Dealing with confounding when investigating time-space clustering of animal disease

Abstract

A one-dimensional scan statistic has been used to study disease clusters in time, and a two-dimensional scan statistic has been proposed for spatial disease clusters.
Kulldorf et al have proposed extending the use of the scan statistic, defined by a cylindrical window with a circular geographic base and height corresponding to time, for time-space clustering. By assuming the number of disease cases within the scanning window to be Poisson distributed, confounders can be controlled through indirect standardisation. This statistic also accommodates the uneven distribution of most populations. Multiple testing can be resolved by Monte Carlo simulation. Blowfly strike is a major economic disease in Australian sheep flocks. Breech and body strike are the most important types of flystrike. Risk factors for breech strike include diarrhoea and urine soiling, and weaner sheep and ewes are therefore more susceptible. Management procedures (eg. mulesing, crutching, tail docking, intestinal parasites control) are used to reduce susceptibility. Body strike appears to be strongly determined by climatic factors. Body and breech strike data were used in this study to assess application of the scan statistic to detect time-space clustering whilst controlling the potential confounding of flock structure.