Ontology field guide
By NOSIBLE Research
ICD-11 Chapters and Blocks
ICD-11 shows when a named health risk requires more detail than a broad disease chapter provides for exposure analysis through time.
Health reporting can remain in a broad chapter or gain qualifiers. ICD-11 preserves that distinction. World joins assignments to entities, events and source-time metadata without treating news as a clinical record.[1]
This guide tracks reporting from broad disease chapters into Extension Codes. The H5N1 study starts with the March 2024 US dairy detection. It measures context, not infections, transmission or losses.[2][4]
- Categories
- 300 categories
- Structure
- 2 levels
- World events labelled
- 7.8%
- Stable codes
- Since v1
- Release data
- CC0
Foundations
ICD-11 classifies reported health conditions without measuring incidence, transmission or severity
The World Health Organization created ICD-11 for consistent recording, reporting and comparison of health conditions. The full standard contains diagnostic categories, extension codes and combinable concepts. World uses 28 chapters and 272 broad blocks. That level supports event research without implying clinical precision.[1]
World classifies the health subject expressed in an event. It does not diagnose a person, infer incidence or establish treatment efficacy. One event can discuss a disease, regulator, company and affected population while receiving one chapter and block path. Counts must be checked for repeated coverage, source concentration and assignment error.[1]
Categories
ICD-11 organises 300 health labels across broad chapters and specific diagnostic blocks
The ontology has two levels. Chapters define broad health systems. Blocks provide the finest World V1.2 classification. The explorer shows every definition, code, path and corpus count. Detailed disease questions still require an explicit text or entity cohort because a broad block does not identify every named pathogen.[1]
1,194,981 of 15,311,040 World events carry labels from ICD-11 Chapters and Blocks. Select a category to see its count and both relevant shares.
Certain infectious or parasitic diseases
Certain infectious or parasitic diseases
Definition
Diseases caused by infectious or parasitic agents, including related outbreaks and public-health responses.
Potential research use
Outbreaks, vaccines and health responses
- Code
- Certain infectious or parasitic diseases
- Events with label
- 100,636
- Share of labelled
- 8.4%
- Share of World
- 0.7%
Events with label is the selected count. Label share divides it by 1,194,981 assigned events; World share divides it by all 15,311,040 events.
Representative World V1.2 events
One strong classified example per available year, with up to ten years shown.
Climate Change Drives Rapid Emergence of Infectious Diseases Globally
Coverage 32Human Diseases from Africa May Have Caused Neanderthal Extinction
Coverage 23World Leaders Pledge 812 Million to End Neglected Tropical Diseases
Coverage 42US Measles Outbreaks Surge in 2019 Amid Global Infectious Disease Crisis
Coverage 16Nigerian Governors Urge National Assembly to Halt Infectious Diseases Bill
Coverage 31NSW and Queensland on High Alert After Victorian Couple Travels Infectious
Coverage 40Study: Climate Change Worsens 58% of Known Human Infectious Diseases
Coverage 155WHO: Tuberculosis Surpasses COVID-19 as Top Infectious Disease Killer
Coverage 190ICMR Study Finds One in Nine Indians Tested Positive for Infectious Diseases
Coverage 27CDC Halts Dozens of Infectious Disease Tests Amid Staffing Cuts
Coverage 141
Browse categories to compare definitions, World V1.2 statistics and representative classified events.
Example usage 1 of 3
Example Usage: H5N1 coverage gains investable context after the virus reaches United States dairy herds
US authorities confirmed H5N1 in dairy cattle on 25 March 2024 and a Texas dairy worker on 1 April. Exact H5N1 attention rises 7.53 times, from 4.0 to 29.8 events per 10,000 relevant health events. Infectious Diseases falls from 69.2% to 48.9% of the assigned cohort. Extension Codes rises from 30.8% to 51.1%.[2][3][4]
Infectious Diseases supplies the broad chapter. Extension Codes add qualifiers for exposure triage. Their share rises from 30.8% to 51.1% after dairy detection, identifying a specific reporting cohort for workers, producers and supply chains. H5N1 language defines the cohort; it does not measure infections, severity, transmission or economic loss.[5][6][7]
Infectious Diseases is the broad chapter. Extension Codes carry supplemental context used to qualify a health condition. Their rise does not measure outbreak severity or supply-chain loss. It identifies a more specific reporting cohort that researchers can join to affected entities, locations and agricultural exposures. The attention chart uses a trailing 28-day rate and preserves the health-event denominator.
