Impact Model: Human Health as the Fulcrum
Scenario Presets
Assumptions
Financial Impact Model for U.S. Population
Cumulative investment in cures, avoided healthcare costs, and polluter recovery over time
Investment in Cures — Cumulative cost of developing and deploying early interventions. Calculated as people treated × estimated intervention cost per disease.
Avoided Healthcare Costs — Cumulative savings from preventing chronic disease. People who received early intervention no longer incur ongoing costs. Compounds as more people are treated.
Recovered from Polluters — Portion of intervention costs recoverable through liability mechanisms. Ramps up over the Attribution Timeline as legal frameworks mature. = Investment × Liability % × Attribution Progress.
Disease Data
Check or uncheck diseases to include/exclude them from the financial model. Click the arrows in each column header to sort the table.
| Disease | Key Exposures | Env. Attrib. % | US Prevalence | Annual Cost | Cure Cost |
|---|
For each disease, we estimate the environmentally-attributable disease burden: the proportion of cases where environmental exposures are believed to play a contributing role. These estimates combine multiple exposure categories: ambient air pollution, heavy metals, and occupational exposures. Where available, we draw on Global Burden of Disease (GBD) estimates. We use GBD Disability-adjusted life-years (DALYs) as proxy for the environmental-attributable fraction. For exposures not covered by GBD, we synthesize estimates from peer-reviewed epidemiological studies. Multi-exposure estimates were combined using the joint attributable fraction formula.
Key Finding
Across all scenarios, investment in early interventions is fully offset by avoided healthcare costs within 20 years. Even with delayed polluter attribution, liability recovery can meaningfully reduce upfront costs and support equitable access.
Bottom line: Curing pollution-linked disease pays for itself—and creates financial accountability for polluters.
About This Model
Environmental pollution drives a significant share of chronic disease, yet the biotech industry has largely ignored this trillion-dollar health burden. Why? Because there's no clear path to market. Unlike genetic diseases with identifiable patient populations, pollution-linked conditions are diffuse, underdiagnosed, and lack the commercial incentives that drive drug development.
This model makes the case that early biological interventions for pollution-linked disease are not only medically viable but financially compelling. By quantifying the costs of developing cures alongside the savings from preventing chronic disease, we demonstrate that human health can serve as a fulcrum for systemic change. When curing disease becomes cheaper than treating it, investment flows. When polluters can be held liable for the diseases they cause, accountability follows.
Use the sliders above to explore different scenarios: How fast can cures be developed? How effectively can they be deployed? What share of costs can be recovered from polluters? The model reveals that across a wide range of assumptions, the economics favor action.
View full methodology, assumptions & limitations →
Disease data from GBD 2023. Attribution estimates synthesized from epidemiological literature. Click column headers in the Disease Data table to sort.