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Record W2747634494

Mortality and Disability-Adjusted Life-Years (Dalys) for Common Neglected Tropical Diseases in Ethiopia, 1990-2015: Evidence from the Global Burden of Disease Study 2015.

2017· article· en· W2747634494 on OpenAlexaff
Amare Deribew, Biruck Kebede, Gizachew Assefa Tessema, Yohannes Adama, A Misganaw, Teshome Gebre, A. Hailu, Sibhatu Biadgilign, Alemayehu Amberbir, Biruck Desalegn, Amanuel Alemu Abajobir, Oumer Shafi, Semaw Ferede Abera, Nebiyu Negussu, B Mengistu, Azmeraw T. Amare, Afework Mulugeta, Zeyede Kebede, Zerihun Tadesse, Meron Sileshi, M Tamiru, E A Chromwel, S D Glenn, Jeffrey D Stanaway, Kebede Deribe

Bibliographic record

VenuePubMed · 2017
Typearticle
Languageen
FieldImmunology and Microbiology
TopicParasites and Host Interactions
Canadian institutionsNutrition International
Fundersnot available
KeywordsNeglected tropical diseasesYears of potential life lostMedicinePublic healthDisease burdenVerbal autopsyTropical diseaseEnvironmental healthMalariaGlobal healthBurden of diseaseDisability-adjusted life yearDemographyCause of deathLife expectancyDiseasePopulation
DOInot available

Abstract

fetched live from OpenAlex

INTRODUCTION: Neglected tropical diseases (NTDs) are important public health problems in Ethiopia. In 2013, the Federal Ministry of Health (FMOH) has launched a national NTD master plan to eliminate major NTDs of public health importance by 2020. Benchmarking the current status of NTDs in the country is important to monitor and evaluate the progress in the implementation of interventions and their impacts. Therefore, this study aims to assess the trends of mortality and Disability-adjusted Life-Years (DALY) for the priority NTDs over the last 25 years. METHODS: We used the Global Burden of Disease (GBD) 2015 estimates for this study. The GBD 2015 data source for cause of death and DALY estimation included verbal autopsy (VA), Demographic and Health Surveys (DHS), and other disease specific surveys, Ministry of Health reports submitted to United Nations (UN) agencies and published scientific articles. Cause of Death Ensemble modeling (CODEm) and/or natural history models were used to estimate NTDs mortality rates. DALY were estimated as the sum of Years of Life Lost (YLL) due to premature mortality and Years Lived with Disability (YLD). RESULTS: All NTDs caused an estimated of 6,293 deaths (95% uncertainty interval (UI): 3699-10,080) in 1990 and 3,593 deaths (95% UI: 2051 - 6178) in 2015, a 43% reduction over the 25 years. Age-standardized mortality rates due to schistosomiasis, STH and leshmaniasis have declined by 91.3%, 73.5% and 21.6% respectively between 1990 to 2015. The number of DALYs due to all NTDs has declined from 814.4 thousand (95% UI: 548 thousand-1.2million) in 1990 to 579.5 thousand (95%UI: 309.4 thousand-1.3 million) in 2015. Age-standardized DALY rates due to all NTDs declined by 30.7%, from 17.6 per 1000(95%UI: 12.5-26.5) in 1990 to 12.2 per 1000(95%UI: 6.5 - 27.4) in 2015. Age-standardized DALY rate for trachoma declined from 92.7 per 100,000(95% UI: 63.2 - 128.4) in 1990 to 41.2 per 100,000(95%UI: 27.4-59.2) in 2015, a 55.6% reduction between 1990 and 2015. Age-standardized DALY rates for onchocerciasis, schistosomiasis and lymphiaticfilariasis decreased by 66.2%, 29.4% and 12.5% respectively between 1990 and 2015. DALY rate for ascariasis fell by 56.8% over the past 25 years. CONCLUSIONS: Ethiopia has made a remarkable progress in reducing the DALY rates for most of the NTDs over the last 25 years. The rapid scale of interventions and broader system strengthening may have a lasting impact on achieving the 2020 goal of elimination of most of NTDs. Ethiopia should strengthen the coverage of integrated interventions of NTD through proper coordination with other health programs and sectors and community participation to eliminate NTDs by 2020.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.008
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.067
GPT teacher head0.362
Teacher spread0.295 · 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

Citations18
Published2017
Admission routes1
Has abstractyes

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