Put a $50 lead test in a family's hands before the baby comes home.
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.
Your assumptions
Defaults are grounded in public data and cited below. Move anything.
Your program's current numbers (optional — stays on your device, we never see it) ►
Fill in what you have. Each field sharpens the output. Blank fields use national defaults. Nothing leaves your browser.
Annual births in your area
CDC WONDER county natality (free, public)
Confirmed EBLL cases per year
Children with BLL ≥3.5 μg/dL from your case system
Children tested for BLL per year
State surveillance or Medicaid claims
Pre-1978 homes in jurisdiction
Auto-sets the housing age slider above
Total occupied housing units
Census ACS B25001 by county or ZIP
Annual reactive lead program budget
Case management + investigation + medical follow-up
Households equipped
spared = homes × pre78 × haz × catch × acts × kids
homes = min( budget ÷ $/kit , partner reach/yr × uptake )
you setProgram design, not an unknown. Budget ÷ ~$25, or annual WIC / OB touchpoints × ~85% uptake.
default10,000 — illustrative scale. ~40M US homes predate 1978 (Census ACS B25034).
to settleNo study needed — your capacity is known internally.
Cost to put a kit in a home
cost = homes · $/kit → net = benefit − cost
$/kit = kit price + distribution − grant. Borrow‑and‑return → ~$2 per next family.
you haveYour unit price, staff time, grant offset. Mail‑out ≈ $27–30; CHW ≈ $26; bare kit ≈ $50; grant‑funded = $0.
default$25. Kit reusable for life, ~600 tests ≈ 13¢/test; refill ~$55 → ~9¢. The funded cost is the kit, not the testing.
to settleValidate the ~600‑tests‑per‑kit field reuse rate over a program year.
Homes built before 1978
spared = homes × pre78 × haz × catch × acts × kids
pre78 = (≤1949 + 1950s + 1960s + 0.78×1970s) ÷ all units
you haveExact, from a ZIP (loader does it) or your assessor / housing‑authority records. Not an assumption once loaded.
default40% national. Old cities 65–85%, Sunbelt suburbs 10–20%. Census ACS B25034; 0.78 = share of the 1970s built before the Aug‑1978 ban.
to settleAlready measured. Load your ZIP or type your local share.
Of those, a real lead-paint hazard present
spared = homes × pre78 × haz × catch × acts × kids
haz = confirmed hazards ÷ pre‑1978 units inspected
age‑weighted: pre‑1940 ~50% · 1940–59 ~33% · 1960–77 ~16%
age‑weighted: pre‑1940 ~50% · 1940–59 ~33% · 1960–77 ~16%
you haveCode‑inspection or lead‑investigation databases give the ratio directly (correct for complaint‑driven selection bias).
default30% of pre‑1978 homes. HUD AHHS‑II 2018–19: 18.6% of ALL housing has a dust‑lead hazard, ~2× that among pre‑1978. Jacobs 2002: ~40%.
to settleStratified random sample ~200 pre‑1978 units by age band, XRF + ASTM E1728 dust wipes, NLLAP lab. ±7‑pt CI.
FluoroSpec catches a real hazard
spared = homes × pre78 × haz × catch × acts × kids
catch = FluoroSpec positives ÷ XRF‑confirmed hazards — field study, none published yet
you haveNothing local. This is intrinsic to the chemistry + lay‑user technique, not derivable from program records.
default90%, deliberately conservative. Comparator only: EPA ETV verified rhodizonate spot kits at 99.7% sensitivity (3M LeadCheck, 2/651 false neg). FluoroSpec dust performance is unmeasured.
to settleThe study to fund first. Blinded field trial, ~200 surfaces across substrates, lay users, XRF + NLLAP lab ground truth.
Family acts on a positive result
spared = homes × pre78 × haz × catch × acts × kids
acts = owner% × 0.65 + renter% × 0.35 (+ follow‑up lift)
you haveYour owner/renter mix (intake or ACS B25003). Renters need landlord cooperation → lower. Halves the uncertainty alone.
default55%. Analogues: radon test+referral 30–35% (no contact) → 45–60% (counseled); HUD hazard‑control ~85% once enrolled. A CHW visit lifts ~15–20 pts.
to settleCheapest high‑value study. 90‑day follow‑up of ~150 positive‑result families, split by tenure and follow‑up protocol.
Young children per home
spared = homes × pre78 × haz × catch × acts × kids
kids = enrolled children <6 ÷ enrolled households
you haveYour intake form has children's ages. Exactly derivable, no external data. WIC reads it straight off enrollment.
default1.0 (conservative — the one new baby). WIC avg ≈ 1.25 children <6/household; Census ≈ 0.38/home across all households.
to settleNo study — your enrollment data has it now.
Value of sparing one child lead exposure
benefit = spared × $/child
$/child = ΔBLL × 0.5 IQ‑pt/µg‑dL × ~$22K/IQ‑pt
you haveCounty median wage (ACS B19013) localizes $/IQ‑pt. Local hazard‑control ΔBLL data sharpens the dose term.
default$22,000, earnings only. Bottom‑up: Lanphear 2005 (0.5 IQ/µg‑dL) × Grosse 2002 ($/IQ‑pt). Top‑down: Pew $84B ÷ 3.8M births = $22,105. Full social cost 1.5–2×; a severely poisoned child >$150K.
to settleMonte‑Carlo per child: baseline BLL → ΔBLL → ΔIQ → Δlifetime earnings, discounted, probabilistic.
Of that, hard public dollars spent reacting today
redirectable = benefit × react%
react% = annual reactive lead budget ÷ model benefit
you haveYour finance office has the case‑management budget line. Cases/yr × loaded cost ÷ benefit = your exact %.
default18%. Loaded cost/confirmed case ≈ $1,500–2,500 (case mgmt $800–1,500 + investigation $430–550 + medical $200–400). CDC CLPPP ≈ $51M/yr, all reactive.
to settleNo study — pull your reactive budget line and divide.
The whole model in three lines
children_spared = homes × pre‑1978% × hazard% × catch% × acts% × kids/home
benefit = children_spared × value‑per‑child
net = benefit − homes × cost‑per‑kit
Every slider below is one bolded term. Open show the math under any slider for the formula to derive that term from your own data, the published default with its citation, and the study that would settle it for good.
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net societal benefit
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Program cost
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Benefit
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Children spared exposure
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Returned per $1
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Reactive spend redirectable
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Break-even $/child
Every slider is an open question, not a fact
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.
- This is the paint and dust pathway only. Not water, not soil.
- "Spared exposure" means a hazard was found and acted on, not a guarantee.
- Load your ZIP to replace the housing-age guess with your Census data.
The break-even question
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.
What a local program already knows vs. what it is estimating
Open the "why this number" dropdown under any slider to see the derivation. Roughly speaking:
- You already know exactly: how many households your program can reach (Slider 1), your loaded cost per kit (Slider 2), your housing age share if you have address-level data or a ZIP code (Slider 3), how many children under 6 are enrolled in your program (Slider 7), and your annual reactive lead spend (Slider 9).
- You can estimate closely from analogues: the hazard rate for your housing stock using HUD age-band data + your local housing vintage (Slider 4), and the action rate using your owner/renter mix and your follow-up protocol (Slider 6).
- You are using a published anchor: the value per child prevented (Slider 8) — the Pew/Trasande $22K figure is peer-reviewed and independently reproduced. Use it or cite a local wage adjustment.
- You are using an assumption: FluoroSpec's real-world sensitivity (Slider 5). The proposed field study would replace this with a measurement.
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.
If you actually deploy this, the cost curve is hyperbolic.
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 →