Applying Bayesian network modelling to understand the links between on-farm biosecurity practice during the 2007 equine influenza outbreak and horse managers' perceptions of a subsequent outbreak

Willingness to adopt personal biosecurity strategies on thoroughbred breeding farms: Findings from a multi-site pilot study in Australia's Hunter Valley

There are almost 9,500 full-time employees in Australia's thoroughbred horse breeding industry. During foaling, they can be exposed to bodily fluids and mucous membranes which may present risks for zoonotic disease. These risks can be mitigated through personal biosecurity strategies. The aim of this study was to identify which personal biosecurity strategies were more or less likely to be adopted by workers. Seventeen participants representing 14 thoroughbred breeding farms and three equine veterinary practices in Australia's largest thoroughbred breeding region trialed up to 16 stakeholder-nominated personal biosecurity strategies over the 2021 foaling season. The strategies encompassed personal protective equipment (PPE), zoonotic disease awareness, policies and protocols, supportive environments, and leadership. Strategy adoption was monitored through three repeated self-audit surveys designed around the Transtheoretical Model of change (TTM) and findings were reviewed in exit interviews. For all survey waves in aggregate, 13 strategies were practiced by at least 50.0% of participants. Participants were most likely to use a ready-made foaling box (98.0%), communicate the message that PPE usage is a personal responsibility (94.1%) and use ready-made PPE kits (88.2%). However, 31.4% had no intention of doing practice sessions and/or dummy runs for PPE use and 27.5% had no intention of using a buddy system on farm/practice to check use of PPE. Whilst these rates indicate workers' willingness to adopt and maintain personal biosecurity strategies, they also indicate capacity for more practices to be implemented more often. Overall, the findings highlight the need for personal biosecurity interventions to be sensitive to the demands of the annual thoroughbred breeding calendar, the size of the breeding operation and the availability of skilled staff.

Producer practices and attitudes: Non-replacement male calf management in the Australian dairy industry

Currently, there is no standardized rearing method or production guidelines for non-replacement male dairy calves that maximizes their economic viability. Producers have highlighted the need to match consumer expectations, but even with broadscale welfare improvement across the dairy industry, challenges remain at providing reliable and valuable pathways for non-replacement male dairy calves for beef production. A key consumer concern has been the use of on-farm euthanasia. Euthanasia has been a catalyst for change in the industry from a human and animal welfare perspective. The practice of euthanasia can lead to a decline in personnel wellbeing. To investigate the relationship between on-farm management practices of non-replacement male dairy calves and producer perceptions of their value proposition, an online questionnaire was provided to Australian dairy producers between June and October 2021. The aim was to identify supply-chain profitability of non-replacement male calves and investigate the attitudes and effects of euthanasia on producer wellbeing as part of managing these calves. A total of 127 useable responses were obtained, and a Bayesian network (BN) was utilized to model the interdependencies between management practices and wellbeing among participants. The results indicated that in general, dairy producers desired high welfare standards in their enterprises with regard to non-replacement male calves as well as expressed a desire to meet industry and consumers' expectations. In line with anecdotal reports of a reduction in practice, euthanasia was not identified as common practice in this group; however, producers were still accessing early-life markets for non-replacement male calves with operational requirements and environmental factors influencing their decisions. Producers expressed dissatisfaction with market access for their calves, as well as the lack of suitability of Australian beef grading standards for dairy-bred carcasses. Australian dairy managers and owners identified that euthanasia influenced employee wellbeing; however, they did not acknowledge euthanasia had an effect on their own wellbeing. Overall, the findings of this study indicate that all non-replacement male calf breeds had the potential to access profitable markets, and avoidance of euthanasia is a strong driver of change among dairy beef production systems in Australia.

