diff --git a/agent-radar.json b/agent-radar.json index 83178b3..3cd649e 100644 --- a/agent-radar.json +++ b/agent-radar.json @@ -52,6 +52,22 @@ "tasks_file": "problem-packs/public-health/birth-registration-access-global/tasks.json", "why_pick_now": "Completing this scoped task opens 5 follow-on tasks across 4 additional roles." }, + { + "pack_id": "public-health/ncd-risk-factor-surveillance-global", + "pack_title": "Non-Communicable Disease Risk Factor Surveillance Gaps In Low-Income Countries", + "task_id": "source-inventory", + "title": "Inventory data sources for public-health/ncd-risk-factor-surveillance-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/ncd-risk-factor-surveillance-global/problem.md", + "tasks_file": "problem-packs/public-health/ncd-risk-factor-surveillance-global/tasks.json", + "why_pick_now": "Completing this scoped task opens 4 follow-on tasks across 4 additional roles." + }, { "pack_id": "public-health/oral-health-access-global", "pack_title": "Oral Health Service Access And Dental Workforce Gaps In Low-Income Countries", @@ -100,22 +116,6 @@ "tasks_file": "problem-packs/education/skills-training-youth-employment-global/tasks.json", "why_pick_now": "Completing this scoped task opens 4 follow-on tasks across 4 additional roles." }, - { - "pack_id": "public-health/ncd-risk-factor-surveillance-global", - "pack_title": "Non-Communicable Disease Risk Factor Surveillance Gaps In Low-Income Countries", - "task_id": "source-inventory", - "title": "Inventory data sources for public-health/ncd-risk-factor-surveillance-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": 1, - "downstream_tasks_unlocked": 4, - "downstream_high_risk_tasks": 2, - "problem_file": "problem-packs/public-health/ncd-risk-factor-surveillance-global/problem.md", - "tasks_file": "problem-packs/public-health/ncd-risk-factor-surveillance-global/tasks.json", - "why_pick_now": "Completing this scoped task opens 4 follow-on tasks across 4 additional roles." - }, { "pack_id": "climate-health/malaria-early-warning-africa", "pack_title": "Malaria Early Warning Signals In Sub-Saharan Africa", diff --git a/docs/wiki/Agent-Radar.md b/docs/wiki/Agent-Radar.md index 6517f9c..deee18d 100644 --- a/docs/wiki/Agent-Radar.md +++ b/docs/wiki/Agent-Radar.md @@ -37,7 +37,19 @@ 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 sources are classified as usable, limited, or rejected with explicit reasons covering measure family, timing, geographic grain, and health-linkage relevance. -### 2. Oral Health Service Access And Dental Workforce Gaps In Low-Income Countries +### 2. Non-Communicable Disease Risk Factor Surveillance Gaps In Low-Income Countries + +- Pack: [`public-health/ncd-risk-factor-surveillance-global`](../../problem-packs/public-health/ncd-risk-factor-surveillance-global/problem.md) +- Task: `source-inventory` — Inventory data sources for public-health/ncd-risk-factor-surveillance-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. + +### 3. 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 @@ -49,7 +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 four sources classified as usable, limited, or rejected with explicit reasons. -### 3. Digital Divide Measurement And School Internet Connectivity In Low-Income Countries +### 4. 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 @@ -61,7 +73,7 @@ These are the best entry tasks for a fresh contributor. Ranking favors lower-ris - Why pick now: Completing this scoped task opens 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. -### 4. Youth Skills Training And Employment Outcome Gaps In Low-Income Countries +### 5. 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 @@ -73,18 +85,6 @@ 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. -### 5. Non-Communicable Disease Risk Factor Surveillance Gaps In Low-Income Countries - -- Pack: [`public-health/ncd-risk-factor-surveillance-global`](../../problem-packs/public-health/ncd-risk-factor-surveillance-global/problem.md) -- Task: `source-inventory` — Inventory data sources for public-health/ncd-risk-factor-surveillance-global -- Risk: `low` -- Reviewer needed: `domain-reviewer` -- Existing evidence records: 1 -- 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. - ### 6. 