Comparison of covariate adjustment methods using space-time scan statistics for food animal syndromic surveillance.
BACKGROUND
Abattoir condemnation data show promise as a rich source of data for syndromic surveillance of both animal and zoonotic diseases. However, inherent characteristics of abattoir condemnation data can bias results from space-time cluster detection methods for disease surveillance, and may need to be accounted for using various adjustment methods. The objective of this study was to compare the space-time scan statistics with different abilities to control for covariates and to assess their suitability for food animal syndromic surveillance. Four space-time scan statistic models were used including: animal class adjusted Poisson, space-time permutation, multi-level model adjusted Poisson, and a weighted normal scan statistic using model residuals. The scan statistics were applied to monthly bovine pneumonic lung and "parasitic liver" condemnation data from Ontario provincial abattoirs from 2001-2007.


RESULTS
The number and space-time characteristics of identified clusters often varied between space-time scan tests for both "parasitic liver" and pneumonic lung condemnation data. While there were some similarities between isolated clusters in space, time and/or space-time, overall the results from space-time scan statistics differed substantially depending on the covariate adjustment approach used.


CONCLUSIONS
Variability in results among methods suggests that caution should be used in selecting space-time scan methods for abattoir surveillance. Furthermore, validation of different approaches with simulated or real outbreaks is required before conclusive decisions can be made concerning the best approach for conducting surveillance with these data.
Department of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, ON N1G 2W1, Canada. altong@uoguelph.ca.
Gillian D
GD
Alton
David L
DL
Pearl
Ken G
KG
Bateman
Bruce
B
McNab
Olaf
O
Berke
D000003:Abattoirs; D000820:Animal Diseases / Q000175:diagnosis / Q000453:epidemiology*; D000818:Animals; D002417:Cattle; D002418:Cattle Diseases / Q000175:diagnosis / Q000453:epidemiology; D016000:Cluster Analysis; D004196:Disease Outbreaks / Q000706:statistics & numerical data*; D059022:Food Safety; D008109:Liver Diseases, Parasitic / Q000175:diagnosis / Q000453:epidemiology / Q000662:veterinary; D058751:Livestock; D008297:Male; D009864:Ontario / Q000453:epidemiology; D010626:Phenylethyl Alcohol / Q000031:analogs & derivatives; D011014:Pneumonia / Q000175:diagnosis / Q000453:epidemiology / Q000662:veterinary; D016012:Poisson Distribution; D011159:Population Surveillance / Q000379:methods*; D062211:Spatio-Temporal Analysis
C039407:4-methyl-1-phenylpentan-2-ol; D010626:Phenylethyl Alcohol