An Integrated Biosecurity Risk Assessment Model (IBRAM) For Evaluating the Risk of Import Pathways for the Establishment of Invasive Species

An important aspect of analyzing the risk of unwanted organisms establishing in an area is understanding the pathways by which they arrive. Evaluating the risks of these pathways requires use of data from multiple sources, which frequently are uncertain. To address the needs of agencies responsible for biosecurity operations, we present an Integrated Biosecurity Risk Assessment Model (IBRAM) for evaluating the risk of establishment and dispersal of invasive species along trade pathways. The IBRAM framework consists of multiple linked models which describe pest entry into the country, escape along trade pathways, initial dispersal into the environment, habitat suitability, probabilities of establishment and spread, and the consequences of these invasions. Bayesian networks (BN) are used extensively to model these processes. The model includes dynamic BN components and geographic data, resulting in distributions of output parameters over spatial and temporal axes. IBRAM is supported by a web-based tool that allows users to run the model on real-world pest examples and investigate the impact of alternative risk management scenarios, to explore the effect of various interventions and resource allocations. Two case studies are provided as examples of how IBRAM may be used: Queensland fruit fly (Bactrocera tryoni) (Diptera: Tephritidae) and brown marmorated stink bug (Halyomorpha halys) (Hemiptera: Pentatomidae) are unwanted organisms with the potential to invade Aotearoa New Zealand, and IBRAM has been influential in evaluating the efficacy of pathway management to mitigate the risk of their establishment in the country.

The Impact of Experiences and Perceptions of Highly Pathogenic Avian Influenza (HPAI) on Water-Related Biosecurity Behaviour in Rural Vietnam

BACKGROUND

In Southeast Asia from 2004 to 2006, highly pathogenic avian influenza (HPAI) resulted in culling 45 million birds and jeopardizing sustainable agricultural production. HPAI is highly virulent; small-scale farms present a high-risk environment for disease transmission between animals and humans. We investigated how attitudes toward HPAI influence water-related biosecurity mitigation behaviors on small-scale farms in Vietnam using the conceptual framework Social Cognitive Theory.

METHOD

We analyzed a secondary cross-sectional data set from northern (Thai Binh) and southern (An Giang) provinces in Vietnam, describing a stratified randomized selection of 600 small-scale farmers who were interviewed using questionnaires and in-person interviews. Logistic regression analysis and odds ratios were used to examine relationships between factors influencing HPAI attitudes, social norms, perceived importance, and behaviors (α = 0.10) RESULTS: Concern about the severity of HPAI was significantly associated with increased perceived importance for all water management biosecurity methods (p < 0.01). Media and/or peer influence had negative effects on perceived importance to practice water-related biosecurity (p < 0.10). High importance of practice water-related biosecurity resulted in high uptake (p < 0.05). Past experiences with HPAI were significant in predicting perceived importance; none were significant in describing behavior uptake.

DISCUSSION

Biosecurity guidelines may not be consistent with management styles of Vietnamese small-scale farms; perceived importance of a behavior may be an important mediating variable. Gaps exist in uptake of water management practices as biosecurity for HPAI, potentially negatively affected by peer and media influence. Our results should be of interest to public health and policy authorities addressing HPAI mitigation.

"HerdGPS-Preprocessor"-A Tool to Preprocess Herd Animal GPS Data; Applied to Evaluate Contact Structures in Loose-Housing Horses

Sensors delivering information on the position of farm animals have been widely used in precision livestock farming. Global Positioning System (GPS) sensors are already known from applications in military, private and commercial environments, and their application in animal science is increasing. However, as trade-offs between sensor cost, battery life and sensor weight have to be made, GPS based studies scheduling long data collection periods and including a high number of animals, have to deal with problems like high hardware costs and data disruption during recharging of sensors. Furthermore, human-animal interaction due to sensor changing at the end of battery life interferes with the animal behaviour under analysis. The present study thus proposes a setting to deal with these challenges and offers the software tool "HerdGPS-Preprocessor", because collecting position data from multiple animals nonstop for several weeks produces a high amount of raw data which needs to be sorted, preprocessed and provided in a suitable format per animal and day. The software tool "HerdGPS-Preprocessor" additionally outputs contact lists to enable a straight analysis of animal contacts. The software tool was exemplarily deployed for one month of daily and continuous GPS data of 40 horses in a loose-housing boarding facility in northern Germany. Contact lists were used to generate separate networks for every hour, which are then analysed with regard to the network parameter density, diameter and clique structure. Differences depending on the day and the day time could be observed. More dense networks with more and larger cliques were determined in the hours prior to the opening of additional pasture.

