What we've built
Working demonstrations of what better data and better models can answer — built on open data where it exists, and proprietary insights where it doesn't. Closing that gap is what the commons is for.
Triple RDT Launch Planning
Should we launch, where, and at what price?
A supplier weighing a new triple rapid test for HIV, syphilis and hepatitis B faces four questions at once: whether the market is worth entering, with which product design, at what price, and in which countries. Existing market landscapes answer none of them — they size the market and stop.
This simulation models the market across sixteen countries to 2037. Change the launch year, product format, price, funding scenario or country set, and it returns the commercial case, the footprint of what you're capturing and leaving behind, how a market of 35 million pregnancies becomes a few million tests, and what the product is worth in health terms. Every assumption is visible, tagged by the evidence behind it.
It runs on published data, government procurement records and market intelligence no public source holds — which is the gap the commons is built to close.
Maternal Mortality Case Study
What would actually reduce maternal and neonatal deaths here?
Every country has a maternal mortality figure and a list of recommended interventions. What nobody can say is which of those interventions would move the number in a particular place, or by how much — so budgets get allocated by consensus and precedent rather than by what the evidence supports.
These causal models cover 203 countries over 24 years, explaining 98% of the variance in maternal mortality between countries and 99% in neonatal mortality. They rank the factors that drive each, and make it possible to test what a change would do: raising skilled birth attendance in Kenya by ten points, or improving health worker density, with the projected effect and its uncertainty. The same predictors turn out to drive both outcomes, which is itself a finding — maternal and newborn survival are not separate problems to be funded separately.
Built entirely on open data, from IHME, WHO, the World Bank and DHS. What it cannot yet see is what any of it costs, or what is actually reaching facilities — which is the gap the commons is built to close.
Read the case study →