First, the availability of data on morbidity and mortality, pathogenicity, host responses to infection, the resources and time required for vaccine development, and potential vaccine utilization varies tremendously for various diseases and national settings. Because this information is incomplete and because the features of vaccines not yet available, their development, and the behavior of health care providers and vaccine recipients cannot be predicted with certainty, any effort to set priorities must incorporate estimates or judgments.
Second, the selection of a structural framework in which to combine these expert opinions with available data does not in itself improve the quality of the data. Although equations may be employed to define how various elements should be organized, their use does not imply that the factors or the results have the accuracy sometimes associated with formal mathematical calculations.
The formal analytical methods described below and the system proposed by the committee in Chapter 3 can improve the quality of the decision-making process. They require identification of each factor contributing to a decision, which makes later reconstruction of the priority-setting process and examination of the effects of changing assumptions easier and more accurate.
The last part of this chapter considers some general issues in implementing any method of ranking, including sources of estimates, appropriate use of sequential or “lexicographic” methods, problems of interdependence among projects, and the “portfolio” question.
The ranking method requiring the least quantification and demanding the fewest normative assumptions is multiattribute accounting. This approach arrays the performance of each alternative on each valued objective, without attempting to produce an explicit overall score for each alternative. In deferring the final ranking to decision makers or consensus panels, multiattribute accounting differs from the other methods considered. In other respects, however, many of the steps in this process are identical to those required for the other techniques.
As in all the methods, the first step in multiattribute accounting is to specify the alternatives from which the projects will be selected. The second step is to define a set of valued objectives or criteria for the program (i.e., costs and benefits of various kinds). The result of the first two steps is to define the rows and columns of a matrix; a simplified example is shown in Table 2.1.
The third step is to fill in the cells in the matrix. Since multiattribute accounting requires no quantitative aggregation of scores across criteria (objectives), the entries in the matrix may be either quantitative or qualitative (e.g., high/medium/low). Table 2.1 contains both quantitative and qualitative information.
The fourth step is to determine if some candidates clearly dominate others, that is, perform equally well or better on all objectives. In Table 2.1, vaccine C is dominated by vaccine B and, therefore, should be ranked below vaccine B in the final rankings.