribution of mastitis pathogens has been investigated within individual animals and across animals, herds, countries and host species, with consideration of the mammary gland, other animal or human body sites, and environmental sources. Molecular epidemiological studies have contributed considerably to our understanding of sources, transmission routes, and prognosis for many bovine mastitis pathogens and to our understanding of mechanisms of host-adaptation and disease causation. In this review, we summarize knowledge gleaned from two decades of molecular epidemiological studies of mastitis pathogens in dairy cattle and discuss aspects of comparative relevance to human medicine.

Individual risk evaluation for landslides: key details.

Risk-taking is an essential part of life. As individuals, we evaluate risks intuitively and often subconsciously by comparing the perceived risks with expected benefits. We do this so commonly that it passes unnoticed, like when we decide to speed home from work or go for a swim. The comparison changes, however, when one entity (such as a government) imposes a risk evaluation on another person. For example, in a quantitative risk management framework, the estimated risk is compared with a tolerable risk threshold to decide if the person is 'safe enough'. Landslide risk management methods are well established and there is consensus on tolerable life-loss risk thresholds. However, beneath this consensus lie several key details that are explored by this article, along with suggestions for refinement. Specifically, we suggest using the risk unit, micromort (one micromort equals a life loss risk of 1 in 1 million), in describing risk estimates and thresholds, to improve risk communication. For risk estimation, we provide guidance for defining and combining landslide scenarios and for recognizing where unquantified risk from low-probability/high-consequence scenarios ought to inform risk management decisions. For risk tolerance thresholds, we highlight the pitfalls of selecting unachievably low thresholds and suggest that there is no single universal threshold. Additionally, we argue that gross disproportion between costs and benefits of further risk reduction, which is integral to the As Low As Reasonably Practicable (ALARP) principle, is a commonly unachievable and counter-productive condition for risk tolerance, and other conditions centered on proportionality often apply. Finally, we provide several figures that can be used as risk communication tools, to provide context for risk estimates and risk tolerance thresholds when these values are reported to decision makers and the public.

Probabilistic prediction of rock avalanche runout using a numerical model.

Rock avalanches can be a significant hazard to communities located in mountainous areas. Probabilistic predictions of the 3D impact area of these events are crucial for assessing rock avalanche risk. Semi-empirical, calibration-based numerical runout models are one tool that can be used to make these predictions. When doing so, uncertainties resulting from both noisy calibration data and uncertain governing movement mechanism(s) must be accounted for. In this paper, a back-analysis of a database of 31 rock avalanche case histories is used to assess both of these sources of uncertainty. It is found that forecasting results are dominated by uncertainties associated with the bulk basal resistance of the path material. A method to account for both calibration and mechanistic uncertainty is provided, and this method is evaluated using pseudo-forecasts of two case histories. These pseudo-forecasts show that inclusion of expert judgement when assessing the bulk basal resistance along the path can reduce mechanistic uncertainty and result in more precise predictions of rock avalanche runout. Supplementary Information: The online version contains supplementary material available at 10.1007/s10346-022-01939-y.

Therapy of Subclinical Mastitis during Lactation.

This study tested the hypothesis that increasing the duration and/or frequency of antimicrobial treatment of subclinical mastitis would result in a higher bacteriological cure rate. Glands with a positive California mastitis test (CMT) from cows with an elevated somatic cell count (>500,000 cells/mL) that had an intramammary infection were randomly assigned at cow level to no treatment (Control; n = 80 glands), intramammary infusion of 200 mg cloxacillin sodium on three occasions at 48 h intervals (3 × 48 h; n = 273 glands), five occasions at 24 h intervals (5 × 24 h; n = 279 glands), or on five occasions at 48 h intervals (5 × 48 h; n = 72 glands). Glands were resampled at 21 (±3) and 28 (±3) days after initiation of treatment. The gland-level cure rate for any pathogen was 5/80 (6.2%), 139/173 (49.8%), 172/297 (61.6%) and 58/72 (80.6%) for Control, 3 × 48 h, 5 × 24 h and 5 × 48 h, respectively. The cure rate for major pathogens (defined as Staphylococcus aureus or Streptococcus spp.) was 4/52 (7.7%), 84/197 (42.6%), 96/183 (52.5%) and 36/48 (75%) for Control, 3 × 48 h, 5 × 24 h and 5 × 48 h, respectively. We conclude that treatment was superior to no treatment, and bacteriological cure rate was higher with the 5 × 24 h protocol than for the 3 × 48 h protocol and was higher with the 5 × 48 h than the 5 × 24 h protocol.

