Optimizing distribution of pandemic influenza antiviral drugs

Bismark Singh*, Hsin Chan Huang, David P. Morton, Gregory P. Johnson, Alexander Gutfraind, Alison P. Galvani, Bruce Clements, Lauren A. Meyers

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

We provide a data-driven method for optimizing pharmacybased distribution of antiviral drugs during an influenza pandemic in terms of overall access for a target population and apply it to the state of Texas, USA. We found that during the 2009 influenza pandemic, the Texas Department of State Health Services achieved an estimated statewide access of 88% (proportion of population willing to travel to the nearest dispensing point). However, access reached only 34.5% of US postal code (ZIP code) areas containing <1,000 underinsured persons. Optimized distribution networks increased expected access to 91% overall and 60% in hard-to-reach regions, and 2 or 3 major pharmacy chains achieved near maximal coverage in well-populated areas. Independent pharmacies were essential for reaching ZIP code areas containing <1,000 underinsured persons. This model was developed during a collaboration between academic researchers and public health officials and is available as a decision support tool for Texas Department of State Health Services at a Web-based interface.

Original languageEnglish (US)
Pages (from-to)251-258
Number of pages8
JournalEmerging Infectious Diseases
Volume21
Issue number2
DOIs
StatePublished - 2015

ASJC Scopus subject areas

  • Epidemiology
  • Microbiology (medical)
  • Infectious Diseases

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