# Epidemiologists

> Investigate and describe the determinants and distribution of disease, disability, or health outcomes. May develop the means for prevention and control.

- **SOC code:** 19-1041.00
- **Canonical URL:** https://singulariki.com/roles/role-19-1041-00
- **Also known as:** Epidemiologist, Infection Control Practitioner (ICP), Nurse Epidemiologist, Research Epidemiologist, Chronic Disease Epidemiologist, Communicable Diseases Specialist, Environmental Epidemiologist, Epidemiology Investigator
- **Frame:** "AI exposure" means task overlap (how codifiable the work is), not jobs lost or a forecast. Every figure below is traced to a named public dataset.

## What this work is

**Core tasks** (O*NET):
- Communicate research findings on various types of diseases to health practitioners, policy makers, and the public.
- Oversee public health programs, including statistical analysis, health care planning, surveillance systems, and public health improvement.
- Investigate diseases or parasites to determine cause and risk factors, progress, life cycle, or mode of transmission.
- Monitor and report incidents of infectious diseases to local and state health agencies.
- Educate healthcare workers, patients, and the public about infectious and communicable diseases, including disease transmission and prevention.
- Plan and direct studies to investigate human or animal disease, preventive methods, and treatments for disease.
- Provide expertise in the design, management and evaluation of study protocols and health status questionnaires, sample selection, and analysis.
- Write articles for publication in professional journals.
- Identify and analyze public health issues related to foodborne parasitic diseases and their impact on public policies, scientific studies, or surveys.
- Write grant applications to fund epidemiologic research.
- Plan, administer and evaluate health safety standards and programs to improve public health, conferring with health department, industry personnel, physicians, and others.
- Conduct research to develop methodologies, instrumentation, and procedures for medical application, analyzing data and presenting findings.

**Emerging tasks** (O*NET):
- Teach epidemiology to students in public health programs.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Mathematics _(knowledge)_
- Oral Comprehension _(ability)_
- Written Comprehension _(ability)_
- Inductive Reasoning _(ability)_
- Biology _(knowledge)_
- Reading Comprehension _(essential_skill)_
- Critical Thinking _(essential_skill)_
- Complex Problem Solving _(transferable_skill)_
- Judgment and Decision Making _(transferable_skill)_
- Oral Expression _(ability)_
- Written Expression _(ability)_
- Problem Sensitivity _(ability)_

**Skills in demand:**
- Mathematics _(Common Skill)_
- Inductive Reasoning _(Common Skill)_
- Biology _(Specialized Skill)_
- Reading Comprehension _(Common Skill)_
- Critical Thinking _(Common Skill)_
- Complex Problem Solving _(Common Skill)_
- Writing _(Common Skill)_
- Deductive Reasoning _(Common Skill)_
- Active Listening _(Common Skill)_
- Systems Analysis _(Specialized Skill)_
- English Language _(Common Skill)_
- Active Learning _(Common Skill)_

**Tools & technology:**
- Microsoft Excel _(hot technology, in demand)_
- Microsoft Office software _(hot technology, in demand)_
- Microsoft PowerPoint _(hot technology, in demand)_
- R _(hot technology, in demand)_
- SAS _(hot technology, in demand)_
- ESRI ArcGIS software _(hot technology)_
- Facebook _(hot technology)_
- IBM SPSS Statistics _(hot technology)_
- Microsoft Access _(hot technology)_
- Microsoft Outlook _(hot technology)_
- Microsoft Word _(hot technology)_
- Python _(hot technology)_

## AI exposure & outlook

- **AI task-overlap index:** 81st percentile (High) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 98th percentile (High) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 76th percentile (High) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 62nd percentile (Moderate) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 33rd percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** yes — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** 16.2% growth (Growing fast); 0.8k annual openings; 12.3k → 14.3k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $83,980; 11,460 employed.

## How people actually use AI here

Anthropic Economic Index — measured AI conversations mapped to this occupation's tasks:

- **Automation vs augmentation:** 12% automation, 75% augmentation (usage-weighted).
- **Autonomy median:** 4.0 (higher = AI acts more independently).
- **Dominant collaboration mode:** learning.

**Tasks most handed to AI here:**
- Consult with and advise physicians, educators, researchers, government health officials and others regarding medical applications of sciences, such as physics, biology, and chemistry. _(1.5% of measured AI use; learning)_
- Educate healthcare workers, patients, and the public about infectious and communicable diseases, including disease transmission and prevention. _(1.2% of measured AI use; learning)_
- Teach principles of medicine and medical and laboratory procedures to physicians, residents, students, and technicians. _(1.0% of measured AI use; learning)_

**Example prompts (honest phrasings of the tasks above — starting points, not endorsed instructions):**
- Help me consult with and advise physicians, educators, researchers, government health officials and others regarding medical applications of sciences, such as physics, biology, and chemistry.
- Help me educate healthcare workers, patients, and the public about infectious and communicable diseases, including disease transmission and prevention.
- Help me teach principles of medicine and medical and laboratory procedures to physicians, residents, students, and technicians.

## Sources

- **O*NET** (30.3) — U.S. Department of Labor / National Center for O*NET Development. https://www.onetcenter.org/database.html
- **BLS Occupational Employment and Wage Statistics (OEWS)** (May 2024) — U.S. Bureau of Labor Statistics. https://www.bls.gov/oes/
- **BLS Employment Projections** (2024–2034) — U.S. Bureau of Labor Statistics. https://www.bls.gov/emp/
- **Anthropic Economic Index** (v4 (2026-01-15) + v2 (2025-03-27)) — Anthropic. https://www.anthropic.com/economic-index
- **Microsoft “Working with AI”** (working-with-ai) — Microsoft Research. https://www.microsoft.com/en-us/research/
- **“GPTs are GPTs” (Eloundou et al.)** (arXiv 2303.10130) — OpenAI / academic. https://arxiv.org/abs/2303.10130
- **AI Occupational Exposure (AIOE)** (Felten, Raj & Seamans) — academic. https://github.com/AIOE-Data/AIOE
- **Frey & Osborne (2013)** (frey-osborne-automation) — academic. https://www.oxfordmartin.ox.ac.uk/publications/the-future-of-employment/
- **Dingel & Neiman (2020)** (dingel-neiman-workathome) — academic. https://github.com/jdingel/DingelNeiman-workathome

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_Generated from Singulariki's joined dataset; data snapshot 2026-06-02T21:00:32.945303+00:00. https://singulariki.com/roles/role-19-1041-00_