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Population Segmentation for COVID-19 Vaccine Outreach: A Clustering Analysis and Implementation in Missouri.

Eleanor G ChessenMadelyn E GanserColin A PaulishAamia MalikAllison G WishnerGeorge TurabelidzeJeffrey J Glenn
Published in: Journal of public health management and practice : JPHMP (2023)
The segmentation analysis served as the foundation for "working groups" comprising the 115 local public health agencies (LPHAs) across the state. LPHAs with similar community segments in their service area were grouped together to discuss their communities' specific challenges, share lessons learned, and brainstorm new approaches. The working groups provided a novel way for public health to organize and collaborate across the state. Widening the aperture beyond Missouri, population segmentation via cluster analysis is a promising approach for public health practitioners interested in developing a richer understanding of the types of populations they serve. By pairing segmentation with behavioral science, practitioners can develop outreach programs and communications campaigns that are personalized to the specific behavioral barriers and needs of the population in focus. While our work focused on COVID-19, this approach has broad applicability to enhance the way public health practitioners understand the populations they serve to deliver more tailored services.
Keyphrases
  • public health
  • primary care
  • deep learning
  • healthcare
  • mental health
  • convolutional neural network
  • coronavirus disease
  • sars cov
  • global health
  • rna seq
  • respiratory syndrome coronavirus
  • quality improvement