Strategic Policy for Pandemic Vaccine Distribution

Abstract

The traditional public health model for mass vaccination, which is based on the assumption that workforce will be sufficient to mount a campaign, is flawed. Funding initiatives by Congress, while addressing certain inadequacies, have failed to consider workforce capacity that continued to decline resulting from state and local budget cuts. Thus, as the nation prepared for its first pandemic in 40 years and first of the twenty-first century, it found itself unprepared for a mass vaccination campaign. This thesis explores pandemic vaccine distribution, contrasting Department of Health and Human Service guidance with pandemic gap analyses and the recent H1N1 vaccination campaign. An analysis of the literature revealed that unresolved state and federal distribution issues contributed to distribution delays during the H1N1 call for mass vaccination. Policy analysis was used to evaluate public health and private sector vaccine distribution models, and a third hybrid model was proposed to improve support for public health emergencies. Adoption of the hybrid model will enhance the vaccination process from production through distribution along with administration to support U.S national security interest in biosecurity. The hybrid model offers a strategic solution for pandemic vaccine distribution and proposes a new approach for efficient, rapid distribution of biological countermeasures.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2010
Accession Number
ADA531503

Entities

People

  • Thomas P. Russo

Organizations

  • Naval Postgraduate School

Tags

DTIC Thesaurus Topics

  • Biological Factors
  • Biological Products
  • Business Administration
  • Congress
  • Disease Outbreaks
  • Health Services
  • Hygiene
  • Infectious Diseases
  • Information Systems
  • Management Personnel
  • Medical Personnel
  • Organizational Structure
  • Patient Care
  • Public Health
  • Public Policy
  • United States Government
  • Vaccines

Readers

  • Computational Modeling and Simulation
  • Infectious Disease/Epidemiology
  • Joint Military Operations and Doctrine.

Technology Areas

  • Biotechnology