Projecting the lives saved by continuing the historical scale-up of child and maternal health interventions in Mozambique until 2030

Abstract

Background Over the past 20 years, Mozambique has achieved substantial reductions in maternal, neonatal, and child mortality. However, mortality rates are still high, and to achieve the Sustainable Development Goals (SDGs) for maternal and child health, further gains are needed. One technique that can guide policy makers to more effectively allocate health resources is to model the coverage increases and lives saved that would be achieved if trends continue as they have in the past, and under differing alternative scenarios. Methods We used historical coverage data to project future coverage levels for 22 child and maternal interventions for 2015-2030 using a Bayesian regression model. We then used the Lives Saved Tool (LiST) to estimate the additional lives saved by the projected coverage increases, and the further child lives saved if Mozambique were to achieve universal coverage levels of selected individual interventions. Results If historical trends continue, coverage of all interventions will increase from 2015 to 2030. As a result, 180 080 child lives (0-59 months) and 3640 maternal lives will be saved that would not be saved if coverage instead stays constant from 2015 to 2030. Most child lives will be saved by preventing malaria deaths: 40.9% of the mortality reduction will come from increased coverage of artemisinin-based compounds for malaria treatment (ACTs) and insecticide treated bednets (ITNs). Most maternal lives will be saved from increased labor and delivery management (29.4%) and clean birth practices (17.1%). The biggest opportunity to save even more lives, beyond those expected by historical trends, is to further invest in malaria treatment. If coverage of ACTs was increased to 90% in 2030, rather than the anticipated coverage of 68.4% in 2030, an additional 3456 child lives would be saved per year. Conclusions Mozambique can expect to see continued reductions in mortality rates in the coming years, although due to population growth the absolute number of child deaths will decrease only marginally, the absolute number of maternal deaths will continue to increase, and the country will not achieve current SDG targets for either child or maternal mortality. Significant further health investments are needed to eliminate all preventable child and maternal deaths in the coming decades.

Projecting the Impact of Nutrition Policy to Improve Child Stunting: A Case Study in Guatemala Using the Lives Saved Tool

“…Our baseline scenario estimated future coverage levels based on past historical trends. As described below and similar to prior LiST analyses, 36 we estimated future trends in intervention coverage based on regression models of historical survey data. The key assumption of this scenario is that past intervention coverage trends predict future coverage.…”

Impact of mass distribution of long-lasting insecticidal nets (LLINs) in Mozambique, 2011 to 2025: Retrospective and prospective modeling of child mortality and lives saved

“…These mortality rate estimates do not re ect coverage changes in any other maternal and child health interventions, so actual rates in 2020 and 2025 would likely be lower. Junior et al used historical coverage data and mathematical modeling to project future coverage for 22 child and maternal health interventions from 2015 to 2030, estimating 29,302 child lives saved nationwide for the same period, second only to treatment with ACTs [11]. This was lower than projections from our models because estimated LLIN coverage was lower than actual and other interventions were not held constant.…”

“…Junior et al used historical coverage data and mathematical modeling to project future coverage levels for 22 interventions for 2015 to 2030, and then used LiST to estimate additional lives saved and changes in the child mortality rate over time [11]. However, the estimates did not take into account the actual number of LLINs distributed.…”

Projecting the impact of nutrition policy to improve child stunting: A case study in Guatemala using the Lives Saved Tool

“…Our baseline scenario projected future coverage levels based on past historical trends. As described below and similar to prior LiST analyses, 32 we projected future trends in intervention coverage based on regression models of historical survey data. The key assumption of this scenario is that past intervention coverage trends predict future coverage.…”

“…Shifting the trendline in this manner has been done in a prior LiST study and reflects our greater confidence in more recent survey estimates in Guatemala. 32 Stata version 16.1 was used in these analyses.…”