Dataset Information

Using the Lives Saved Tool to aid country planning in meeting mortality targets: a case study from Mali.

ABSTRACT: Mali is one of four countries implementing a National Evaluation Platform (NEP) to build local capacity to answer evaluation questions for maternal, newborn, child health and nutrition (MNCH&N). In 2014-15, NEP-Mali addressed questions about the potential impact of Mali's MNCH&N plans and strategies, and identified priority interventions to achieve targeted mortality reductions.The NEP-Mali team modeled the potential impact of three intervention packages in the Lives Saved Tool (LiST) from 2014 to 2023. One projection included the interventions and targets from Mali's ten-year health strategy (PDDSS) for 2014-2023, and two others modeled intervention packages that included scale up of antenatal, intrapartum, and curative interventions, as well as reductions in stunting and wasting. We modeled the change in maternal, newborn and under-five mortality rates under these three projections, as well as the number of lives saved, overall and by intervention.If Mali were to achieve the MNCH&N coverage targets from its health strategy, under-5 mortality would be reduced from 121 per 1000 live births to 93 per 1000, far from the target of 69 deaths per 1000. Projections 1 and 2 produced estimated mortality reductions from 121 deaths per 1000 to 70 and 68 deaths per 1000, respectively. With respect to neonatal mortality, the mortality rate would be reduced from 39 to 32 deaths per 1000 live births under the current health strategy, and to 25 per 1000 under projections 1 and 2.This study revealed that achieving the coverage targets for the MNCH&N interventions in the 2014-23 PDDSS would likely not allow Mali to achieve its mortality targets. The NEP-Mali team was able to identify two packages of MNCH&N interventions (and targets) that achieved under-5 and neonatal mortality rates at, or very near, the PDDSS targets. The Malian Ministry of Health and Public Hygiene is using these results to revise its plans and strategies.

SUBMITTER: Keita Y

PROVIDER: S-EPMC5688424 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Using the Lives Saved Tool to aid country planning in meeting mortality targets: a case study from Mali.

Keita Youssouf Y Sangho Hamadoun H Roberton Timothy T Vignola Emilia E Traoré Mariam M Munos Melinda M

BMC public health 20171107 Suppl 4

<h4>Background</h4>Mali is one of four countries implementing a National Evaluation Platform (NEP) to build local capacity to answer evaluation questions for maternal, newborn, child health and nutrition (MNCH&N). In 2014-15, NEP-Mali addressed questions about the potential impact of Mali's MNCH&N plans and strategies, and identified priority interventions to achieve targeted mortality reductions.<h4>Methods</h4>The NEP-Mali team modeled the potential impact of three intervention packages in the ...[more]

PMID: 29143682

Similar Datasets

Project description:The worldwide burden of stillbirths is large, with an estimated 2.6 million babies stillborn in 2015 including 1.3 million dying during labour. The Every Newborn Action Plan set a stillbirth target of ?12 per 1000 in all countries by 2030. Planning tools will be essential as countries set policy and plan investment to scale up interventions to meet this target. This paper summarises the approach taken for modelling the impact of scaling-up health interventions on stillbirths in the Lives Saved tool (LiST), and potential future refinements.The specific application to stillbirths of the general method for modelling the impact of interventions in LiST is described. The evidence for the effectiveness of potential interventions to reduce stillbirths are reviewed and the assumptions of the affected fraction of stillbirths who could potentially benefit from these interventions are presented. The current assumptions and their effects on stillbirth reduction are described and potential future improvements discussed.High quality evidence are not available for all parameters in the LiST stillbirth model. Cause-specific mortality data is not available for stillbirths, therefore stillbirths are modelled in LiST using an attributable fraction approach by timing of stillbirths (antepartum/ intrapartum). Of 35 potential interventions to reduce stillbirths identified, eight interventions are currently modelled in LiST. These include childbirth care, induction for prolonged pregnancy, multiple micronutrient and balanced energy supplementation, malaria prevention and detection and management of hypertensive disorders of pregnancy, diabetes and syphilis. For three of the interventions, childbirth care, detection and management of hypertensive disorders of pregnancy, and diabetes the estimate of effectiveness is based on expert opinion through a Delphi process. Only for malaria is coverage information available, with coverage estimated using expert opinion for all other interventions. Going forward, potential improvements identified include improving of effectiveness and coverage estimates for included interventions and addition of further interventions.Known effective interventions have the potential to reduce stillbirths and can be modelled using the LiST tool. Data for stillbirths are improving. Going forward the LiST tool should seek, where possible, to incorporate these improving data, and to continually be refined to provide an increasingly reliable tool for policy and programming purposes.

