diff --git a/agent-radar.json b/agent-radar.json index 10c91a2..c27ea3e 100644 --- a/agent-radar.json +++ b/agent-radar.json @@ -4,12 +4,12 @@ "schema_version": 1, "total_packs": 105, "total_tasks": 544, - "scoped_tasks": 101, - "latent_tasks": 443, + "scoped_tasks": 100, + "latent_tasks": 444, "status_counts": { - "scoped": 101, + "scoped": 100, "needs-triage": 439, - "needs-review": 4 + "needs-review": 5 }, "owner_role_counts": { "literature-scout": 105, @@ -19,7 +19,7 @@ "field-reality-reviewer": 106 }, "scoped_role_counts": { - "literature-scout": 101 + "literature-scout": 100 }, "reviewer_needed_counts": { "domain-reviewer": 225, @@ -37,22 +37,6 @@ "protocol_alerts": [], "contributor_lanes": { "first_moves": [ - { - "pack_id": "public-health/oral-health-access-global", - "pack_title": "Oral Health Service Access And Dental Workforce Gaps In Low-Income Countries", - "task_id": "source-inventory", - "title": "Inventory data sources for public-health/oral-health-access-global", - "owner_role": "literature-scout", - "reviewer_needed": "domain-reviewer", - "safety_risk": "low", - "done_condition": "At least four sources classified as usable, limited, or rejected with explicit reasons.", - "evidence_count": 5, - "downstream_tasks_unlocked": 4, - "downstream_high_risk_tasks": 2, - "problem_file": "problem-packs/public-health/oral-health-access-global/problem.md", - "tasks_file": "problem-packs/public-health/oral-health-access-global/tasks.json", - "why_pick_now": "Completing this scoped task opens 4 follow-on tasks across 4 additional roles." - }, { "pack_id": "education/digital-divide-school-access-global", "pack_title": "Digital Divide Measurement And School Internet Connectivity In Low-Income Countries", @@ -228,6 +212,22 @@ "problem_file": "problem-packs/disaster-resilience/urban-flooding-south-asia/problem.md", "tasks_file": "problem-packs/disaster-resilience/urban-flooding-south-asia/tasks.json", "why_pick_now": "Completing this scoped task opens 5 follow-on tasks across 4 additional roles." + }, + { + "pack_id": "public-health/substandard-falsified-medicines-global", + "pack_title": "Substandard And Falsified Medicine Detection And Surveillance Gaps In Low- And Middle-Income Countries", + "task_id": "source-inventory", + "title": "Inventory quality-surveillance, field-survey, market-distribution, and regulatory data sources for SF medicines analysis", + "owner_role": "literature-scout", + "reviewer_needed": "domain-reviewer", + "safety_risk": "medium", + "done_condition": "At least six candidate data sources are classified as usable, limited, or rejected with explicit reasons covering sampling frame, test method, geographic grain, supply-chain tier, and substandard-versus-falsified disaggregation status.", + "evidence_count": 4, + "downstream_tasks_unlocked": 5, + "downstream_high_risk_tasks": 3, + "problem_file": "problem-packs/public-health/substandard-falsified-medicines-global/problem.md", + "tasks_file": "problem-packs/public-health/substandard-falsified-medicines-global/tasks.json", + "why_pick_now": "Completing this scoped task opens 5 follow-on tasks across 4 additional roles." } ], "unlock_paths": [ @@ -657,7 +657,7 @@ "scoped_tasks": 0, "latent_tasks": 127, "share_of_all_tasks": 0.233, - "share_of_latent_tasks": 0.287 + "share_of_latent_tasks": 0.286 }, { "owner_role": "field-reality-reviewer", @@ -671,21 +671,21 @@ "scoped_tasks": 0, "latent_tasks": 105, "share_of_all_tasks": 0.193, - "share_of_latent_tasks": 0.237 + "share_of_latent_tasks": 0.236 }, { "owner_role": "data-cleaner", "scoped_tasks": 0, "latent_tasks": 101, "share_of_all_tasks": 0.186, - "share_of_latent_tasks": 0.228 + "share_of_latent_tasks": 0.227 }, { "owner_role": "literature-scout", - "scoped_tasks": 101, - "latent_tasks": 4, + "scoped_tasks": 100, + "latent_tasks": 5, "share_of_all_tasks": 0.193, - "share_of_latent_tasks": 0.009 + "share_of_latent_tasks": 0.011 } ] } diff --git a/docs/wiki/Agent-Radar.md b/docs/wiki/Agent-Radar.md index 38053f7..1348a82 100644 --- a/docs/wiki/Agent-Radar.md +++ b/docs/wiki/Agent-Radar.md @@ -15,8 +15,8 @@ Without routing, a new agent sees a flat task list and misses the actual shape o - **105 problem packs** - **544 total tasks** -- **101 scoped now** -- **443 follow-on tasks still latent** +- **100 scoped now** +- **444 follow-on tasks still latent** - **Owner roles:** `data-cleaner`: 101, `field-reality-reviewer`: 106, `implementation-planner`: 127, `literature-scout`: 105, `red-team-reviewer`: 105 - **Reviewer demand:** `domain-reviewer`: 225, `field-reality-reviewer`: 107, `red-team-reviewer`: 105, `replicator`: 107 - **Safety mix:** `high`: 284, `low`: 13, `medium`: 247 @@ -25,19 +25,7 @@ Without routing, a new agent sees a flat task list and misses the actual shape o These are the best entry tasks for a fresh contributor. Ranking favors lower-risk scoped work first, then packs where a successful first move unlocks the most downstream tasks. -### 1. Oral Health Service Access And Dental Workforce Gaps In Low-Income Countries - -- Pack: [`public-health/oral-health-access-global`](../../problem-packs/public-health/oral-health-access-global/problem.md) -- Task: `source-inventory` — Inventory data sources for public-health/oral-health-access-global -- Risk: `low` -- Reviewer needed: `domain-reviewer` -- Existing evidence records: 5 -- Downstream tasks unlocked: 4 -- Downstream high-risk tasks: 2 -- Why pick now: Completing this scoped task opens 4 follow-on tasks across 4 additional roles. -- Done condition: At least four sources classified as usable, limited, or rejected with explicit reasons. - -### 2. Digital Divide Measurement And School Internet Connectivity In Low-Income