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Geographic disparities and socio-demographic predictors of pertussis risk in Florida

Corinne B Tandy1, Agricola Odoi1

  • 1Biomedical and Diagnostic Sciences, University of Tennessee, Knoxville, Tennessee, United States.

Peerj
|September 20, 2021
PubMed

Insights

Geographic disparities in pertussis (whooping cough) risk persist in Florida, with high-risk areas concentrated in specific regions. Rurality, higher median incomes, and a greater percentage of females were linked to increased pertussis risk.

Area of Science:

  • Epidemiology
  • Public Health
  • Spatial Analysis

Background:

  • Pertussis, a severe respiratory illness caused by Bordetella pertussis, poses a significant threat, especially to infants.
  • From 2008-2011, infants under 3 months accounted for 83% of US pertussis deaths.
  • Understanding geographic pertussis risk distribution is crucial for effective public health interventions.

Purpose of the Study:

  • To investigate geographic disparities and temporal trends in pertussis risk in Florida (2010-2018).
  • To identify socioeconomic and demographic predictors of these disparities.

Main Methods:

  • Utilized county-level pertussis data from Florida HealthCHARTS (2010-2018).
  • Employed spatial scan statistics to identify high-risk clusters.
  • Used ordinary least squares (OLS) regression to determine significant risk predictors.

Main Results:

  • Identified 11 significant spatial clusters (risk ratios 1.5-5.8).
  • High-risk areas persisted in the western panhandle, northeastern coast, and western coast.
  • Rurality, higher median incomes, and a greater percentage of females predicted higher pertussis risk.

Conclusions:

  • Geographic disparities in pertussis risk are evident and persistent in Florida.
  • Geographic Information Systems (GIS) and spatial epidemiological tools are vital for identifying high-risk areas.
  • Targeted resource allocation can help reduce health disparities and improve public health outcomes.
Abstract

Keywords:
Cluster detectionFlexScanFlexible scan statisticsGISGeographic information systemsOrdinary least squares regressionPertussisTango’s spatial scan statistics

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