Background: In the absence of planned efforts to target the poor, child survival programs often favour the rich. Further evidence is needed urgently about which interventions and programme approaches are most effective in addressing inequities. The Lives Saved Tool (LiST) is available and can be used to model mortality levels across economic groups based on coverage levels for child survival interventions.
Methods: We used LiST to model neonatal and under-5 mortality levels among the highest and the lowest wealth quintiles in Bangladesh based on national and wealth-quintile-specific coverage of child survival interventions. The cause-of-death structure among children under-5 was also modelled using the coverage levels. Modelled rates were compared to the rates measured directly from the 2004 Bangladesh Demographic and Health Survey and associated verbal autopsies.
Results: Modelled estimates of mortality within wealth quintiles fell within the 95% confidence intervals of measured mortality for both neonatal and post-neonatal mortality. LiST also performed well in predicting the cause-of-death structure for these two age groups for the poorest quintile of the population, but less well for the richest quintile.
Conclusions: LiST holds promise as a useful tool for assessing socio-economic inequities in child survival in low-income countries.