What is Atlas Lyme?

Atlas Lyme is an Epidemiologist Decision Intelligence Platform for Lyme disease and other tick-borne diseases. It is an AI-enabled, disease-focused public-health platform that brings One Health evidence into a shared place so epidemiologists can recognize patterns, understand context, and decide what deserves investigation.

The product vision is:

From fragmented surveillance data to timely, interpretable, evidence-backed public-health action.

The North Star is:

A system that identifies what matters, explains why it matters, communicates uncertainty, and helps epidemiologists decide what deserves investigation.

Why Atlas exists

Tick-borne disease questions rarely fit inside one dataset. Human disease observations, tick and vector measures, pathogen prevalence, climate, habitat, population context, and scientific evidence may be published by different organizations, on different schedules, at different geographic or time scales.

Atlas connects those perspectives while keeping the context needed to interpret them. The goal is less manual joining and searching, earlier recognition of signals worth reviewing, and more defensible public-health conversations.

What Atlas helps you do

Depending on the current release, Atlas can help you:

• review geographic patterns and potential areas of concern;
• bring human, ecological, environmental, pathogen, and population context into the same investigation;
• inspect the evidence behind a signal, including source, release or time period, methodology, and limitations;
• compare supported geographies or filter states that another reviewer can reproduce; and
• turn a broad surveillance question into a smaller, evidence-backed investigation question.

These are decision-support capabilities. Atlas helps organize evidence and focus attention; the epidemiologist remains responsible for interpretation, follow-up, and public-health action.

What “AI-enabled” means here

AI-enabled describes the product direction: Atlas is being built to help people find relevant patterns, connect evidence, summarize context, and ask better follow-up questions. Any AI-assisted experience must remain grounded in approved evidence, show its sources and limitations, and preserve a human review step.

The public application does not treat an AI output as an authoritative finding. A generated explanation or suggested investigation path is a prompt for review, not a diagnosis, causal conclusion, or automatic public-health decision.

What Atlas is not

Atlas is not:

• a clinical diagnostic tool or a substitute for medical advice;
• an individual exposure, infection, or disease-risk predictor;
• a direct measure of disease burden merely because a place ranks highly;
• proof that a vector, pathogen, environment, or population factor caused an outcome;
• a guarantee that an outbreak will or will not occur; or
• a replacement for epidemiologists, public-health analysts, local knowledge, or domain experts.

The current release is an early public prototype and situational-awareness foundation. A visible signal means “review this question with the available evidence,” not “this place is definitively high risk” or “this place is safe.”

A public, evidence-first platform

Atlas is designed to be useful without requiring an account to explore the public experience. A signed-in profile can store a default jurisdiction for the next Review session. That preference does not change evidence, scores, or which geographies you can open. Public results should be understandable through the map and an equivalent table or text path, with provenance and limitations kept close to the result.

To begin, sign in and open Atlas Explorer. The professional workspace guide names the six destinations. Return to the decision-support workflow when you want to understand how to review a result.