Biosecurity risk factors for highly pathogenic avian influenza (H5N8) virus infection in duck farms, France

Highly pathogenic avian influenza (HPAI) subtype H5N8 outbreaks occurred in poultry farms in France in 2016-2017, resulting in significant economic losses and disruption to the poultry industry. Current evidence on associations between actual on-farm biosecurity risk factors and H5N8 occurrence is limited. Therefore, a retrospective matched case-control study was undertaken to investigate the inter-relationships between on-farm biosecurity practices and H5N8 infection status to provide new insights regarding promising targets for intervention. Data were collected on 133 case and 133 control duck farms (i.e. the most affected species) located in one area of the country that was mostly affected by the disease. Data were analysed using Additive Bayesian Networks which offer a rich modelling framework by graphically illustrating the dependencies between variables. Factors indirectly and directly positively associated with farm infection were inadequate management of vehicle movements (odds ratio [OR] 9.3, 95% credible interval [CI] 4.0-22.8) and inadequate delimitation of farm and units (OR 3.0, 95% CI 1.6-5.8), respectively. Inadequate disposal of dead birds was instead negatively associated with the outcome (OR 0.1, 95% CI 0.0-0.3). The findings highlight that reinforcing farm access control systems and reducing the number of visitors are key biosecurity measures to control farm vulnerability to H5N8 infection and could help setting priorities in biosecurity practices to prevent outbreaks' re-occurrence.

Australian beef producers' knowledge and attitudes relating to hydatid disease are associated with their control practices

Despite available control strategies, hydatid disease in beef cattle has been shown to have a wider geographic range and higher prevalence than previously recognised in Australia. The aim of the current study was to determine whether producer knowledge and attitudes are associated with farm management practices that could influence transmission among domestic dogs, wildlife, livestock and humans. Between June and August 2019, a cross-sectional study was conducted among beef producers throughout Australia (N = 62). Producers were asked to complete an online survey to obtain information on their knowledge about hydatid disease, their attitudes towards the disease and their farm management practices that could affect transmission. Descriptive statistics were conducted to investigate potential predictors for practices that might influence transmission of the parasite. A Bayesian network (BN) model was then constructed to evaluate the interrelationships between variables. The results show that most respondents (87 %; 54/62) had heard of hydatid disease. However, only 61 % of respondents knew how hydatid disease is transmitted (38/62) and only half knew how to prevent transmission (52 %; 32/62). Of respondents that knew that hydatid disease could affect humans (44/62), many did not think their family was at risk (46 %, 20/44) because they dewormed their dogs and prevented their dogs' access to offal. However, most respondents who owned dogs did not deworm their dogs frequently enough to prevent patency of Echinococcus granulosus infection (86 %; 49/57). Almost all respondents (94 %; 58/62) said they would take action if they found out their cattle were infected. BN analysis revealed that implementation of practices that could reduce the risk of hydatid disease transmission were associated with producers' knowledge and attitudes. In the model, practices were most influenced by attitudes (percentage change in variance = 42 %). All respondents in the "hydatid prevention" practices group were in the "good" knowledge group and the "less concerned" attitudes group. In comparison, most of the respondents in the "standard husbandry" practices group were in the "poor" knowledge group and the "more concerned" attitudes group. In summary, the results indicate that greater knowledge of hydatid disease among beef producers is associated with practices that reduce hydatid risk and attitudes of less concern about hydatid impact on properties. Therefore, increasing producer knowledge is warranted to encourage adoption and improvement of hydatid prevention practices and would be well received by beef producers.

