Dataset Information

Effectiveness and Economic Viability of Johne's Disease (Paratuberculosis) Control Practices in Dairy Herds.

ABSTRACT: Johne's disease (JD or paratuberculosis) control programs have been established in many dairy-producing regions. However, the effectiveness (reduction of within-herd prevalence) and the relative economic impact as measured by, for example, the ratio of benefits to costs (BCR) across a comprehensive selection of regions and potential control practices require further investigation. Within a Markovian framework using region-specific economic variables, it was estimated that vaccination was the most promising type of JD control practice modeled, with dual-effect vaccines (reducing shedding and providing protective immunity) having BCRs between 1.48 and 2.13 in Canada, with a break-even period of between 6.17 and 7.61 years. Dual-effect vaccines were also estimated to yield BCRs greater than one in almost all major dairy-producing regions, with greater ratios in regions characterized by above-average farm-gate prices and annual production per cow. Testing and culling was comparably effective to a dual-effect vaccine at test sensitivities >70% but would remain economically unviable in almost all regions modeled.

SUBMITTER: Rasmussen P

PROVIDER: S-EPMC7843527 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Publications

Effectiveness and Economic Viability of Johne's Disease (Paratuberculosis) Control Practices in Dairy Herds.

Rasmussen Philip P Barkema Herman W HW Hall David C DC

Frontiers in veterinary science 20210115

Johne's disease (JD or paratuberculosis) control programs have been established in many dairy-producing regions. However, the effectiveness (reduction of within-herd prevalence) and the relative economic impact as measured by, for example, the ratio of benefits to costs (BCR) across a comprehensive selection of regions and potential control practices require further investigation. Within a Markovian framework using region-specific economic variables, it was estimated that vaccination was the mos ...[more]

PMID: 33521086

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Project description:BackgroundA common approach to the application of epidemiological models is to determine a single (point estimate) parameterisation using the information available in the literature. However, in many cases there is considerable uncertainty about parameter values, reflecting both the incomplete nature of current knowledge and natural variation, for example between farms. Furthermore model outcomes may be highly sensitive to different parameter values. Paratuberculosis is an infection for which many of the key parameter values are poorly understood and highly variable, and for such infections there is a need to develop and apply statistical techniques which make maximal use of available data.ResultsA technique based on Latin hypercube sampling combined with a novel reweighting method was developed which enables parameter uncertainty and variability to be incorporated into a model-based framework for estimation of prevalence. The method was evaluated by applying it to a simulation of paratuberculosis in dairy herds which combines a continuous time stochastic algorithm with model features such as within herd variability in disease development and shedding, which have not been previously explored in paratuberculosis models. Generated sample parameter combinations were assigned a weight, determined by quantifying the model's resultant ability to reproduce prevalence data. Once these weights are generated the model can be used to evaluate other scenarios such as control options. To illustrate the utility of this approach these reweighted model outputs were used to compare standard test and cull control strategies both individually and in combination with simple husbandry practices that aim to reduce infection rates.ConclusionsThe technique developed has been shown to be applicable to a complex model incorporating realistic control options. For models where parameters are not well known or subject to significant variability, the reweighting scheme allowed estimated distributions of parameter values to be combined with additional sources of information, such as that available from prevalence distributions, resulting in outputs which implicitly handle variation and uncertainty. This methodology allows for more robust predictions from modelling approaches by allowing for parameter uncertainty and combining different sources of information, and is thus expected to be useful in application to a large number of disease systems.

Project description:Various measures have been advocated for the control of Johne's disease (caused by Mycobacterium avium subsp. paratuberculosis, MAP) in different countries. Farmers' compliance has been reported to be variable depending on disease prevalence and incentives to participate in control programs. After the prevalence of MAP shedding and risk factors for within-herd spread of MAP were assessed in 17 Swiss cattle herds (10 dairy and 7 beef), general and herd-specific recommendations were given to the farmers to reduce MAP transmission within the herd. Participation in the study and implementation of control measures were voluntary, no financial incentives were provided for the realization of control measures. After a 3-year period of monitored observation including biannual farm visits and discussion of the situation, the implementation of the recommended control measures and their effect on prevalence of MAP shedding were evaluated. Implementation of recommended general and farm-specific control measures was only partially realized. Neither the number of animals tested positive (before or during the study) nor the farmers' knowledge about paratuberculosis were significantly associated with their compliance for the implementation of management changes. The apparent within-herd prevalence remained constant despite limited implementation of control measures, and no particular group of control measures was found to be associated with changes in prevalence. Farmers' compliance for the implementation of control measures to reduce the impact of Johne's disease in infected farms was very limited under Swiss farming conditions in the frame of voluntary participation in a research project. These results indicate that the losses associated with paratuberculosis in Swiss dairy and beef operations are not estimated to be high enough by the farmers to justify important efforts for control measures, and that incentives may be necessary to achieve efficient implementation of such measures.

