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Record W4403815716 · doi:10.1093/eurpub/ckae144.076

2.C. Round table: A Pandemic Treaty to deliver global health equity: negotiating under a ticking clock

2024· article· en· W4403815716 on OpenAlexaboutno aff

Bibliographic record

VenueEuropean Journal of Public Health · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Public Health Policies and Epidemiology
Canadian institutionsnot available
Fundersnot available
KeywordsTreatyEquity (law)NegotiationPandemicTable (database)Coronavirus disease 2019 (COVID-19)Political scienceMedicineLawComputer scienceInfectious disease (medical specialty)Internal medicineDiseaseDatabase

Abstract

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Abstract Access to medical countermeasures (vaccines, therapeutics, diagnostics), fair resource allocation and a global health framework to counter future pandemics are to be provided for by the Pandemic Treaty, intensely debated in the Intergovernmental Negotiating Body (INB) over the past two years. The final negotiations round began under tremendous pressure (Apr 29, 2024), with dissonance on structural treaty elements and a ticking clock to finalise the text at the World Health Assembly (end of May 2024). At a time of shifting geopolitical powers, in a year of elections across the world, war in Europe and rising defence expenditure, countries are reluctant to commit; the draft postpones key decisions, proposing to establish two intergovernmental working groups for instruments on One Health and prevention, and on a Pathogen Access and Benefits (PABS), with technology transfer and capacity-building remain largely unaddressed, despite COVID-19 lessons. With EU and G7 countries holding to their positions on surveillance, financing, and intellectual property (IP), negotiations will continue. A more critical question remains: will the Treaty’s be adequate and timely enough to meet the challenges of inevitable future pandemics? Will it deliver the global framework of its foundational purpose of equity and justice? This RT aims to inform and involve the European public health community, continuing the series of activities embarked upon at the beginning of the pandemic, empowering its members for evidence-informed advocacy and concerted action. Following a brief presentation on the Treaty’s key provisions, each panel member will deliver a brief (2-3 min) intervention based on core expertise, with two rounds of panel questions/statements to follow, and with an interactive element to prioritise and submit questions. The first elaborating on the current provisions, linking them to the key expertise of panel members, i.e., international and EU law, public health law, One Health and infectious disease control, global health policies, technology transfer, fair pricing and access to countermeasures. The second examining what can be achieved via evidence-informed advocacy, and with a special focus on the role of the European public health community. Has it been well represented so far in negotiations? Should it be more involved? Is it well equipped to provide expert advice to Europe’s policymakers? Is there complementarity in relation to Europe’s Global Health Strategy (GHS) and national global health plans? Finally, the role of WHO will be briefly debated. How can sovereignty be safeguarded without compromising implementation? What is the role of transparency and sound governance to remain in line with national and EU laws and priorities? The last five minutes of this RT will be used to consolidate messages and share plans to inform future formal EUPHA positioning in negotiations. Key messages • Pandemic accord deliberation has have taken place under extreme urgency and geopolitical pressure. The European public health community must be informed and engaged for EU and country-level advocacy. • At a time of permacrisis, the adoption of a global framework for fair resouce allocation, access to medical countermeasures,and to strengthen health systems for future pandemics is urgently needed. Speakers/Panelists Sujitha Subramanian University of Liverpool, Liverpool, UK Dimitra Lingri European Healthcare Fraud and Corruption Network, Brussels, Belgium Debjani Muller HTAi, Edmonton, Canada Ricardo Mexia National Institute of Health Dr. Ricardo Jorge, Lisbon, Portugal Bettina Borisch WFPHA, Geneva, Switzerland

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)0.010
metaresearch head score (Gemma)0.020
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: Commentary · Consensus signal: none
Teacher disagreement score0.051
Threshold uncertainty score0.169

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0050.003
Scholarly communication0.0190.006
Open science0.0020.003
Research integrity0.0250.019
Insufficient payload (model declined to judge)0.0510.030

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 head0.399
Teacher spread0.243 · 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
GenreCommentary

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

Citations0
Published2024
Admission routes1
Has abstractyes

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