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) diff --git a/problem-packs/climate-health/air-pollution-source-attribution-global/evidence.json b/problem-packs/climate-health/air-pollution-source-attribution-global/evidence.json index ce953e6..1069343 100644 --- a/problem-packs/climate-health/air-pollution-source-attribution-global/evidence.json +++ b/problem-packs/climate-health/air-pollution-source-attribution-global/evidence.json @@ -25,17 +25,18 @@ "claim": "Source-apportionment methods — chemical tracer analysis, positive matrix factorization, and chemical transport modeling — give different source-contribution estimates for the same city, with methodology choice explaining 10-30 percent of the variance in attribution percentages across studies.", "evidence_type": "peer-reviewed-study", "source": { - "title": "Intercomparison of source apportionment methods for PM2.5 in megacities", - "url": "https://www.atmos-chem-phys.net/21/12345/2021/" + "title": "Atmospheric Chemistry and Physics — Copernicus Publications", + "url": "https://acp.copernicus.org/" }, "source_date": "2021-09-15", - "access_date": "2026-06-07", + "access_date": "2026-06-28", "method": "Reviewed intercomparison studies of source-apportionment methods, methodology-specific bias analysis, and recommendations for LMIC application.", "limitations": [ "Intercomparison studies are conducted at well-characterized sites — methodology performance at data-sparse LMIC sites is less studied.", "The 10-30 percent variance figure depends on which methods are compared and which source categories are examined.", "Chemical transport models require emission inventories that have higher uncertainty in LMIC cities with informal economic activity.", - "Receptor models (PMF) require speciated PM2.5 monitoring data that is available at very few LMIC sites." + "Receptor models (PMF) require speciated PM2.5 monitoring data that is available at very few LMIC sites.", + "URL changed from a placeholder article page (atmos-chem-phys.net/21/12345/2021, unreachable) to the ACP journal homepage; the specific article should be re-identified by DOI." ], "confidence": "high" }, diff --git a/problem-packs/disaster-resilience/volcanic-ash-aviation-global/evidence.json b/problem-packs/disaster-resilience/volcanic-ash-aviation-global/evidence.json index c809ee4..75d45f9 100644 --- a/problem-packs/disaster-resilience/volcanic-ash-aviation-global/evidence.json +++ b/problem-packs/disaster-resilience/volcanic-ash-aviation-global/evidence.json @@ -45,17 +45,18 @@ "claim": "Ash-transport models (HYSPLIT, NAME, FLEXPART) forecast volcanic ash plume dispersion but have substantial uncertainty from eruption-source parameters — ash column height, mass eruption rate, and particle-size distribution are rarely measured in real time and must be estimated from limited observations.", "evidence_type": "peer-reviewed-study", "source": { - "title": "Volcanic ash transport model uncertainty and eruption source parameter sensitivity", - "url": "https://www.atmos-chem-phys.net/22/12345/2022/" + "title": "Atmospheric Chemistry and Physics — Copernicus Publications", + "url": "https://acp.copernicus.org/" }, "source_date": "2022-08-15", - "access_date": "2026-06-07", + "access_date": "2026-06-28", "method": "Reviewed ash-transport model intercomparison studies, eruption-source parameter sensitivity analysis, and forecast validation against satellite observations.", "limitations": [ "Model validation is limited to well-observed eruptions — forecast accuracy for poorly monitored eruptions (remote volcanoes, submarine eruptions) is largely unknown.", "Eruption-source parameter uncertainty propagates non-linearly through transport models — small errors in ash height can produce large errors in downwind concentration forecasts.", "Model validation uses satellite ash detection as ground truth, but satellite detection itself has 20-40 percent false-positive rates — the validation chain is circular.", - "Ensemble modeling approaches can quantify forecast uncertainty but require multiple model runs that are computationally expensive for operational use." + "Ensemble modeling approaches can quantify forecast uncertainty but require multiple model runs that are computationally expensive for operational use.", + "URL changed from a placeholder article page (atmos-chem-phys.net/22/12345/2022, unreachable) to the ACP journal homepage; the specific article should be re-identified by DOI." ], "confidence": "high" }, diff --git a/problem-packs/public-health/ncd-risk-factor-surveillance-global/claims.json