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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. [ABSTRACT FROM AUTHOR]

Background: African countries are working to achieve rapid reductions in maternal and child mortality and meet their targets for the Millennium Development Goals (MDGs). Partners in the Catalytic Initiative to Save One Million Lives (CI) are assisting them by providing funding and technical assistance to increase and accelerate coverage for proven interventions. Here we describe how the Lives Saved Tool (LiST) was used as part of an early assessment of the expected impact of CI plans in Malawi, Burkina Faso and Ghana.Methods: LiST builds on country-specific demographic and cause-of-death profiles, and models the effect of changes in coverage for proven interventions on future levels of mortality among children less than 5 years of age. We worked with representatives of Ministries of Health and their development partners to apply LiST to assess the potential impact of CI plans and coverage targets, generating a short list of the highest-priority interventions for additional scale-up to achieve rapid reductions in under-5 mortality.Results: The results show that in each country, achieving national coverage targets for just four or five high-impact interventions could reduce under-5 mortality by at least 20% by 2011, relative to 2006 levels. Even greater gains could be obtained in Burkina Faso and Ghana by scaling up these high-impact interventions to 80%. Discussion LiST can contribute to the development of stronger programmes by identifying the highest-impact interventions in a given epidemiological setting. The quality of LiST estimates is dependent on the available data on coverage levels and causes of death, and assumes that the target levels of coverage are feasible in a given context while maintaining service quality. Further experience is needed in the feasibility and usefulness of LiST as part of the program planning process at district and subdistrict levels. [ABSTRACT FROM AUTHOR]