In this episode of Sciencing Out, host Reyhaneh Maktoufi introduces you to two of these experts—statistician and pioneer of modern nursing Florence Nightingale, and modern-day data journalist Mona Chalabi, who’s used her illustrations and graphics to visualize everything from how hairy you are to healthcare inequities.
Also known as the "Lady with the Lamp" during the Crimean War of the 1850s, Florence was dispatched to a hospital in Scutari where wounded British soldiers sought treatment. But many of the soldiers there, due to the unsanitary conditions in the hospital, died from illnesses—like typhus—unrelated to their battle wounds. Florence advocated for more cleaning supplies, which the British government eventually sent over. typhus
After the war, Florence wanted to prove that cleaner conditions lead to better health. So she gathered statistics from military hospitals near battlegrounds across Britain. Then she created a chart to help visualize the data—instead of simply reporting numbers. By correlating filth and poor health, Florence's research pushed Parliament to pass the Public Health Act of 1875, improving the overall life expectancy of English citizens.This was one of the first-known moments of data visualization influencing public policy.
Today, Mona uses her statistical knowledge in graphics to help people understand big concepts. "I really enjoyed making charts,” she told NOVA. “I would kind of obsess for hours over things like the font and the placement and the colors that I used. They stay in people's memories better, and they have greater impact.”
Mona has visualized and shared to social media many data sets, from topics related to animal extinction to police brutality, in her unique style—imperfect lines and easy-to-understand whole numbers.
Sciencing Out: What it Means to Make Information Tangible
Published: June 4
Reyhaneh Maktoufi: Oh hi, I didn’t see you there. How long is a waiting line consisting of 24 king cobras stretched end to end? How heavy would a large school bus be, if it’s only filled with clones of Nicholas Cage? Sometimes, it’s pretty hard to get a sense of numbers or imagine what they mean. But thankfully, there are experts in the world whose job is to make these numbers tangible.
One of these people was Florence Nightingale, a dedicated nurse, a pioneer of modern nursing, and a statistician who made lasting changes to Britain’s healthcare system.
Another is Mona Chalabi, a data journalist who’s dedicated to visualizing everything from how hairy you are to vaccination rates to health care inequities based on race and ethnicity.
Let’s start with Florence’s story. Time machine, 1854 please, during the Crimean War in Scutari, what is now Üsküdar, a district of modern-day Istanbul.
Onscreen: Sciencing Out with Florence and Mona
Reyhaneh Maktoufi: You might know her as the Lady with the Lamp, that nurse who saved lives during the Crimean War of the 1850s, the hospital guru, Florence Nightingale, named after the Italian city of her birth, Florence. She was a strong-willed, kind of awkward, and also an educated lady, who at one point cared for a tiny pet owl named Athena.
But it’s also important to recognize that Florence was a strong supporter of British colonial rule, that caused the death and subjugation of Indigenous people all around the world. Through her writings, we know that she believed that imposing the British culture and norms on other people was very necessary for the expansion of the British empire. The alternative, and I’m quoting here, “would be simply preserving their barbarism for the sake of preserving their lives.”
So yeah, Florence, and many other iconic science figures throughout history have problematic stories. Many times, their contributions to their societies came at horrible costs to other people — impacting their lives even today. So as we talk about these figures, we have to be aware of the complicated legacies these people have.
Ok, back to the Crimean War when Florence was dispatched to a hospital in Scutari. Wounded British soldiers ended up at this hospital, where Florence was in charge of supervising 38 nurses. She was going around trying to take care of the wounded as best as she could, getting them food, clean utensils and towels, making the hospital more resistant to the cold weather and providing cleaner water.
But many of the soldiers there were dying from illnesses unrelated to their actual battle wounds. Things like typhus...
Onscreen: a disease caused by bacteria transmitted by flea or tick bites
Reyhaneh Maktoufi: typhoid...
Onscreen: a Salmonella bacterial infection
Reyhaneh Maktoufi: and cholera...
Onscreen: an infection caused by eating food or drinking water contaminated with the bacterium Vibrio cholerae
Reyhaneh Maktoufi: Why, you ask? "Look at this place, it’s filthy. I mean look at this. It’s a rat. It’s ew. Ew, ew, ew. It’s licking a bandage now. Why? Hey, hey! Bring it back. And there it goes. The rat stole the bandage. Wow, yeah. Ok, this place is legit filthy.” Eventually, the British government sent out supplies and people to help clean up the hospitals. And after that, the death rate super plummeted.
