Concept Taxonomy — Introduction to Public Health¶

16 categories covering 500 concepts. Each category is tagged with a 3-6 letter TaxonomyID used in the CSV and JSON files.

FOUND — Public Health Foundations¶

Concepts 1–20 (20 concepts) Core definitions, functions, and prevention levels that underpin all other public health knowledge. No prerequisites assumed.

EPID — Epidemiology¶

Concepts 21–69 (49 concepts) Measures of disease frequency and association, study designs, causal inference, surveillance systems, outbreak investigation, and epidemic dynamics including R₀ and herd immunity.

BSTAT — Biostatistics¶

Concepts 70–109 (40 concepts) Descriptive and inferential statistics, regression methods, survival analysis, meta-analysis, and reproducibility concepts applied to public health data.

ENVH — Environmental Health¶

Concepts 110–137 (28 concepts) Environmental risk assessment, air and water quality, toxicology, built environment, climate change, and environmental justice.

Concepts 138–172 (35 concepts) Health behavior theories, social-ecological model, behavioral economics, health literacy, cultural humility, and structural determinants of behavior.

POLMGT — Health Policy and Management¶

Concepts 173–202 (30 concepts) US health system structure, policy development, insurance and financing, public health law, program planning, and quality improvement.

GLOB — Global Health¶

Concepts 203–227 (25 concepts) Global burden of disease, epidemiological transition, universal health coverage, SDGs, pandemic governance, and neglected tropical diseases.

EQUITY — Health Equity and SDOH¶

Concepts 228–257 (30 concepts) Health disparities, social determinants, racial inequities, historical trauma, intersectionality, and place-based interventions.

ETHICS — Public Health Ethics¶

Concepts 258–277 (20 concepts) Bioethical principles, stewardship model, research ethics, mandatory intervention ethics, data ethics, and justice frameworks.

COMM — Public Health Communication¶

Concepts 278–302 (25 concepts) Risk communication, CERC framework, audience segmentation, health misinformation, prebunking, and infodemic management.

PREV — Prevention Science¶

Concepts 303–332 (30 concepts) IOM prevention spectrum, evidence-based practice, immunization, chronic disease prevention, harm reduction, and implementation science.

SYS — Systems Thinking¶

Concepts 333–397 (65 concepts) Stocks and flows, feedback loops, causal loop diagrams, system archetypes, stock-and-flow modeling, SIR/SEIR compartmental models, agent-based models, network analysis, and policy leverage points.

DATSCI — Data Science¶

Concepts 398–442 (45 concepts) R and Python for public health, reproducible research, public health data sources, GIS and spatial analysis, time-series analysis, machine learning, NLP for surveillance, and novel digital data sources.

SIM — Simulation Design¶

Concepts 443–464 (22 concepts) MicroSim design principles and implementation using p5.js, Chart.js, Plotly, and vis-network for interactive public health educational simulations.

COVID — COVID-19 Case Studies¶

Concepts 465–484 (20 concepts) COVID-19 as a master case study spanning epidemiology, data infrastructure, NPI evidence, vaccine development and equity, communication failures, systems analysis, and pandemic preparedness lessons.

FRAUD — Health Fraud and Misinformation¶

Concepts 485–500 (16 concepts) DSHEA regulation, supplement industry, MLM dynamics, digital health fraud, consumer protection, and policy reform debates.