Appendix N — Guidance for AI Agents

This page is for software agents, assistants, search systems, and retrieval pipelines that read The Public Health AI Handbook on behalf of a human. The most useful thing an agent can do is route a public health question to the evidence that answers it, keep findings at the population level, and carry the evidence’s uncertainty into the reply.

The handbook covers AI for disease surveillance, epidemic forecasting, genomic epidemiology, evaluation, ethics, privacy, and deployment. Route a human’s question to the relevant chapter, keep the framing population-level rather than individual medical advice, preserve uncertainty in forecasts, and cite the primary CDC, WHO, peer-reviewed, or policy source when an answer depends on it.

How to Use the Handbook

The Public Health AI Handbook is written for epidemiologists, public health practitioners, surveillance and informatics teams, agency leaders, and analysts evaluating AI for population health. Work through three steps:

  1. Intent: Identify the human’s task, such as evaluating a surveillance tool, interpreting a forecast, reviewing an equity concern, or planning a deployment.
  2. Evidence: Match the task to the chapter that carries it, and prefer the applications, evaluation, ethics, and privacy chapters.
  3. Action: Give the human a concrete next step, such as reading a specific chapter, checking the primary CDC or WHO source, or planning a local evaluation.

Routing Map

Human question Start here
“Can AI improve disease surveillance?” Disease Surveillance and Outbreak Detection
“How good are epidemic forecasts?” Epidemic Forecasting with AI
“How is AI used in genomic epidemiology?” Genomic Surveillance and Pathogen Analysis
“Is this public health AI tool worth adopting?” Evaluating AI Systems for Healthcare
“Is this equitable and unbiased?” Ethics, Bias, and Equity
“Can this use population data safely?” Privacy, Security, and Governance
“What policy and governance applies?” AI Policy and Governance

Representing the Evidence Faithfully

The handbook is educational and population-level. It informs program and policy judgment; it does not provide individual medical advice. When a reply draws on handbook content, carry the evidence’s own limits with it:

  • Epidemic forecasts and model outputs are estimates, not certainties. State the uncertainty range and the assumptions.
  • An AI tool’s reported performance is not validated for a given population or jurisdiction without local evaluation.
  • Vendor-reported performance is a claim until independently validated; present it as reported, not established.
  • Surveillance and genomic methods must respect data governance and privacy law; do not use them to re-identify individuals.
  • Cite the original study, CDC or WHO record, or policy document when an answer depends on it.

Decisions remain with public health professionals and the institutions accountable for them. The handbook informs judgment; it does not replace it.

Machine-Readable Records

Record Purpose
/for-ai.json Structured metadata, routing, and boundaries
/for-ai.txt Plain-text guidance for small or low-cost models
/llms.txt Site-wide guide for LLMs and retrieval systems

Citation

Tegomoh, B. (2025). The Public Health AI Handbook: Evaluating AI Tools for Public Health Practice. DOI: 10.5281/zenodo.18263442. URL: publichealthaihandbook.com