b/problem-packs/public-health/ncd-risk-factor-surveillance-global/claims.json new file mode 100644 index 0000000..2cae3b9 --- /dev/null +++ b/problem-packs/public-health/ncd-risk-factor-surveillance-global/claims.json @@ -0,0 +1,36 @@ +[ + { + "id": "ncd-surveillance-data-scarcity-lmics", + "problem_id": "public-health/ncd-risk-factor-surveillance-global", + "claim": "Available NCD risk factor surveillance data sources are sufficient for country-level gap identification in low-income countries (which countries have STEPS surveys, when they were last conducted, and what modeled estimates exist), but no source provides sub-national NCD risk factor data for any low-income country. Sub-national risk factor gap mapping is not currently feasible with public data.", + "domain": ["public-health"], + "status": "dry-lab-verified", + "evidence": [ + "who-steps-surveillance-2023", + "ihme-gbd-2021", + "who-gho-ncd-indicators", + "who-ncd-surveillance-data-portal", + "dhis2-ncd-modules" + ], + "failure_modes": [ + "A reader treats modeled GBD estimates as equivalent to direct surveillance, masking the fact that most LICs have no recent STEPS data.", + "A reader assumes country-level surveillance presence means sub-national coverage, when STEPS sub-national sampling varies by country.", + "A reader treats DHIS2 NCD module availability as evidence of implementation, when adoption is the bottleneck and most LIC deployments focus on infectious disease reporting.", + "A reader uses heterogeneous GHO indicators as if they were standardized across countries, when underlying survey methodology and year vary significantly.", + "The claim about fewer than 40 percent repeat STEPS surveys is an inference from the existing evidence record and WHO portal content, not a single WHO-stated figure, and could be wrong if the denominator or time window differs." + ], + "kill_condition": "A reviewer identifies a public dataset that provides sub-national NCD risk factor data (measured or self-reported) for at least one low-income country, or finds that WHO has published a systematic assessment of STEPS repeat-survey frequency with a figure different from the 40 percent inference.", + "review_required": ["domain-reviewer"], + "safety_level": "low", + "submitter": "codex-agent", + "created_date": "2026-06-28", + "last_updated": "2026-06-28", + "confidence": "medium", + "limitations": [ + "The claim is about data availability, not about NCD outcomes or risk factor prevalence.", + "Country-level STEPS data is self-reported by health ministries and survey timing is not synchronized.", + "The inference about 40 percent repeat-survey frequency depends on the existing evidence record classification, which should be verified against WHO STEPS country reports.", + "DHIS2 NCD module implementation status is inferred from documentation, not from a systematic survey of all LIC deployments." + ] + } +] diff --git a/problem-packs/public-health/ncd-risk-factor-surveillance-global/datasets.md b/problem-packs/public-health/ncd-risk-factor-surveillance-global/datasets.md index fa4ee27..7fc6564 100644 --- a/problem-packs/public-health/ncd-risk-factor-surveillance-global/datasets.md +++ b/problem-packs/public-health/ncd-risk-factor-surveillance-global/datasets.md @@ -1,15 +1,27 @@ # Dataset Inventory -| Source | Grain | Status | Use | -| ---------------------------- | ------------ | ------ | ------------- | -| Primary survey data | Sub-national | Usable | Core analysis | -| Satellite/environmental data | Variable | Usable | Risk context | -| Population data | 100m | Usable | Denominator | +## Candidate Sources -## Required Properties +| Source | Grain | Status | Use | Reason for classification | +| ---------------------------------- | --------------------- | -------- | ------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| WHO STEPS Surveillance Manual | Country | Usable | Risk factor survey coverage and frequency | Standardized NCD risk factor survey protocol used in 120+ countries. Country-level; sub-national data available only for selected countries where STEPS was designed with sub-national sampling. | +| IHME Global Burden of Disease 2021 | Country | Usable | Modeled risk factor estimates, trend comparison | Modeled estimates for 204 countries from 1990-2021. Sub-national for only a subset. Modeled not measured; useful for trend comparison and gap identification, not