A New Tool for Measuring the Brutality of War

Earlier this year, Hans Rosling, Professor of International Health at the Karolinska Institute, Sweden, delivered the 2008 International Health Lecture for the Academy of Medical Sciences in London, a lecture entitled “A factbased world view”. Rosling co-founded the Gapminder project (http://www. gapminder.org/): animated software that makes a multitude of quantitative datasets visible and meaningful. It was fascinating in his lecture to see health and wealth data from 166 countries move through time, making some important messages visible to a broad audience. For instance, Rosling showed the major health improvements over the last couple of decades in most countries in the world, in comparison to a small set of countries where all health development seems to have totally stagnated. This stagnant set of countries consists of most African countries and a number of conflictaffected countries elsewhere, such as Afghanistan. In theory at least, mortality rates during war should not need the kind of visual tools that Rosling uses to make an impact—they should speak for themselves. For example, a series of mortality surveys conducted by the International Rescue Committee in the Democratic Republic of the Congo found an excess of almost 4 million deaths between 1998–2004, all attributable to the ongoing conflict [1]. However, when reported mortality rates are high, they may be challenged by those who do not like the message. Comparable mortality surveys in Northern Uganda and Darfur were contested, which undermined their credibility. A similar fate befell one of the mortality surveys in Iraq, which estimated that 650,000 deaths in Iraq had occurred since the invasion in 2003 [2]. While this number made the survey headline news, it was also subject to a range of criticisms that undermined the report’s main message, which was that many had died as a result of the invasion. Despite their potential to clearly convey the brutality of war, mortality surveys have rarely been conducted in so-called “modern wars” [3]—the International Rescue Committee studies in the Democratic Republic of the Congo were some of the first such surveys. It is obviously not easy to conduct large-scale populationbased surveys in areas affected by conflict. But sometimes even larger challenges loom when communicating the findings. A mortality figure based on a survey may appear unambiguous, but critics tend to exploit the public’s unfamiliarity with sampling methods, inferences from samples, and resulting confidence intervals to undermine the credibility of the report. Some recent publications [4,5] and a dedicated Web site [6] specifically aim to support field staff, donors, journalists, and others in understanding epidemiological studies in crisis situations. The Importance of Indices