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Record W2763443614 · doi:10.1016/s2214-109x(17)30331-5

How Ethiopia achieved Millennium Development Goal 4 through multisectoral interventions: a Countdown to 2015 case study

2017· article· en· W2763443614 on OpenAlexfundaboutno aff
Jenny Ruducha, Carlyn Mann, Neha Singh, Tsegaye Demisse Gemebo, Negussie S. Tessema, Angela Baschieri, Ingrid K. Friberg, Taddese Alemu Zerfu, Mohammed A. Yassin, Giovanny Araújo França, Peter Berman

Bibliographic record

VenueThe Lancet Global Health · 2017
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsnot available
FundersGovernment of CanadaUNICEFBill and Melinda Gates Foundation
KeywordsCountdownMillennium Development GoalsPsychological interventionChild mortalityReproductive healthEnvironmental healthHealth equityMedicineInfant mortalityDemographyHealth indicatorPublic healthDeveloping countryEconomic growthSocioeconomicsPopulationEconomicsNursing

Abstract

fetched live from OpenAlex

BACKGROUND: 3 years before the 2015 deadline, Ethiopia achieved Millennium Development Goal 4. The under-5 mortality decreased 69%, from 205 deaths per 1000 livebirths in 1990 to 64 deaths per 1000 livebirths in 2013. To understand the underlying factors that contributed to the success in achieving MDG4, Ethiopia was selected as a Countdown to 2015 case study. METHODS: We used a set of complementary methods to analyse progress in child health in Ethiopia between 1990 and 2014. We used Demographic Health Surveys to analyse trends in coverage and equity of key reproductive, maternal health, and child health indicators. Standardised tools developed by the Countdown Health Systems and Policies working group were used to understand the timing and content of health and non-health policies. We assessed longitudinal trends in health-system investment through a financial analysis of National Health Accounts, and we used the Lives Saved Tool (LiST) to assess the contribution of interventions towards reducing under-5 mortality. FINDINGS: The annual rate of reduction in under-5 mortality increased from 3·3% in 1990-2005 to 7·8% in 2005-13. The prevalence of stunting decreased from 60% in 2000 to 40% in 2014. Overall levels of coverage of reproductive, maternal health, and child health indicators remained low, with disparities between the lowest and highest wealth quintiles despite improvement in coverage for essential health interventions. Coverage of child immunisation increased the most (21% of children in 2000 vs 80% of children in 2014), followed by coverage of satisfied demand for family planning by women of reproductive age (19% vs 63%). Provision of antenatal care increased from 10% of women in 2000 to 32% of women in 2014, but only 15% of women delivered with a skilled birth attendant by 2014. A large upturn occurred after 2005, bolstered by a rapid increase in health funding that facilitated the accelerated expansion of health infrastructure and workforce through an innovative community-based delivery system. The LiST model could explain almost 50% of the observed reduction in child mortality between 2000 and 2011; and changes in nutritional status were responsible for about 50% of the 469 000 lives saved between 2000 and 2011. These developments occurred within a multisectoral policy platform, integrating child survival and stunting goals within macro-level policies and programmes for reducing poverty and improving agricultural productivity, food security, water supply, and sanitation. INTERPRETATION: The reduction of under-5 mortality in Ethiopia was the result of combined activities in health, nutrition, and non-health sectors. However, Ethiopia still has high neonatal and maternal morbidity and mortality from preventable causes and an unfinished agenda in reducing inequalities, improving coverage of effective interventions, and strengthening multisectoral partnerships for further progress. FUNDING: Bill & Melinda Gates Foundation and Government of Canada.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.193
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.121
GPT teacher head0.457
Teacher spread0.336 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations145
Published2017
Admission routes2
Has abstractyes

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