Disease Mapping: New Technology Meets an Ancient Discipline

The disease map made by John Snow after a London cholera outbreak in 1854 changed the way cities studied public health. Wiki Commons

The ability to track — and thus limit — the spread of disease paved the way for modern urban growth.

November 10, 2017


This piece is part of the Sidewalk Talk series “15 Innovations That Shaped the City.”

The evolution of major cities around the world has been checkered by tragic outbreaks of disease. Population density, which encourages free flow of goods and ideas, also eases the spread of parasites. Faced with outbreaks of plague and cholera, scientists eventually discovered a data-driven way to pinpoint the source of the problem: spatial epidemiology, and in particular, disease mapping. While many other innovations help keep city residents safe—sewers, fire safety, and vaccines all have more immediately observable effects—the disease map stands out for its ability to change the way we think about population health.

“What [disease maps] ended up doing was making the idea of large-scale metropolitan living a sustainable one,” says Steven Johnson in a TED talk about his book, The Ghost Map: The Story of London’s Most Terrifying Epidemic—and How It Changed Science, Cities, and the Modern World.

The origins

When the bubonic plague reached Europe in the mid-14th century, it found perfect conditions to spread: countries assaulted by war and famine, filled with cities that had organized few sanitation initiatives. Up to a third of the population died within three years.

Unaware of the transmission vector—fleas—people came up with other explanations. Many believed Armageddon had come. Others, more correctly, feared transmission between people. “Father abandoned child, wife husband, one brother another; for this illness seemed to strike through the breath and sight,” wrote Agnolo di Tura, a merchant in Siena.

The earliest disease maps searched for causes in line with traditional medical beliefs, such as bad air or disagreeable temperaments. One of the first such maps, made in 1796 by Valentine Seaman to track yellow fever in New York City, correctly followed the disease to fetid sites in the city, but blamed foul miasmas rather than the true cause, mosquitoes.

The breakthrough

The key moment for disease mapping came during the London cholera outbreak of 1854. At the time London was the largest city ever built, home to some 2.5 million people. But it was also a city filled with cesspools and the overwhelming stench of sewage. As polluted waters led to cholera outbreaks, people blamed the deaths on the smell.

Enter John Snow, a local doctor who is often credited as the “father of epidemiology.” Believing cholera to be waterborne, not airborne, Snow traced an August 1854 outbreak back to a local watering hole in the working-class neighborhood of Soho. After interviewing people in the area, he created a map showing deaths in the neighborhood linked to address: sure enough, the farther he got from the pump, the less concentrated the deaths became.

Convinced in part by the map, local authorities told people to start boiling their water when the next outbreak seemed imminent, dramatically limiting the impact. “That was the last time London has seen a cholera outbreak since,” according to Johnson. The 1854 outbreak “in many ways helped create the world we live in today, and particularly the kind of city we live in today.”


Satirical cartoon by William Heath, showing a woman observing monsters in a drop of London water (at the time of the Commission on the London Water Supply report, 1828). Courtesy Wikimedia Commons.

The impact

Combined with the printing press, a growing adoption of statistics, and the rise of germ theory, disease mapping became an essential safeguard for a growing majority of people. While only 3 percent of the human population lived in cities in 1800, that number had grown to 14 percent by 1900, and 50 percent in 2008. Of course disease mapping is not the only reason for this rise, but such urban growth would not have been possible without improvements in the understanding and treatment of diseases like cholera, syphilis, and smallpox.

Despite a century’s worth of medical advances, epidemiologists still fear the return of a global pandemic like the Spanish flu of 1918, racing to map the origins and characteristics of new diseases that emerge. During the 2003 outbreak of Severe Avian Respiratory Syndrome in Asia, for instance, disease mapping helped determine that the disease was not highly infectious in most people, but that a small number of “super spreaders” were capable of infecting dozens of others. As a result, hospitals were able to identify potential spreaders to isolate while sick.

Today, most disease mapping falls under the more heading of medical geographic information systems, and can apply to more than just infectious disease. GIS has been used to study concepts such as whether living near nuclear facilities caused outbreaks of leukemia, or how heart disease and strokes are connected to where you live. The public is also increasingly involved in disease mapping. Google Flu Trends, for instance, sought to predict the spread of flu based on search patterns.

The future

Growing urban populations, increased air travel, and climate change all increase the risk of a new disease emerging and rapidly spreading, especially in highly networked major cities. The good news for disease mappers is that the amount of available data has also vastly increased, with global databases now capable of overlying things like disease incidence, bat or insect reservoirs, and other crucial information that was difficult to compile just a couple decades ago.

The Institute for Health Metrics and Evaluation, a group at the University of Washington, aims to “quantify and map every disease state,” says David Pigott, a spatial epidemiologist at the institute. Doing so requires data from satellites, government, and thousands of on-the-ground researchers around the world, leveraging new digital tools. “Mobile phones have completely revolutionized how people go out and do routine surveillance,” says Pigott. “The idea of going around with a massive logbook and noting things down has completely transformed.”

The flood of data will ultimately help shift cities from response to prediction, whether for diseases or other public health issues like traffic collisions. Chicago, for example, has adopted an algorithmic approach to food safety, sending inspectors to food preparation locations predicted to produce foodborne illness and thus finding violations, on average, a week earlier. Already vastly safer than in previous generations, cities can use the great new influx of urban information to become even healthier.

November 10, 2017