Bayesian Network Modeling Applied to Feline Calicivirus Infection Among Cats in Switzerland

Bayesian network (BN) modeling is a rich and flexible analytical framework capable of elucidating complex veterinary epidemiological data. It is a graphical modeling technique that enables the visual presentation of multi-dimensional results while retaining statistical rigor in population-level inference. Using previously published case study data about feline calicivirus (FCV) and other respiratory pathogens in cats in Switzerland, a full BN modeling analysis is presented. The analysis shows that reducing the group size and vaccinating animals are the two actionable factors directly associated with FCV status and are primary targets to control FCV infection. The presence of gingivostomatitis and Mycoplasma felis is also associated with FCV status, but signs of upper respiratory tract disease (URTD) are not. FCV data is particularly well-suited to a network modeling approach, as both multiple pathogens and multiple clinical signs per pathogen are involved, along with multiple potentially interrelated risk factors. BN modeling is a holistic approach—all variables of interest may be mutually interdependent—which may help to address issues, such as confounding and collinear factors, as well as to disentangle directly vs. indirectly related variables. We introduce the BN methodology as an alternative to the classical uni- and multivariable regression approaches commonly used for risk factor analyses. We advise and guide researchers about how to use BNs as an exploratory data tool and demonstrate the limitations and practical issues. We present a step-by-step case study using FCV data along with all code necessary to reproduce our analyses in the open-source R environment. We compare and contrast the findings of the current case study using BN modeling with previous results that used classical regression techniques, and we highlight new potential insights. Finally, we discuss advanced methods, such as Bayesian model averaging, a common way of accounting for model uncertainty in a Bayesian network context.

Revealing the structure of the associations between housing system, facilities, management and welfare of commercial laying hens using Additive Bayesian Networks

After the ban of battery cages in 1988, a welfare control programme for laying hens was developed in Sweden. Its goal was to monitor and ensure that animal welfare was not negatively affected by the new housing systems. The present observational study provides an overview of the current welfare status of commercial layer flocks in Sweden and explores the complexity of welfare aspects by investigating and interpreting the inter-relationships between housing system, production type (i.e. organic or conventional), facilities, management and animal welfare indicators. For this purpose, a machine learning procedure referred to as structure discovery was applied to data collected through the welfare programme during 2010-2014 in 397 flocks housed in 193 different farms. Seventeen variables were fitted to an Additive Bayesian Network model. The optimal model was identified by an exhaustive search of the data iterated across incremental parent limits, accounting for prior knowledge about causality, potential over-dispersion and clustering. The resulting Directed Acyclic Graph shows the inter-relationships among the variables. The animal-based welfare indicators included in this study - flock mortality, feather condition and mite infestation - were indirectly associated with each other. Of these, severe mite infestations were rare (4% of inspected flocks) and mortality was below the acceptable threshold (< 0.6%). Feather condition scored unsatisfactory in 21% of the inspected flocks; however, it seemed to be only associated to the age of the flock, ruling out any direct connection with managerial and housing variables. The environment-based welfare indicators - lighting and air quality - were an issue in 5 and 8% of the flocks, respectively, and showed a complex inter-relationship with several managerial and housing variables leaving room for several options for intervention. Additive Bayesian Network modelling outlined graphically the underlying process that generated the observed data. In contrast to ordinary regression, it aimed at accounting for conditional independency among variables, facilitating causal interpretation.

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

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.

Comparison between generalized linear modelling and additive Bayesian network; identification of factors associated with the incidence of antibodies against Leptospira interrogans sv Pomona in meat workers in New Zealand

BACKGROUND

Additive Bayesian Network (ABN) is a graphical model which extends Generalized Linear Modelling (GLM) to multiple dependent variables. The present study compares results from GLM with those from ABN analysis used to identify factors associated with Leptospira interrogans sv Pomona (Pomona) infection by exploring the advantages and disadvantages of these two methodologies, to corroborate inferences informing health and safety measures at abattoirs in New Zealand (NZ).

