Modelling of Johne's disease control options in beef cattle: A decision support approach

Investigating effective testing strategies for the control of Johne's disease in western Canadian cow-calf herds using an agent-based simulation model

Johne's disease is an insidious infectious disease of ruminants caused by Mycobacterium avium subspecies paratuberculosis (MAP). Johne's disease can have important implications for animal welfare and risks causing economic losses in affected herds due to reduced productivity, premature culling and replacement, and veterinary costs. Despite the limited accuracy of diagnostic tools, testing and culling is the primary option for controlling Johne's disease in beef herds. However, evidence to inform specific test and cull strategies is lacking. In this study, a stochastic, continuous-time agent-based model was developed to investigate Johne's disease and potential control options in a typical western Canadian cow-calf herd. The objective of this study was to compare different testing and culling scenarios that included varying the testing method and frequency as well as the number and risk profile of animals targeted for testing using the model. The relative effectiveness of each testing scenario was determined by the simulated prevalence of cattle shedding MAP after a 10-year testing period. A second objective was to compare the direct testing costs of each scenario to identify least-cost options that are the most effective at reducing within-herd disease prevalence. Whole herd testing with individual PCR at frequencies of 6 or 12 months were the most effective options for reducing disease prevalence. Scenarios that were also effective at reducing prevalence but with the lowest total testing costs included testing the whole herd with individual PCR every 24 months and testing the whole herd with pooled PCR every 12 months. The most effective method with the lowest annual testing cost per unit of prevalence reduction was individual PCR on the whole herd every 24 months. Individual PCR testing only cows that had not already been tested 4 times also ranked well when considering both final estimated prevalence at 10 years and cost per unit of gain. A more in-depth economic analysis is needed to compare the cost of testing to the cost of disease, taking into account costs of culling, replacements and impacts on calf crops, and to determine if testing is an economically attractive option for commercial cow-calf operations.

A flexible tool for the assessment of the economic cost of pig disease in growers and finishers at farm level

Pigmeat is the most consumed red meat globally and consumption is expected to continue to increase. The sector is faced by the risk of epidemic and endemic disease impacts and other adverse influences. The aim of this study was to develop a dynamic simulation model of pig growing and finishing that can be used to model the financial and economic impacts of a variety of scenarios both related to disease effects and other influences on production. The model consists of a physical performance module and financial performance module. The core of the physical performance module comprises three stocks to model the flow of pigs from purchase to slaughter. Mortality rates, daily live weight gain and feed conversion ratios influence the dynamics of the physical performance. Since contracts between farmers and slaughterhouses often include large price penalties for over- and underweight pigs, carcase weight distribution is an important determinant of revenues. The physical performance module, therefore, simulates slaughter weight variations. The financial performance module calculates revenue, costs and gross margins. The revenue calculations take into account price penalties for over- and underweight pigs. To demonstrate the capabilities of the model, we apply the model to assess the economic consequences of production impacts associated with respiratory disease. We use estimated production impacts associated with respiratory disease from a study of all-in-all out growing and finishing systems based on pig production data and information from slaughterhouse monitoring in the UK. Our model suggests a reduction in the gross margin of nearly 40 % as a consequence of the estimated production impacts associated with a 10% increase in respiratory disease prevalence. Due to the lack of reliable information on slaughter weight variation, we also simulate the model using different assumptions about the slaughter weight distribution. An increase in the standard deviation of carcase weights from 8 kg to 12 kg, holding average weights constant, more than halves gross margins under our scenarios. We suggest that for all-in-all-out systems, carcase weight variation is likely to be a substantial factor in reducing income in the presence of respiratory disease and the economic impact of respiratory disease may be underestimated if the effects of disease on variation in carcase weights are not included in any analysis.

