Detection of high risk campylobacteriosis clusters at three geographic levels

  • Jennifer Weisent | jweisent@utk.edu Department of Comparative and Experimental Medicine, College of Veterinary Medicine, The University of Tennessee, Knoxville TN, United States.
  • Barton Rohrbach Department of Comparative and Experimental Medicine, College of Veterinary Medicine, The University of Tennessee, Knoxville TN, United States.
  • John R. Dunn Tennessee Department of Health, Communicable and Environmental Disease Service, Nashville, TN, United States.
  • Agricola Odoi Department of Comparative and Experimental Medicine, College of Veterinary Medicine, The University of Tennessee, Knoxville TN, United States.

Abstract

Campylobacteriosis is a leading cause of bacterial gastroenteritis in the United States and many other developed countries. Understanding the spatial distribution of this disease and identifying high-risk areas is vital to focus resources for prevention and control measures. In addition, determining the appropriate scale for geographical analysis of surveillance data is an area of concern to epidemiologists and public health officials. The purpose of this study was to (i) compare standardized risk estimates for campylobacteriosis in Tennessee over three distinct geographical scales (census tract, zip code and county subdivision), and (ii) identify and investigate high-risk spatial clustering of campylobacteriosis at the three geographical scales to determine if clustering is scale dependent. Significant high risk clusters (P <0.05) were detected at all three spatial scales. There were overlaps in regions of high-risk and clusters at all three geographic levels. At the census tract level, spatial analysis identified smaller clusters of finer resolution and detected more clusters than the other two levels. However, data aggregation at zip code or county subdivision yielded similar findings. The importance of this line of research is to create a framework whereby economically efficient disease control strategies become more attainable through improved geographical precision and risk detection. Accurate identification of disease clusters for campylobacteriosis can enable public health personnel to focus scarce resources towards prevention and control programmes on the most at-risk populations. Consistent results at multiple spatial levels highlight the robustness of the geospatial techniques utilized in this study. Furthermore, analyses at the zip code and county subdivision levels can be useful when address level information (finer resolution data) are not available. These procedures may also be used to help identify regionally specific risk factors for campylobacteriosis

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Published
2011-11-01
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Original Articles
Keywords:
cluster detection, spatial smoothing, Campylobacter, USA.
Statistics
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How to Cite
Weisent, J., Rohrbach, B., Dunn, J. R., & Odoi, A. (2011). Detection of high risk campylobacteriosis clusters at three geographic levels. Geospatial Health, 6(1), 65-76. https://doi.org/10.4081/gh.2011.158