Advances in verbal autopsy: pragmatic optimism or optimistic theory?

Methodological development in recent years, particularly in relation to probabilistic interpretation of VA data, has brought VA into an exciting era that is creating new opportunities for reliable, timely, and useful cause-specific mortality measurement. A shift away from limited individual-level and clinical paradigms towards population-based epidemiological thinking and public health utility has been characterized by a flurry of new methodological thinking and innovations from relatively small groups of researchers. Among these like-minded researchers, however, there is risk of a divide between pragmatic optimists and optimistic theorists. The pragmatic optimists are driven by the realities, perils, and pitfalls of real-life health measurement in low-income settings and strive to enhance health knowledge with methods that are good enough to fill data gaps reliably and efficiently. The optimistic theorists, whose methodological developments are often theoretically superior, are often far from offering practical solutions to those on the ground who need to know the major burdens of cause-specific mortality in their populations simply, quickly, and cheaply in the absence of pre-existing data and where "true validity" is difficult to establish. Such dichotomization is perhaps somewhat artificial, but there is a real risk that unrealistic standards and expectations in method development and evaluation will become the enemy of good enough methods that are able to provide essential data to those who need it.The Global Congress on VA was attended by over 100 delegates representing numerous agencies and academic institutions from around the globe. This level of participation illustrates not only the persistent desire to know who died from what in the world's poorest settings, but also a desire for clear leadership on what the best methods are and how to use them. Whilst methodological favoritism, ideology, and competition can be a threat to an objective answer to this ques