Project description:BackgroundDiarrhea is a leading cause of morbidity and mortality among children under five years of age. The Lives Saved Tool (LiST) is a model used to calculate deaths averted or lives saved by past interventions and for the purposes of program planning when costly and time consuming impact studies are not possible.DiscussionLiST models the relationship between coverage of interventions and outputs, such as stunting, diarrhea incidence and diarrhea mortality. Each intervention directly prevents a proportion of diarrhea deaths such that the effect size of the intervention is multiplied by coverage to calculate lives saved. That is, the maximum effect size could be achieved at 100% coverage, but at 50% coverage only 50% of possible deaths are prevented. Diarrhea mortality is one of the most complex causes of death to be modeled. The complexity is driven by the combination of direct prevention and treatment interventions as well as interventions that operate indirectly via the reduction in risk factors, such as stunting and wasting. Published evidence is used to quantify the effect sizes for each direct and indirect relationship. Several studies have compared measured changes in mortality to LiST estimates of mortality change looking at different sets of interventions in different countries. While comparison work has generally found good agreement between the LiST estimates and measured mortality reduction, where data availability is weak, the model is less likely to produce accurate results. LiST can be used as a component of program evaluation, but should be coupled with more complete information on inputs, processes and outputs, not just outcomes and impact.SummaryLiST is an effective tool for modeling diarrhea mortality and can be a useful alternative to large and expensive mortality impact studies. Predicting the impact of interventions or comparing the impact of more than one intervention without having to wait for the results of large and expensive mortality studies is critical to keep programs focused and results oriented for continued reductions in diarrhea and all-cause mortality among children under five years of age.

Project description:Background:As one of several countries that pledged to achieve the Millennium Development Goals (MDGs), Mozambique sought to reduce child, neonatal, and maternal mortality by two thirds by 2015. This study examines the impact of Mozambique's efforts between 1997 and 2015, highlighting the increases in intervention coverage that contributed to saving the most lives. Methods:A retrospective analysis of available household survey data was conducted using the Lives Saved Tool (LiST). Baseline mortality rates, cause-of-death distributions, and coverage of child, neonatal, and maternal interventions were entered as inputs. Changes in mortality rates, causes of death, and additional lives saved were calculated as results. Due to limited coverage data for the year 2015, we reported most results for the period 1997-2011. For 2011-2015 we reported additional lives saved for a subset of interventions. All analyses were performed at national and provincial level. Results:Our modelled estimates show that increases in intervention coverage from 1997 to 2011 saved an additional 422?282 child lives (0-59 months), 85?450 neonatal lives (0-1 month), and 6528 maternal lives beyond those already being saved at baseline coverage levels in 1997. Malaria remained the leading cause of child mortality from 1997 to 2011; prematurity, asphyxia, and sepsis remained the leading causes of neonatal mortality; and hemorrhage remained the leading cause of maternal mortality. Interventions to reduce acute malnutrition and promote artemisinin-based combination therapy (ACT) for malaria were responsible for the largest number of additional child lives saved in the 1997-2011 period. Increases in coverage of delivery management were responsible for most additional newborn and maternal lives saved in both periods in Mozambique. Conclusion:Mozambique has made impressive gains in reducing child mortality since 1997. Additional effort is needed to further reduce maternal and neonatal mortality in all provinces. More lives can be saved by continuing to increase coverage of existing health interventions and exploring new ways to reach underserved populations.

Project description:BackgroundKwaZulu-Natal province in South Africa has the largest population of children under the age of five and experiences the highest number of child births per annum in the country. Its population has also been ravaged by the dual epidemics of HIV and TB and it has struggled to meet targets for maternal and child mortality. In South Africa's federal system, provinces have decision-making power on the prioritization and allocation of resources within their jurisdiction. As part of strategic planning for 2015-2019, KwaZulu-Natal provincial authorities requested an assessment of current mortality levels in the province and identification and costing of priority interventions for saving additional maternal, newborn and child lives, as well as preventing stillbirths in the province.MethodsThe Lives Saved Tool (LiST) was used to determine the set of interventions, which could save the most additional maternal and child lives and prevent stillbirths from 2015-2019, and the costs of these. The impact of family planning was assessed using two scenarios by increasing baseline coverage of modern contraception by 0.5 percentage points or 1 percentage point per annum.ResultsA total of 7,043 additional child and 297 additional maternal lives could be saved, and 2,000 stillbirths could be prevented over five years. Seventeen interventions account for 75% of additional lives saved. Increasing family planning contributes to a further reduction of up to 137 maternal and 3,168 child deaths. The set of priority interventions scaled up to achievable levels, with no increase in contraception would require an additional US$91 million over five years or US$1.72 per capita population per year. By increasing contraceptive prevalence by one percentage point per year, overall costs to scale up to achievable coverage package, decrease by US$24 million over five years.ConclusionFocused attention on a set of key interventions could have a significant impact on averting stillbirths and maternal and neonatal mortality in KwaZulu-Natal. Concerted effort to prioritize family planning will save more lives overall and has the potential to decrease costs in other areas of maternal and child care.

Dataset Information

Using the Lives Saved Tool to aid country planning in meeting mortality targets: a case study from Mali.

Publications

Using the Lives Saved Tool to aid country planning in meeting mortality targets: a case study from Mali.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets