posted on 2016-05-04, 00:00authored byB. Singh, H.C. Huang, D.P. Morton, G.P. Johnson, A. Gutfraind, A.P. Galvani, B. Clements, L.A. Meyers
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.
Funding
This study was supported by the National Institutes of
Health (Models of Infectious Disease Agent Study grant U01
GM087719-01).