Resources for the Future
Chow, Darley, and Laxminarayan
because their units are the same: Rs. per discounted year of healthy life. Since the vast majority of the disease burden in such cases typically is due to reduced life expectancy rather than disability during life, cost-effectiveness ratios that are reported in terms of Rs. per averted YLL would not be substantially lower if they took disability into account and could be reported as Rs. per averted DALY. In other words, considering only the disease burden from averted YLL results in more conservative estimates of cost-effectiveness. Finally, the particular characteristics of each disease and treatment necessitated methodological variation across analyses. Moreover, the estimates were based on the best available data, which were often weak. We therefore encourage readers to note the order of magnitude of each estimate rather than the specific number, particularly when comparing costeffectiveness of interventions for different diseases. III. Data and methods We conducted new analyses for all interventions except those for HIV/AIDS, cardiovascular diseases, and screening interventions for cervical and breast cancer, since recent cost-effectiveness analyses specific to India have been undertaken for these diseases by other researchers. For each new analysis, specific methods for calculating the costs and outcomes of disease interventions were designed based on the unique epidemiological characteristics of the disease and the nature of the investigated treatment. Detailed descriptions of the analytical methods and assumptions for each are described in their individual sections. Certain methods were common to all the analyses newly conducted for this study, though not necessarily for reviewed works. Wide disparities in the underlying disease burden exist between states in India. The impoverished EAGA states—Assam, Bihar, Chhattisgarh, Jharkand, Madhya Pradesh, Orissa, Rajasthan, Uttar Pradesh, and Uttarakhand—have approximately 47 percent of the total population of India but account for two-thirds of all neonatal deaths and two-thirds of all maternal deaths (SRS 2006). To help account for such differences, we calculated costs and effects for India as a whole, for the EAG states and Assam (EAGA), and for all other states combined (non-EAGA) where sufficient information (e.g., state-level coverage, morbidity, and mortality rates) allowed. These analyses considered only long-run marginal costs that vary with the number of individuals treated and did not include the fixed costs of initiating a program where none currently exists. Therefore, we did not vary the treatment costs and effectiveness rates between
6