Kaelo

/ka.ˈe.lo/·Setswana·"to care for, to nurture, to look after"

Botswana imports nearly all of its medicines. Getting them from a port to a patient in a rural clinic, on time and unexpired, is a logistics problem before it is a clinical one.

Kaelo exists to help close that gap.

619
health facilities
2.4M
people
18
health districts

What we do

Kaelo is an antimicrobial supply chain optimization platform developed in collaboration with ACHAP and presented to Botswana's Ministry of Health and Central Medical Stores. It uses advanced mathematical models, including robust optimization and adaptive (affine) decision rules, to determine how medicines should be procured, stored, and distributed across the country's 619 health facilities.

The system accounts for demand uncertainty, transport constraints, procurement costs, and the complex tiered network of warehouses, hospitals, clinics, and health posts that cover 2.4M people across 18 health districts.

How it works

Robust optimization

Instead of assuming a single forecast is correct, the model optimizes against theworst-case demand scenario within a plausible uncertainty set. Decisions that hold up under the hardest month hold up under every month.

Affine decision rules

Rather than fixing every order up front, Kaelo learns a linear policy: "order x if we've observed demand y." This keeps the math tractable while letting the system adapt as real demand unfolds month by month.

Software

A public build of the planning tool, with the optimization model intact and every procurement figure stripped out. You supply the demand and cost numbers yourself.

Open the software →

Best on a desktop browser for now. The solver sleeps when idle, so the first load can take a moment to wake up.

Team & collaborators

Princeton ORFE
  • Dr. Bartolomeo Stellato (advisor)
ACHAP
  • Mr. Lesego Busang
  • Mr. Stanley Mapiki
  • Mr. Tiro Molefe
  • Dr. Khumo Seipone
Presented to
  • Ministry of Health, Botswana
  • Central Medical Stores