Data Visualization

Blog of the Data Visualization & Communication Course at OSB-AUB

This is my favorite part about analytics: Taking boring flat data and bringing it to life through visualization” John Tukey

Where You Live Shapes the Care You Get: A Data Story from Lebanon

If you grew up in Lebanon, you’ve probably heard someone say: “If this illness happened in Beirut, things would’ve been easier.”

I’ve heard it from relatives and friends who had to drive for hours for a simple check-up.
Healthcare in Lebanon has never felt equal, but I always wondered: Is this just a feeling, or is the data telling the same story?

To explore this, I combined  two national datasets:

One mapping where chronic diseases and special needs appear across Lebanese towns, and another showing where healthcare facilities are actually located.

  • These visuals show that rural regions, especially Akkar, Baalbeck-Hermel, and the North, have the highest share of towns reporting chronic diseases, confirming that Lebanon’s heaviest health burdens fall on its most underserved areas.
  • We can see that most healthcare facilities are concentrated in urban Mount Lebanon, creating an imbalance where the regions with the greatest health needs have the least medical infrastructure.

To understand this imbalance more clearly, I looked at disease prevalence side-by-side with the availability of the healthcare resources that matter most for each condition.
The question was simple: when a disease appears in a town, is the right type of care actually nearby?

Therefore, I paired each condition with the resource most relevant to its management, based on clinical practice and literature:
• Hypertension → hospitals
• Diabetes → clinics
• Cardiovascular disease → pharmacies or medical centers
• Special needs → dedicated care centers

Once I paired each condition with the care it requires, a clear imbalance appeared:
• The regions most affected by disease had the least access to the services they needed.
• The regions with lighter disease presence had the strongest concentration of facilities.

A clear example is hypertension vs hospitals:
•Akkar, Baalbeck-Hermel, the North, and parts of the South showed high hypertension presence, yet had some of the lowest hospital capacity.
•Meanwhile, Mount Lebanon, with lower prevalence, had more hospitals than all of them combined.

This is more than an imbalance; it’s an access gap that shapes real health outcomes.

So, what does Lebanon need?

  1. Targeted decentralization, not more hospitals everywhere.
    Rural regions don’t need giant new medical complexes.
    They need strategically placed clinics, chronic-disease screening units, hypertension/diabetes corners, and even mobile health programs.
  2. Allocate resources based on data
    Mount Lebanon already has the largest medical footprint.
    But Akkar, Baalbeck-Hermel, the North, and the South need urgent investment.
  3. Build capacity where it matters.
    Even a single medical center, diagnostic pharmacy, or special-needs support unit can shift accessibility for hundreds of towns.
  4. Make data-driven planning routine.
    Lebanon produces far more data than most people realize, we just don’t use it.
    Dashboards and visual can guide ministries, municipalities, NGOs, donors, and health planners to invest where impact will be highest.

Lebanon doesn’t suffer from a lack of medical knowledge, it suffers from a lack of medical access.
And the good news is that access can change.
If resources finally start following the data, rural Lebanon won’t stay medically invisible. The map is clear, now the planning needs to follow.