Aarhus University Seal / Aarhus Universitets segl

Søren Østergaard

Modelling the economic impact of three lameness causing diseases using herd and cow level evidence

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Modelling the economic impact of three lameness causing diseases using herd and cow level evidence. / Ettema, Jehan Frans; Østergaard, Søren; Kristensen, Anders Ringgaard.

I: Preventive Veterinary Medicine, Bind 95, 2010, s. 64-73.

Publikation: Bidrag til tidsskrift/Konferencebidrag i tidsskrift /Bidrag til avisTidsskriftartikelForskningpeer review

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Ettema, Jehan Frans ; Østergaard, Søren ; Kristensen, Anders Ringgaard. / Modelling the economic impact of three lameness causing diseases using herd and cow level evidence. I: Preventive Veterinary Medicine. 2010 ; Bind 95. s. 64-73.

Bibtex

@article{88eabe40f6b211dd8b7a000ea68e967b,
title = "Modelling the economic impact of three lameness causing diseases using herd and cow level evidence",
abstract = "Diseases to the cow's hoof, interdigital skin and legs are highly prevalent and of large economic impact in modern dairy farming. In order to support farmer's decisions on preventing and treating lameness and its underlying causes, decision support models can be used to predict the economic profitability of such actions. An existing approach of modelling lameness as one health disorder in a dynamic, stochastic and mechanistic simulation model has been improved in two ways. First of all, three underlying diseases causing lameness were modelled: digital dermatitis, interdigital hyperplasia and claw horn diseases. Secondly, the existing simulation model was set-up inwaythat it uses hyper-distributions describing diseases risk of the three lameness causing diseases. By combining information on herd level risk factors with prevalence of lameness or prevalence of underlying diseases among cows, marginal posterior probability distributions for disease prevalence in the specific herd are created in a Bayesian network. Random draws from these distributions are used by the simulation model to describe disease risk. Hereby field data on prevalence is used systematically and uncertainty around herd specific risk is represented. Besides the fact that estimated profitability of halving disease risk depended on the hyper-distributions used, the estimates differed for herds with different levels of diseases risk and reproductive efficiency.",
keywords = "Lameness, Dairy cattle, Stochastic simulation, Hyper-distributions",
author = "Ettema, {Jehan Frans} and S{\o}ren {\O}stergaard and Kristensen, {Anders Ringgaard}",
year = "2010",
language = "English",
volume = "95",
pages = "64--73",
journal = "Preventive Veterinary Medicine",
issn = "0167-5877",
publisher = "Elsevier BV",

}

RIS

TY - JOUR

T1 - Modelling the economic impact of three lameness causing diseases using herd and cow level evidence

AU - Ettema, Jehan Frans

AU - Østergaard, Søren

AU - Kristensen, Anders Ringgaard

PY - 2010

Y1 - 2010

N2 - Diseases to the cow's hoof, interdigital skin and legs are highly prevalent and of large economic impact in modern dairy farming. In order to support farmer's decisions on preventing and treating lameness and its underlying causes, decision support models can be used to predict the economic profitability of such actions. An existing approach of modelling lameness as one health disorder in a dynamic, stochastic and mechanistic simulation model has been improved in two ways. First of all, three underlying diseases causing lameness were modelled: digital dermatitis, interdigital hyperplasia and claw horn diseases. Secondly, the existing simulation model was set-up inwaythat it uses hyper-distributions describing diseases risk of the three lameness causing diseases. By combining information on herd level risk factors with prevalence of lameness or prevalence of underlying diseases among cows, marginal posterior probability distributions for disease prevalence in the specific herd are created in a Bayesian network. Random draws from these distributions are used by the simulation model to describe disease risk. Hereby field data on prevalence is used systematically and uncertainty around herd specific risk is represented. Besides the fact that estimated profitability of halving disease risk depended on the hyper-distributions used, the estimates differed for herds with different levels of diseases risk and reproductive efficiency.

AB - Diseases to the cow's hoof, interdigital skin and legs are highly prevalent and of large economic impact in modern dairy farming. In order to support farmer's decisions on preventing and treating lameness and its underlying causes, decision support models can be used to predict the economic profitability of such actions. An existing approach of modelling lameness as one health disorder in a dynamic, stochastic and mechanistic simulation model has been improved in two ways. First of all, three underlying diseases causing lameness were modelled: digital dermatitis, interdigital hyperplasia and claw horn diseases. Secondly, the existing simulation model was set-up inwaythat it uses hyper-distributions describing diseases risk of the three lameness causing diseases. By combining information on herd level risk factors with prevalence of lameness or prevalence of underlying diseases among cows, marginal posterior probability distributions for disease prevalence in the specific herd are created in a Bayesian network. Random draws from these distributions are used by the simulation model to describe disease risk. Hereby field data on prevalence is used systematically and uncertainty around herd specific risk is represented. Besides the fact that estimated profitability of halving disease risk depended on the hyper-distributions used, the estimates differed for herds with different levels of diseases risk and reproductive efficiency.

KW - Lameness

KW - Dairy cattle

KW - Stochastic simulation

KW - Hyper-distributions

M3 - Journal article

VL - 95

SP - 64

EP - 73

JO - Preventive Veterinary Medicine

JF - Preventive Veterinary Medicine

SN - 0167-5877

ER -