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.

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.

A Q study: exploring the purpose of transdisciplinary dairy advisory services in Denmark.

Background: Structural changes in dairy farming increase farm complexity, thereby inducing a need to combine herd health management, technological solutions, legislation, and human relations among farmers, farm workers, and advisors. This complex situation may require 'transdisciplinary advisory service', i.e.

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.

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.

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.