Literature DB >> 17112610

A stochastic model simulating paratuberculosis in a dairy herd.

Anne Braad Kudahl1, Søren Ostergaard, Jan Tind Sørensen, Søren Saxmose Nielsen.   

Abstract

Paratuberculosis (PTB) causes severe economic losses to farmers and the infection has very complex effects (many indirect) on the production of a dairy herd. These indirect effects have not or only briefly been described by earlier PTB-simulation models, and therefore they were included in a new model called PTB-Simherd. Our aim was to develop the basis for a decision-support tool which can predict herd-specific production-related effects from introduction of different control strategies against PTB. The PTB-Simherd is a dynamic, stochastic, and mechanistic Monte-Carlo model simulating a dairy herd including young stock. Paratuberculosis and relevant control strategies against this infection were built into an existing herd simulation model. The model simulates epidemiological and production related consequences of PTB and control strategies against it in the herd. It also reflects indirect effects of PTB and control strategies through effects on replacements and herd demographics. Every animal in the herd is specified with biological parameters (including PTB state and test results) and it is updated in weekly time-steps. Management is specified at herd level with 353 parameters of which 78 are related to PTB. To demonstrate the basic characteristics of the model, scenarios with varying infection risks (sensitivity analyses) plus scenarios with seven different control strategies in two herds with good and poor reproduction were simulated for 10 years. Breaking of infection routes turned out to be the only strategy predicted to reduce the true prevalence of PTB in a herd. Supplementing this strategy with test-&-cull strategies had limited effect on prevalence and using test-&-cull alone just delayed the increase in prevalence. The effects of different PTB-control strategies on the production (especially sale/purchase of heifers, feed consumption and prevalences of other diseases) were predicted to be affected by other conditions like heat-detection success, replacement% and herd demographics--which were again affected by PTB infection of the herd. These links and indirect effects of control strategies thus seem important to include when modeling and predicting effects of PTB control in dairy herds.

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Year:  2006        PMID: 17112610     DOI: 10.1016/j.prevetmed.2006.05.015

Source DB:  PubMed          Journal:  Prev Vet Med        ISSN: 0167-5877            Impact factor:   2.670


  15 in total

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Journal:  J Clin Microbiol       Date:  2020-11-18       Impact factor: 5.948

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Authors:  Roxanne B Pillars; Daniel L Grooms; John B Kaneene
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3.  Dynamics of specific anti-Mycobacterium avium subsp. paratuberculosis antibody response through age.

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Journal:  PLoS One       Date:  2013-04-29       Impact factor: 3.240

4.  Predicting fadeout versus persistence of paratuberculosis in a dairy cattle herd for management and control purposes: a modelling study.

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Journal:  Vet Res       Date:  2011-02-15       Impact factor: 3.683

5.  A survey of management practices on Irish dairy farms with emphasis on risk factors for Johne's disease transmission.

Authors:  Aideen E Kennedy; Eugene F O'Doherty; Noel Byrne; Jim O'Mahony; E M Kennedy; Riona G Sayers
Journal:  Ir Vet J       Date:  2014-12-24       Impact factor: 2.146

6.  Calves shedding Mycobacterium avium subspecies paratuberculosis are common on infected dairy farms.

Authors:  Robert Wolf; Karin Orsel; Jeroen De Buck; Herman Wildrik Barkema
Journal:  Vet Res       Date:  2015-06-19       Impact factor: 3.683

7.  Simulating the Epidemiological and Economic Impact of Paratuberculosis Control Actions in Dairy Cattle.

Authors:  Carsten Kirkeby; Kaare Græsbøll; Søren Saxmose Nielsen; Lasse E Christiansen; Nils Toft; Erik Rattenborg; Tariq Halasa
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8.  Accounting for uncertainty in model-based prevalence estimation: paratuberculosis control in dairy herds.

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Journal:  BMC Vet Res       Date:  2012-09-10       Impact factor: 2.741

9.  Detection and confirmation of Mycobacterium avium subsp. paratuberculosis in direct quantitative PCR positive fecal samples by the manual fluorescent MGIT culture system.

Authors:  Satoko Kawaji; Reiko Nagata; Yasuyuki Mori
Journal:  J Vet Med Sci       Date:  2013-09-20       Impact factor: 1.267

10.  Mycobacterium avium Subspecies paratuberculosis and Bovine Leukemia Virus Seroprevalence and Associated Risk Factors in Commercial Dairy and Beef Cattle in Northern and Northeastern China.

Authors:  Wu-Wen Sun; Wen-Fa Lv; Wei Cong; Qing-Feng Meng; Chun-Feng Wang; Xiao-Feng Shan; Ai-Dong Qian
Journal:  Biomed Res Int       Date:  2015-10-04       Impact factor: 3.411

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