In just a few weeks, the “flatten the curve” image of two overlapping graphs, one taller than the other, has become an iconic image representing the global COVID-19 pandemic. Since mid-march, different versions of the image have been widely shared to explain and encourage the concept of managing disease outbreak by slowing the initial spread so that fewer people are sick at once.
The image first gained traction online when Drew Harris tweeted his original version of it on February 28. Since then, many versions of it have been shared on social media and featured in news broadcasts and articles.
But even though many people saw this curve for the first time, it’s not a new idea. The curve shows the usual progress of an infectious disease outbreak. First a few people get sick, then the numbers rapidly increase, until the level of new cases reaches a plateau and the curve starts going down.
We know that this is how infectious diseases progress in communities because researchers and medical experts have many decades worth of data from different diseases that all plot to similar graphs.
Some of these graphs are archived online, such as this detailed graph tracking cholera deaths in England in 1849, available through the image library of the Wellcome Collection
By tracking known disease cases or deaths, doctors and public health experts can see how – and how fast – a disease is spreading through the community. Once it starts going down they’ll be able to make estimates about the duration of the outbreak.
Besides the graph above, there is a more famous image related to the 19th century London cholera epidemic, and it’s a map rather than a curve.
In 1854 physician John Snow tried to find the source of a localised cholera outbreak in London’s Soho neighbourhood. Rather than plotting the cases over time he mapped each individual cholera patient to their home, and quickly saw a pattern.
Most of the cases were located in a few streets, with the epicenter being on Broad Street, close to a communal water pump. By visualising the data in this way, Snow was able to interpret the information and come to an important conclusion: the water from the pump was contaminated!
This happened during a period when London was still seeing regular cholera cases. It wasn’t an isolated incident, but clever visualization made it possible to see through the data and find one source of contamination.
Many of the London cholera patients were treated at Middlesex Hospital, under care of Florence Nightingale. Just a few months after that, in October 1854, Nightingale and her trainee nurses would be sent to the Ottoman Empire to look after British soldiers in the Crimean War.
Here, Nightingale noticed that the main cause of death among the soldiers was not related to the war itself, but to infectious diseases that spread through the camps. To alert the British government to these conditions, she created a set of graphs that showed the cause of reported deaths in different colors, radiating out from a central point.
Nightingale’s image isn’t perfect – radial charts such as this one distort some of the data, but in this case the difference was so large and obvious that it still made for a convincing case. Just a quick glimpse at it and it’s obvious that too many soldiers were dying of infectious diseases.
That quick and immediate understanding is also the power behind the flatten the curve graph. However, unlike Nightingale’s chart, Snow’s map and the 1849 graph of London’s cholera cases, the flatten the curve image was not based on existing data — at least, not yet.
Over the last few weeks, countries have tracked new cases and COVID-19-related deaths within their borders, and the curves are starting to emerge. The curve for new cases can be a bit misleading, because it’s based on diagnoses (and may miss people who were ill but never tested). Deaths are less ambiguous, and follow the same pattern.
It’s too early to say how the COVID-19 outbreak curves will look after all the data are in. Even China still has active cases and every country has to take into account the possibility of a second wave. This story is far from over, but the graphic of two disease curves – one tall and one flat – will likely be linked to the COVID-19 pandemic for years to come.