METHODOLOGY AND FINDINGS

In a cohort study in four sheep slaughtering abattoirs in NZ, sera were collected twice a year from 384 meat workers and tested by Microscopic Agglutination with a 91% sensitivity and 94% specificity for Pomona. The study primarily addressed the effect of work position, personal protective equipment (PPE) and non-work related exposures such as hunting on a new infection with Pomona. Significantly associated with Pomona were "Work position" and two "Abattoirs" (GLM), and "Work position" (ABN). The odds of Pomona infection (OR, [95% CI]) was highest at stunning and hide removal (ABN 41.0, [6.9-1044.2]; GLM 57.0, [6.9-473.3]), followed by removal of intestines, bladder, and kidneys (ABN 30.7, [4.9-788.4]; GLM 33.8, [4.2-271.1]). Wearing a facemask, glasses or gloves (PPE) did not result as a protective factor in GLM or ABN.

CONCLUSIONS/SIGNIFICANCE

The odds of Pomona infection was highest at stunning and hide removal. PPE did not show any indication of being protective in GLM or ABN. In ABN all relationships between variables are modelled; hence it has an advantage over GLM due to its capacity to capture the natural complexity of data more effectively.

Use of Bayesian Belief Network techniques to explore the interaction of biosecurity practices on the probability of porcine disease occurrence in Canada

Identification and quantification of pathogen threats need to be a priority for the Canadian swine industry so that resources can be focused where they will be most effective. Here we create a tool based on a Bayesian Belief Network (BBN) to model the interaction between biosecurity practices and the probability of occurrence of four different diseases on Canadian swine farms. The benefits of using this novel approach, in comparison to other methods, is that it enables us to explore both the complex interaction and the relative importance of biosecurity practices on the probability of disease occurrence.

In order to build the BBN we used two datasets. The first dataset detailed biosecurity practices employed on 218 commercial swine farms across Canada in 2010. The second dataset detailed animal health status and disease occurrence on 90 of those farms between 2010 and 2012. We used expert judgement to identify 15 biosecurity practices that were considered the most important in mitigating disease occurrence on farms. These included: proximity to other livestock holdings, the health status of purchased stock, manure disposal methods, as well as the procedures for admitting vehicles and staff. Four diseases were included in the BBN: Porcine reproductive and respiratory syndrome (PRRS), (a prevalent endemic aerosol pathogen), Swine influenza (SI) (a viral respiratory aerosol pathogen), Mycoplasma pneumonia (MP) (an endemic respiratory disease spread by close contact and aerosol) and Swine dysentery (SD) (an enteric disease which is re-emerging in North America).

This model indicated that the probability of disease occurrence was influenced by a number of manageable biosecurity practices. Increased probability of PRRS and of MP were associated with spilt feed (feed that did not fall directly in a feeding trough), not being disposed of immediately and with manure being brought onto the farm premises and spread on land adjacent to the pigs. Increased probabilities of SI and SD were associated with the farm allowing access to visiting vehicles without cleaning or disinfection. SD was also more likely to occur when the health status of purchased stock was not known. Finally, we discuss how such a model can be used by the Canadian swine industry to quantify disease risks and to determine practices that may reduce the probability of disease occurrence.

Attitudes of Austrian veterinarians towards euthanasia in small animal practice: impacts of age and gender on views on euthanasia

Background

Euthanasia of pets has been described by veterinarians as “the best and the worst” of the profession. The most commonly mentioned ethical dilemmas veterinarians face in small animal practice are: limited treatment options due to financial constraints, euthanizing of healthy animals and owners wishing to continue treatment of terminally ill animals. The aim of the study was to gain insight into the attitudes of Austrian veterinarians towards euthanasia of small animals. This included assessing their agreement with euthanasia in exemplified case scenarios, potentially predicted by demographic variables (e.g. gender, age, working in small animal practice, employment, working in a team, numbers of performed euthanasia). Further describing the veterinarians’ agreement with a number of different normative and descriptive statements, including coping strategies. A questionnaire with nine euthanasia scenarios, 26 normative and descriptive statements, and demographic data were sent to all members of the Austrian Chamber of Veterinary Surgeons (n = 2478).