Challenges and priorities for modelling livestock health and pathogens in the context of climate change

Climate change has the potential to impair livestock health, with consequences for animal welfare, productivity, greenhouse gas emissions, and human livelihoods and health. Modelling has an important role in assessing the impacts of climate change on livestock systems and the efficacy of potential adaptation strategies, to support decision making for more efficient, resilient and sustainable production. However, a coherent set of challenges and research priorities for modelling livestock health and pathogens under climate change has not previously been available. To identify such challenges and priorities, researchers from across Europe were engaged in a horizon-scanning study, involving workshop and questionnaire based exercises and focussed literature reviews. Eighteen key challenges were identified and grouped into six categories based on subject-specific and capacity building requirements. Across a number of challenges, the need for inventories relating model types to different applications (e.g. the pathogen species, region, scale of focus and purpose to which they can be applied) was identified, in order to identify gaps in capability in relation to the impacts of climate change on animal health. The need for collaboration and learning across disciplines was highlighted in several challenges, e.g. to better understand and model complex ecological interactions between pathogens, vectors, wildlife hosts and livestock in the context of climate change. Collaboration between socio-economic and biophysical disciplines was seen as important for better engagement with stakeholders and for improved modelling of the costs and benefits of poor livestock health. The need for more comprehensive validation of empirical relationships, for harmonising terminology and measurements, and for building capacity for under-researched nations, systems and health problems indicated the importance of joined up approaches across nations. The challenges and priorities identified can help focus the development of modelling capacity and future research structures in this vital field. Well-funded networks capable of managing the long-term development of shared resources are required in order to create a cohesive modelling community equipped to tackle the complex challenges of climate change.

Development of an Interspecies Nested Dose-Response Model for Mycobacterium avium subspecies paratuberculosis

Mycobacterium avium subspecies paratuberculosis (MAP) causes chronic inflammation of the intestines in humans, ruminants, and other species. It is the causative agent of Johne's disease in cattle, and has been implicated as the causative agent of Crohn's disease in humans. To date, no quantitative microbial risk assessment (QMRA) for MAP utilizing a dose-response function exists. The objective of this study is to develop a nested dose-response model for infection from oral exposure to MAP utilizing data from the peer-reviewed literature. Four studies amenable to dose-response modeling were identified in the literature search and optimized to the one-parameter exponential or two-parameter beta-Poisson dose-response models. A nesting analysis was performed on all permutations of the candidate data sets to determine the acceptability of pooling data sets across host species. Three of four data sets exhibited goodness of fit to at least one model. All three data sets exhibited good fit to the beta-Poisson model, and one data set exhibited goodness of fit, and best fit, to the exponential model. Two data sets were successfully nested using the beta-Poisson model with parameters α = 0.0978 and N50 = 2.70 × 10(2) CFU. These data sets were derived from sheep and red deer host species, indicating successful interspecies nesting, and demonstrate the highly infective nature of MAP. The nested dose-response model described should be used for future QMRA research regarding oral exposure to MAP.

Avaliação sorológica e de fatores de risco para a infecção por Mycobacterium avium subsp. paratuberculosis em rebanhos leiteiros da Microrregião de Garanhuns, Pernambuco

Objetivou-se com esse trabalho realizar um inquérito epidemiológico da infecção por Mycobacterium avium subsp. paratuberculosis (MAP) em bovinos leiteiros da microrregião de Garanhuns, Pernambuco, Brasil. Para este estudo foram coletadas amostras sanguíneas de 408 animais, provenientes de 19 rebanhos localizados em 15 municípios. O exame sorológico foi realizado por Ensaio Imunoenzimático (ELISA) indireto para detecção de anticorpos frente ao MAP. Em todas as propriedades, foi aplicado um questionário investigativo para análise dos fatores de risco, e as coordenadas geográficas coletadas por um aparelho de Global Position System (GPS) para realização da distribuição espacial. A prevalência da infecção por MAP foi de 2,7% (11/408; I.C. 1,4-4,9). O número de focos foi 47,4% (9/19). Na análise de regressão logística foi identificado como fator de risco a taxa anual de nascimentos superior a 51 bezerros/ano (OR 3,8; I.C. 1,1-13,1). Desta forma, conclui-se que a infecção por MAP encontra-se presente nos rebanhos bovinos leiteiros da microrregião estudada e que medidas de controle baseadas nos fatores de risco identificados devem ser implementadas com o objetivo de reduzir o número de focos da infecção.