Kenya is one country in the developing world making . Nearly 15 million people in the country (of 41.6 million) are subscribed to mobile phone services. With the ability to track data from all those cell phone users, researchers used that information to better understand malaria in the region.
In the study, published in the latest issue of the journal Science, researchers from Harvard School of Public Health mapped every call and text made between June 2008 and June 2009 by all 14,816,521 Kenya cell phone subscribers to one of 11,920 cell towers throughout 692 settlements. Each time someone left their primary settlement, the destination and duration of the visit was calculated. Then, using a 2009 malaria prevalence map that estimates where malaria was most prominent in the different settlements researchers calculated the likelihood that residents and visitors would get infected by malaria.
The researchers combined these two giant data measures to see how travel patterns impact the spread of the disease. In Nairobi, for example, researchers found that there were a surprising number of "imported infections" from people who travel to a place where they are more likely to get infected.
What practical measures can this data be used for? The researchers offer two: a map can be made showing the places that mostly emit the disease and the places that mostly receive the disease. Another could be sending text messages to people traveling to high-risk areas and encouraging the use of a mosquito net.
"This is the first time that such a massive amount of cell phone data—from millions of individuals over the course of a year—has been used, together with detailed infectious disease data, to measure human mobility and understand how a disease is spreading," said senior author Caroline Buckee, HSPH assistant professor of epidemiology.
Nearly half the world is at risk of malaria. In sub-saharan Africa, about 1 million people -- mostly young children -- die from the disease each year.
Get the full study here.
Photo: Flickr/Internews Network
This post was originally published on Smartplanet.com