Countries +### 1. Digital Divide Measurement And School Internet Connectivity In Low-Income Countries - Pack: [`education/digital-divide-school-access-global`](../../problem-packs/education/digital-divide-school-access-global/problem.md) - Task: `source-inventory` — Inventory school connectivity, mobile-network, and digital-learning data sources for low-income countries @@ -49,7 +37,7 @@ These are the best entry tasks for a fresh contributor. Ranking favors lower-ris - Why pick now: Completing this scoped task opens 4 follow-on tasks across 4 additional roles. - Done condition: At least five candidate data sources are classified as usable, limited, or rejected with explicit reasons covering connectivity-classification methodology, data currency, and cross-validation status. -### 3. Youth Skills Training And Employment Outcome Gaps In Low-Income Countries +### 2. Youth Skills Training And Employment Outcome Gaps In Low-Income Countries - Pack: [`education/skills-training-youth-employment-global`](../../problem-packs/education/skills-training-youth-employment-global/problem.md) - Task: `source-inventory` — Inventory training-provider, employment-outcome, labor-market, and skills-mismatch data sources for LMICs @@ -61,7 +49,7 @@ These are the best entry tasks for a fresh contributor. Ranking favors lower-ris - Why pick now: Completing this scoped task opens 4 follow-on tasks across 4 additional roles. - Done condition: At least five candidate data sources are classified as usable, limited, or rejected with explicit reasons covering provider-data fragmentation, outcome-tracking rates, and informal-sector measurement gaps. -### 4. Stillbirth Measurement Gaps And Intrapartum Care Quality In High-Burden Countries +### 3. Stillbirth Measurement Gaps And Intrapartum Care Quality In High-Burden Countries - Pack: [`public-health/stillbirth-measurement-quality-global`](../../problem-packs/public-health/stillbirth-measurement-quality-global/problem.md) - Task: `source-inventory` — Inventory stillbirth data sources across survey, CRVS, and facility systems @@ -73,7 +61,7 @@ These are the best entry tasks for a fresh contributor. Ranking favors lower-ris - Why pick now: Completing this scoped task opens 4 follow-on tasks across 4 additional roles. - Done condition: At least six candidate sources are classified as usable, limited, or rejected with explicit reasons covering definition threshold, measure family, time reference, geographic grain, and relevance to intrapartum versus counting-system interpretation. -### 5. Satellite-Driven Deforestation Detection And Species Loss Risk In The Amazon Basin +### 4. Satellite-Driven Deforestation Detection And Species Loss Risk In The Amazon Basin - Pack: [`biodiversity/deforestation-amazon`](../../problem-packs/biodiversity/deforestation-amazon/problem.md) - Task: `source-inventory` — Inventory deforestation and biodiversity data sources for Amazon basin @@ -85,7 +73,7 @@ These are the best entry tasks for a fresh contributor. Ranking favors lower-ris - Why pick now: Completing this scoped task opens 5 follow-on tasks across 4 additional roles. - Done condition: At least five candidate data sources are classified as usable, limited, or rejected with explicit reasons. -### 6. Sea-Level Rise Coastal Exposure And Adaptation Prioritization In Small Island Developing States +### 5. Sea-Level Rise Coastal Exposure And Adaptation Prioritization In Small Island Developing States - Pack: [`climate-adaptation/sea-level-rise-small-islands`](../../problem-packs/climate-adaptation/sea-level-rise-small-islands/problem.md) - Task: `source-inventory` — Inventory SLR projection and coastal exposure data sources for SIDS @@ -97,7 +85,7 @@ These are the best entry tasks for a fresh contributor. Ranking favors lower-ris - Why pick now: Completing this scoped task opens 5 follow-on tasks across 4 additional roles. - Done condition: At least five candidate data sources are classified as usable, limited, or rejected with explicit reasons. -### 7. Cyclone Early Warning And Evacuation Signal Verification In Bangladesh +### 6. Cyclone Early Warning And Evacuation Signal Verification In Bangladesh - Pack: [`disaster-resilience/cyclone-early-warning-bangladesh`](../../problem-packs/disaster-resilience/cyclone-early-warning-bangladesh/problem.md) - Task: `source-inventory` — Inventory cyclone data sources for Bay of Bengal @@ -109,7 +97,7 @@ These are the best entry tasks for a fresh contributor. Ranking favors lower-ris - Why pick now: Completing this scoped task opens 5 follow-on tasks across 3 additional roles. - Done condition: At least five candidate data sources are classified as usable, limited, or rejected with explicit reasons. -### 8. PM2.5 Monitoring Gaps And Health Impact In South Asia +### 7. PM2.5 Monitoring Gaps And Health Impact In South Asia - Pack: [`air-quality/pm25-monitoring-south-asia`](../../problem-packs/air-quality/pm25-monitoring-south-asia/problem.md) - Task: `source-inventory` — Inventory PM2.5 monitoring and air quality data sources for South Asia @@ -121,7 +109,7 @@ These are the best entry tasks for a fresh contributor. Ranking favors lower-ris - Why pick now: Completing this scoped task opens 5 follow-on tasks across 4 additional roles. - Done condition: At least five candidate data sources are classified as usable, limited, or rejected with explicit reasons. -### 9. Antimicrobial Resistance Surveillance Gaps In Low- And Middle-Income Countries +### 8. Antimicrobial Resistance Surveillance Gaps In Low- And Middle-Income Countries - Pack: [`public-health/antimicrobial-resistance-surveillance-global`](../../problem-packs/public-health/antimicrobial-resistance-surveillance-global/problem.md) - Task: `source-inventory` — Inventory AMR surveillance data @@ -133,7 +121,7 @@ These are the best entry tasks for a fresh contributor. Ranking favors lower-ris - Why pick now: Completing this scoped task opens 5 follow-on tasks across 4 additional roles. - Done condition: Five sources classified as usable, limited, or rejected. -### 10. Malaria Early Warning Signals In Sub-Saharan Africa +### 9. Malaria Early Warning Signals In Sub-Saharan Africa - Pack: [`climate-health/malaria-early-warning-africa`](../../problem-packs/climate-health/malaria-early-warning-africa/problem.md) - Task: `source-inventory` — Inventory malaria and climate data sources for Sub-Saharan Africa @@ -145,7 +133,7 @@ These are the best entry tasks for a fresh contributor. Ranking favors lower-ris - Why pick now: Completing this scoped task opens 5 follow-on tasks across 4 additional roles. - Done condition: At least five candidate data sources are classified as usable, limited, or rejected with explicit reasons. -### 11. Aflatoxin Exposure From Contaminated Staple Grains In Sub-Saharan Africa +### 10. Aflatoxin Exposure From Contaminated Staple Grains In Sub-Saharan Africa - Pack: [`food-safety/aflatoxin-exposure-sub-saharan-africa`](../../problem-packs/food-safety/aflatoxin-exposure-sub-saharan-africa/problem.md) - Task: `source-inventory` — Inventory mycotoxin test data, climate suitability models, and post-harvest practice surveys for SSA aflatoxin risk mapping @@ -157,7 +145,7 @@ These are the best entry tasks for a fresh contributor. Ranking favors lower-ris - Why pick now: Completing this scoped task opens 5 follow-on tasks across 4 additional roles. - Done condition: At least six candidate data sources are classified as usable, limited, or rejected with explicit reasons covering contamination test method, geographic grain, crop specificity, sampling frame adequacy, and intervention-relevance. -### 12. Urban Pluvial Flooding Risk In South Asian Megacities +### 11. Urban Pluvial Flooding Risk In South Asian Megacities - Pack: [`disaster-resilience/urban-flooding-south-asia`](../../problem-packs/disaster-resilience/urban-flooding-south-asia/problem.md) - Task: `source-inventory` — Inventory satellite impervious-surface, drainage, rainfall, flood-extent, and population data sources for South Asian megacities @@ -169,6 +157,18 @@ These are the best entry tasks for a fresh contributor. Ranking favors lower-ris - Why pick now: Completing this scoped task opens 5 follow-on tasks across 4 additional roles. - Done condition: At least five candidate data sources are classified as usable, limited, or rejected with explicit reasons covering resolution, urban accuracy, and drainage-data availability. +### 12. Substandard And Falsified Medicine Detection And Surveillance Gaps In Low- And Middle-Income Countries + +- Pack: [`public-health/substandard-falsified-medicines-global`](../../problem-packs/public-health/substandard-falsified-medicines-global/problem.md) +- Task: `source-inventory` — Inventory quality-surveillance, field-survey, market-distribution, and regulatory data sources for SF medicines analysis +- Risk: `medium` +- Reviewer needed: `domain-reviewer` +- Existing evidence records: 4 +- Downstream tasks unlocked: 5 +- Downstream high-risk tasks: 3 +- Why pick now: Completing this scoped task opens 5 follow-on tasks across 4 additional roles. +- Done condition: At least six candidate data sources are classified as usable, limited, or rejected with explicit reasons covering sampling frame, test method, geographic grain, supply-chain tier, and substandard-versus-falsified disaggregation status. + ## Unlock Paths These packs have a scoped front door and the deepest follow-on queue behind it. If your goal is not just one contribution but opening a sustained lane, start here. @@ -387,11 +387,11 @@ This is the actual pipeline shape. The flat scoped list hides it. | Role | Scoped now | Latent backlog | Share of all tasks | Share of latent tasks | | ------------------------ | ---------- | -------------- | ------------------ | --------------------- | -| `implementation-planner` | 0 | 127 | 0.233 | 0.287 | +| `implementation-planner` | 0 | 127 | 0.233 | 0.286 | | `field-reality-reviewer` | 0 | 106 | 0.195 | 0.239 | -| `red-team-reviewer` | 0 | 105 | 0.193 | 0.237 | -| `data-cleaner` | 0 | 101 | 0.186 | 0.228 | -| `literature-scout` | 101 | 4 | 0.193 | 0.009 | +| `red-team-reviewer` | 0 | 105 | 0.193 | 0.236 | +| `data-cleaner` | 0 | 101 | 0.186 | 0.227 | +| `literature-scout` | 100 | 5 | 0.193 | 0.011 | ## Protocol Alerts diff --git a/docs/wiki/Index.md b/docs/wiki/Index.md index d6b5475..b907e3d 100644 --- a/docs/wiki/Index.md +++ b/docs/wiki/Index.md @@ -11,7 +11,7 @@ | Packs with accepted claims | 0 | | Total evidence records | 326 | | Total tasks | 544 | -| Scoped tasks (ready for work) | 101 | +| Scoped tasks (ready for work) | 100 | | High-risk tasks | 284 | ## All Problem Packs diff --git a/problem-packs/occupational-health/heat-stress-outdoor-workers-global/evidence.json b/problem-packs/occupational-health/heat-stress-outdoor-workers-global/evidence.json index 5b80a7e..56c8191 100644 --- a/problem-packs/occupational-health/heat-stress-outdoor-workers-global/evidence.json +++ b/problem-packs/occupational-health/heat-stress-outdoor-workers-global/evidence.json @@ -154,8 +154,7 @@ "evidence_type": "dataset", "source": { "title": "MERRA-2: Modern-Era Retrospective analysis for Research and Applications, version 2", - "url": "https://gmao.gsfc.nasa.gov/reanalysis/MERRA-2/", - "archive_url": "https://web.archive.org/web/2024/https://gmao.gsfc.nasa.gov/reanalysis/MERRA-2/" + "url": "https://disc.gsfc.nasa.gov/datasets/M2T1NXSLV_5.12.4/summary" }, "source_date": "2015-01-01", "access_date": "2026-07-03", diff --git a/problem-packs/public-health/disability-access-barriers-global/evidence.json b/problem-packs/public-health/disability-access-barriers-global/evidence.json index d747537..99ca249 100644 --- a/problem-packs/public-health/disability-access-barriers-global/evidence.json +++ b/problem-packs/public-health/disability-access-barriers-global/evidence.json @@ -6,7 +6,7 @@ "evidence_type": "primary-source", "source": { "title": "WHO Global Report on Health Equity for Persons with Disabilities", - "url": "https://www.who.int/publications/i/item/9789240063600" + "url": "https://iris.who.int/handle/10665/364621" }, "source_date": "2023-12-01", "access_date": "2026-06-07", diff --git a/problem-packs/public-health/oral-health-access-global/AGENTS.md b/problem-packs/public-health/oral-health-access-global/AGENTS.md new file mode 100644 index 0000000..59450a3 --- /dev/null +++ b/problem-packs/public-health/oral-health-access-global/AGENTS.md @@ -0,0 +1,55 @@ +# Oral Health Access Pack + +## Overview + +This pack is about evidence readiness for oral health access, not oral disease advocacy. The useful question is whether public sources can support sub-national service-access or workforce-gap analysis in low-income countries without pretending that country-level burden estimates are facility or district data. + +Do not treat a WHO burden fact, a dentist-density country indicator, or a general health-spending denominator as proof of local access. Those sources frame the problem; they do not locate the bottleneck. + +## Key Components + +- `problem.json` and `problem.md`: scope, decision wedge, and baseline facts. +- `evidence.json` and `evidence.md`: dated source-family records and source-use notes. +- `datasets.md`: usable, limited, and rejected source classifications. +- `claims.json`: current falsifiable data-scarcity claim. +- `tasks.json` and `task-map.md`: work queue and dependency order. +- `validation.md`: validation, review, and replication gates. + +## Diagrams + +### Flowchart + +```mermaid +flowchart TD + A["WHO burden and workforce sources"] --> B["Source inventory"] + B --> C["Country-by-country survey and source-year extraction"] + C --> D["Sub-national data availability test"] + D --> E["Gap analysis only if public grain is sufficient"] + B -. "Reject country-level proxy as local access proof" .-> F["Boundary note"] +``` + +### Component Diagram + +```mermaid +flowchart LR + Evidence["evidence.json"] --> Claim["claims.json"] + Evidence --> Datasets["datasets.md"] + Datasets --> Tasks["tasks.json"] + Claim --> Review["domain review"] + Tasks --> Validation["validation.md"] +``` + +### Sequence Diagram + +```mermaid +sequenceDiagram + participant Agent + participant Evidence + participant DatasetInventory + participant Reviewer + Agent->>Evidence: Add or repair dated source records + Agent->>DatasetInventory: Classify usable, limited, rejected + Agent->>Reviewer: Submit narrow data-availability claim + Reviewer->>Evidence: Verify URLs, dates, and source scope + Reviewer->>DatasetInventory: Confirm source classifications +``` diff --git a/problem-packs/public-health/oral-health-access-global/claims.json b/problem-packs/public-health/oral-health-access-global/claims.json index 9c514fd..4f1a99a 100644 --- a/problem-packs/public-health/oral-health-access-global/claims.json +++ b/problem-packs/public-health/oral-health-access-global/claims.json @@ -9,6 +9,7 @@ "who-oral-health-2022", "who-global-health-observatory-dental-workforce", "who-oral-health-survey-methods-2013", + "who-oral-health-fact-sheet-2025", "world-bank-health-nutrition-population-stats" ], "failure_modes": [ @@ -22,7 +23,7 @@ "safety_level": "low", "submitter": "codex-agent", "created_date": "2026-06-28", - "last_updated": "2026-06-28", + "last_updated": "2026-07-06", "confidence": "medium", "limitations": [ "The claim is about data availability, not about oral health outcomes or access quality.", diff --git a/problem-packs/public-health/oral-health-access-global/datasets.md b/problem-packs/public-health/oral-health-access-global/datasets.md index 735661b..d0339b6 100644 --- a/problem-packs/public-health/oral-health-access-global/datasets.md +++ b/problem-packs/public-health/oral-health-access-global/datasets.md @@ -2,14 +2,14 @@ ## Candidate Sources -| Source | Grain | Status | Use | Reason for classification | -| ----------------------------------------------- | -------------- | -------------- | --------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | -| WHO Global Oral Health Status Report 2022 | Country/global | Usable | Disease burden, workforce ratios, framing | Published WHO report with country-level data on oral disease prevalence and dentist density. Country-level only; no sub-national breakdowns. | -| WHO GHO Dentistry Workforce Density | Country | Usable | Workforce density comparison across countries | Country-level dentist-to-population ratios for most UN member states. Self-reported by ministries; no sub-national data for any LMIC. Useful for cross-country comparison, not for sub-national gap mapping. | -| WHO Oral Health Surveys -- Basic Methods 5th ed | Methodology | Usable (proxy) | Survey protocol reference, not a data source | Standardized clinical examination protocols. Fewer than 30 LMICs have conducted a national survey using these protocols since 2013. Useful for methodology calibration, not for direct prevalence estimates. | -| IOMT water fluoridation systematic review 2020 | Study-level | Limited | Intervention evidence, not access data | Effect sizes from high-income country studies; transferability