Using state space models to monitor and estimate the effects of interventions on treatment risk and milk yield in dairy farms.

Fast, flexible, and internally valid analytical tools are needed to evaluate the effects of management interventions made on dairy farms to support decisions about which interventions to continue or discontinue. The objective of this observational study was to demonstrate the use of state space models (SSM) to monitor and estimate the effect of interventions on 2 specific outcomes: a dynamic linear model (DLM) evaluating herd-level milk yield and a dynamic generalized linear model evaluating treatment risk in a pragmatic pretest/posttest design under field conditions. This demonstration study is part of a Danish common learning project that ran from March 2020 to May 2021 within the framework of veterinary herd health consultancy in relation to reducing antimicrobial use and improving herd health. Specific interventions for 2 commercial herds were suggested by 4 visiting farmers and were implemented during the project period. The intervention for herd 1 was the application of teat sealers, implemented in August 2020. For herd 2, the intervention was an adjustment of cubicles for cows of parity 2 and above, implemented from November 2020. A shift to an automatic milking system in October 2020 was also modeled as an intervention for herd 1 because the 2 interventions coincided. Data available from the Danish Cattle Database on obligatory registrations for individual cow movements and treatments, as well as test day information on milk yield, were used for model building and testing. Data from a 3-yr period before the project were used to calibrate the SSM to herd conditions, and data from the study period (March 2020 to May 2021) were used for monitoring and intervention testing based on application of the SSM. Herd bulk tank milk recordings were added to the data set during the study period to increase the precision of the estimates in the DLM. The developed SSM monitored herd-level milk yield and the overall probability of treatment throughout the study period in both herds. Furthermore, at the time of intervention, the SSM estimated the effect on herd-level milk yield and treatment risk associated with the implemented intervention in each herd. The SSM were used because they can be calibrated to herd conditions and they take into account herd dynamics and autocorrelation and provide standard deviations of estimates. For herd 1, the intervention effect of applying teat sealers was inconclusive with the current SSM application. For herd 2, no statistically significant changes in cow treatment risk or milk production were identified following the adjustment of cubicles. The use of SSM on observational data under field conditions shows that in this case, the interventions had a nonspecific onset of effect, were implemented during unstable times, and had varying coherence with the measured outcomes, making fully automated SSM analysis difficult. However, similar or expanded SSM with both monitoring and effect estimation functions could, if applied under the right conditions, serve as improved data-based decision support tools for farmers (and veterinarians) to minimize the risk of misinterpreting data due to confounding bias related to dynamics in dairy herds.

Danish cattle veterinarians' perspectives on antimicrobial use: Contextual and individual influencing factors.

The global risk for antimicrobial resistance (AMR) can be reduced by reducing antimicrobial use (AMU). Veterinarians are one of the key actors in relation to AMU in livestock, and understanding the dynamics of veterinary treatment and prescription is central to achieving AMU reduction. Veterinary AMU decisions are influenced by a complex pattern of both individual and contextual factors. In this study, we conducted semi-structured interviews with 16 Danish cattle veterinarians to investigate their perspectives on AMU and current practices in a national context with low use and extensive legal control. We found that personal experiences and emotions, rather than scientific evidence, guided some veterinarians when making AMU choices. Furthermore, less-experienced veterinarians felt pressure to prescribe according to colleagues' and farmers' preferences for certain antimicrobials. We found that changes in Danish legislation seemed to have introduced hesitancy and a lack of motivation within the veterinary profession, and that AMR was perceived as an abstract threat not applicable to the veterinarians' daily professional decision making. We concluded that the lack of field-generated research of local relevance nourished a culture in which AMU choices are built on personal experience rather than scientific evidence, which also diminished newly educated veterinarians' self-confidence in relation to their AMU choices. Future research should focus on developing locally relevant research on optimal AMU choices and AMR, and the implications of extensive legal control of AMU in livestock farming should be further investigated to find a balance on the path to reducing AMU.

The antimicrobial landscape as outlined by Danish dairy farmers.

