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Spatiotemporal analysis of invasive meningococcal disease, Germany

Johannes Elias1, Dag Harmsen, Heike Claus

  • 1University of Würzburg, Würzburg, Germany.

Emerging Infectious Diseases
|February 8, 2007
PubMed

Insights

Molecular fine-typing and spatiotemporal analysis identified 26 significant meningococcal disease clusters in Germany. This approach helps assess infectious disease outbreaks in large populations.

Area of Science:

  • Epidemiology
  • Microbiology
  • Public Health

Background:

  • Meningococci are known to cause disease clusters.
  • Effective surveillance requires understanding disease distribution and transmission patterns.

Purpose of the Study:

  • To apply molecular fine-typing and spatiotemporal analysis to identify and characterize meningococcal disease clusters in Germany.
  • To assess the utility of combining these methods for infectious disease surveillance.

Main Methods:

  • Serogrouping and sequence typing of PorA and FetA genes for molecular fine-typing of 1,616 patient specimens.
  • Retrospective spatiotemporal scan statistic (SaTScan) analysis to detect significant disease clusters.
  • Definition of finetypes based on PorA and FetA variable regions (VRs).

Main Results:

  • A highly diverse dataset of meningococcal strains was generated (Simpson's index 0.963).
  • A total of 26 significant spatiotemporal clusters (p<=0.05) were detected.
  • Clusters averaged 2.6 patients, with a median population of 475,011 and duration of 4.0 days. 4.2% of cases were in clusters.

Conclusions:

  • The combination of molecular fine-typing and spatiotemporal analysis is effective for identifying meningococcal disease clusters.
  • This integrated approach enhances the assessment of infectious diseases in large European countries.
  • The findings provide insights into meningococcal disease epidemiology and support targeted public health interventions.

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