Exploring expert opinion on the practicality and effectiveness of biosecurity measures on dairy farms in the United Kingdom using choice modeling

Shortall, Orla; Green, Martin J.; Wapenaar, Wendela; Kaler, Jasmeet

doi:10.3168/jds.2016-11435

Cited by 40 publications

(43 citation statements)

References 49 publications

(4 reference statements)

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“…A similarly lack of implementation of biosecurity measures has been observed on dairy farms elsewhere in Europe (7,11,20). The implementation of biosecurity plans on dairy farms is voluntary in almost all countries, with the exception of larger dairy farms in Denmark (21).…”

Section: Discussionsupporting

confidence: 57%

A survey of biosecurity measures applied on dairy cattle farms in Spain

Villaamil¹,

Arnaiz²,

Allepuz

et al. 2019

Preprint

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32Attention to biosecurity has been highlighted as the most important measure to reduce 33 and prevent the introduction of diseases to farms. There is little published information 34 about the biosecurity of dairy cattle in Spain. We therefore aimed to assess and 35 characterize the current application of biosecurity measures on dairy cattle farms in 36 Spain, and relate these to bovine viral diarrhea and infectious bovine rhinotracheitis. 37From July 2017 to April 2018, data on biosecurity measures for 124 dairy herds were 38 collected using a questionnaire. We also assessed the sanitary status of these farms 39 (efficacy of measures implemented against both diseases using antibody ELISA. Data 40 were analyzed descriptively, and using multiple correspondence analysis and a two-step 41 cluster analysis. Measures to prevent disease introduction were often poorly 42 implemented. Three main clusters of farms were identified: Clusters 1 and 2 included 43 herds of small and intermediate sizes, respectively. These, particularly cluster 1, showed 44 the most deficiencies in the control of vehicles and visitors. However, individual 45 purchases usually involved low numbers of animals, especially in cluster 2, and animals 46 were tested for bovine viral diarrhea and infectious bovine rhinotracheitis at their places 47 of origin or on arrival at farms. Farms in clusters 1 and 2 were frequently under 48 voluntary control programs. Cluster 3 had the largest herd sizes, with somewhat better 49 biosecurity control of vehicles and visitors. However, farms in this cluster also 50 purchased the most animals, sometimes without testing, and hired external workers 51 most often. Farms in cluster 1 showed the best sanitary level, followed by clusters 2 and 52 3. Collecting data such as these is an important first step to identification of biosecurity 53 shortcomings, and to structuring of adequate follow-up to ensure that measures are 54 implemented correctly on farms in Spain. 4 55

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Section: Discussionsupporting

confidence: 57%

A survey of biosecurity measures applied on dairy cattle farms in Spain

Villaamil¹,

Arnaiz²,

Allepuz

et al. 2019

Preprint

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“…Many studies in the literature suggest that farmers will not continue to perform a practice if they do not perceive it to be effective, beneficial in terms of cost, or feasible in terms of both labor and cost ( 30 , 46 , 61 , 68 ). Moreover, these farmers' assessments are not fixed in time—milk price, for instance, may drop and practices currently feasible may suddenly become costly.…”

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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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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“…Separately, it is emphasized that the lower the cost of the animal, the better its economic return in the ratio of received and spent money. This statement is also followed by British researchers [19].…”

Section: Introductionmentioning

confidence: 79%

Automated system of optimal cattle selection for breeding (part 1)

Deshevykh¹,

Kovalchuk²

2019

Proceedings of the International Scientific and Practical Conference “Digital Agriculture - Development Strategy” (ISPC 2019)

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According to studies by various authors from countries with developing and underdeveloped economies, the main stumbling block in the field of animal husbandry is the lack of methods for selecting the optimal breed of cattle on the basis of ecological and geographical characteristics of the region. The need can be solved by developing a multiparameter automated system capable of taking into account exogenous and endogenous factors. The base of indicators to be processed takes into account biological and economically significant characteristics of animals, which in turn will allow to identify a balance between high productivity, economic feasibility, regional needs, quality of dairy products. No less important function of the program is the prediction of the specified characteristics, which will allow breeders to select the types of animals depending on the dynamics of indicators. The article considers: the experience of dairy cattle breeding in different countries of the world, as well as the risks specific to the industry; the method of determining the economically optimal for breeding cattle in different ecological and geographical conditions. The result of the research is the developed core of the information system, which contains a database, a set of algorithms, methods for determining the number of livestock of different breeds of cattle to cover the need for dairy products.

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Exploring expert opinion on the practicality and effectiveness of biosecurity measures on dairy farms in the United Kingdom using choice modeling

Cited by 40 publications

References 49 publications

A survey of biosecurity measures applied on dairy cattle farms in Spain

A survey of biosecurity measures applied on dairy cattle farms in Spain

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

Automated system of optimal cattle selection for breeding (part 1)

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