by Jason S. Brinkley, PhD, MA, MS

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On the Brink addresses topics related to data, analytics, and visualizations on personal health and public health research. This column explores current practices in the health arena and how both the data and mathematical sciences have an impact. (The opinions and views represented here are the author’s own and do not reflect any group for which the author has an association.)

The old saying “a picture is worth a thousand words” is nowhere more true than in the data sciences where visualizations often reveal patterns that the best analytic techniques may not effectively bring to the forefront. This is especially true in the area of mapping, where humans can combine insights from topography, climate, psychology, and common sense to understand complex patterns from an effectively generated map almost intuitively, without the need of statistical modeling. Maps are the staple in political science and meteorology but also epidemiology and public health; but what happens when our traditional systems for creating maps fail large swaths of people? This was the starting point for a British group that has developed an alternative mapping strategy, which is radically different.

The website www.what3words.com divides the world into a set of 3-meter by 3-meter squares and then uses a set of three distinct words to name each of the over 57 trillion squares. So while many people know the White House as 1600 Pennsylvania Ave NW, Washington, DC 20500, what3words refers to part of it as engine.doors.cubs. One can get even more specific and use rich.soup.noble as one square inside the oval office. This alternative methodology for assigning locations has been well covered by the press, including The New York Times and Wired magazine. The creators describe traditional longitude and latitude as “great for computers but what3words is useful when people are involved: either people-to-people, people-to-device or device-to-people.” Longitude and latitude show some limitations when truncating decimal places. For example, both the White House and Joe’s Seafood, Prime Steak, and Snow Crab Restaurant are located at 38.89 degrees north and 77.03 degrees west.

What3words is already realizing possibilities for commerce but has a lot of implications for health, from monitoring illness in refugee camps or managing health access in the wake of disasters. The system isn’t without flaws–most notable is that the word-based methodology doesn’t distinguish adjacent grid cells. That is to say that neighboring squares can have very different sets of three words. Words could be misrepresented or transposed (eg, riches.soup.nobles takes you to a location in Iowa). But traditional methods have this same potential issue. From a data perspective, what3words represents an idea often overlooked in analytics: the best method for data collection may not be the best method for data analysis. What3words and postal addresses represent alternative methods for organizing geographic data, but both require computer algorithms to translate information into coordinates in order to perform analysis. This presents an important lesson for researchers of all types, that data can be collected in a lot of different forms and still be made useful for analysis. The out-of-the-box thinking represented by what3words should inspire all of us to explore ways to ease data collection without compromising data analytics, or at the very least, remind us that these two areas can be separated.

That’s all for today. I encourage everyone to spend some time on the website where you will find interesting choices for locales. Maybe you are near blog.apple.town in West Hollywood, CA, or nerds.spray.custard in southern Iraq. Given the previous discussion of the usual chaos at the Brinkley house, I expected to find our what3words to be mischief.mayhem.soap but then found that the location is actually in Libya. And as far as I’m concerned, they can have it.

For further reading, consider these related articles from the Journal of Public Health Management & Practice*:

• Using Environmental Public Health Tracking to Identify Community Targets for Public Health Actions in Childhood Lead Poisoning in Wisconsin
• Measurement, Geospatial, and Mechanistic Models of Public Health Hazard Vulnerability and Jurisdictional
• Risk Putting Diabetes on the Map: What Does Population Health Really Look Like at the Local Level?

*Articles may require a subscription to JPHMP or purchase.

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Jason S. Brinkley, PhD, MS, MA is a Senior Researcher and Biostatistician at Abt Associates Inc. where he works on a wide variety of data for health services, policy, and disparities research. He maintains a research affiliation with the North Carolina Agromedicine Institute and serves on the executive committee for the NC Chapter of the American Statistical Association and the Southeast SAS Users Group. Follow him on Twitter. [Full Bio]

Previous posts by this author:

• Are We Asking Too Much From Surveys?
• Making Better Comparisons
• What Kills Us?