to LMICs with fragmented water systems is uncertain. Does not provide access or workforce data. Rejected as a source for gap mapping; usable for context. | -| World Bank HNP Statistics | Country | Usable | Health expenditure and workforce denominators | Country-level health spending and workforce density. No oral-health-specific indicators. Useful as a denominator and comparator context source, not as a direct oral health access measure. | -| DHS / MICS oral health modules | Sub-national | Rejected | Insufficient coverage | Demographic and Health Surveys and MICS do not include oral health examination modules in most LMICs. Oral health questions, where present, are limited to self-reported symptoms with no clinical validation. | +| Source | Grain | Status | Use | Reason for classification | +| ----------------------------------------------- | -------------- | -------------- | ------------------------------------------------------------ | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| WHO Global Oral Health Status Report 2022 | Country/global | Usable | Disease burden, health-system integration, workforce framing | Published WHO report with country-level oral health burden and workforce framing. Country-level only; no sub-national service access or dentist distribution data. | +| WHO GHO Dentistry Workforce Density | Country | Usable | Workforce density comparison across countries | Country-level dentist-to-population ratios for most UN member states. Self-reported by ministries; no sub-national data for any LMIC. Useful for cross-country comparison, not for sub-national gap mapping. | +| WHO Oral Health Surveys -- Basic Methods 5th ed | Methodology | Usable (proxy) | Survey protocol reference, not a data source | Standardized clinical examination protocols. Fewer than 30 LMICs have conducted a national survey using these protocols since 2013. Useful for methodology calibration, not for direct prevalence estimates. | +| WHO oral health fact sheet 2025 | Global framing | Limited | Current burden and service-availability framing | Current WHO fact sheet estimates nearly 3.7 billion people affected and states that most LMICs lack sufficient services. It is not a dataset and cannot identify country-level or sub-national access gaps. | +| World Bank HNP Statistics | Country | Usable | Health expenditure and workforce denominators | Country-level health spending and workforce density. No oral-health-specific indicators. Useful as a denominator and comparator context source, not as a direct oral health access measure. | +| DHS / MICS oral health modules | Sub-national | Rejected | Insufficient coverage | Demographic and Health Surveys and MICS do not include oral health examination modules in most LMICs. Oral health questions, where present, are limited to self-reported symptoms with no clinical validation. | ## Required Dataset Properties @@ -25,3 +25,7 @@ ## Rejection Rule A dataset is rejected for canonical modeling if grain, date range, license, or method cannot be verified. Rejected datasets may still be listed as context. + +## Task Completion Note + +The `source-inventory` task is ready for domain review. Six candidate source families are classified with explicit reasons. The next useful task is not gap mapping; it is a country-by-country extraction of oral health survey dates, dentist density source years, and whether any public source preserves sub-national service-access or workforce distribution. diff --git a/problem-packs/public-health/oral-health-access-global/evidence.json b/problem-packs/public-health/oral-health-access-global/evidence.json index 45b890b..82e4393 100644 --- a/problem-packs/public-health/oral-health-access-global/evidence.json +++ b/problem-packs/public-health/oral-health-access-global/evidence.json @@ -2,7 +2,7 @@ { "id": "who-oral-health-2022", "problem_id": "public-health/oral-health-access-global", - "claim": "WHO estimates 3.5 billion people suffer from oral diseases, with untreated dental caries the most common condition globally and dentist-to-population ratios below 1:100,000 in most low-income countries.", + "claim": "WHO's 2022 Global Oral Health Status Report is a usable country-level source for oral disease burden, health-system integration, and workforce framing, but it does not provide sub-national oral health service access or dentist distribution data for low-income countries.", "evidence_type": "primary-source", "source": { "title": "Global Oral Health Status Report 2022", @@ -44,8 +44,7 @@ "evidence_type": "primary-source", "source": { "title": "Oral Health Surveys -- Basic Methods 5th edition", - "url": "https://www.who.int/publications/i/item/9789241548649", - "doi": "10.1" + "url": "https://www.who.int/publications/i/item/9789241548649" }, "source_date": "2013-01-01", "access_date": "2026-06-28", @@ -58,23 +57,23 @@ "confidence": "medium" }, { - "id": "iomt-fluoride-dental-caries-systematic-review-2020", + "id": "who-oral-health-fact-sheet-2025", "problem_id": "public-health/oral-health-access-global", - "claim": "A systematic review and meta-analysis found that community water fluoridation reduces dental caries by approximately 35 percent in primary teeth and 26 percent in permanent teeth, but the evidence base is dominated by high-income country studies with limited transferability to low-income countries with different water infrastructure.", - "evidence_type": "peer-reviewed-study", + "claim": "WHO's 2025 oral health fact sheet estimates that oral diseases affect nearly 3.7 billion people and states that most low- and middle-income countries do not have sufficient services to prevent and treat oral health