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Published on: August 7, 2017

Spatiotemporal patterns of infant bronchiolitis in a Tennessee Medicaid population

Chantel D Sloan1, Tebeb Gebretsadik, Pingsheng Wu

  • 1Vanderbilt Center for Asthma & Environmental Health Sciences Research, Vanderbilt University Medical Center, Nashville, TN, United States.

Spatial and Spatio-Temporal Epidemiology
|August 20, 2013
PubMed

Insights

Respiratory syncytial virus (RSV) causes infant bronchiolitis epidemics that vary seasonally and geographically. This study found distinct timing patterns for RSV in East and Central Tennessee, highlighting the need for localized epidemic modeling.

Area of Science:

  • Epidemiology
  • Public Health
  • Pediatrics

Background:

  • Respiratory syncytial virus (RSV) is a leading cause of infant morbidity and mortality globally, primarily manifesting as bronchiolitis.
  • RSV epidemics exhibit significant seasonality, typically occurring during winter months in the Northern Hemisphere.
  • The spatiotemporal dynamics of RSV epidemics show considerable variation within regions, including the United States.

Purpose of the Study:

  • To analyze spatiotemporal patterns of infant bronchiolitis clusters.
  • To identify variations in the timing of RSV epidemics within Tennessee using a large Medicaid cohort.
  • To inform future RSV epidemic modeling by considering local factors.

Main Methods:

  • Utilized a retrospective space–time scan statistic analysis.
  • Examined a cohort of 52,468 infants (<6 months old) with outpatient, emergency department, or hospitalization records for bronchiolitis.
  • Data spanned from 1995 to 2008 within the Tennessee Medicaid population.

Main Results:

  • Identified distinct spatiotemporal clustering patterns of infant bronchiolitis.
  • Eastern Tennessee (Knoxville area) exhibited RSV epidemic clustering in January and February.
  • Central Tennessee (Nashville area) showed RSV epidemic clustering in November and December.

Conclusions:

  • RSV epidemic timing demonstrates consistent geographical variations within Tennessee.
  • Local geographical factors likely influence the observed differences in epidemic timing.
  • Future RSV epidemic modeling should incorporate these region-specific temporal dynamics.

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