This lack of speed makes it relatively easy to predict hunger. And, accordingly, the Ethiopian emergency was well forecast. As a climate reporter, I’ve heard fretting about the situation in the Horn of Africa since at least October. That was when I began to wonder: How do you know when a famine is coming?

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For almost a year, U.S. officials have warned that food could become scarce in regions of the Horn of Africa. These warnings came in the form of the Famine Early Warning Systems Network, a USAID program usually shortened to FEWSNET. With rationalist clarity, FEWSNET classifies the food security situation in 36 of the world’s countries:

FEWSNET

FEWSNET categorizes each country, and some provinces and regions, according to a five-scale food-security scale. Most areas have “none to minimal” food-security problems. The scale elevates after that: Some areas will experience a “stressed” food-security situation, which becomes a food-security “crisis,” then a food-security “emergency” and, eventually, a “famine.” (I’m putting quotes around certain terms only because they are technical terms within the scale.)

FEWSNET also regularly puts out forecasts for regions, detailing why it’s forecasting certain food situations for certain regions and why. While FEWSNET has been going on for more than 30 years, it can seem hyper-rational to the point of being algorithmic. Put a lot of numbers about a faraway place into a super computer, pop down to the corner Starbucks, and come back in time to watch it spit out a prediction.

The reality is both much more involved and much less mathematical.

“It is not a computer program, it is not a quantitative modeling process,” says Chris Hillbruner, a senior advisor at FEWSNET. “There really isn’t a mathematical formula that lets you calculate where food security is going. There’s not even a mathematical formula to calculate what current food security is.”

Nor, says Hillbrunner, is there any easy way to check on hunger levels in a region. “There is no gold standard food-security indicator,” he told me.

So even though FEWSNET looks algorithmic, it’s not. To arrive at their classifications, the program’s experts meet in one place and consult a lot of information. This information encompasses data from local markets, weather and climactic reports; and data on local livelihoods, nutritional reports, and what kind of humanitarian assistance is already being provided. It includes information as specific as intra-provincial requests for local water-truck usage and documentation of recent crop diseases.

Most of this data isn’t scraped from the Internet. Employees in the field collect the bulk of FEWSNET’s data in person. More than 300 FEWSNET employees work full-time in the 36 presence countries that it follows, collecting information on the ground and advising its central office.