Epidemiology to One Health.
For the first time, we can calculate health results across humans, animals, and the earth's ecology to improve health and stop pandemics at their source.
Level 2: What is epidemiology not just?
We start with what epidemiology is not just.
Epidemiology:
≠ Just Medicine
is not just the practice of medicine. If that were true, then epidemiology would begin with the skilled healthcare of quarter of a million years ago.
≠ Just Rational Records
is not just rational, documented medicine. If that were true, then epidemiology would begin 2400 years ago with meticulous clinical case notes which seek to identify natural (not divine) causes.
≠ Just Public Health
is not just effective public health. If that were true, then epidemiology would begin with the government systems of hospitals, vaccinations, written records and social care of 1000 years ago.
≠ Just Germ Theory
is not just modern scientific medicine. If that were true, then epidemiology would begin with the era of germ theory, sanitation and rapid development of medical science from 150 years ago.
These are essential, life-saving steps towards epidemiology, but not effective disease management. Consider that despite medical progress 1900-1950, at least 600 million people died from smallpox, TB, malaria and the 1918 flu alone, and at least 15% of children died before their first birthday. And that was the century of antibiotics, improved nutrition, sanitation and institutional structures – the toll in previous centuries was far higher.
Then, 75 years ago, entire populations of urbanised people (even some poor and colonised ones) were made safe from deadly pathogens and behaviours. From about 1950 epidemiologists had standard scientific ways to reason about health and perform mathematical calculations. Whole societies engaged with mass efforts to implement policy arising from this reasoning. Diseases were controlled and then suppressed, en route to elimination.
The Turning Point: 1950
Modern epidemiology emerges
When standard scientific methods met mathematical calculation (1950–2010), epidemiologists controlled diseases at scale:
- Smallpox eradicated (the only human disease ever eliminated)
- Polio, malaria, TB suppressed through mass vaccination and antibiotics
- Millions of lives saved annually
Interactive Timeline: 250,000 Years to One Health
Click any era to explore the progression:
250,000 BP – Neanderthal Medicine
Technically advanced pro-social healthcare. Evidence of caregiving for injured individuals, but no systematic disease tracking.
1000 CE – Public Health Systems
Hippocratic-style records, hospitals, vaccinations (variolation), and social safety nets. State-funded responses to disease, but lacking statistical frameworks.
1880 – Scientific Medicine
Germ theory established. Tabular data and environmental interventions (John Snow's cholera maps). Foundation for evidence-based medicine.
1960 – Epidemiology Controls Diseases
Global mass vaccinations and antibiotics at scale. Millions of lives saved annually following control of smallpox, malaria, polio, TB.
1970 – Actuarial Orientation
Risk factor analysis, surveillance systems, and child vaccination programs. Control of measles, rubella, yellow fever.
1980 – Modern Tools
Computers enable SEIR models and large cohort studies. Smallpox eradication certified. Elimination of malaria, polio, and measles targeted.
1990 – Population-Scale Policy
Stochastic models and epidemic simulation. Solutions for complex epidemics: AIDS, SIDS, Ebola, Hepatitis C.
2010 – Limits Reached
Narrow technical approaches hit barriers. Models exclude environment, vector ecology, and climate. Emerging diseases accelerate.
→ 2010-2026 – One Health (The New Epidemiology)
For the first time in history, technical ability and political motivation converge to integrate:
- Human health data
- Animal surveillance (zoonoses)
- Ecosystem monitoring (vectors, climate)
The WHO One Health Initiative aims to get derailed 2030 global health goals back on track.
Note: The US withdrawal from WHO in 2025 has created funding instability, but global commitment continues.
Why This Matters for You
One Health involves most natural and social sciences. Whether you're a computer scientist (agent-based models), ecologist (vector ecology), veterinarian (zoonotic spillover), or climate researcher (changing disease ranges)—your discipline contains variables and rates essential to global health.
Level 3: Technical Monograph
Discovering Epidemiology and One Health
For scientists joining the new health collaboration
Author: Dan Shearer, University of Southampton
Format: PDF (45 pages, 692 KB)
Date: February 2026
License: CC BY-SA (where applicable)
Contents:
- Introduction
- What is epidemiology not just?
- What exactly is One Health?
- Conclusion
- Appendix A: Cheatsheet glossary for non-epidemiologists
- Appendix B: Historical steps towards epidemiology
- Appendix C: How did Epidemiology forget the environment?
- Appendix D: Minimum requirement: mathematics (SIR, Gillespie Algorithm)
- Appendix E: US withdrawal from WHO and One Health
- Appendix F: Governance structures (CBPP, Polycentricity)
- Bibliography: 80+ references (ancient sources to 2026)
Also available: BibTeX source | LaTeX source
Audience Guide
Computer Scientists
See Appendix D for Rule-Based Epidemiology Modelling (RBEM), agent-based vs. compartmental models, and the combinatorial explosion problem in multi-species modeling.
Ecologists & Veterinarians
See Appendix C on environmental exclusion from 20th-century epidemiology, and Appendix A for zoonosis/reservoir/vector definitions.
Policy Researchers
See Appendix E for analysis of the 2025 US withdrawal from WHO and the WHO Pandemic Agreement (May 2025).
Historians of Science
See Appendix B for the "Can epidemiology be done?" test applied to ancient medical texts (Hippocrates to Al-Razi).
Next Steps
One Health needs your disciplinary expertise. Start here:
Search Google Scholar WHO One Health RBEM Codeberg
Last updated: February 2026 | Contact