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Bayesian Geostatistical Analysis and Ecoclimatic Determinants of Corynebacterium pseudotuberculosis Infection among Horses.

Boysen C, Davis EG, Beard LA, Lubbers BV, Raghavan RK - PLoS ONE (2015)

Bottom Line: Covariate information for environmental and climatic determinants were obtained from USDA (soil attributes), USGS (land use/land cover), and NASA MODIS and NASA Prediction of Worldwide Renewable Resources (climate).Candidate covariates were screened using univariate regression models followed by Bayesian geostatistical models with and without covariates.Preventative and ecoclimatic significance of these findings are discussed.

View Article: PubMed Central - PubMed

Affiliation: Department of Clinical Sciences, College of Veterinary Medicine, Kansas State University, Manhattan, Kansas, United States of America.

ABSTRACT
Kansas witnessed an unprecedented outbreak in Corynebacterium pseudotuberculosis infection among horses, a disease commonly referred to as pigeon fever during fall 2012. Bayesian geostatistical models were developed to identify key environmental and climatic risk factors associated with C. pseudotuberculosis infection in horses. Positive infection status among horses (cases) was determined by positive test results for characteristic abscess formation, positive bacterial culture on purulent material obtained from a lanced abscess (n = 82), or positive serologic evidence of exposure to organism (≥ 1:512)(n = 11). Horses negative for these tests (n = 172)(controls) were considered free of infection. Information pertaining to horse demographics and stabled location were obtained through review of medical records and/or contact with horse owners via telephone. Covariate information for environmental and climatic determinants were obtained from USDA (soil attributes), USGS (land use/land cover), and NASA MODIS and NASA Prediction of Worldwide Renewable Resources (climate). Candidate covariates were screened using univariate regression models followed by Bayesian geostatistical models with and without covariates. The best performing model indicated a protective effect for higher soil moisture content (OR = 0.53, 95% CrI = 0.25, 0.71), and detrimental effects for higher land surface temperature (≥ 35°C) (OR = 2.81, 95% CrI = 2.21, 3.85) and habitat fragmentation (OR = 1.31, 95% CrI = 1.27, 2.22) for C. pseudotuberculosis infection status in horses, while age, gender and breed had no effect. Preventative and ecoclimatic significance of these findings are discussed.

No MeSH data available.


Related in: MedlinePlus

Case control distribution in the study region.Dark circles indicate case locations and open circles are control locations.
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pone.0140666.g001: Case control distribution in the study region.Dark circles indicate case locations and open circles are control locations.

Mentions: Most cases reported to VHC and KSVDL during the 2012 outbreak originated from Kansas, and few were from neighboring Nebraska and Missouri (Fig 1). With a mid-latitude and continental location, temperature extremes in Kansas occur in July (26°C) and January (−1.6°C) (30 year averages). Over 70% of the precipitation occurs during the warm season, with a peak in June (105 mm) and the minimum in January (18 mm) (30 year averages) [12]. There are large variations in the yearly precipitation received across the state of Kansas, with eastern Kansas receiving up to three times more rainfall than west [13]. As a result, climate and vegetation are transitional between the humid east and semi-arid western portions of Kansas.


Bayesian Geostatistical Analysis and Ecoclimatic Determinants of Corynebacterium pseudotuberculosis Infection among Horses.

Boysen C, Davis EG, Beard LA, Lubbers BV, Raghavan RK - PLoS ONE (2015)

Case control distribution in the study region.Dark circles indicate case locations and open circles are control locations.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4608828&req=5

pone.0140666.g001: Case control distribution in the study region.Dark circles indicate case locations and open circles are control locations.
Mentions: Most cases reported to VHC and KSVDL during the 2012 outbreak originated from Kansas, and few were from neighboring Nebraska and Missouri (Fig 1). With a mid-latitude and continental location, temperature extremes in Kansas occur in July (26°C) and January (−1.6°C) (30 year averages). Over 70% of the precipitation occurs during the warm season, with a peak in June (105 mm) and the minimum in January (18 mm) (30 year averages) [12]. There are large variations in the yearly precipitation received across the state of Kansas, with eastern Kansas receiving up to three times more rainfall than west [13]. As a result, climate and vegetation are transitional between the humid east and semi-arid western portions of Kansas.

Bottom Line: Covariate information for environmental and climatic determinants were obtained from USDA (soil attributes), USGS (land use/land cover), and NASA MODIS and NASA Prediction of Worldwide Renewable Resources (climate).Candidate covariates were screened using univariate regression models followed by Bayesian geostatistical models with and without covariates.Preventative and ecoclimatic significance of these findings are discussed.

View Article: PubMed Central - PubMed

Affiliation: Department of Clinical Sciences, College of Veterinary Medicine, Kansas State University, Manhattan, Kansas, United States of America.

ABSTRACT
Kansas witnessed an unprecedented outbreak in Corynebacterium pseudotuberculosis infection among horses, a disease commonly referred to as pigeon fever during fall 2012. Bayesian geostatistical models were developed to identify key environmental and climatic risk factors associated with C. pseudotuberculosis infection in horses. Positive infection status among horses (cases) was determined by positive test results for characteristic abscess formation, positive bacterial culture on purulent material obtained from a lanced abscess (n = 82), or positive serologic evidence of exposure to organism (≥ 1:512)(n = 11). Horses negative for these tests (n = 172)(controls) were considered free of infection. Information pertaining to horse demographics and stabled location were obtained through review of medical records and/or contact with horse owners via telephone. Covariate information for environmental and climatic determinants were obtained from USDA (soil attributes), USGS (land use/land cover), and NASA MODIS and NASA Prediction of Worldwide Renewable Resources (climate). Candidate covariates were screened using univariate regression models followed by Bayesian geostatistical models with and without covariates. The best performing model indicated a protective effect for higher soil moisture content (OR = 0.53, 95% CrI = 0.25, 0.71), and detrimental effects for higher land surface temperature (≥ 35°C) (OR = 2.81, 95% CrI = 2.21, 3.85) and habitat fragmentation (OR = 1.31, 95% CrI = 1.27, 2.22) for C. pseudotuberculosis infection status in horses, while age, gender and breed had no effect. Preventative and ecoclimatic significance of these findings are discussed.

No MeSH data available.


Related in: MedlinePlus