Example usage 2 of 3
Example Usage: GLP-1 coverage expands from metabolic treatment into cardiovascular and adverse-event contexts
GLP-1 reporting moves beyond diabetes and obesity as clinical evidence and approvals expand. Metabolic classifications remain central, while cardiovascular, digestive and adverse-event contexts produce distinct bursts of normalized attention. The chart aligns those category-specific rates with major trial and approval dates rather than pooling each Ozempic, Wegovy or Zepbound event inside one undifferentiated clinical series.[8]
The distinction changes the exposure map. Metabolic events address obesity and diabetes demand. Cardiovascular outcomes expand the eligible population and reimbursement case. Digestive and injury classifications surface safety risk. Researchers can connect each clinical channel to manufacturers, payers, providers and consumer sectors while preserving a separate event clock for each investment thesis.[9]
- Endocrine and metabolic
- +11.3pp
- Extension Codes
- +28.3pp
- Circulatory system
- +3.6pp
- Digestive system
- +4.5pp
The fixed English cohort covers 11 July 2023 through 20 March 2024 and requires a named GLP-1 drug or GLP-1 term. Each line pools category counts across the current and prior twenty days, then divides by all English World events in that window. Markers identify public trial or regulatory milestones.
Example usage 3 of 3
Example Usage: Mental-health reporting shifts from mortality toward clinical disorders during the first lockdowns
During the first COVID-19 lockdowns, the clinical meaning of mental-health coverage changes within weeks. Mental, Behavioral or Neurodevelopmental Disorders rises from 34.9% of ICD-assigned events in the 28 days ending 10 March to 68.4% by 21 April. External Causes of Morbidity or Mortality falls from 49.5% to 16.5%.[10]
That rotation separates clinical demand from mortality reporting. The first channel maps to care utilization, telehealth, pharmaceuticals, insurers, employers and productivity. The second maps more directly to suicide and public-safety outcomes. ICD-11 supplies separate event clocks for testing demand, claims, workforce disruption and policy responses without treating mental-health reporting as one signal in model testing.[11]
- Clinical mental health
- +33.5pp
- External causes
- -33.0pp
The fixed English cohort requires mental-health, depression, anxiety-disorder or suicide language from January through September 2020. Each line pools ICD chapter counts across the current and prior twenty-seven days, then divides by all ICD-assigned cohort events. It measures classified reporting, not clinical prevalence, diagnosis rates or population-level changes in mental-health outcomes.
Data and sources
Download ICD-11 and References
Downloads
Download categories and counts as CSV, or the complete machine-readable release as JSON.
Release details and citation files
ManifestRelease READMECC0 license and scopeCitation fileChangelog
Need the complete World event schema? Open the World data dictionary.
References
- [1]World Health Organization. (2022). ICD-11 fact sheet.
- [2]US Department of Agriculture. (2024). USDA and HHS announce new actions to reduce the impact and spread of H5N1.
- [3]Uyeki, T. M. et al. (2024). Highly pathogenic avian influenza A(H5N1) virus infection in a dairy farm worker. Morbidity and Mortality Weekly Report, 73, 501-505.
- [4]Caserta, L. C. et al. (2024). Spillover of highly pathogenic avian influenza H5N1 virus to dairy cattle. Nature, 634, 669-676.
- [5]US Department of Agriculture. (2024, July 1). USDA begins accepting applications for expanded Emergency Assistance for Livestock, Honeybees, and Farm-raised Fish Program assistance.
- [6]Morel, C. M. et al. (2026). The economic burden of highly pathogenic avian influenza H5N1. Communications Earth & Environment.
- [7]US Centers for Disease Control and Prevention. (2025, January 6). CDC reports first H5 bird flu death in United States.
- [8]Lincoff, A. M. et al. (2023). Semaglutide and cardiovascular outcomes in obesity without diabetes. New England Journal of Medicine, 389, 2221–2232.
- [9]U.S. Food and Drug Administration. (2024). FDA approves first treatment to reduce serious cardiovascular risks in adults with obesity or overweight.
- [10]World Health Organization. (2020). Mental health and psychosocial considerations during the COVID-19 outbreak.
- [11]Organisation for Economic Co-operation and Development. (2021). Tackling the mental health impact of the COVID-19 crisis.
Continue exploring
Complementary ontologies
237 categories
GICS Industry Classification
Map clinical event regimes to the healthcare and consumer industries carrying financial exposure.
Explore ontology →
186 categories
UN Sustainable Development Goals
Connect health classifications to the development targets they affect across countries and time.
Explore ontology →