conditions.", + "evidence_type": "primary-source", "source": { - "title": "Effects of community water fluoridation on dental caries in children and adults: a systematic review", - "url": "https://doi.org/10.5664/jcsm.10068" + "title": "Oral health", + "url": "https://www.who.int/news-room/fact-sheets/detail/oral-health" }, - "source_date": "2020-06-01", - "access_date": "2026-06-28", - "method": "Reviewed the systematic review abstract, methods, and findings sections. Assessed the country distribution of included studies and the transferability discussion.", + "source_date": "2025-03-17", + "access_date": "2026-07-06", + "method": "Reviewed the WHO fact sheet key facts and overview sections for current burden framing, service-availability wording, and what the source can support for an access-gap source inventory.", "limitations": [ - "The review included primarily high-income country studies; community water fluoridation feasibility in LMICs with fragmented piped water systems is not addressed.", - "Effect sizes may not generalize to populations with different baseline caries levels, fluoride exposure from other sources, or dietary patterns.", - "The review does not provide sub-national access data for any low-income country." + "Fact sheet wording is global and broad; it does not provide country-level or sub-national service access data.", + "The burden estimate is a modeled global estimate, not a direct count by country.", + "The statement that most LMICs lack sufficient services is useful for framing but does not identify which facilities, districts, or workforce categories are missing." ], - "confidence": "medium" + "confidence": "high" }, { "id": "world-bank-health-nutrition-population-stats", diff --git a/problem-packs/public-health/oral-health-access-global/evidence.md b/problem-packs/public-health/oral-health-access-global/evidence.md index a5159b2..4432edc 100644 --- a/problem-packs/public-health/oral-health-access-global/evidence.md +++ b/problem-packs/public-health/oral-health-access-global/evidence.md @@ -8,7 +8,7 @@ The machine-readable ledger is `evidence.json`. ### WHO Global Oral Health Status Report 2022 -Use this source for global oral disease burden (3.5 billion people), untreated caries prevalence, and country-level dentist-to-population ratios. The report is the strongest framing source for this pack. Do not use it as proof of sub-national access gaps in any specific country -- the data is country-level only. +Use this source for country-level oral disease burden, health-system integration, and workforce framing. The report is a strong framing source for this pack. Do not use it as proof of sub-national access gaps in any specific country -- the data is country-level only. ### WHO Global Health Observatory -- Dentistry Workforce Density @@ -18,14 +18,18 @@ Use this source for cross-country comparison of dentist density. The GHO provide Use this source for survey methodology calibration, not for prevalence data. The manual defines the DMFT index, gingival bleeding, and periodontal assessment protocols. Fewer than 30 LMICs have conducted a national oral health survey using these protocols since 2013, which is itself a finding about data scarcity. -### IOMT Water Fluoridation Systematic Review 2020 +### WHO Oral Health Fact Sheet 2025 -Use this source for intervention context on community water fluoridation. The effect sizes (35 percent caries reduction in primary teeth, 26 percent in permanent teeth) come from high-income country studies. Transferability to LMICs with fragmented piped water systems is uncertain. This source does not provide access or workforce data and is classified as limited for gap-mapping purposes. +Use this source for current global burden framing and WHO's high-level statement that most low- and middle-income countries do not have sufficient services to prevent and treat oral health conditions. Do not use it as a dataset. It does not identify country-level service gaps, sub-national workforce distribution, facility readiness, or treatment capacity. ### World Bank HNP Statistics Use this source for health expenditure and general health workforce denominators. Oral health is not disaggregated from general health spending in this database. Useful as a comparator context source, not as a direct oral health access measure. +## Task Completion Note + +The scoped `source-inventory` task is satisfied because the inventory classifies six candidate source families as usable, usable proxy, limited, or rejected with explicit reasons. The current evidence supports a narrow discovery claim: public global sources are enough for burden and workforce framing, but not enough for sub-national oral health access mapping in low-income countries. + ## Evidence Quality Rule Evidence is not accepted because it sounds plausible. It is accepted when the source, method, limitations, and confidence are explicit enough for a reviewer to attack. diff --git a/problem-packs/public-health/oral-health-access-global/problem.md b/problem-packs/public-health/oral-health-access-global/problem.md index d11bead..0040aca 100644 --- a/problem-packs/public-health/oral-health-access-global/problem.md +++ b/problem-packs/public-health/oral-health-access-global/problem.md @@ -8,7 +8,7 @@ Build a verified workflow for measuring oral health service access and dental wo ## Known Facts -- Verified fact: WHO estimates 3.5 billion people suffer from oral diseases, with untreated dental caries the most common condition globally and dentist-to-population ratios below 1:100,000 in most low-income countries. +- Verified fact: WHO's 2025 oral health fact sheet estimates that oral diseases affect nearly 3.7 billion people, that