I still remember the early months of the pandemic so vividly. Not the lockdowns or the empty streets, everyone remember those, but a feeling that something was uneven. Some areas felt like they were drowning in cases, while others seemed quitter, almost detached from the chaos. All this time, I kept wondering whether COVID-19 had really hit all Lebanon equally, or if some regions carried a heavier burden without anyone noticing.

All we had back then were stories. People were updating, hospitals were warning, and rumors flew around faster than the virus itself. Nobody had the big picture, though. Months later, I was working on a class visualization. I decided I wanted to finally see the data for myself. I mapped COVID-19 cases by governorate, expecting differences, maybe slight variation here and there…what is saw was far from slight.

One bar rose so high that for a moment I thought I made a mistake. Mount Lebanon didn’t just have more cases-it had dramatically more. The difference was overwhelming. All the other governorates sat together in a similar range, almost aligned with the each other, but Mount Lebanon stood on its own, towering over the rest of the chart. I started at that one bar for a long time. It wasn’t just a number; it felt like a memory reshaping itself in front of me.

In an instant, so many things fell into place; the constant ambulance sirens, the overflowing hospitals, the stories from friends who lived there of whole families falling ill at once. We all lived through the same pandemic then, but clearly not the same experience. Some regions had time to breathe, others barely had space to stand. That massive difference in the data felt strangely personal, like the chart was confirming something I had sensed but could not articulate back then.

What struck me the most was how unfair it all seemed. We speak about COVID-19 as a shared national crisis, but the weight of it wasn’t equally shared. Risk was not equal, exposure was not equal, the burden was not equal, and no headline back then reflected the size of that imbalance. But here it was, visually undeniable, in a single chart.

Looking at the numbers now, from a more calm distance, it allowed me to realize why these insights matter. They show which communities were stretched thin, which areas needed more support, and where the system struggled the most. If we ever face something like this again, we can’t afford to treat every region the same. The patterns in the data are not just historical facts; they’re warnings.

To me, this visualization became more than an assignment; it was a reminder of just how differently we lived the very same story and how important it was to pay attention to the details we had overlooked. Mount Lebanon was not just “more affected.” It carried a disproportionate share of the pandemic’s weight, and seeing that so clearly now changes the way I remember everything that happened. Sometimes, one simple chart is all it takes to understand a moment in time differently, and this one did exactly that.