Ok, fast-forward some years and the war is over. Florence is back in England and everyone is like, "Oh my god! It's Florence. Fangirl, fangirl. Woo! You so great. You so famous. We love you Floflo." But Florence is not about the celebrity glam life. You see, Florence was not only a capable nurse, but as I said before, she was also a great statistician. And she didn’t forget the lessons she learned during the Crimean War. So when Florence got back to England she was very adamant to prove her point using stats. Stats, stats, stats, stats.
So with some help, she started collecting numbers from military hospitals near the battleground and from military hospitals across Britain. “So how many people died here? And was that from the battle wounds or was it like... The filth literally killed them? Aha, aha” And based on those numbers, she confirmed her hunch, “Hey y’all, we need to make our hospitals cleaner. Soldiers in the hospitals are dying from all the dirt and poop and sewers infecting them rather than the wounds themselves”
She prepared a whole report to prove her point. But she knew it couldn’t be a regular report, you know, a big boring one filled with numbers that none of the ministers or decision-makers are going to understand. Who's going to read that? So, she took refuge in data visualization.
She gathered up all her data and put them in a fancy-looking chart that turned all the numbers into an easy-to-understand image. Each wedge corresponds to a different month from April 1854 to March 1856. See the blue parts? Those are all the deaths from diseases, not war wounds. The pink sections are war-related deaths from injuries suffered on the battlefield. And the black bits are other causes of death. Florence’s use of data visualization to show the importance of sanitation in hospitals was a big deal, like when I decided to never again get bangs.
With her visualization, it was pretty obvious what was really causing all the deaths: soldiers were 10 times more likely to die from diseases spread through filth than from battle wounds themselves. So Florence proposed that Parliament do something to improve overall public health. You see, hygiene was not just a problem in hospitals but also a problem in the streets and homes of people in England. Poop, poop everywhere. And all that dirt was getting people really sick.
Eventually, Parliament passed the Public Health Act of 1875, which forced landlords to connect their pads to main sewage lines. Life expectancy in England went up so hooray for data and no more poop on the street. This is one of the first moments, that we know of, when data visualization successfully influenced public policy.
Data visualization can help us understand numbers and figures better. And that’s not just limited to pie charts, bar charts, or that chart with lots of dots on it.
Onscreen: Scatter plot
Reyhaneh Maktoufi: Yeah, that one. Data visualizations can get fun and creative, too — like the work of Mona Chalabi, a superstar data journalist.
Mona Chalabi: I grew up in East London, where I was raised by my parents who are both Iraqi immigrants. When I was much younger, I really, really loved math. I found it really kind of exciting and satisfying, but that feeling of satisfaction kind of really quickly started to slip away when I went to college. I had grown up in an area of East London that was incredibly multicultural. All kinds of different people lived around us, all kinds of different cultural backgrounds. And then I kind of like landed in this college campus that was overwhelmingly white.
Reyhaneh Maktoufi: Sounds familiar. I remember how it felt sometimes to be the only brown person in the room. It’s isolating, socially, and you start questioning your own knowledge, your experiences and expertise. And on top of of that, Mona had to deal with a topic just felt very disconnected.
Mona Chalabi: So initially, I had tried to study economics and philosophy. And the further that you go into economics, the more that these formulas were just presented to you as abstract. I have a really clear memory of kind of sitting in this university auditorium and looking at this textbook that had this formula in it. And I found it really difficult to grasp those concepts and also to care about them when they weren't attached to the real world. I just didn't really care anymore.
Reyhaneh Maktoufi: Eventually, Mona dropped out of the undergrad program to go to the land of croissants and camembert — France! — not to study baguetteology, which obviously I would, but to do a Master’s in International Relations. During her degree, Mona started working on a project that involved lots of data collection.
Mona Chalabi: I really enjoyed making the charts. I would kind of obsess for hours over things like the font and the placement and the colors that I'd use. They stay in people's memories better, and they have greater impact.
My role was to take all of the statistical data about what Iraqis needed, specifically Iraqis who had been displaced as a result of the conflict, and then to create figures that could be taken to international donors to say, “Hey, this is what these Iraqis need. Can you supply those goods, those services?”
