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APHA Scientific Session and Event Listing

Theresa J. Jordan, PhD¹, Richard L. Montgomery, DDS, MPH², Gary L. Dillon Jr.¹, and Mark Kim¹. (1) Applied Psychology, New York University, 239 Greene St., Department of Applied Psychology, New York, NY 10003, 212-998-5378, theresa.jordan@nyu.edu, (2) School of Public Health, University of Medicine and Dentistry, 110 Bergen St., Newark, NJ 071003

One of the CDC's 2005 recommendations/objectives is to achieve 90% influenza vaccination coverage for U.S. populations aged 65 years and older. The need for prioritization of at-risk groups for vaccination is based on a history of seasons in which shortfalls of inactivated influenza vaccine have occurred. In their prioritization, the CDC generated tiers of risk, based on influenza-related mortalities as well as hospitalization and complication rates; and set elderly populations at high priority. Recent reports that have applied sophisticated correlational models to the Healthy People 2000 database were unable to reconcile increased vaccination coverage in the 65+ population with a concomitant increase in mortality rates. These reports appear to counter the CDC's recommendations, and can be interpreted as evidence to eliminate the elderly from prioritization. We contend that formal decision models rather than correlational models more aptly address the question of who to vaccinate under conditions of shortfall. In this investigation, we developed decision models including groups in contention for prioritization as well as low-tier middle adults. Sensitivity procedures were applied to cover vaccine efficacy rates from 38% to 90%, with a ceiling of 58% for older adults, and reflecting seasons when circulating viruses and vaccines are antigenically similar, as well as seasons when these were not well matched. When rates of complications and hospitalizations were used in the models as well as quality adjusted life expectancy outcomes rather than estimated mortalities alone, our models support the existing CDC recommendation to include the elderly population for prioritization.

Learning Objectives: At the conclusion of the session, the participant will be able to

• evaluate the utilization of decision models for analysis of a puplic health policy.
• assess the outcomes of policy decisions under different conditions of vaccine effectiveness and for different populations.

Keywords: Decision-Making, Policy/Policy Development

Presenting author's disclosure statement:

Any relevant financial relationships? No