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Big Data for development: preventing the spread of epidemics

​"The use of Information and Communication Technologies (ICTs) plays an important role to break the chain of health-related emergencies such as Ebola virus transmission" (Resolution 202, PP-2014).

Big data derived from the use of ICTs holds great promises to help address global development challenges. Digital footprints left through the use of online services, phones and other digital transactions, can be gathered, analyzed and used to develop better policies, and provide more individualized services and critical information. Because of the near ubiquity of the mobile-cellular network and since a growing number of people are using mobile phones, data from mobile phone operators are particularly valuable, including in the case of emergencies.

As part of ITU's efforts to support its Members States in the area of emergency telecommunications, a big data project was launched in 2015. The project showcased the potential of big data to facilitate the timely exchange of information to combat the Ebola epidemic - which had gripped West Africa in 2014 - and future health crises. The project used Call Detail Record (CRD) data, which includes information on the use of the mobile phone, including the location, from mobile network operators in Liberia, Guinea and Sierra Leone. The project demonstrated how analyzed CDR data can provide information on human mobility, including cross-border movement, and the spatiotemporal distribution of people, while safeguarding individual privacy. In the case of the outbreak of a disease this information is critical for governments as well as for humanitarian aid agencies, for effective intervention, and to tackle the disease. It can further be used to build models of population flow patterns over time, and at specific events, and to combine these data with other information. 

Three separate country case studies for Guinea, Liberia, and Sierra Leone were published as a result of the project. The case studies include detailed information on the CDR datasets, analysis and results, as well as the anonymization process and limitations and challenges.

Country Case Studies