Use of a Bayesian risk-mapping technique to estimate spatial risks for mare reproductive loss syndrome in Kentucky.
Abstract: To estimate spatial risks associated with mare reproductive loss syndrome (MRLS) during 2001 among horses in a specific study population and partition the herd effects into those attributable to herd location and those that were spatially random and likely attributable to herd management. Animals-Pregnant broodmares from 62 farms in 7 counties in central Kentucky. Methods: Veterinarians provided the 2001 abortion incidence proportions for each farm included in the study. Farms were georeferenced and data were analyzed by use of a fully Bayesian risk-mapping technique. Results: Large farm-to-farm variation in MRLS incidence proportions was identified. The farm-to-farm variation was largely attributed to spatial location rather than to spatially random herd effects. Conclusions: Results indicate that there are considerable data to support an ecologic cause and potential ecologic risk factors for MRLS. Veterinary practitioners with more detailed knowledge of the ecology in the 7 counties in Kentucky that were investigated may provide additional data that would assist in the deduction of the causal factor of MRLS via informal geographic information systems analyses and suggest factors for inclusion in further investigations.
Publication Date: 2005-02-05 PubMed ID: 15691030DOI: 10.2460/ajvr.2005.66.17Google Scholar: Lookup
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- Journal Article
- Research Support
- Non-U.S. Gov't
- Bayesian Analysis
- Diagnosis
- Disease
- Disease control
- Disease Diagnosis
- Disease Etiology
- Disease Management
- Disease Outbreaks
- Disease Prevalence
- Disease Surveillance
- Disease Treatment
- Ecology
- Epidemiology
- Equine Diseases
- Equine Health
- Herd Management
- Horses
- Infection
- Infectious Disease
- Mare's Milk
- Pregnancy
- Risk Factors
- Spatial Analysis
- Vascular
- Veterinary Medicine
- Veterinary Research
- Veterinary Science
Summary
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The research article discusses how a Bayesian risk-mapping technique was used to estimate spatial risks associated with a horse disease known as Mare Reproductive Loss Syndrome (MRLS) in Kentucky. It found significant variation in the incidence of the disease from farm to farm and suggested an ecological causal factor for MRLS.
Objective of the Study
- The main objective of the paper was to estimate spatial risks associated with Mare Reproductive Loss Syndrome (MRLS) among the horse population in Kentucky during 2001. The researchers intended to separate the herd effects caused by herd location from those that were spatially random and likely due to herd management.
Methodology
- The study involved pregnant broodmares from 62 farms in 7 counties in central Kentucky. Veterinarians provided the 2001 abortion incidence proportions for each farm involved in the study.
- The farms were georeferenced and the data were analyzed using a fully Bayesian risk-mapping technique – a statistical method used to estimate and provide a graphical display of the geographical distribution of a particular disease.
Results
- The study found a significant variation in MRLS incidence proportions from farm to farm. The research found that this variation was largely due to spatial location rather than spatially random herd effects.
Conclusions
- The research concluded that there is substantial data to support an ecological cause and potential risk factors for MRLS. This suggests that location-based factors such as terrain, climate, flora and fauna may play a significant role in the occurrence and spread of MRLS.
- The study suggests that veterinary practitioners with granular understanding of the ecological conditions in the studied counties may provide more data to help identify the causal factor of MRLS through geographical information system analysis. This may further suggest elements to include in future investigations.
Cite This Article
APA
Thompson JA, Brown SE, Riddle WT, Seahorn JC, Cohen ND.
(2005).
Use of a Bayesian risk-mapping technique to estimate spatial risks for mare reproductive loss syndrome in Kentucky.
Am J Vet Res, 66(1), 17-20.
https://doi.org/10.2460/ajvr.2005.66.17 Publication
Researcher Affiliations
- Department of Large Animal Medicine and Surgery, College of Veterinary Medicine, Texas A&M University, College Station, TX 77843-4475, USA. USA.
MeSH Terms
- Abortion, Veterinary / epidemiology
- Animals
- Bayes Theorem
- Female
- Geography
- Horse Diseases / epidemiology
- Horses
- Kentucky / epidemiology
- Models, Statistical
- Pregnancy
- Risk Factors
Citations
This article has been cited 3 times.- Thompson JA, Bissett WT, Sweeney AM. Evaluating geostatistical modeling of exceedance probability as the first step in disease cluster investigations: very low birth weights near toxic Texas sites.. Environ Health 2014 Jun 7;13(1):47.
- Bissett W Jr, Smith R, Adams LG, Field R, Moyer W, Phillips T, Scott HM, Thompson JA. Geostatistical analysis of biomarkers of genotoxicity in cattle, Bos taurus and Bos taurus x Bos indicus, sentinels near industrial facilities.. Ecotoxicology 2009 Jan;18(1):87-93.
- Thompson JA, Scott HM. Bayesian kriging of seroprevalence to Mycobacterium avium subspecies paratuberculosis and Neospora caninum in Alberta beef and dairy cattle.. Can Vet J 2007 Dec;48(12):1281-5.
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