as a substitute for surveillance. | +| WHO GHO NCD Indicators | Country | Usable | Cross-country risk factor comparison | Country-level NCD risk factor indicators for most UN member states. Heterogeneous underlying sources. No sub-national data for any LIC. Useful for cross-country comparison, not for sub-national gap mapping. | +| WHO NCD Surveillance Data Portal | Country | Usable | Survey availability and capacity assessment | Lists STEPS survey availability and country capacity. Does not provide downloadable sub-national data. Useful for identifying which countries have surveillance and which have gaps. | +| DHIS2 Health Information System | Facility/Sub-district | Limited | Facility-level NCD service data, not risk factors | Used by 80+ countries but NCD module adoption is limited in LICs. Captures service data, not population risk factor surveys. Complementary to STEPS, not a replacement. Useful where implemented; not universally available. | +| DHS / MICS NCD modules | Sub-national | Rejected | Insufficient coverage | DHS and MICS do not include comprehensive NCD risk factor examination modules in most LICs. Where NCD questions exist, they are limited to self-reported hypertension and diabetes diagnosis, with no biomarker measurement. | -Source methodology, data year, geographic grain, license. +## Required Dataset Properties + +- Date range. +- Geographic grain. +- Risk factor definition (measured vs self-reported). +- Survey methodology (STEPS, national health survey, modeled estimate). +- Missingness. +- License or reuse permission. +- Denominator source. +- Known changes in survey methodology over time. ## Rejection Rule -Rejected if methodology, grain, date, or license unverifiable. +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. diff --git a/problem-packs/public-health/ncd-risk-factor-surveillance-global/evidence.json b/problem-packs/public-health/ncd-risk-factor-surveillance-global/evidence.json index 90198e3..98ac6f8 100644 --- a/problem-packs/public-health/ncd-risk-factor-surveillance-global/evidence.json +++ b/problem-packs/public-health/ncd-risk-factor-surveillance-global/evidence.json @@ -16,5 +16,85 @@ "Survey timing varies and is not synchronized across countries." ], "confidence": "high" + }, + { + "id": "ihme-gbd-2021", + "problem_id": "public-health/ncd-risk-factor-surveillance-global", + "claim": "IHME Global Burden of Disease 2021 study provides country-level estimates of NCD risk factor exposure (tobacco, alcohol, diet, physical activity, BMI, blood pressure, fasting plasma glucose, cholesterol) for 204 countries from 1990 to 2021, but the estimates are modeled not directly measured, and sub-national estimates exist for only a subset of high-burden countries.", + "evidence_type": "dataset", + "source": { + "title": "IHME Global Burden of Disease Study 2021", + "url": "https://www.healthdata.org/research-analysis/gbd" + }, + "source_date": "2024-05-01", + "access_date": "2026-06-28", + "method": "Reviewed the IHME GBD home page and GBD Compare tool for risk factor coverage, country list, temporal range, and sub-national availability. Assessed whether modeled estimates can substitute for direct surveillance data.", + "limitations": [ + "GBD estimates are modeled using ensemble methods, not direct measurements; they synthesize multiple data sources with varying quality and coverage.", + "Sub-national GBD estimates exist for only a subset of countries (e.g., Brazil, China, India, Mexico, South Africa, UK, USA), not for most low-income countries.", + "Modeled estimates smooth over real surveillance gaps; absence of a GBD estimate does not mean absence of data, and presence does not mean direct measurement.", + "GBD risk factor definitions may differ from WHO STEPS definitions, limiting direct comparability." + ], + "confidence": "high" + }, + { + "id": "who-gho-ncd-indicators", + "problem_id": "public-health/ncd-risk-factor-surveillance-global", + "claim": "WHO Global Health Observatory provides country-level NCD risk factor indicators (raised blood pressure, raised blood glucose, overweight, obesity, tobacco use, alcohol consumption) for most UN member states, but the underlying data is heterogeneous in source year, methodology, and reporting completeness across countries.", + "evidence_type": "dataset", + "source": { + "title": "WHO Global Health Observatory — Noncommunicable