Project description:Mycobacterium avium subsp. paratuberculosis (MAP) is the causative agent of Johne's disease in ruminants, which has important health consequences for dairy cattle. The Regional Dairy Quality Management Alliance (RDQMA) project is a multistate research program involving MAP isolates taken from three intensively studied commercial dairy farms in the northeastern United States, which emphasized longitudinal data collection of both MAP isolates and animal health in three regional dairy herds for a period of about 7 years. This paper reports the results of a pan-GWAS analysis involving 318 MAP isolates and dairy cow Johne's disease phenotypes, taken from these three farms. Based on our highly curated accessory gene count the pan-GWAS analysis identified several MAP genes associated with bovine Johne's disease phenotypes scored from these three farms, with some of the genes having functions suggestive of possible cause/effect relationships to these phenotypes. This paper reports a pan-genomic comparative analysis between MAP and Mycobacterium tuberculosis, assessing functional Gene Ontology category enrichments between these taxa. Finally, we also provide a population genomic perspective on the effectiveness of herd isolation, involving closed dairy farms, in preventing MAP inter-farm cross infection on a micro-geographic scale.IMPORTANCE Mycobacterium avium subsp. paratuberculosis (MAP) is the causative agent of Johne's disease in ruminants, which has important health consequences for dairy cattle, and enormous economic consequences for the dairy industry. Understanding which genes in this bacterium are correlated with key disease phenotypes can lead to functional experiments targeting these genes and ultimately lead to improved control strategies. This study represents a rare example of a prolonged longitudinal study of dairy cattle where the disease was measured and the bacteria were isolated from the same cows. The genome sequences of over 300 MAP isolates were analyzed for genes that were correlated with a wide range of Johne's disease phenotypes. A number of genes were identified that were significantly associated with several aspects of the disease and suggestive of further experimental follow-up.

Project description:BackgroundOne of the key steps in the management of chronic diseases in animals including Johne's disease (JD), caused by Mycobacterium avium subsp. paratuberculosis (MAP), is the ability to track disease incidence over space and time. JD surveillance in the U.S. dairy cattle is challenging due to lack of regulatory requirements, imperfect diagnostic tests, and associated expenses, including time and labor. An alternative approach is to use voluntary testing programs. Here, data from a voluntary JD testing program, conducted by the Minnesota Dairy Herd Improvement Association, were used to: a) explore whether such a program provides representative information on JD-prevalence in Minnesota dairy herds, b) estimate JD distribution, and, c) identify herd and environmental factors associated with finding JD-positive cows. Milk samples (n?=?70,809) collected from 54,652 unique cows from 600 Minnesota dairy herds between November 2014 and April 2017 were tested using a MAP antibody ELISA. Participant representativeness was assessed by comparing the number of JD-tested herds with the number of herds required to estimate the true disease prevalence per county based on official statistics from the National Agricultural Statistical Services. Multivariable logistic regression models, with and without spatial dependence between observations, were then used to investigate the association between herd status to JD (positive/negative), as indicated by milk ELISA results, and available covariates at the herd level.ResultsWithin the study population, at least one test-positive cow was found in 414 of 600 (69%) herds. Results indicated that large herds that test frequently and herds located in loamy or silt soils are more likely to have at least one MAP test-positive cow. After adjusting for herd size, testing frequency, and soil type, there was no spatial dependence in JD risk between neighboring dairies within 5 to 20?km. Furthermore, the importance of collecting data on herd management, feed, and biosecurity for insightful interpretations was recognized. The study suggested that, although limited, the voluntary testing database may support monitoring JD status.ConclusionsResults presented here help elucidate the spatial characteristics of JD in Minnesota and the study may ultimately contribute to the design and implementation of surveillance programs for the disease.

Dataset Information

Effectiveness and Economic Viability of Johne's Disease (Paratuberculosis) Control Practices in Dairy Herds.

Publications

Effectiveness and Economic Viability of Johne's Disease (Paratuberculosis) Control Practices in Dairy Herds.

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