Can We Get Ahead of Ebola?

EarthzineHealth

In this map, connectivity by travel time is shown in color with red indicating high connectivity ‰ÛÒ shorter travel time ‰ÛÒ and green indicating low connectivity ‰ÛÒ longer travel time. Black dots represent outbreaks of Ebola since 1976. Image Credit: PLOS Currents.

In this map, connectivity by travel time is shown in color with red indicating high connectivity ‰ÛÒ shorter travel time ‰ÛÒ and green indicating low connectivity ‰ÛÒ longer travel time. Black dots represent outbreaks of Ebola since 1976. Image Credit: PLOS Currents.

 

 

The current outbreak of the Ebola virus is having a calamitous effect in several countries across Western Africa, overwhelming already woefully inadequate health care systems and threatening to destabilize nations. Public health experts are trying to contain the disease by drawing on all the standard protocols. But, given the enormity of the challenge, researchers are also turning to new techniques ‰ÛÒ including analyzing data from mobile phones.

andrew tatem

‰Û÷This outbreak has occurred in one of the most well-connected parts of Africa,‰Ûª says Andrew Tatem. Image Credit: University of Southhampton.

“Anonymized mobile phone call data records provide a fantastically rich data set,‰Û says Andrew Tatem, a researcher in spatial demography and epidemiology at England‰Ûªs University of Southampton and a board member of the Flowminder Foundation. ‰ÛÏThey can reveal population locations by the day. The information we get from phones is really the gold standard for understanding human mobility today.‰Û

To understand the importance of this information, some background on Ebola is necessary. According to Dr. Margaret Chan, head of the World Health Organization, ‰ÛÏWHO has successfully managed many big outbreaks in recent years. But this Ebola event is different. Very different.‰Û

When Ebola first appeared in 1976 it was confined to remote African villages. The current outbreak began in the West African nation of Guinea in March 2014 and quickly spread to Sierra Leone and Liberia, where it has killed more than 3,400 people so far.

 

Transmission electron micrograph of the Ebola virus (Reston virus strain). Image Credit: CDC/ Cynthia Goldsmith.

Transmission electron micrograph of the Ebola virus (Reston virus strain). Image Credit: CDC/ Cynthia Goldsmith.

A September article in the journal eLife, co-authored by Tatem, pointed to key demographic differences between 1976 and 2014: the phenomenal growth in urban populations in this part of the African continent and advances in transportation. Epidemiologists, who look for patterns in how diseases spread, have known for decades that, along with the many benefits of increased human mobility, there is a downside. Pathogens, like their human hosts, can spread farther and faster. From the moment a person is infected with the Ebola virus, there is a delay of between two to 21 days before they become symptomatic and can transmit the disease. Ebola victims are quickly incapacitated once symptoms begin, so they‰Ûªre unlikely to travel after the incubation period. Before highways and motor vehicles, Ebola outbreaks were localized. Today, most of the world‰Ûªs population can board a bus and, in a few hours, step off in a distant city. In a day or two, nearly anyone can easily reach a different country. Add in air travel, and by the end of the three week incubation period, that same person can be anywhere on the planet.

With mobile phone ownership now widespread in the affected countries, the anonymized call record data sets can reveal patterns of human movement and help researchers pinpoint areas that are especially vulnerable in the current Ebola outbreak.

‰ÛÏThis outbreak has occurred in one of the most well-connected parts of Africa,‰Û explains Tatem, who is director of the mapping site WorldPop. That makes cell phone data a uniquely useful tool in deciding where limited health resources will do the most good. Although the methodology is still in its early stages, the information has the potential to help experts get ahead of the outbreak.

There are obstacles that must be overcome to reach that potential, however, says Tatem.

The huge size of the data sets involved is itself both an opportunity and a challenge. Tatem cites his previous work analyzing a year of anonymized mobile phone data in Namibia, a country with a population of just over 2 million people which contained 9 billion data entries.

‰ÛÏIt is exciting to have so much data to work with,‰Û he says, ‰ÛÏbut it takes a lot of work to make it useful.‰Û

Integrating data sets from anonymized mobile phone usage and demographic indicators, researchers are building maps like this one that model mobility within countries of West Africa. Image Credit: PLOS Currents.

Integrating data sets from anonymized mobile phone usage and demographic indicators, researchers are building maps like this one that model mobility within countries of West Africa. Image Credit: PLOS Currents.

That work is beginning to pay off. Tatem is part of a team that used anonymized mobile phone data from Senegal and Cote d‰ÛªIvoire to understand previously unknown mobility patterns in the countries involved in the current Ebola outbreak. Their findings appeared in the Sept. 29 issue of PLOS Currents.

For more on Ebola and mapping:

WorldPop

HealthMap

University of Oxford

Centers for Disease Control and Prevention