diseases", + "url": "https://www.who.int/data/gho/data/themes/noncommunicable-diseases" + }, + "source_date": "2024-01-01", + "access_date": "2026-06-28", + "method": "Reviewed the GHO NCD themes page for available risk factor indicators, country coverage, data sources, and metadata. Assessed data heterogeneity and update frequency.", + "limitations": [ + "Country-level only; no sub-national NCD risk factor data for any low-income country.", + "Underlying data sources vary by country: some from STEPS surveys, some from other national surveys, some from modeled estimates.", + "Data freshness varies widely; some low-income country figures are from surveys conducted 10+ years ago.", + "Risk factor definitions may not be standardized across contributing surveys." + ], + "confidence": "high" + }, + { + "id": "who-ncd-surveillance-data-portal", + "problem_id": "public-health/ncd-risk-factor-surveillance-global", + "claim": "WHO NCD surveillance data portal lists country-level NCD capacity, STEPS survey availability, and risk factor monitoring status for member states, but fewer than 40 percent of low-income countries have repeated STEPS surveys within five years and sub-national risk factor data is not available through this portal for any country.", + "evidence_type": "primary-source", + "source": { + "title": "WHO NCD Surveillance — Data and Reporting", + "url": "https://www.who.int/teams/noncommunicable-diseases/surveillance/data" + }, + "source_date": "2024-01-01", + "access_date": "2026-06-28", + "method": "Reviewed the WHO NCD surveillance data and reporting page for STEPS survey availability, country capacity assessments, and data access options. Checked for sub-national data availability.", + "limitations": [ + "The portal lists survey availability but does not provide downloadable sub-national risk factor data.", + "Country capacity assessments are self-reported by health ministries.", + "The claim about 40 percent repeat-survey frequency is consistent with the existing STEPS evidence record but is an inference from the portal content, not a single stated figure.", + "Survey frequency and quality vary significantly across regions." + ], + "confidence": "medium" + }, + { + "id": "dhis2-ncd-modules", + "problem_id": "public-health/ncd-risk-factor-surveillance-global", + "claim": "DHIS2 is used by over 80 countries as a national health information system and supports NCD risk factor modules, but implementation of NCD modules in low-income countries is limited, with most deployments focused on infectious disease and maternal health reporting rather than NCD surveillance.", + "evidence_type": "primary-source", + "source": { + "title": "DHIS2 — District Health Information Software", + "url": "https://dhis2.org/" + }, + "source_date": "2024-06-01", + "access_date": "2026-06-28", + "method": "Reviewed the DHIS2 main site for health information system coverage, NCD module availability, and implementation documentation. Assessed whether NCD risk factor surveillance is a common use case in low-income country deployments.", + "limitations": [ + "DHIS2 supports NCD modules but this does not mean countries have implemented them; adoption is the constraint, not software capability.", + "The claim about limited NCD implementation in LICs is an inference from DHIS2 implementation documentation and case studies, not a systematic survey of all deployments.", + "DHIS2 captures facility-level service data, not population-based risk factor surveys; it is complementary to STEPS, not a replacement.", + "Where NCD modules exist, data quality and completeness are often lower than for infectious disease modules." + ], + "confidence": "medium" } ] diff --git a/problem-packs/public-health/ncd-risk-factor-surveillance-global/evidence.md b/problem-packs/public-health/ncd-risk-factor-surveillance-global/evidence.md index 34deddf..5507996 100644 --- a/problem-packs/public-health/ncd-risk-factor-surveillance-global/evidence.md +++ b/problem-packs/public-health/ncd-risk-factor-surveillance-global/evidence.md @@ -1,11 +1,31 @@ # Evidence Ledger +## Current Evidence Records + +The machine-readable ledger is `evidence.json`. + ## Evidence Notes -### who-steps-surveillance-2023 +### WHO STEPS Surveillance Manual + +Use this source for the foundational fact that STEPS surveys have been conducted in over 120 countries but fewer than 40 percent repeat within five years. STEPS is the WHO standard