There’s a common misconception that, whether we’re ordinary citizens or professional disaster-responders, we’re all helplessly at the mercy of unexpected, random disasters, both natural and man-made.
The truth is, it’s rare for disasters to be totally random — and they’re almost never totally unexpected!
Organizations like World Vision and professionals who engage in disaster response are increasingly investing time and energy into what we call “early warning/early action.” The more we can predict when and where a disaster will strike, the more we can prepare for it. And the more we prepare for it, the less traumatic and devastating it will be when it actually happens.
There are a number of different tools we have available to assist in the prediction of disasters. Let’s talk about two main types here.
The technological advances of the past decade have been amazing. We now commonly have access to imaging and communications tools that were literally the stuff of science fiction and spy thrillers when I was starting out in the aid world.
With just a smartphone, we can view public satellite imagery to see storms coming; track locations on the other side of the world (accurate to within inches) using GPS; or communicate via voice, text, or images instantly, with amazing quantities of data embedded.
All of these assets make it potentially easier for us to see disasters coming and to share current information once they happen. For natural disasters in particular, there are two that we often look at:
- The Pacific Tsunami Warning Center (PTWC) tracks seismic activity across the Pacific Ocean in real time and generates a news feed that we can follow to predict the timing and location of potential tsunamis. When undersea earthquakes trigger tsunamis, we typically only have hours before the tsunami hits land. Tools like the PTWC help us pinpoint the areas most likely to be affected so that World Vision staff members on the ground can help evacuate people in those places.
- The Famine Early Warning Systems Network (FEWS-NET) is a concept similar to the PTWC. Basically, it gathers data over time to predict the onset of droughts, food crises, and potential famines. Because of the nature of the data being compiled and analyzed, the information on FEWS-NET can require a bit more background knowledge to understand and use, compared with the tsunami warnings on PTWC. Nonetheless, FEWS-NET is incredibly valuable for humanitarians whose job is to make strategic decisions about where to put food- and famine-related resources to minimize (or avoid altogether) escalating crises that we can often see approaching months in advance.
Local behavior, local knowledge
One of the most significant personal benefits of my line of work is the incredible cultural diversity that I encounter during a typical day on the job — whether in my office near Seattle, or out in the field. And what I’ve found is that local cultural knowledge often has inherent predictive value for disasters.
For example, when I was once leading a discussion on early warning with some local colleagues in Afghanistan, they told me that whenever they suddenly saw a lot of snakes slithering around on the ground, they’d know to prepare for an earthquake. Or in Sri Lanka, a few hours before the tsunamis of December 2004, there were reports of wild elephants fleeing to higher ground.
Too few people understood what that meant — somehow, the elephants could sense danger that people could not — but I think it’s safe to say that if all the elephants suddenly run inland again, there will be some people following them.
These stories of early warnings are interesting, and where we hear about them, of course, we also pay attention. But there a number of characteristics that we can look for in the behavior of a community or a population, too, to get an emergent picture of what kind of stress exists there.
For instance, when we see a spike in the rate at which families in a particular region begin to sell off “productive assets” — items like livestock, or perhaps land — we know that something is going on and that we should look deeper.
The same applies to family members moving from rural to urban areas in search of wage labor. It’s quite common to see one family member migrate to the city to work (often an older sibling) in order to make ends meet. But when two or three do so, we know that that family is under real economic stress.
Similarly, at the community level, it’s not necessarily a good thing to see a few families leaving their rural homesteads and moving to the city — but it’s also not terribly uncommon. On the other hand, if we see, say, a 5-percent increase of this within a three- to four-month period, we know that something more serious is going on within the population.
Utilizing technology, listening to people who know their environments best, and paying attention to changes in a given area over time are some of the best assets we have in predicting when and where disasters will strike. They may often be devastating — but the more we prepare, the more we can mitigate the effects of these events.
Predicting and preparing for humanitarian emergencies is the first step in saving lives. But this needs to be followed by a prompt, effective response to the disaster once it occurs.
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