untreated caries in permanent teeth is the most common health condition in Global Burden of Disease 2021, and that most low- and middle-income countries do not have sufficient services to prevent and treat oral health conditions. ## Uncertain Areas diff --git a/problem-packs/public-health/oral-health-access-global/tasks.json b/problem-packs/public-health/oral-health-access-global/tasks.json index 07c7b29..f641d8f 100644 --- a/problem-packs/public-health/oral-health-access-global/tasks.json +++ b/problem-packs/public-health/oral-health-access-global/tasks.json @@ -3,7 +3,7 @@ "id": "source-inventory", "problem_id": "public-health/oral-health-access-global", "title": "Inventory data sources for public-health/oral-health-access-global", - "status": "scoped", + "status": "needs-review", "owner_role": "literature-scout", "outcome": "A dated source inventory separating usable, limited, and rejected data sources for oral health service access and dental workforce gaps in low-income countries.", "inputs": ["primary survey data", "satellite data", "population data", "program data"], diff --git a/problem-packs/water-security/arsenic-groundwater-exposure-bangladesh/claims.json b/problem-packs/water-security/arsenic-groundwater-exposure-bangladesh/claims.json index 127a0e2..2705c00 100644 --- a/problem-packs/water-security/arsenic-groundwater-exposure-bangladesh/claims.json +++ b/problem-packs/water-security/arsenic-groundwater-exposure-bangladesh/claims.json @@ -2,20 +2,20 @@ { "id": "arsenic-testing-coverage-data-sufficiency", "problem_id": "water-security/arsenic-groundwater-exposure-bangladesh", - "claim": "Available public data sources are sufficient to establish that arsenic-contaminated groundwater is a massive chronic exposure problem in Bangladesh (WHO guideline, BGS/DPHE survey, EHP systematic review) and to characterise the well-depth-arsenic relationship for testing prioritisation (Flanagan et al. 2012). However, no public dataset provides current upazila-level testing-coverage status at sufficient grain to identify which specific upazilas have the largest gap between known contamination and household-level testing. The BAMWSP testing records cover 1.4 million wells but are 20 years old, unevenly distributed at upazila grain, and do not account for wells installed after 2006. WorldPop provides population denominators but not water-source or testing-status data. The available data can support historical and district-level analysis but cannot produce a current upazila-level testing-coverage gap map without supplementary testing-status data that does not currently exist in a public, systematically structured form.", + "claim": "Available public data sources are sufficient to establish that arsenic-contaminated groundwater is a major chronic exposure problem in Bangladesh (WHO guideline, BGS/DPHE survey, and HEALS cohort health-risk evidence) and to characterise the well-depth-arsenic relationship for testing prioritisation (Flanagan et al. 2012). However, no public dataset provides current upazila-level testing-coverage status at sufficient grain to identify which specific upazilas have the largest gap between known contamination and household-level testing. The BAMWSP testing records cover 1.4 million wells but are 20 years old, unevenly distributed at upazila grain, and do not account for wells installed after 2006. WorldPop provides population denominators but not water-source or testing-status data. The available data can support historical and district-level analysis but cannot produce a current upazila-level testing-coverage gap map without supplementary testing-status data that does not currently exist in a public, systematically structured form.", "domain": ["water-security", "public-health"], "status": "unverified", "evidence": [ "who-arsenic-factsheet-2022", "bgs-dphe-arsenic-survey-2001", - "ehp-arsenic-exposure-review-2024", + "argos-heals-arsenic-mortality-2010", "bamwsp-testing-coverage-2006", "flanagan-ararsenic-well-depth-2012", "worldpop-bangladesh-population-data" ], "failure_modes": [ "A reader treats the BGS/DPHE 1998-1999 survey as current arsenic concentrations when newer well installations may have different contamination patterns.", - "A reader uses the 35-77 million exposure range as a point estimate rather than a wide uncertainty interval reflecting different survey methods and time periods.", + "A reader treats cohort health-risk evidence as a current national exposure-count estimate.", "A reader treats BAMWSP's 1.4 million tested wells as current coverage when the figure is from 2006 and millions of wells have been installed since.", "A decision-maker uses population density as a proxy for arsenic exposure without linking to well-testing or water-source data.", "A reader uses the well-depth-arsenic relationship as deterministic when it varies by geological zone and is non-monotonic.", @@ -32,7 +32,7 @@ "The claim is about public data availability for upazila-level testing-coverage gap analysis, not about actual arsenic exposure or testing status in specific upazilas.", "The assessment that no public dataset provides current upazila-level testing status is an inference from reviewing available data portals and published literature, not a systematic survey of all Bangladeshi government databases.", "The National Arsenic Mitigation Cell may hold more granular testing-coverage data that is not publicly accessible; this claim is based on publicly available information only.", - "The BGS/DPHE DOI may not resolve correctly for all access paths; the BGS project page is the primary stable URL." + "The BGS/DPHE report page is a source directory rather than a DOI-backed article landing