Abstract
BackgroundThere is a growing body of evidence that integrated packages of community-based interventions, a form of programming often implemented by NGOs, can have substantial child mortality impact. More countries may be able to meet Millennium Development Goal (MDG) 4 targets by leveraging such programming. Analysis of the mortality effect of this type of programming is hampered by the cost and complexity of direct mortality measurement. The Lives Saved Tool (LiST) produces an estimate of mortality reduction by modelling the mortality effect of changes in population coverage of individual child health interventions. However, few studies to date have compared the LiST estimates of mortality reduction with those produced by direct measurement.MethodsUsing results of a recent review of evidence for community-based child health programming, a search was conducted for NGO child health projects implementing community-based interventions that had independently verified child mortality reduction estimates, as well as population coverage data for modelling in LiST. One child survival project fit inclusion criteria. Subsequent searches of the USAID Development Experience Clearinghouse and Child Survival Grants databases and interviews of staff from NGOs identified no additional projects. Eight coverage indicators, covering all the project’s technical interventions were modelled in LiST, along with indicator values for most other non-project interventions in LiST, mainly from DHS data from 1997 and 2003.ResultsThe project studied was implemented by World Relief from 1999 to 2003 in Gaza Province, Mozambique. An independent evaluation collecting pregnancy history data estimated that under-five mortality declined 37% and infant mortality 48%. Using project-collected coverage data, LiST produced estimates of 39% and 34% decline, respectively.ConclusionsLiST gives reasonably accurate estimates of infant and child mortality decline in an area where a package of community-based interventions was implemented. This and other validation exercises support use of LiST as an aid for program planning to tailor packages of community-based interventions to the epidemiological context and for project evaluation. Such targeted planning and assessments will be useful to accelerate progress in reaching MDG4 targets.
Highlights
There is a growing body of evidence that integrated packages of community-based interventions, a form of programming often implemented by NGOs, can have substantial child mortality impact
The available data was not collected as part of a research project, the coverage data input into Lives Saved Tool (LiST) was of sufficient quality to generate relatively accurate estimates within the limits of the tool
Project interventions targeted children 0-59 month olds, which is the cohort modeled in LiST and whose mortality was measured directly in the pregnancy history, the coverage data used for LiST was collected for children 0-23 months old
Summary
There is a growing body of evidence that integrated packages of community-based interventions, a form of programming often implemented by NGOs, can have substantial child mortality impact. The Lives Saved Tool (LiST) produces an estimate of mortality reduction by modelling the mortality effect of changes in population coverage of individual child health interventions. There are encouraging trends in some key countries, meeting Millennium Development Goal (MDG) 4 for reduction of child mortality will be challenging, given current trends.[1] Community-based intervention packages are not commonly implemented at large scale, recent evidence demonstrates that they are effective for neonatal and child mortality reduction at moderate scale in various resource-constrained settings. The Lives Saved Tool (LiST) produces mortality reduction estimates by modelling the mortality effect of increases in population coverage for key child health interventions. LiST calculates this by combining coverage change data with data on effectiveness of each intervention against common serious child illnesses, and country-specific cause of death profiles. Population based surveys in which mortality is directly measured are costly, difficult, and time-consuming, and LiST modelling could be an attractive alternative to estimate mortality reduction
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