Methods used in the Lives Saved Tool (LiST)

Winfrey, William; McKinnon, Robert; Stover, John

doi:10.1186/1471-2458-11-s3-s32

Cited by 70 publications

(63 citation statements)

References 7 publications

(5 reference statements)

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“…There is already evidence that LiST identifies priority areas for child health investment based on modelling the impact of evidence-based interventions at varying levels of coverage [15][16][17][18]20]. Although LiST has been mainly used to model the impact of scaling up maternal, newborn and child health intervention on child mortality [15][16][17][18][19][20], in our study, we presented the impact of reducing the prevalence of stunting on child survival in a rural setting. It is therefore important to note that the approach used in our study, models the impact of reducing stunted growth on child mortality but does not provide details on how stunting reduction can be achieved.…”

Section: Discussionmentioning

confidence: 99%

“…The Lives Saved Tool (LiST) [16][17][18][19][20] which is incorporated into the OneHealth software was used to estimate the impact of stunting reduction on child mortality and cases of stunting averted in two scenarios -a) halving the prevalence of stunting by 2040, b) zero stunted children in Buhweju district by 2040. The modelling period was set at 2017-2040 to align with the Uganda vision target of zero stunted growth by 2040 [7].…”

Section: Lives Saved and Number Of Cases Of Stunting Avertedmentioning

confidence: 99%

“…Several studies have used the Lives Saved Tool (LiST) in developing countries to model the impact of evidence-based interventions and stunting on child survival at national level [15][16][17][18][19][20]. However, the impact of stunting on child survival has not been formally modelled at sub-national level particularly in resourcelimited settings where the burden of child mortality is highest.…”

Section: Introductionmentioning

confidence: 99%

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Modelling the impact of stunting on child survival in a rural Ugandan setting

2018

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Background: Uganda ranks among the top 10 countries in the world for newborn and child mortality rates and among the top 34 for burden of stunting. This study was conducted to model the impact of stunting on child mortality in the southwest region of Uganda where the prevalence of stunting and child mortality are of great public health concern. Methods: The study was conducted in Buhweju district in the southwest region of Uganda. The study was cross-sectional involving use of a structured household questionnaire, focus group discussions and interviews with key informants in order to gather relevant information on infant and young child feeding (IYCF) and coverage of antenatal care (ANC) and vaccination programs. The survey of stunting, vaccination and ANC services covered 221 children aged 6-59 months while the assessment of IYCF practices covered 83 children aged 0-23. The Lives Saved Tool (LiST) was used to estimate the impact of stunting on child mortality and cases of stunting averted. Results: The study findings indicated that only 33% of the mothers had knowledge of optimal IYCF and 39% of the sampled children were exclusively breastfed. The majority of the mothers (57%) breastfed their children for less than 2 years and only 31% of the mothers practiced appropriate introduction of complementary foods at 6 months. Only 17% of the 0-23-month-olds received a good standard of IYCF. Only 37% of the mothers reportedly attended ANC 4 times or more during pregnancy and among children aged 6-59 months, only 28% were fully vaccinated. The high impact LiST model estimated that 1297 children under 5 years would be saved and 24,850 cases of stunting averted in the study district. Conclusions: The study concludes that IYCF practices and coverage of expanded programme on immunization (EPI) and ANC in the study population are sub-optimal thus the high prevalence of stunting and child mortality in the region. LiST demonstrated that prevention of stunting would reduce child mortality in rural Uganda. Therefore, increased investment in cost-effective child survival interventions targeting rural areas of Uganda would have a significant impact on stunting and child mortality.

