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Record W2925159988 · doi:10.1016/s0140-6736(19)30024-8

Building a tuberculosis-free world: The Lancet Commission on tuberculosis

2019· review· en· W2925159988 on OpenAlexaff
Michael Reid, Nimalan Arinaminpathy, Amy Bloom, Barry R. Bloom, Catharina Boehme, Richard E. Chaisson, Daniel P. Chin, Gavin Churchyard, Helen Cox, Lucica Diţiu, Mark Dybul, Jeremy Farrar, Anthony S. Fauci, Endalkachew Fekadu, Paula I. Fujiwara, Timothy B. Hallett, Christy Hanson, Mark Harrington, Nick Herbert, Philip C. Hopewell, Chieko Ikeda, Dean T. Jamison, Aamir Khan, Irene Koek, Nalini Krishnan, Aaron Motsoaledi, Madhukar Pai, Mario Raviǵlione, Almaz Sharman, Peter M. Small, Soumya Swaminathan, Zelalem Temesgen, Anna Vassall, Nandita Venkatesan, Kitty Van Weezenbeek, Gavin Yamey, Bruce Agins, Sofia Alexandru, Jason R. Andrews, Naomi Beyeler, Stela Bivol, Grania Brigden, Adithya Cattamanchi, Danielle Cazabon, Valeriu Crudu, Amrita Daftary, Puneet Dewan, Laurie Doepel, Robert W. Eisinger, Victoria Y. Fan, Sara Fewer, Jennifer Furin, Jeremy D. Goldhaber‐Fiebert, Gabriela B. Gomez, Stephen M. Graham, Devesh Gupta, Maureen Kamene, Sunil Khaparde, Eunice Mailu, Enos Masini, Lorrie McHugh, Ellen M.H. Mitchell, Suerie Moon, Michael Osberg, Tripti Pande, Lea Prince, Kiran Rade, Raghuram Rao, Michelle Remme, James A. Seddon, Casey Selwyn, Priya B. Shete, Kuldeep Singh Sachdeva, Guy Stallworthy, Juan F Vesga, Valentina Vilc, Eric Goosby

Bibliographic record

VenueThe Lancet · 2019
Typereview
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsMcGill UniversityMcGill University Health Centre
FundersWellcome TrustWorld Health OrganizationMedical Research CouncilUnited States Agency for International Development
KeywordsTuberculosisMedicineGlobal healthDiseasePandemicInfectious disease (medical specialty)Development economicsEconomic growthPublic healthCoronavirus disease 2019 (COVID-19)Economics

Abstract

fetched live from OpenAlex

___Key messages___ The Commission recommends five priority investments to achieve a tuberculosis-free world within a generation. These investments are designed to fulfil the mandate of the UN High Level Meeting on tuberculosis. In addition, they answer the question of how countries with high-burden tuberculosis and their development partners should target their future investments to ensure that ending tuberculosis is achievable. __Invest first to ensure that high quality rapid diagnostics and treatment are provided to all individuals receiving care for tuberculosis, wherever they seek care__ This priority includes rapid drug susceptibility testing and second-line treatment for resistant forms of tuberculosis. Achieving universal, high-quality person-centred and family-centred care—including sustained improvement in the performance of private sector providers—usually should be the top policy and budget priority. __Reach people and populations at high risk for tuberculosis (such as household and other close contacts of people with tuberculosis, and people with HIV) and bring them into care__ Active case-finding and treatment in high-risk populations demands adequate resources to reach and care for these populations. At the same time, reaching certain high-risk populations, such as people co-infected with tuberculosis and HIV, for tuberculosis preventive therapy is essential to achieve epidemiologic control. Once high-risk populations have access to affordable, high-quality diagnostic, treatment and preventive services, invest in identifying tuberculosis cases in the general population, primarily by strengthening the capacity to deliver health services and move toward universal health coverage. __Increase investment to accelerate tuberculosis research and development and bring new diagnostics, therapeutic strategies, and vaccines to clinical practice to quickly end the pandemic__ Strong advocacy with science ministries and research-oriented pharmaceutical companies is crucial, including ministries and companies in middle-income countries, to highlight the importance of investing in new tools. Financing the early uptake of new products will provide important confidence signals to product developers. __Make investment in tuberculosis programmes a shared responsibility, increasing development assistance for tuberculosis according to the financial needs of individual low-income and middle-income countries__ As countries successfully mobilise more domestic resources towards tuberculosis programmes, external assistance to middle-income countries should address the following priorities: reduce the spread of drug-resistant tuberculosis in all affected low-income and middle-income countries; facilitate market-shaping activities to enable access to high quality drugs and diagnostics for high-burden countries; and finance tuberculosis research and development, including product development as well as population, policy, and implementation research that will provide lessons and international sharing of best practices. __Hold countries and key stakeholders accountable for progress made towards ending tuberculosis__ Accountability entails establishing independent, multisectoral processes, such as national tuberculosis report cards, to ensure that all stakeholders carry out their responsibilities to contribute to ending the pandemic. Accountability mechanisms should not only assess progress, but also guarantee that Heads of Governments, national tuberculosis programmes, and even regional and site-level clinics, as well as key non-governmental organisations, take the necessary corrective actions to remove obstacles to ending tuberculosis.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.019
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0040.005
Open science0.0020.002
Research integrity0.0050.008
Insufficient payload (model declined to judge)0.0190.006

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 head0.156
GPT teacher head0.430
Teacher spread0.273 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

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Citations369
Published2019
Admission routes1
Has abstractyes

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