Limiting antimicrobial use (AMU) in dairy farming is an important step toward reducing antimicrobial resistance (AMR). Therefore, it is relevant to understand dairy farmers' choices and the potential for change in relation to AMU, even in countries with low usage. Furthermore, there is an increasing recognition of the need to focus on both the individual farmer's behavior as well as the context surrounding and influencing the farmer's decisions in relation to AMU if the goal is further reduction. To date, no studies have taken into account both the individual farmer and their context in both conventional and organic dairy farms under Danish conditions. For this study, 15 Danish dairy farmers were interviewed using qualitative semi-structured research interviews, and the notion of landscape was used to describe the context of their AMU. We found that AMR was considered a distant element of the farmers' antimicrobial landscape. Daily challenges such as acutely diseased animals and poor housing conditions seemed more urgent and overruled the threat of AMR. We also found that interviewed farmers had differing opinions on farm management, partly shaped by changes in legislation and ways of farming over time. At one end of the scale, some organic farmers had rethought the current way of farming; keeping robust animals in a natural setting was expected to prevent disease. They were positive about legislation, and the numerous restrictions on AMU over time were thought to contribute to ensuring quality for consumers. At the other end of the scale, some conventional farmers perceived disease as something that should be controlled through treatment, and the currently eased legislation and intensification of farming have legitimatized AMU for this purpose, leading to an expectation among these farmers of certain rights to handle medicines themselves. These contrasting views might lead to inspiration and competition in terms of reducing AMU, as the farmers appeared to value the opinions of other farmers, and they were found to continuously assess each other. Through such ongoing assessment, pioneers of AMU reduction-whether organic or conventional-might motivate their colleagues to change their AMU. Future research should address the potential of experience- and attitude-sharing among farmers as motivation to reduce AMU.

Veterinary Herd Health Consultancy and Antimicrobial Use in Dairy Herds.

The globally increasing level of antimicrobial resistance affects both human and animal health, why it is necessary to identify ways to change our current use of antimicrobials. The veterinary herd health collaboration between veterinarians and dairy farmers provides a useful setting for changing antimicrobial use in livestock. However, farmers and veterinarians work in a complex agricultural setting influenced by socio-economic factors, which complicates their choices regarding antimicrobial usage. It is therefore necessary to be aware of the range of potential influencing factors and to integrate this knowledge in the relevant local settings. This manuscript presents a literature review of relevant factors relating to antimicrobial use within the veterinary herd health consultancy setting, including knowledge gaps of relevance for changing the use of antimicrobials. An enriched version of the framework of the Theory of Planned Behaviour was used to organise the literature review. We identified diverging attitudes on correct treatment practices and perceptions of antimicrobial resistance among veterinarians and farmers, influenced by individual risk perception as well as social norms. Furthermore, disagreements in terms of goal setting and in the frequency of herd visits in relation to herd health consultancy can negatively influence the collaboration and the intention to change antimicrobial use. Farmers and veterinarians emphasise the importance of legislation and the role of the dairy industry in changing antimicrobial use, but the relevance of specific factors depends on the country-specific context. Overall, farmers and veterinarians must communicate better to understand each other's perspectives and establish common goals within the collaboration if they are to work efficiently to reduce antimicrobial use. Farmers and veterinarians both requested changes in individual behaviour; however, they also called for national and structural solutions in terms of balanced legislation and the availability of better diagnostics to facilitate a change in antimicrobial use practices. These various paths to achieving the desired changes in antimicrobial use illustrate the need to bridge methodological research approaches of veterinary science and social sciences for a better understanding of our potential to change antimicrobial use within the dairy farm animal sector.

Veterinary decision making in relation to metritis--a qualitative approach to understand the background for variation and bias in veterinary medical records.

BACKGROUND: Results of analyses based on veterinary records of animal disease may be prone to variation and bias, because data collection for these registers relies on different observers in different settings as well as different treatment criteria. Understanding the human influence on data collection and the decisions related to this process may help veterinary and agricultural scientists motivate observers (veterinarians and farmers) to work more systematically, which may improve data quality. This study investigates qualitative relations between two types of records: 1) 'diagnostic data' as recordings of metritis scores and 2) 'intervention data' as recordings of medical treatment for metritis and the potential influence on quality of the data. METHODS: The study is based on observations in veterinary dairy practice combined with semi-structured research interviews of veterinarians working within a herd health concept where metritis diagnosis was described in detail. The observations and interviews were analysed by qualitative research methods to describe differences in the veterinarians' perceptions of metritis diagnosis (scores) and their own decisions related to diagnosis, treatment, and recording. RESULTS: The analysis demonstrates how data quality can be affected during the diagnostic procedures, as interaction occurs between diagnostics and decisions about medical treatments. Important findings were when scores lacked consistency within and between observers (variation) and when scores were adjusted to the treatment decision already made by the veterinarian (bias). The study further demonstrates that veterinarians made their decisions at 3 different levels of focus (cow, farm, population). Data quality was influenced by the veterinarians' perceptions of collection procedures, decision making and their different motivations to collect data systematically. CONCLUSION: Both variation and bias were introduced into the data because of veterinarians' different perceptions of and motivations for decision making. Acknowledgement of these findings by researchers, educational institutions and veterinarians in practice may stimulate an effort to improve the quality of field data, as well as raise awareness about the importance of including knowledge about human perceptions when interpreting studies based on field data. Both recognitions may increase the usefulness of both within-herd and between-herd epidemiological analyses.