7. Economic Approaches to Valuing Global Health Research

Although VOI calculations can be quite complex (for example, Claxton and others 2001), they need not be. For a researcher seeking funding, much simpler calculations may be sufficient to build a compelling case for funding. For example, quantifying the burden of illness in life years, QALYs, or DALYs lost and converting this into a burden or cost-of-illness measure in economic terms using an estimate of the statistical value of life may even be sufficient. To take a simple example, imagine a research program in a country with a statistical value of life of US$0.6 million (for example, the estimate for India) for a disease that currently kills 1,000 people per year. If one abstracts from issues such as the age of death and how one might differentially value deaths at different ages, this would have a potential value of US$0.6 billion per year. If the research study were viewed as having a 10 percent chance of preventing 50 percent of those deaths, its expected value would be P(success) x percent efficacy x statistical value of life = 0.1 x 0.5 x US$0.6 billion = US$30 million per year. Potential annual productivity gains produced by a successful treatment and annual costs of the treatment could be added to, or subtracted from, these US$0.6 billion annual benefits as well. One could go further, arguing that the research would be valuable into the future, and discount an infinite stream of those annual returns. At a discount rate (R) of 10 percent, this stream would have a value of US$20 million/R = US$200 million. This result suggests that a research program costing up to this amount would be worthwhile if it could be expected to have this likelihood of success and percent efficacy. Even if those probabilities could not be reliably estimated, minimum values could be calculated at which the research program would continue to be worthwhile.

As in their use in affluent countries, such calculations are likely to suggest that health research is of great value, often being predicted to return value many times its cost even accounting for uncertainty. In the preceding example, for instance, even an immense US$100 million research program would have an expected return 20 times as large. Such results would reflect the immense value in health research but would also suggest caution: with limited research funds, not all programs whose benefits exceed their costs should be funded if more valuable projects remain unfunded. In this area, funding agencies can be helpful to the research community by highlighting how they have used calculations such as these and publicizing the ratio of research costs to returns for those projects they have been able to fund. Even when a project is not funded despite a favorable ratio of expected returns to research costs, reporting the missed opportunity will serve as a reminder to the world community of the potential of health research for lower-income countries that remains unrealized and thereby, perhaps, promote greater investment in health research to benefit the people of these countries.