Antimicrobial use on Australian dairy cattle farms - A survey of veterinarians.

AIMS: The aims of this study were to determine antimicrobial prescription patterns and the factors affecting antimicrobial selection amongst Australian dairy veterinarians. METHODS: A structured questionnaire was administered to Australian dairy cattle veterinarians using the Qualtrics online survey platform. Questions focused on their (1) demographics; (2) opinions surrounding antimicrobial use, resistance, and stewardship; (3) decision-making drivers of both prescription and selection of commonly prescribed antimicrobials; (4) awareness on the guidelines for antimicrobial usage and sources of information concerning antimicrobials. KEY RESULTS: A total of 135 responses (14.1% response rate) from all eight dairying regions in Australia were received. The attitudes, perceptions, and concerns of dairy veterinarians towards antimicrobials indicated a high agreement regarding label indications (96%), consequences of off-label prescription (95%), and the presence of an antimicrobial resistance (AMR) risk (73%), when prescribing antibiotics. A four-dimensional categorical principal components analysis (CATPCA) model indicated most of the variation in opinion was due to AMR risk, trade-offs, prescription concerns and active substance concerns. The first active substance most dairy veterinarians chose for a scenario involving mastitis and dry cow therapy (DCT) treatment was cloxacillin. Decision-making drivers for antimicrobial choice when providing advice regarding the supply of antimicrobials for mastitis and DCT treatment were predominately clinical factors; however, diagnostics were rarely used in determining antimicrobial choice due to cost of implementation, diagnostic accuracy (sensitivity, specificity), and benefit issues. Non-clinical decision-making drivers included the perception of practicality for Australian Veterinary Association (AVA) prescription guidelines, opinions surrounding AMR risk and prescription concerns, consideration of Expert Advisory Group on Antimicrobial Resistance (EAGAR) scores, number of years worked with dairy farms, and the number of dairy farms they regularly consult for. When available at the practice, prescription policies were considered to impact on animal welfare outcomes and on the probability of AMR emergence. The major information sources influencing decision making on antimicrobial prescription for the Australian dairy veterinarians were clinical experience (93%) and product labels (81%). CONCLUSIONS: Australian dairy veterinarians are generally aware of the risk of resistance to antimicrobials and the need for stewardship, with clinical factors having the most impact on antimicrobial prescription. However, non-clinical factors incorporating awareness of guidelines and their attitudes on antimicrobial resistance risk and prescription concerns impact on the choice and prescription of antimicrobials. IMPLICATIONS: The development of prescription policy and guidelines, alongside effective communicative extension programs to increase veterinarian uptake, provides an avenue to mitigate AMR risk in Australian dairy cattle.

A benchmarking study of four numerical runout models for the simulation of tailings flows.

Numerical runout models are important tools for predicting the potential downstream impacts of tailings dam breaches that generate tailings flows, which is a crucial step in emergency preparedness and planning, and risk management. Most existing runout models were originally developed for the analysis of water floods or flow-like landslides (e.g. debris flows). In this study, we back-analyze two well-documented historical tailings dam breaches (1985 Stava, Italy and 1994 Merriespruit, South Africa) using four numerical models (DAN3D, MADflow, FLO-2D and FLOW-3D). The main objective of this multi-case, multi-model benchmarking exercise is to identify collective opportunities to adapt these types of models and associated modelling methods to tailings dam breach runout applications. Comparing best-fit simulation results, we find that all four models are capable of reproducing the bulk behaviour of the real events; however, (i) multiple sets of rheological parameters may produce very similar output results, (ii) the best-fit input parameter combinations are non-transferable between models and inconsistent with independently measured rheological properties of stored tailings, and (iii) choosing an appropriate set requires sufficient understanding of material rheological properties and expert judgment. Using a systematic sensitivity analysis with the First-Order Second-Moment (FOSM) approach, we also find that each model is sensitive to different input parameters, although the total released volume is among the main high-influence parameters in every scenario. We conclude that more case study back-analyses are needed to enhance our understanding of these sensitivities and develop better guidance on the use of these types of numerical models for tailings flow runout prediction.