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Using Spatial Analysis to Inform Community Immunization Strategies.

Moises E Maravi1, Lauren E Snyder1, L Dean McEwen1

  • 1Denver Public Health, Denver, CO, USA.

Biomedical Informatics Insights
|May 5, 2017
PubMed
Summary
This summary is machine-generated.

Spatial analysis of pertussis (whooping cough) outbreaks in Denver revealed disease clusters. Identifying these areas with low vaccination rates allows for targeted public health interventions to improve Bordetella pertussis control.

Keywords:
AutocorrelationImmunizationPertussisSpatial Analysis

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Area of Science:

  • Epidemiology
  • Geographic Information Systems (GIS)
  • Public Health

Background:

  • Pertussis (whooping cough) outbreaks necessitate improved local disease control strategies.
  • Spatial analytical methods using immunization data can enhance understanding of vaccine-preventable disease outbreaks at a subcounty level.

Purpose of the Study:

  • To apply spatial analytical methods to subcounty-level data for understanding pertussis outbreaks.
  • To assess the relationship between pertussis incidence and vaccination coverage using geocoded data.

Main Methods:

  • Geocoded pertussis cases and immunization records for Denver residents under 19.
  • Assessed up-to-date (UTD) vaccination status and calculated disease incidence rates.
  • Employed spatial analysis, including Moran's I statistics, to identify disease and vaccination coverage clusters.

Main Results:

  • Identified clusters of pertussis incidence and vaccination coverage in Denver census tracts.
  • Spatial analysis improved correlation estimates compared to raw data, revealing non-random distributions.
  • Highlighted 21 census tracts (15%) with high incidence and low coverage for targeted interventions.

Conclusions:

  • Simple correlations between raw incidence and vaccination rates in subcounty regions were insufficient for decision-making.
  • Spatial clustering analysis effectively identified areas for targeted public health interventions to combat pertussis.