By Dr Jemilah Mahmood, IFRC Under Secretary General

Here’s something that might never have occurred to you.

In the aftermath of a major emergency like an earthquake or storm, it can be really hard to find people. I’m not just talking about people trapped under rubble, I’m talking about large numbers of survivors.

This might sound strange, but when you think about it, it makes sense. In the chaos that follows a disaster, people often move quickly in search of safety. They might leave the disaster area entirely and head back to a nearby city or town, or into rural areas.

This can have major ramifications on relief and recovery efforts. Where should we be sending our volunteers and emergency teams? Where should our relief supply chains be focused? What do people need? All these questions are harder to answer without knowing where people have gone.

But gathering information from these approaches can take days, weeks. And in that time decisions need to be made.

A new tool in our data toolkit

Last week, American Red Cross, the International Federation of Red Cross and Red Crescent Societies (IFRC), the World Food Programme and UNICEF announced a partnership with Facebook that could in some situations, bridge this data gap and allow us to see these dynamics in real time.

Facebook is going to make anonymized, aggregated and real-time data available for our organizations, making it possible for humanitarians to request access to three types of data:

  1. Population density: where concentrations of people are located before, during, and after a disaster.
  2. Population movement: where concentrations of people are moving, revealing patterns of movement over several hours.
  3. Safety check: where people have checked in safe, using de-identified aggregated data.

These data from Facebook has the possibility to help us focus on getting aid to exactly where people are or where they are moving to.

Taken alongside other sources of data – including Red Cross and Red Crescent volunteers on the ground, satellite imagery, population density maps, OpenStreetMap, and the like– these data will help us build better maps and better target our community interventions.

Mapping Malawi

The American Red Cross is already showing how it is done. In Malawi, the American Red Cross, the Malawi Red Cross and partners set a goal of vaccinating 7.5 million children in the space of a few weeks the month of June 2017. Mobilizing this many families to stand in line for a vaccination shot requires knowing where to send volunteers door-to-door to explain the disease and convince families to participate. For this, one needs a very good map.

But when one looks at the map of Malawi, many rural areas are blank spots. American Red Cross data experts have been able to use Facebook data to identify settlements in rural areas, and then mobilized volunteers to put these places onto OpenStreetMap through a campaign known as Missing Maps.

This work meant volunteers to focus their effort on a more precisely defined area. It opened our eyes, it helped our volunteers work smarter, and it (indirectly) saved lives.

Patterns, not people

Equally as exciting is the fact that none of this work required knowing anything about individual Facebook subscribers; just where concentrations of them lived. The data we have access to is aggregated in such a way that we cannot see individuals or families. It shows us density and movement in a way that seems useful, but that protects the privacy of people we are trying to help. Patterns, not people.

Of course there are limitations. If a disaster knocks out networks, then this kind of information might not be available (although, knowing where power and internet are down could be useful in and of itself). In other contexts, where internet access is limited or where Facebook isn’t in wide use, then it might offer a very limited picture. But at the very least, it will help us know more than we knew before. And that will, in some way, help us get people and supplies to where they are needed.

We’re excited about this initiative. It’s by no means a panacea. It’s not going to solve all the challenges we face. But it gives us more information than we had before. And taken alongside other data sources, including more traditional ones, it helps us become smarter. That means we will be better able to help people in need.

That’s the point, after all.