Comparing modelled to measured mortality reductions: applying the Lives Saved Tool to evaluation data from the Accelerated Child Survival Programme in West Africa

Background The Lives Saved Tool (LiST) projects the magnitude of mortality reduction based on baseline coverage, demographic characteristics and coverage targets. As a validation exercise, we compared neonatal, post-neonatal, infant, child and under-5 mortality reductions as projected by LiST to changes in mortality measured through demographic surveys in Ghana and Mali as part of a recently completed, retrospective evaluation of a child survival programme. Methods Using coverage and other information collected during the evaluation, we modelled the predicted mortality reduction, using logical assumptions to fill gaps if no data were available. We performed a sensitivity analysis on several indicators for which we used a proxy, using the results to examine model sensitivity and readdress our assumptions. Results In Ghana, the modelled mortality reductions were within the 95% confidence boundaries of the measured reduction. In Mali LiST significantly underestimated the reduction. Several coverage indicators were found to influence the projection, specifically case management of serious neonatal illness in both countries and pneumonia treatment, vitamin A measles treatment and breastfeeding promotion in Mali. Conclusions We consider LiST to be a useful tool given the limitations of the available data. Although the model was a good match in Ghana, we identified several limiting factors with the input data in the Mali projection. This exercise highlights the importance of continually improving the availability of sound demographic, epidemiological and intervention coverage data at district and national levels. More comparative studies are needed to fully assess the strengths and weaknesses of LiST.