Performance of the Tariff Method: validation of a simple additive algorithm for analysis of verbal autopsies

Tariff calculates a score, or "tariff," for each cause, for each sign/symptom, across a pool of validated verbal autopsy data. The tariffs are summed for a given response pattern in a verbal autopsy, and this sum (score) provides the basis for predicting the cause of death in a dataset. We implemented this algorithm and evaluated the method's predictive ability, both in terms of chance-corrected concordance at the individual cause assignment level and in terms of CSMF accuracy at the population level. The analysis was conducted separately for adult, child, and neonatal verbal autopsies across 500 pairs of train-test validation verbal autopsy data.Tariff is capable of outperforming physician-certified verbal autopsy in most cases. In terms of chance-corrected concordance, the method achieves 44.5% in adults, 39% in children, and 23.9% in neonates. CSMF accuracy was 0.745 in adults, 0.709 in children, and 0.679 in neonates.Verbal autopsies can be an efficient means of obtaining cause of death data, and Tariff provides an intuitive, reliable method for generating individual cause assignment and CSMFs. The method is transparent and flexible and can be readily implemented by users without training in statistics or computer science.Verbal autopsies (VAs) are increasingly being used to provide information on causes of death in demographic surveillance sites (DSSs), national surveys, censuses, and sample registration schemes [1-3]. Physician-certified verbal autopsy (PCVA) is the primary method used to assign cause once VA data are collected. Several alternative expert-based algorithms [4-6], statistical methods [7-9], and computational algorithms [7] have been developed. These methods hold promise, but their comparative performance needs to be evaluated. Large-scale validation studies, such as the Population Health Metrics Research Consortium (PHMRC) [10], provide objective information on the performance of these different approaches.The main limitation to date of PCVA is