title: Using exceedance probabilities to detect anomalies in routinely recorded animal health data, with particular reference to foot-and-mouth disease in Viet Nam.
abstract: The widespread availability of computer hardware and software for recording and storing disease event information means that, in theory, we have the necessary information to carry out detailed analyses of factors influencing the spatial distribution of disease in animal populations. However, the reliability of such analyses depends on data quality, with anomalous records having the potential to introduce significant bias and lead to inappropriate decision making. In this paper we promote the use of exceedance probabilities as a tool for detecting anomalies when applying hierarchical spatio-temporal models to animal health data. We illustrate this methodology through a case study data on outbreaks of foot-and-mouth disease (FMD) in Viet Nam for the period 2006-2008. A flexible binomial logistic regression was employed to model the number of FMD infected communes within each province of the country. Standard analyses of the residuals from this model failed to identify problems, but exceedance probabilities identified provinces in which the number of reported FMD outbreaks was unexpectedly low. This finding is interesting given that these provinces are on major cattle movement pathways through Viet Nam.
authors.affiliation: Institute of Fundamental Sciences, Massey University, Private Bag 11-222, Palmerston North 4412, New Zealand.
authors.forename: K K
authors.initials: KK
authors.lastname: Richards
authors.affiliation: Institute of Fundamental Sciences, Massey University, Private Bag 11-222, Palmerston North 4412, New Zealand. Electronic address: m.hazelton@massey.ac.nz.
authors.forename: M L
authors.initials: ML
authors.lastname: Hazelton
authors.affiliation: EpiCentre, Institute of Veterinary, Animal, and Biomedical Sciences, Massey University, Private Bag 11-222, Palmerston North 4412, New Zealand.
authors.forename: M A
authors.initials: MA
authors.lastname: Stevenson
authors.affiliation: Food and Agriculture Organization of the United Nations, Viale delle Terme di Caracalla, Rome 00153, Italy.
authors.forename: C Y
authors.initials: CY
authors.lastname: Lockhart
authors.affiliation: Food and Agriculture Organization of the United Nations, Viale delle Terme di Caracalla, Rome 00153, Italy.
authors.forename: J
authors.initials: J
authors.lastname: Pinto
authors.affiliation: Department of Animal Health, Phuong Mai, Dong Da, Ha Noi, Viet Nam.
authors.forename: L
authors.initials: L
authors.lastname: Nguyen
mesh_terms: D000818:Animals; D002417:Cattle; D002418:Cattle Diseases / Q000453:epidemiology*; D004196:Disease Outbreaks / Q000706:statistics & numerical data* / Q000662:veterinary*; D005536:Foot-and-Mouth Disease / Q000453:epidemiology*; D016015:Logistic Models; D011336:Probability; D015203:Reproducibility of Results; D062206:Spatial Analysis; D014744:Vietnam / Q000453:epidemiology
keywords: Bayesian; Exceedance probabilities; Logistic regression; Random effects; Under-reporting; Veterinary epidemiology