Results

In total, 486 veterinarians answered sufficiently completely to enable analyses. Responses were first explored descriptively before being formally analysed using linear regression and additive Bayesian networks – a multivariate regression methodology – in order to identify joint relationships between the demographic variables, the statements and each of the nine euthanasia scenarios. Mutual dependencies between the demographic variables were found, i.e. female compared to male veterinarians worked mostly in small animal practice, and working mostly in small animal practice was linked to performing more euthanasia per month.

Conclusions

Gender and age were found to be associated with views on euthanasia: female veterinarians and veterinarians having worked for less years were more likely to disagree with euthanasia in at least some of the convenience euthanasia scenarios. The number of veterinarians working together was found to be the variable with the highest number of links to other variables, demographic as well as ethical statements. This highlights the role of a team potentially providing support in stressful situations. The results are useful for a better understanding of coping strategies for veterinarians with moral stress due to euthanasia of small animals.

Electronic supplementary material

The online version of this article (doi:10.1186/s12917-016-0649-0) contains supplementary material, which is available to authorized users.

The effect of animal health compensation on 'positive' behaviours towards exotic disease reporting and implementing biosecurity: A review, a synthesis and a research agenda

With an increasing burden on public sector budgets, increased responsibility and cost sharing mechanisms for animal diseases are being considered. To achieve this, fiscal and non-fiscal intervention policies need to be designed such that they consistently promote positive disease risk management practices by animal keepers. This paper presents a review of the available evidence towards whether and how the level and type of funding mechanism affects change within biosecurity behaviours and the frequency of disease reporting. A Nuffield Health Ladder of Interventions approach is proposed as a way to frame the debate surrounding both current compensation mechanisms and how it is expected to change behaviour. Results of the review reveal a division between economic modelling approaches, which implicitly assume a causal link between payments and positive behaviours, and socio-geographic approaches which tend to ignore the influence of compensation mechanisms on influencing behaviours. Generally, economic studies suggest less than full compensation rates will encourage positive behaviours, but the non-economic literature indicate significant variation in response to compensation reflecting heterogeneity of livestock keepers in terms of their values, goals, risk attitudes, size of operation, animal species and production chain characteristics. This may be of encouragement to Western Governments seeking to shift cost burdens as it may induce greater targeting of non-fiscal mechanisms, or suggest more novel ways to augment current compensation mechanisms to both increase responsibility sharing and reduce this cost burden. This review suggests that a range of regulatory, fiscal and nudging policies are required to achieve socially optimal results with respect to positive behaviour change. However, the lack of directly available evidence which proves these causal links may hinder progress towards this optimal mixture of choice and non-choice based interventions.

Risk assessment as a tool for improving external biosecurity at farm level

Background

Biosecurity routines at herd level may reduce the probability of introduction of disease into the herd, but some measures may be regarded as expensive and cumbersome for the farmers. Custom-made measures based on individual farm characteristics may aid in improving the actual application of on-farm biosecurity.

The aim of the study was to provide a tool for calculating the effects of different biosecurity measures and strategies on the individual farm level.

A simple model was developed to assess the risk of disease introduction and the need for biosecurity measures in individual farms. To illustrate the general applicability of the tool, it was applied to theoretical examples of Swedish cattle and pig farms and diseases endemic in those animal species in the EU, in two scenarios with different between-farm contact patterns.

Results

The model illustrated that the most important factors affecting the risk, and the effect of biosecurity measures such as quarantine routines and protective clothing, were the frequency of between-farm contacts and prevalence of the disease. The risk of introduction as well as the effect of biosecurity measures differed between farm types and disease transmission routes. Adapting contact patterns to mitigate a specific disease risk was as important as biosecurity measures for some farm types, but the largest effect was seen when combining biosecurity measures with more planned contact patterns.

Conclusions

The risk assessment model proved useful for illustrating the risk of introduction of endemic diseases and the mitigating effect of different biosecurity measures on farm level. Model outputs could be used to justify prioritisation of measures or adapting contact patterns. The theoretic exercise of adjusting model inputs and comparing outputs may help veterinary advisors to understand farm-specific risks and motivate farmers to improve biosecurity in their individual farm, as it can be tailored to each farmer’s needs and preferences.