Understanding how new evidence influences practitioners’ beliefs regarding dry cow therapy: A Bayesian approach using probabilistic elicitation

Higgins, Helen M.; Mouncey, J; Nanjiani, Ian; Cook, A. J. C.

doi:10.1016/j.prevetmed.2016.08.012

Cited by 5 publications

(7 citation statements)

References 25 publications

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“…Not relying on these models, Higgins et al investigated how veterinary clinicians make a treatment decision based on a result from the previous treatment action ( 77 ). The authors compared observed clinicians' treatment practices to those theoretically predicted assuming they logically update their beliefs using a Bayesian framework.…”

Section: Methods For Modeling Dynamic Human Behavioral Changesmentioning

confidence: 99%

“…Second, there seems to be large heterogeneity in veterinarians' advice and farmers' uptake of such advice. The former may be influenced by veterinarians' previous experience with specific measures (e.g., having positive or negative experiences with a specific vaccine), confidence in performing the intervention, knowledge of disease, and general attitudes toward disease ( 30 , 62 , 76 , 77 ). The latter may be influenced by relationship and trust developed between farmers and veterinarians, and it is known that veterinarians often provide an advice and treatment tailored to each farmer ( 62 , 78 ).…”

Section: Disease-related Factors Relevant To Farmers' Dynamic Behaviomentioning

confidence: 99%

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Modeling Dynamic Human Behavioral Changes in Animal Disease Models: Challenges and Opportunities for Addressing Bias

et al. 2018

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Over the past several decades, infectious disease modeling has become an essential tool for creating counterfactual scenarios that allow the effectiveness of different disease control policies to be evaluated prior to implementation in the real world. For livestock diseases, these models have become increasingly sophisticated as researchers have gained access to rich national livestock traceability databases, which enables inclusion of explicit spatial and temporal patterns in animal movements through network-based approaches. However, there are still many limitations in how we currently model animal disease dynamics. Critical among these is that many models make the assumption that human behaviors remain constant over time. As many studies have shown, livestock owners change their behaviors around trading, on-farm biosecurity, and disease management in response to complex factors such as increased awareness of disease risks, pressure to conform with social expectations, and the direct imposition of new national animal health regulations; all of which may significantly influence how a disease spreads within and between farms. Failing to account for these dynamics may produce a substantial layer of bias in infectious disease models, yet surprisingly little is currently known about the effects on model inferences. Here, we review the growing evidence on why these assumptions matter. We summarize the current knowledge about farmers' behavioral change in on-farm biosecurity and livestock trading practices and highlight the knowledge gaps that prohibit these behavioral changes from being incorporated into disease modeling frameworks. We suggest this knowledge gap can be filled only by more empirical longitudinal studies on farmers' behavioral change as well as theoretical modeling studies that can help to identify human behavioral changes that are important in disease transmission dynamics. Moreover, we contend it is time to shift our research approach: from modeling a single disease to modeling interactions between multiple diseases and from modeling a single farmer behavior to modeling interdependencies between multiple behaviors. In order to solve these challenges, there is a strong need for interdisciplinary collaboration across a wide range of fields including animal health, epidemiology, sociology, and animal welfare.

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Section: Methods For Modeling Dynamic Human Behavioral Changesmentioning

confidence: 99%

Section: Disease-related Factors Relevant To Farmers' Dynamic Behaviomentioning

confidence: 99%

Modeling Dynamic Human Behavioral Changes in Animal Disease Models: Challenges and Opportunities for Addressing Bias

et al. 2018

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“…Knowledge alone is not enough, as many mastitis‐related management practices that are generally considered to be important by experts are not widely used by farmers (Down et al., ). In recent years, evidence‐based decision‐making by veterinarians and communication of health‐management advice have become topics of study in their own right (Higgins et al., ; Jansen & Lam, ). Involvement of farmer discussion groups may play an important role in empowering farmers and promoting udder health through hygiene measures when reducing use of antimicrobials in lactating and dry cows (Bennedsgaard et al., ).…”

Section: Prevention Detection and Controlmentioning

confidence: 99%

An update on environmental mastitis: Challenging perceptions

Klaas

Zadoks

2017

Transbound Emerg Dis

197

144

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“…Changing veterinary perceptions and access to new information did not always follow a logical progression (Higgins et al, 2017b). Although new data supporting TSL use were accepted by most veterinarians, research conclusions close to their own beliefs were more readily accepted.…”

Section: Veterinariansmentioning

confidence: 96%

“…Although new data supporting TSL use were accepted by most veterinarians, research conclusions close to their own beliefs were more readily accepted. Consequently, new data on SDCT and TSL may contribute to feelings of uncertainty and decreased confidence in decision-making (Higgins et al, 2017b). Advocating SDCT instead of BDCT, the long-standing industry norm, is a considerable change from an udder health perspective; it may therefore take substantial evidence to convince some veterinarians to change their beliefs regarding SDCT.…”

Section: Veterinariansmentioning

confidence: 99%

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

McCubbin

Jong

Lam

et al. 2022

Journal of Dairy Science

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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.

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Understanding how new evidence influences practitioners’ beliefs regarding dry cow therapy: A Bayesian approach using probabilistic elicitation

Cited by 5 publications

References 25 publications

Modeling Dynamic Human Behavioral Changes in Animal Disease Models: Challenges and Opportunities for Addressing Bias

Modeling Dynamic Human Behavioral Changes in Animal Disease Models: Challenges and Opportunities for Addressing Bias

An update on environmental mastitis: Challenging perceptions

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

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