Health Impact
How AI links air quality to health outcomes
We pair exposure models with epidemiological evidence to estimate health impacts, helping policymakers prioritize interventions that matter most for communities.
Why health impact modeling
Translating pollution into health metrics puts urgency and equity into focus-showing where cleaner air delivers the biggest human gains.
Inputs
High-resolution concentration fields, population and vulnerability data, baseline health rates, and weather modifiers.
Outputs
Health burden estimates, uncertainty ranges, and maps that highlight priority areas.
Our approach
Exposure modeling
Combine air quality fields with population distribution, time-activity patterns, and vulnerability indicators.
Risk estimation
Translate exposures into health impact metrics using peer-reviewed concentration-response functions.
Equity insights
Highlight groups and neighborhoods bearing disproportionate burden to guide targeted interventions.
What you get
Clear, defensible health impact estimates that connect air quality to human outcomes, ready for policy briefs and funding proposals.
- Health-weighted pollution burden by neighborhood and demographic group
- Attributable cases estimates (e.g., hospital visits) with uncertainty bands
- Scenario comparisons for interventions and seasonal changes
- Downloadable summaries and visualizations for policy briefs
Transparent and equitable
Every estimate carries context on data sources, assumptions, and uncertainty so communities and policymakers can trust the results.
Explainable
See which factors drive risk in each neighborhood.
Actionable
Compare scenarios to plan interventions and funding.