An integrated inventory of One Health tools: Mapping and analysis of globally available tools to advance One Health
Bibliographic record
Abstract
Abstract The global demand from multi-sectoral partners for operational tools for One Health implementation and capacity building is increasing, yet a validated global inventory of One Health tools did not exist. Here, we map and analyze available One Health tools and assess their suitability to support One Health implementation, including the One Health Joint Plan of Action 2022–2026 (OH JPA). Our objectives were to identify (i) publicly available One Health tools to support capacity building and OH JPA implementation; (ii) optimal outcomes for countries/regions using available One Health tools; (iii) linkages to OH JPA Action Tracks and pathways in the One Health Theory of Change (TOC); and (iv) gaps and priorities for the development of additional One Health tools. One Health High Level Expert Panel (OHHLEP) members compiled information on One Health tools that were publicly available and released up to June 30, 2023, via online sources and partner networks including the Quadripartite organizations. Inclusion criteria addressed One Health relevance, use at the national, subnational, or regional level in ≥5 locations, and publicly available information. Tools were assessed for applicability by OH JPA action track, TOC pathway, scope, and intended outcomes, as well as the extent to which tools addressed gender equality, social inclusion, and environmental dimensions of One Health. Of 132 candidate tools, 50 (38%) met the inclusion criteria. These tools addressed all six OH JPA Action Tracks, but relatively fewer tools addressed Action Tracks 4 (Food Safety), 5 (Antimicrobial Resistance), and 6 (Environmental Integration). Tools were available to support all three TOC outcome pathways, and many addressed more than one Action Track and TOC outcome pathway. Most available One Health tools addressed assessment and to a lesser extent implementation, with fewer tools available for action planning, prioritization, and monitoring. Gaps and opportunities for improving One Health tools were identified, including the integration of the environment dimension, gender equality, and social inclusion. Ultimately, our findings will contribute to further the advancement of One Health globally, including via OH JPA implementation, while spurring adjustments to existing One Health tools and the development of new ones to address key gaps. One Health impact statement The One Health approach is gaining momentum globally, and this study represents the first integrated mapping and analysis of globally available One Health tools. Our findings aim to improve the quality, applicability, and availability of tools to support One Health implementation at the subnational, national, regional, and global levels, including through the Quadripartite’s One Health Joint Plan of Action. By using the OHHLEP definition of One Health to assess available One Health tools and map them onto the One Health Joint Plan of Action, we identify the need for a systematic approach and enhanced integration across dimensions of One Health to lead to sustainable One Health systems.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.039 | 0.092 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.034 | 0.055 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".