Médecins Sans Frontières and other international aid organizations are furiously working to contain an outbreak of Ebola in Guinea and nearby African countries. Latest reports estimate that the virus has infected 157 people and killed 101 in Guinea alone.
A New Scientist story published today explains how health workers from Médecins Sans Frontières were initially at a disadvantage when they arrived in Guinea to combat the deadly virus because they only had topographic charts to use in pinpointing the source of the disease. Desperately in need of maps that would be useful in understanding population distribution, the organization turned to Humanitarian OpenStreetMap Team, which coordinated a crowdsourcing effort to produce the first digital map of Guéckédou, a city of around 250,000 people in southern Guinea. Hal Hodson writes:
As of 31 March, online maps of Guéckédou were virtually non-existent, says Sylvie de Laborderie of cartONG, a mapping NGO that is working with MSF to coordinate the effort with HOT. "The map showed two roads maybe - nothing, nothing."
Within 12 hours of contacting the online group, Guéckédou's digital maps had exploded into life. Nearly 200 volunteers from around the world added 100,000 buildings based on satellite imagery of the area, including other nearby population centres. "It was amazing, incredible. I have no words to describe it. In less than 20 hours they mapped three cities," says de Laborderie.
Mathieu Soupart, who leads technical support for MSF operations, says his organisation started using the maps right away to pinpoint where infected people were coming from and work out how the virus, which had killed 95 people in Guinea when New Scientist went to press, is spreading. "Having very detailed maps with most of the buildings is very important, especially when working door to door, house by house," he says. The maps also let MSF chase down rumours of infection in surrounding hamlets, allowing them to find their way through unfamiliar terrain.
Previously: Using crowdsourcing to diagnose malaria and On crowdsourced relief efforts in Haiti