page; reviewers should confirm the specific report file before using it for numeric extraction." ] } ] diff --git a/problem-packs/water-security/arsenic-groundwater-exposure-bangladesh/evidence.json b/problem-packs/water-security/arsenic-groundwater-exposure-bangladesh/evidence.json index d690ad4..19a734c 100644 --- a/problem-packs/water-security/arsenic-groundwater-exposure-bangladesh/evidence.json +++ b/problem-packs/water-security/arsenic-groundwater-exposure-bangladesh/evidence.json @@ -26,8 +26,7 @@ "evidence_type": "primary-source", "source": { "title": "Arsenic contamination of groundwater in Bangladesh — BGS/DPHE Phase 1 Groundwater Studies", - "url": "https://www.bgs.ac.uk/projects/arsenic-bangladesh/", - "doi": "10.1016/S0048-9697(01)00600-3" + "url": "https://www.bgs.ac.uk/groundwater/quality/groundwater-and-health/arsenic-contamination-of-groundwater/bangladesh-reports/" }, "source_date": "2001-01-01", "access_date": "2026-06-30", @@ -41,23 +40,23 @@ "confidence": "high" }, { - "id": "ehp-arsenic-exposure-review-2024", + "id": "argos-heals-arsenic-mortality-2010", "problem_id": "water-security/arsenic-groundwater-exposure-bangladesh", - "claim": "A 2024 systematic review estimated that 35-77 million people in Bangladesh have been chronically exposed to arsenic above the WHO 10 micro-grams-per-litre guideline, with exposure varying sharply by upazila and well depth, and that long-term exposure is associated with increased risk of skin, bladder, and lung cancers.", + "claim": "The HEALS prospective cohort study in Bangladesh found a dose-response association between arsenic exposure from drinking water and all-cause and chronic-disease mortality, supporting health-risk framing but not current upazila-level testing-coverage mapping.", "evidence_type": "peer-reviewed-study", "source": { - "title": "Arsenic exposure and health effects in Bangladesh: a systematic review and meta-analysis", - "url": "https://doi.org/10.1289/EHP12000", - "doi": "10.1289/EHP12000" + "title": "Arsenic exposure from drinking water, and all-cause and chronic-disease mortalities in Bangladesh (HEALS): a prospective cohort study", + "url": "https://pubmed.ncbi.nlm.nih.gov/20646756/", + "doi": "10.1016/S0140-6736(10)60481-3" }, - "source_date": "2024-03-01", - "access_date": "2026-06-30", - "method": "Reviewed systematic review for exposure population estimates, dose-response relationships, and cancer risk estimates. Checked methodology section for inclusion criteria and meta-analysis approach.", + "source_date": "2010-07-24", + "access_date": "2026-07-06", + "method": "Reviewed the PubMed record and Lancet study metadata for cohort design, exposure-health association, publication date, and DOI. Classified the source as health-risk evidence rather than a current testing-coverage dataset.", "limitations": [ - "The 35-77 million range reflects uncertainty in exposure estimates from different survey methods and time periods.", - "Systematic review aggregates studies of variable quality and geographic coverage.", - "Exposure estimates are modeled from survey data, not direct individual-level measurement for the entire population.", - "Cancer risk estimates are based on epidemiological studies primarily from Taiwan and Chile, extrapolated to Bangladesh exposure levels." + "Cohort evidence supports health-risk framing; it does not estimate current national exposure counts.", + "The study population is not a current national testing-coverage dataset and cannot identify untested upazilas.", + "Exposure-health associations do not replace household well-testing or water-source data.", + "Publication date is 2010, so it cannot capture post-2010 changes in well installation, mitigation, or testing coverage." ], "confidence": "high" }, diff --git a/tasks-available.json b/tasks-available.json index c62232b..740f8af 100644 --- a/tasks-available.json +++ b/tasks-available.json @@ -3,17 +3,17 @@ "generated_by": "scripts/generate-task-index.mjs", "schema_version": 1, "total_packs": 105, - "total_scoped_tasks": 101, + "total_scoped_tasks": 100, "by_role": { - "literature-scout": 101 + "literature-scout": 100 }, "by_risk": { "medium": 97, - "low": 4 + "low": 3 }, "by_domain": { "air-quality": 6, - "public-health": 64, + "public-health": 63, "climate-health": 13, "biodiversity": 7, "food-security": 19, @@ -1336,23 +1336,6 @@ "tasks_file": "problem-packs/public-health/ntd-mass-drug-administration-global/tasks.json", "problem_file": "problem-packs/public-health/ntd-mass-drug-administration-global/problem.md" }, - { - "pack_id": "public-health/oral-health-access-global", - "pack_title": "Oral Health Service Access And Dental Workforce Gaps In Low-Income Countries", - "pack_status": "scoped", - "domain": ["public-health"], - "region": ["global"], - "task_id": "source-inventory", - "title": "Inventory data sources for public-health/oral-health-access-global", - "owner_role": "literature-scout", - "reviewer_needed": "domain-reviewer", - "safety_risk": "low", - "outcome": "A dated source inventory separating usable, limited, and rejected data sources for oral health service access and dental workforce gaps in low-income countries.", - "expected_artifact": "datasets.md update plus evidence.json records.", - "done_condition": "At least four sources classified as usable, limited, or rejected with explicit reasons.", - "tasks_file": "problem-packs/public-health/oral-health-access-global/tasks.json", - "problem_file": "problem-packs/public-health/oral-health-access-global/problem.md" - }, { "pack_id": "public-health/prison-health-tb-hiv-global", "pack_title": "Prison Health Tuberculosis And HIV Service Gaps In Low- And Middle-Income Countries",