Dataset Information

Economic consequences of paratuberculosis control in dairy cattle: A stochastic modeling study.

ABSTRACT: The cost of paratuberculosis to dairy herds, through decreased milk production, early culling, and poor reproductive performance, has been well-studied. The benefit of control programs, however, has been debated. A recent stochastic compartmental model for paratuberculosis transmission in US dairy herds was modified to predict herd net present value (NPV) over 25 years in herds of 100 and 1000 dairy cattle with endemic paratuberculosis at initial prevalence of 10% and 20%. Control programs were designed by combining 5 tests (none, fecal culture, ELISA, PCR, or calf testing), 3 test-related culling strategies (all test-positive, high-positive, or repeated positive), 2 test frequencies (annual and biannual), 3 hygiene levels (standard, moderate, or improved), and 2 cessation decisions (testing ceased after 5 negative whole-herd tests or testing continued). Stochastic dominance was determined for each herd scenario; no control program was fully dominant for maximizing herd NPV in any scenario. Use of the ELISA test was generally preferred in all scenarios, but no paratuberculosis control was highly preferred for the small herd with 10% initial prevalence and was frequently preferred in other herd scenarios. Based on their effect on paratuberculosis alone, hygiene improvements were not found to be as cost-effective as test-and-cull strategies in most circumstances. Global sensitivity analysis found that economic parameters, such as the price of milk, had more influence on NPV than control program-related parameters. We conclude that paratuberculosis control can be cost effective, and multiple control programs can be applied for equivalent economic results.

SUBMITTER: Smith RL

PROVIDER: S-EPMC5330211 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature

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Economic consequences of paratuberculosis control in dairy cattle: A stochastic modeling study.

Smith R L RL Al-Mamun M A MA Gröhn Y T YT

Preventive veterinary medicine 20170110

The cost of paratuberculosis to dairy herds, through decreased milk production, early culling, and poor reproductive performance, has been well-studied. The benefit of control programs, however, has been debated. A recent stochastic compartmental model for paratuberculosis transmission in US dairy herds was modified to predict herd net present value (NPV) over 25 years in herds of 100 and 1000 dairy cattle with endemic paratuberculosis at initial prevalence of 10% and 20%. Control programs were ...[more]

PMID: 28237232

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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:Paratuberculosis is a major endemic disease caused by Mycobacterium avium subspecies paratuberculosis (MAP) infection and leads to huge economic loss in the dairy sector worldwide. Alternative splicing (AS) events, playing indispensable regulatory roles in many protein functions and biological pathways, are shown to be associated with complex traits and diseases. In this study, by integrating the RNA sequencing (RNA-seq) data of 24 samples from three tissues (peripheral blood, jejunum and salivary gland) of Holstein cows, we obtained 2,706,541,696 uniquely mapped reads in total that represented 12,870 expressed genes, and detected 4285 differentially expressed genes (DEGs) between MAP-infected and healthy cows (p < 0.05). Of them, 92 differentially expressed splicing factors (DESFs) were included. Further, 119, 150 and 68 differential alternative splicing (DAS) events between MAP-infected and healthy cows were identified in peripheral blood, jejunum and salivary glands, respectively. Of note, six DAS events were highly and significantly correlated with the DESFs (R2 > 0.9; p < 0.01), and their corresponding genes (COPI coat complex subunit gamma 2gene (COPG2), kinesin family member 2C gene (KIF2C), exocyst complex component 7 (EXOC7), Rab9 effector protein with kelch motifs gene (RABEPK), deoxyribonuclease 1 gene (DNASE1) and early endosome antigen 1gene (EEA1)) were significantly enriched in immune response such as vesicle-mediated transport, regulation of acute inflammatory response and tuberculosis through gene ontology (GO) and KEGG analysis. KS test showed that the DAS events in the EXOC7 and KIF2C genes indeed displayed differences between MAP-infected cows and healthy cows. The DAS in EXOC7 might produce a new protein sequence with lack of 23 amino acids, and the DAS in KIF2C induced a stop codon of premature occurrence and resulted in a lack of functional domain. In summary, this study identified the DAS events and corresponding genes related to MAP-infection base on the RNA-seq data from multiple tissues of Holstein cows, providing novel insights into the regulatory mechanisms underpinning paratuberculosis in dairy cattle.

Dataset Information

Economic consequences of paratuberculosis control in dairy cattle: A stochastic modeling study.

Publications

Economic consequences of paratuberculosis control in dairy cattle: A stochastic modeling study.

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