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Section: Discussionmentioning

confidence: 99%

Section: Lives Saved and Number Of Cases Of Stunting Avertedmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Modelling the impact of stunting on child survival in a rural Ugandan setting

2018

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“…The population at-risk at the start of each phase is dependent on the coverage of interventions in the preceding phase. The methods for the estimation of intervention impact (% reduction in maternal, neonatal and under-five mortality) were adapted from the Lives Saved Tool (LiST) [12]. Deaths are first distributed into the major defined causes, then reduced by the cause-specific effectiveness (efficacy x marginal increase in coverage) of each intervention.…”

Section: Methodsmentioning

confidence: 99%

Investment case for improving maternal and child health: results from four countries

et al. 2013

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BackgroundWithout addressing the constraints specific to disadvantaged populations, national health policies such as universal health coverage risk increasing equity gaps. Health system constraints often have the greatest impact on disadvantaged populations, resulting in poor access to quality health services among vulnerable groups.MethodsThe Investment Cases in Indonesia, Nepal, Philippines, and the state of Orissa in India were implemented to support evidence-based sub-national planning and budgeting for equitable scale-up of quality MNCH services. The Investment Case framework combines the basic setup of strategic problem solving with a decision-support model. The analysis and identification of strategies to scale-up priority MNCH interventions is conducted by in-country planners and policymakers with facilitation from local and international research partners.ResultsSignificant variation in scaling-up constraints, strategies, and associated costs were identified between countries and across urban and rural typologies. Community-based strategies have been considered for rural populations served predominantly by public providers, but this analysis suggests that the scaling-up of maternal, newborn, and child health services requires health system interventions focused on 'getting the basics right'. These include upgrading or building facilities, training and redistribution of staff, better supervision, and strengthening the procurement of essential commodities. Some of these strategies involve substantial early capital expenditure in remote and sparsely populated districts. These supply-side strategies are not only the 'best buys', but also the 'required buys' to ensure the quality of health services as coverage increases. By contrast, such public supply strategies may not be the 'best buys' in densely populated urbanised settings, served by a mix of public and private providers. Instead, robust regulatory and supervisory mechanisms are required to improve the accessibility and quality of services delivered by the private sector. They can lead to important maternal mortality reductions at relatively low costs.ConclusionsNational strategies that do not take into consideration the special circumstances of disadvantaged areas risk disempowering local managers and may lead to a “business-as-usual” acceptance of unreachable goals. To effectively guide health service delivery at a local level, national plans should adopt typologies that reflect the different problems and strategies to scale up key MNCH interventions.

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“…We observed the expected change of mortality in maternal and under-fives and lives saved over the five-year period. Details on the assumptions built into the LiST module have been well documented elsewhere [23,24]. …”

Section: Methodsmentioning

confidence: 99%

Addressing inequity to achieve the maternal and child health millennium development goals: looking beyond averages

2012

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BackgroundInequity in access to and use of child and maternal health interventions is impeding progress towards the maternal and child health Millennium Development Goals. This study explores the potential health gains and equity impact if a set of priority interventions for mothers and under fives were scaled up to reach national universal coverage targets for MDGs in Tanzania.MethodsWe used the Lives Saved Tool (LiST) to estimate potential reductions in maternal and child mortality and the number of lives saved across wealth quintiles and between rural and urban settings. High impact maternal and child health interventions were modelled for a five-year scale up, by linking intervention coverage, effectiveness and cause of mortality using data from Tanzania. Concentration curves were drawn and the concentration index estimated to measure the equity impact of the scale up.ResultsIn the poorest population quintiles in Tanzania, the lives of more than twice as many mothers and under-fives were likely to be saved, compared to the richest quintile. Scaling up coverage to equal levels across quintiles would reduce inequality in maternal and child mortality from a pro rich concentration index of −0.11 (maternal) and −0.12 (children) to a more equitable concentration index of −0,03 and −0.03 respectively. In rural areas, there would likely be an eight times greater reduction in maternal deaths than in urban areas and a five times greater reduction in child deaths than in urban areas.ConclusionsScaling up priority maternal and child health interventions to equal levels would potentially save far more lives in the poorest populations, and would accelerate equitable progress towards maternal and child health MDGs.

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Methods used in the Lives Saved Tool (LiST)

Cited by 70 publications

References 7 publications

Modelling the impact of stunting on child survival in a rural Ugandan setting

Modelling the impact of stunting on child survival in a rural Ugandan setting

Investment case for improving maternal and child health: results from four countries

Addressing inequity to achieve the maternal and child health millennium development goals: looking beyond averages

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