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Updated: May 20, 2026

Detection and Isolation of Campylobacter spp. from Raw Meat
Published on: February 23, 2024
The detection of spatially localised outbreaks in campylobacteriosis notification data
Simon E F Spencer1, Jonathan Marshall, Ruth Pirie
1Molecular Epidemiology and Veterinary Public Health Laboratory, Hopkirk Research Institute, Massey University, Private Bag 11 222, Palmerston North 4442, New Zealand. s.e.f.spencer@warwick.ac.uk
Abstract:
This paper applies a Bayesian hierarchical model designed to identify potential outbreaks of campylobacteriosis from a background of sporadic cases. We assume that such outbreaks are characterized by spatially-localised periods of increased incidence. As well as calculating an outbreak probability for each potential disease cluster, the model simultaneously estimates the underlying spatial and temporal distribution of sporadic cases. The model is applied to notification data from a region of New Zealand for the period 2001-2007 and correctly identifies known outbreaks, whilst highlighting an appropriate number of potential outbreaks for further investigation. Using simulated data, we show that if additional epidemiological information is included in the construction of the model then it can outperform an established method.
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