Supply Chain LabHow Supply Chains Save Lives · A 5-Minute Story
True story · Supply Chain Lab

Supply chains save lives. For real.

Doctors treat you. But when a pandemic hits, someone has to figure out who gets the vaccine first, which clinic has it, and how it gets there before it spoils. That someone? Supply chain people. Here’s how we did it for a whole city - for real.

↓ Scroll - it’s a story
1The problem

Vaccines existed. Enough of them didn't.

Melbourne, COVID. 5.1 million people, everyone needs two doses, and vaccines arrive in tiny, unpredictable batches. The government calls us and asks:

"Who gets vaccinated first - and how do the doses physically reach them?"

You can’t answer that with opinions - people would riot. You answer it with data, maps and maths. So that’s what we did.

5.1M+
People to protect
2
Jabs each, three weeks apart
174d
Days to get it done
Never
Enough doses in the fridge
1
Shot at getting the plan right
2Step 1 · Find who can’t wait

Where are the people who need it most?

We mapped every single suburb: where do the grandparents live? The heart patients? The diabetics? And where is the virus spreading fastest, right now?

Maps of health risk criteria across Greater Melbourne
The maps
Every suburb, scored - heart disease, cancer, smoking, age, density…
COVID-19 case-rate hot spots across Greater Melbourne
The hot spots
Where the virus actually was - live case rates across the city.
3Step 2 · Rank the suburbs

The map decides who goes first

All those maps fuse into one. Red = go first. Green = you can wait. Computed and fair - nobody can argue their suburb to the front of the queue.

Vaccination priority surface for Greater Melbourne
The answer
The priority map - the spatial answer to “who first?”
4Step 3 · Book 5 million people

Which clinic? Which day? × 5,100,000

The model books everyone in, day by day, for 174 days. And every first jab is a promise: your second dose is reserved for you, three weeks later. Break that promise and people stop trusting the whole campaign.

Daily vaccination coverage over the 174-day campaign
Day by day
Day 1 → day 174: the city turns from red (waiting) to covered.
5Step 4 · Roll the trucks

Every morning, refrigerated trucks roll out

Vaccines are divas: too warm - ruined. Too late - wasted. Every day the model plans which truck goes where, in what order, carrying exactly how many doses.

Daily vaccine distribution routing plans across Melbourne
The routes
Real optimised truck routes across Melbourne, planned fresh every day.
6Step 5 · People are picky

“Nah, I’ll wait for Pfizer”

Sound familiar? Some people want Pfizer, some are fine with AstraZeneca, some will wait weeks for their pick. Ignore that and doses expire on shelves while people queue elsewhere. Our newest research builds those preferences straight into the maths of what to buy.

Pfizer

Preferred by a majority - but supply is tighter and the cold chain is stricter
~62%

AstraZeneca

Easier to store and move - but some of the population will wait rather than take it
~38%

Illustrative split for discussion - the research models preference as uncertain, which is exactly the point.

7The real thing

The actual research output, day by day

No cartoons here - this is the published simulation’s real output for Scenario I: shortage. Watch Melbourne turn from blue (waiting) to green (protected), one day at a time.

Day 1
Scenario I · Shortage · 195-day campaign
0%
First dose covered
0%
Fully protected
Still waiting First dose Fully protected Vaccine centres

This is supply chain management. This is how we save lives.

Cheap chocolate, concert tours, flood relief, pandemics - it’s all the same skill: deciding who, where, when and how when there isn’t enough to go around. Study supply chain, and problems like this become your day job. (True story: published in Transportation Research Part E, 2022 - built at RMIT.)

How to play · 30 seconds

Two missions, five taps to learn

MISSION 1 · Tap a district
0/30/30/20/40/41
10k10k10k…
  • 1Tap the red district first - most points per batch of 10k doses
Fill the need - then stop
3/33/32/22/40/423
LOCK IT IN →
  • 23/3 = full. Extra batches get wasted
  • 3Done early? Tap Lock it in
MISSION 2 · Build routes
2,2001,5002,6001,6001,4002,00045
VAN 1 · 34/60 min+ Van (−1,200)
  • 4Tap hospitals in order - watch the 60-min clock
  • 5Out of time? + Van (costs 1,200)
Your turn

Your turn - grab your phone

Scan the code and play Vaccine Rush: split scarce doses, route the cold-chain vans, beat our algorithm. Up here, the live simulation keeps running - Scenario III is the supply crash.

LIVE MODEL · GREATER MELBOURNE · PRIORITY SURFACE Distribution depot Day 1 protected lowhigh priority delivery route
Live model
What you are watching. The priority surface drives dose allocation; refrigerated vans run two-dose deliveries while the ring fills with the share of people fully protected.

Choose a supply scenario

Supply shock in progress - deliveries cut, plan re-optimising…
Day 1 of 174running…
0
Doses delivered
0%
Fully protected
0%
First-dose coverage
0
Severe cases averted*
QR code to play Vaccine Rush on your phone
SCAN → PLAY
Vaccine Rush · beat the algorithm

About this tool

Mock Lecture Story: How Supply Chains Save Lives

The concept

A scroll-through story of a published vaccine-distribution decision support system: from mapping the vulnerable to routing refrigerated trucks, ending in a live simulation.

How it works

Each chapter shows one decision from the real Greater Melbourne study - risk mapping, prioritisation, scheduling, routing, vaccine preferences - using the paper's own figures.

Winning strategy

Prioritise by risk, keep the second-dose promise, respect people's preferences, and re-optimise fast when supply is disrupted.

who first → which clinic, which day → which truck, which route → re-optimise under disruption
Vaccine logisticsHumanitarian logisticsPrioritisationStorytelling
Source: Shahparvari et al. (2022), Transportation Research Part E
Developed by Dr. Shahrooz Shahparvari · RMIT University · Supply Chain Lab