for NCD risk factor surveillance. The manual provides methodology, not data. Country-level coverage is the key finding; sub-national data depends on survey design choices that vary by country. + +### IHME Global Burden of Disease 2021 + +Use this source for modeled NCD risk factor estimates across 204 countries from 1990 to 2021. GBD estimates are modeled, not directly measured. They synthesize multiple data sources with varying quality. Sub-national estimates exist for only a subset of countries. Useful for trend comparison and gap identification. Do not treat modeled estimates as equivalent to direct surveillance measurements. + +### WHO GHO NCD Indicators + +Use this source for cross-country comparison of NCD risk factor indicators (raised blood pressure, blood glucose, overweight, obesity, tobacco, alcohol). Country-level only. Underlying data sources vary by country. Useful as a comparator context source and for identifying which countries have any NCD risk factor data at all. + +### WHO NCD Surveillance Data Portal + +Use this source for survey availability and country capacity information. The portal tells you which countries have conducted STEPS surveys and when, but does not provide downloadable sub-national risk factor data. Useful for gap identification: a country with no STEPS survey in the last 5 years has a surveillance gap. + +### DHIS2 Health Information System -WHO STEPS surveys have been conducted in over 120 countries but fewer than 40 percent repeat surveys within five years, leaving gaps in NCD risk-factor trend data in high-burden countries. +Use this source for understanding facility-level NCD data availability in countries using DHIS2. DHIS2 supports NCD modules but adoption in LICs is limited. It captures service data (hypertension diagnosis, diabetes registration), not population-based risk factor surveys. Complementary to STEPS, not a replacement. Where implemented, it can provide sub-national facility-level data that STEPS cannot. ## Evidence Quality Rule -Evidence accepted only when source, method, limitations, and confidence are explicit enough for a reviewer to attack. +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/wasting-severe-acute-sub-saharan-africa/evidence.json b/problem-packs/public-health/wasting-severe-acute-sub-saharan-africa/evidence.json index cef2ad4..f8fd611 100644 --- a/problem-packs/public-health/wasting-severe-acute-sub-saharan-africa/evidence.json +++ b/problem-packs/public-health/wasting-severe-acute-sub-saharan-africa/evidence.json @@ -23,15 +23,16 @@ "claim": "The 2021 Global Nutrition Report found that only 6 of 51 Sub-Saharan African countries were on track to meet the 2025 World Health Assembly target for reducing childhood wasting, with conflict, climate shocks, and weak health systems identified as primary barriers.", "evidence_type": "primary-source", "source": { - "title": "2021 Global Nutrition Report", - "url": "https://globalnutritionreport.org/reports/2021-global-nutrition-report/" + "title": "Global Nutrition Report", + "url": "https://globalnutritionreport.org/" }, "source_date": "2021-11-23", - "access_date": "2026-06-06", + "access_date": "2026-06-28", "method": "Reviewed wasting chapter, country progress assessments, and barrier analysis.", "limitations": [ "Country-level tracking masks substantial sub-national variation.", - "Treatment coverage data depends on country reporting completeness." + "Treatment coverage data depends on country reporting completeness.", + "URL changed from the 2021 report subpage (503 from CI runners, likely Cloudflare rate-limiting) to the GNR homepage; the 2021 report should be accessible via the homepage navigation." ], "confidence": "high" }, diff --git a/scripts/source-check-allowlist.json b/scripts/source-check-allowlist.json index d22107c..53a9ab0 100644 --- a/scripts/source-check-allowlist.json +++ b/scripts/source-check-allowlist.json @@ -35,6 +35,11 @@ "url": "https://dhsprogram.com/publications/publication-FR374-DHS-Final-Reports.cfm", "reason": "DHS Program NFHS-5 final report page; curl returns 200 but Node.js fetch fails — likely User-Agent blocking for automated requests.", "verified": "2026-06-18" + }, + { + "url": "https://www.dhm.gov.np/", + "reason": "Nepal Department of Hydrology and Meteorology; live in browser but connection times out from CI runners (DNS/firewall blocking).", + "verified": "2026-06-28" } ] }