Most childhood lead exposure is lead-paint dust in homes built before 1978, and it is almost entirely preventable if someone finds it before a child ever crawls on that floor. This models handing families a test at birth, before the child is ever screened for lead, so exposure is stopped instead of discovered later in a blood draw. Every number below is an assumption you control.
Defaults are grounded in public data and cited below. Move anything.
Fill in what you have. Each field sharpens the output. Blank fields use national defaults. Nothing leaves your browser.
This is a model for thinking clearly, not a forecast. Each default is a defensible placeholder rooted in published data, and each one is a question a local program can answer more precisely than this model does nationally. The "why this number" dropdown under each slider shows the word equation for deriving your own local input. Most programs already have the data for at least five of the nine sliders. You do not have to share any of it with us — just move the slider.
Defaults: ~40% of US homes predate the 1978 ban (Census ACS B25034, ZIP-loadable); hazard-present rate from HUD's American Healthy Homes Survey II (2018–19); FluoroSpec sensitivity is an engineering assumption with a proposed field study; per-child value the Pew/Trasande ~$22K earnings anchor, where the published benefit-cost literature finds $17 to $221 returned per $1 spent on hazard control (Gould 2009). The kit is reusable for ~600 tests, refills ~$55, so the real per-test cost is pennies — the funded cost is simply putting a kit in the home.
The model's output panel shows a "break-even $/child" figure. That is the answer to: how low would the value of sparing one child have to be before this program costs more than it returns? At default settings (10,000 households, $25/kit), the break-even is roughly $421 per child. The lowest estimate in the published literature for the economic value of preventing a case of childhood lead poisoning is several thousand dollars. The question for a skeptic is not whether $22,000 is exactly right — it is whether $421 is too high. Every peer-reviewed estimate puts the per-child value at least 10–50× above the break-even threshold.
The full formula the model runs: children spared = households × (pre-1978 share) × (hazard rate) × (detection rate) × (action rate) × (children per home). Benefit = children spared × value per child. The program pays for itself the moment benefit exceeds program cost. At the default inputs, that happens before the first 20 kits are distributed.
Open the "why this number" dropdown under any slider to see the derivation. Roughly speaking:
Five of nine sliders are data you hold. Two more are derivable. One is well-anchored in the literature. One is assumed and labeled as such. That is the honest structure of the model.
The model above assumes a fixed cost per test. In a deployed program that is not what happens. The same kit gets refilled and reused; the per-test cost drops sharply as more tests get done, and at scale it approaches the marginal cost of the reagent itself.
A $50 kit used for 10 tests is $5 per test. The same kit at 500 tests, with refills, is about 15 cents per test. The shape of that decrease is what makes a kit program sustainable on a small budget.
See the cost curve →