So I recall one particular conference where there was an Iraqi that was there who was responsible for actually conducting the questionnaires themselves. And he said to us, “You know, you gave us surveys to ask the Iraqis: do you need food or blankets. But what we actually need is electricity generators.” And that just wasn't on the survey. And it was just so transparent how data can create self-fulfilling prophecies, this idea of a feedback loop that you see the world one day and then that reinforces that vision of the world and then recreates the world as it is. It became so clear to me the importance of disseminating information as widely as possible, but also especially to get the information in front of people who you're claiming to represent.
At its base, data journalism is about representation, right? A chart is claiming to represent a constituency of people. And very often those people didn't ask necessarily to be represented in that way. So the very least you can do is ask those people, did we get it right?
Reyhaneh Maktoufi: So obviously the natural path for her after this experience was data journalism: communicating data to more and more people. But yet again, like in college, Mona found herself surrounded by people and ideas that felt just not at all like her.
Mona Chalabi: I first moved to the U.S. to work for a data journalism site. I was really excited to be working with other data journalists, but we didn't have the same approach to journalism. Their goal was to communicate to people who described themselves as geeks and nerds. It was an almost entirely white male organization. I was the only person of color. I was the only immigrant writing on the staff. It was just awful, like I was repeatedly made to feel like an outsider. And so I just quickly became quite depressed, really.
I recall one one situation in particular really vividly. We were sitting in a conference room and we were talking about how to cover the U.K. general election. And I recall one of the editors saying, “You know, who could we have to cover the U.K. election?” And I'm sitting there in this room with 25 people that I've worked with for a year. I'm the only British person in the room. They know that I covered politics in the U.K. before coming to join them. And there was a pause. And then one of the editors was like, "Of course. I know who we could ask." And he mentioned the name of a guy who is American, who was still in college, and up until that point, the only thing he had written for us were a couple of pieces about the joys of Scrabble. And I was just like, “Ok, like, you don't see me at all.” Like, there's no point me saying to you, "I'm qualified to do this."
Reyhaneh Maktoufi: Mona’s job was to make information visible, but she herself felt invisible. Even the data she was working with did not really represent her. It was just so disconnecting. Eventually, though, Mona found a platform and a style that really worked for her. That made her feel seen again.
Mona Chalabi: I started to draw these data visualizations that I would put up on Instagram. Even though it sounds superficial to have the validation of strangers seeing your work and saying, “A) This makes sense to me, and B) This is useful information for me to have” really solidified my identity as a journalist and that I could do this. And so I just leaned into doing more of that. I started to create more and more of these hand-drawn data visualizations and kind of haven't stopped since.
Reyhaneh Maktoufi: Mona has visualized many data sets from topics related to animal extinction to police brutality and even the cost of living or dying. Mona downloads data from different databases and then gets to work. She has a pretty unique style: imperfect lines, whole numbers, none of those percentages estimated to the second decimal point. What does that even mean? Her style is just very human.
Mona Chalabi: When most people look at a computer-generated graphic, it presents the world with these sharp edges and this degree of precision that feels like it's not quite true to our lived experience. I think I'm communicating that uncertainty is inherently a shaky line. And that's the way that we know the world. For example, somewhere between 5% and 10% of women are doing X. It's not down to decimal places. So I really wanted to communicate the uncertainty with which we understand the world around us as a way to build trust.
Reyhaneh Maktoufi: Data visualization is not just arranging numbers on a page or a screen — it’s about telling stories about the data, breathing life into the numbers. And it’s important for people to feel represented and seen in those stories, like what Mona is trying to do. Also, data visualization can serve different purposes: whether it’s to improve conditions in hospitals through policy or bringing attention to social or environmental issues. We just have to be creative, caring, and find a space for all of us in the numbers.
A waiting line consisting of 24 king cobras stretched end-to-end would be only a few feet longer than the statue of liberty is tall.
A large school bus filled with Nicholas Cage clones would weigh as much as two T-rexes.
Hosted and Illustrated by: Reyhaneh Maktoufi
Produced by: Ana Aceves and Reyhaneh Maktoufi
Edited by: Ana Aceves
Camera and Sound: Arlo Pérez
Production Assistance: Amanda Axel, Ralph Bouquet, and Christina Monnen
Nicolas Genin / flikr / CC BY-SA 2.0
Alfie Ianni / flickr / CC BY 2.0
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