Spatial pattern in prevalence of paratuberculosis infection diagnosed with misclassification in Danish dairy herds in 2009 and 2013

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt

Standard

Spatial pattern in prevalence of paratuberculosis infection diagnosed with misclassification in Danish dairy herds in 2009 and 2013. / Bihrmann, Kristine; Nielsen, Søren Saxmose; Ersbøll, Annette Kjaer.

I: Spatial and Spatio-temporal Epidemiology, Bind 16, 02.2016, s. 1-10.

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt

Harvard

Bihrmann, K, Nielsen, SS & Ersbøll, AK 2016, 'Spatial pattern in prevalence of paratuberculosis infection diagnosed with misclassification in Danish dairy herds in 2009 and 2013', Spatial and Spatio-temporal Epidemiology, bind 16, s. 1-10. https://doi.org/10.1016/j.sste.2015.10.001

APA

Bihrmann, K., Nielsen, S. S., & Ersbøll, A. K. (2016). Spatial pattern in prevalence of paratuberculosis infection diagnosed with misclassification in Danish dairy herds in 2009 and 2013. Spatial and Spatio-temporal Epidemiology, 16, 1-10. https://doi.org/10.1016/j.sste.2015.10.001

Vancouver

Bihrmann K, Nielsen SS, Ersbøll AK. Spatial pattern in prevalence of paratuberculosis infection diagnosed with misclassification in Danish dairy herds in 2009 and 2013. Spatial and Spatio-temporal Epidemiology. 2016 feb.;16:1-10. https://doi.org/10.1016/j.sste.2015.10.001

Author

Bihrmann, Kristine ; Nielsen, Søren Saxmose ; Ersbøll, Annette Kjaer. / Spatial pattern in prevalence of paratuberculosis infection diagnosed with misclassification in Danish dairy herds in 2009 and 2013. I: Spatial and Spatio-temporal Epidemiology. 2016 ; Bind 16. s. 1-10.

Bibtex

@article{ee64b64e4c2d4da4b61e590b986834a3,
title = "Spatial pattern in prevalence of paratuberculosis infection diagnosed with misclassification in Danish dairy herds in 2009 and 2013",
abstract = "Paratuberculosis is a chronic infection of economic importance to the dairy industry. The infection may be latent for years, which makes diagnostic misclassification a general challenge. The objective of this study was to identify the spatial pattern in infection prevalence, when results were adjusted for covariate information and diagnostic misclassification. Furthermore, we compared the estimated spatial pattern with the spatial pattern obtained without adjustment for misclassification. The study included 1242 herds in 2009 and 979 herds in 2013. The within-herd prevalence was modelled using a hierarchical logistic regression model and included a spatial component modelled by a continuous Gaussian field. The Stochastic Partial Differential Equation (SPDE) approach and Integrated Nested Laplace Approximation (INLA) were used for Bayesian inference. We found a significant spatial component, and our results suggested that the estimated range of influence and the overall location of areas with increased prevalence are not very sensitive to diagnostic misclassification.",
author = "Kristine Bihrmann and Nielsen, {S{\o}ren Saxmose} and Ersb{\o}ll, {Annette Kjaer}",
year = "2016",
month = feb,
doi = "10.1016/j.sste.2015.10.001",
language = "English",
volume = "16",
pages = "1--10",
journal = "Spatial and Spatio-temporal Epidemiology",
issn = "1877-5845",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - Spatial pattern in prevalence of paratuberculosis infection diagnosed with misclassification in Danish dairy herds in 2009 and 2013

AU - Bihrmann, Kristine

AU - Nielsen, Søren Saxmose

AU - Ersbøll, Annette Kjaer

PY - 2016/2

Y1 - 2016/2

N2 - Paratuberculosis is a chronic infection of economic importance to the dairy industry. The infection may be latent for years, which makes diagnostic misclassification a general challenge. The objective of this study was to identify the spatial pattern in infection prevalence, when results were adjusted for covariate information and diagnostic misclassification. Furthermore, we compared the estimated spatial pattern with the spatial pattern obtained without adjustment for misclassification. The study included 1242 herds in 2009 and 979 herds in 2013. The within-herd prevalence was modelled using a hierarchical logistic regression model and included a spatial component modelled by a continuous Gaussian field. The Stochastic Partial Differential Equation (SPDE) approach and Integrated Nested Laplace Approximation (INLA) were used for Bayesian inference. We found a significant spatial component, and our results suggested that the estimated range of influence and the overall location of areas with increased prevalence are not very sensitive to diagnostic misclassification.

AB - Paratuberculosis is a chronic infection of economic importance to the dairy industry. The infection may be latent for years, which makes diagnostic misclassification a general challenge. The objective of this study was to identify the spatial pattern in infection prevalence, when results were adjusted for covariate information and diagnostic misclassification. Furthermore, we compared the estimated spatial pattern with the spatial pattern obtained without adjustment for misclassification. The study included 1242 herds in 2009 and 979 herds in 2013. The within-herd prevalence was modelled using a hierarchical logistic regression model and included a spatial component modelled by a continuous Gaussian field. The Stochastic Partial Differential Equation (SPDE) approach and Integrated Nested Laplace Approximation (INLA) were used for Bayesian inference. We found a significant spatial component, and our results suggested that the estimated range of influence and the overall location of areas with increased prevalence are not very sensitive to diagnostic misclassification.

U2 - 10.1016/j.sste.2015.10.001

DO - 10.1016/j.sste.2015.10.001

M3 - Journal article

C2 - 26919750

VL - 16

SP - 1

EP - 10

JO - Spatial and Spatio-temporal Epidemiology

JF - Spatial and Spatio-temporal Epidemiology

SN - 1877-5845

ER -

ID: 151955114