ity of life (HRQOL) such as the Health Utilities Index Mark 2, or HUI2—a tool to measure morbidity reduction—have been developed using methods of multi-attribute utility theory (Feeny et al., 1996). HUI2 has been combined with actuarial measures of life expectancy changes in order to compute quality-adjusted life years (QALYs) as one of the main health valuation measures.

To derive its vaccine priorities, the 2000 report relied on incremental dollar costs per incremental QALY gained ($/QALY) for both preventive and therapeutic vaccines that are of importance to the United States. In the nearly three decades since the 1985–1986 report was published, the theoretical basis for its calculations has not changed. By contrast, in the years since the 2000 report, the methods of cost-effectiveness analysis have become somewhat more sophisticated when it comes to assessing the effectiveness of $/QALY values for health care technologies.

The self-reported health status data needed for population-based measures such as HUI2 are not available in much of the world. Instead, researchers at the World Health Organization in collaboration with researchers at other institutions developed a similar tool: disability-adjusted life years (DALYs). In calculating DALYs, disability weights are assigned to typical manifestations of a wide variety of diseases; such measures have been used for many countries around the world (Fox-Rushby and Hanson, 2001; Gold et al., 2002; Murray and Lopez, 2000).

Methods to incorporate uncertainties in decision models were undergoing rapid development at the time of the 2000 report. They have since progressed and become more generally applicable (Fenwick et al., 2001; Meckley et al., 2010). There have also been advances in population-based data collection supporting HUI2 and similar indexes of generic health-related quality of life that the 2000 report incorporated (Fryback et al., 2007, 2010; Luo et al., 2005, 2009).

In recent years, advances in complex systems modeling have helped characterize the nature and spread of infections in populations. These dynamical techniques can now be used for estimating the impact of a new vaccine for a specific population (e.g., Epstein et al., 2008). But the underlying decision framework and conceptual approaches to estimating costs and health benefits have essentially remained unchanged.

The previous reports developed a computational model based on two important (but distinctly different) attributes for prioritizing vaccines, although more sophisticated methods could have been used. The main criticism of the 2000 report was related to the basic framework itself: the system was too limited and considered only costs and aggregated health benefits (e.g., see Plotkin et al., 2000).



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