The regionality of campylobacteriosis seasonality in New Zealand

Int J Environ Health Res. 2003 Dec;13(4):337-48. doi: 10.1080/09603120310001616128.

Abstract

New Zealand has one of the highest incidences of campylobacteriosis in the developed world, which leads a global trend of increasing notifications of Campylobacter infections over the last decade. Foodborne and waterborne transmission have been implicated as significant mechanisms in the complex ecology of the disease in New Zealand. We examined both regional and temporal variation in notification rates to gain some insight into the role of the New Zealand environments in modifying disease incidence. Firstly, there is a marked difference in the seasonality of campylobacteriosis between the North and South Islands of New Zealand. The Far North and much of the rural North Island were found to display relatively low summer incidence and small inter-seasonal variation. Secondly, there appears to be a dispersed grouping of North Island urban areas, including Auckland, Hamilton, Napier and their hinterlands as well as a few areas on the South Island that exhibit higher summer incidence and more seasonality than the first group. Thirdly, Christchurch, Dunedin, much of the South Island and the lower North Island cities of Wellington and Upper Hutt appear to experience the highest summer incidence and strongest inter-seasonal variation in New Zealand. These three broad groupings of campylobacteriosis seasonality, constructed using a principal components analysis, suggest that the importance of transmission routes may vary regionally in New Zealand. The observed variation in seasonal incidence indicates a complex ecology that is unlikely to be explained by a single dominant transmission route across these three groupings.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Campylobacter Infections / epidemiology*
  • Campylobacter Infections / transmission
  • Epidemiologic Studies
  • Humans
  • Incidence
  • New Zealand
  • Principal Component Analysis*
  • Rural Population
  • Seasons
  • Time Factors
  • Urban Population