The Ebola virus epidemic in West Africa has been grabbing international headlines for weeks, and now, as authorities fight to contain the disease’s spread, some experts are recommending the use of a new tool: data analytics. In the countries where the epidemic began, the World Health Organization (WHO) has acknowledged the difficulty in obtaining reliable numbers, and organizations including the Centers for Disease Control and Prevention (CDC) have begun using mobile data to gain insights into the spread of the virus.

Mobile phones are ubiquitous in many African countries where landline infrastructure is sorely lacking. French telecommunications company Orange S.A. recently handed over anonymized data from 150,000 users in Senegal, helping to create a map of population movement and communications. The hope is that this information will allow authorities to better plan the location of treatment centers and, if necessary, restrict travel between certain regions.

Mobile devices can give exact data on people’s locations and identify calls to hospitals or specialized hotlines to detect specific cities or regions where outbreaks occur. Similar tactics have been used since 2010 during the Haiti cholera outbreak.

“Big data analytics is about bringing together many different data sources and mining them to find patterns,” said Accenture Health managing director Frances Dare to the BBC. “We have health clinic and physician reports, media reports, comment on social media, information from public health workers on the ground, transactional data from retailers and pharmacies, travel ticket purchases, helpline data, as well as geo-spatial tracking.”

A comprehensive ETL architecture can gather data from all of these disparate sources and organize it into a unified format that authorities and health organizations can use to track a disease’s spread and optimize containment and preventative measures.