Quantitative modeling results
Burden of Disease
The largest contributors to under-five mortality in Rwanda in 2000 and 2015 are shown below.
Under-five mortality in Rwanda over time, death rates per 100,000 children under 5
Quantitative Modeling Approach
The research team collaborated with IHME to look at quantitative modeling results using a decomposition method, and also collaborated with the Johns Hopkins Bloomberg School of Public Health to model results using the Lives Saved Tool (LiST). These analyses complement the primary research by looking at what the models suggest about the likely contribution of specific interventions in reducing child mortality. A summary of the results is presented in the following sections.
The decomposition method estimates the percentage decline in U5M attributed to changes in risk factors and intervention coverage, based on efficacy assumptions derived from published literature.
From this method, the most significant contributor to the decline in Rwanda’s U5M rate is health interventions, which includes preventive measures like vaccines and curative treatments. Another significant contributor is program-related risk factors, which includes child growth failure, low birth weight, suboptimal breastfeeding, and vitamin A & zinc deficiency.
The decomposition analysis found an additional 18 percent reduction in child mortality (26 percent of the total reduction during this period) was attributed to risk factors corresponding to other communicable diseases, other non-communicable diseases, and other injuries. This reflects the portion of reduction in each of these causes of death (CoD) that is not accounted for by health systems interventions (bottom row).1
We checked these results against LiST estimates of the number of lives saved attributed to each intervention based on estimates of disease incidence and deaths from the United Nations Inter-Agency Group for Child Mortality Estimation (IGME), as well as assumptions about effectiveness of interventions from published literature.
This model attributes a total of 261,186 lives saved between 2000 and 2016 to specific health interventions, with the largest contributors being vaccines and supplements (especially Hib vaccine, measles vaccine, and Vitamin A), neonatal and antenatal interventions (particularly labor and delivery management and case management of neonatal sepsis and pneumonia), and Integrated Management of Childhood Illness (IMCI) treatments (especially oral antibiotics for pneumonia).2
Lives Saved tool results for Rwanda
Across both modeling methods, neonatal and antenatal interventions and vaccines are estimated to have had a significant impact on reducing under-five deaths in Rwanda. The results of the primary research findings on implementation outcomes for each intervention are presented in the next section. A description of the quantitative modeling methods can be found in the Methodology section.