Arai et al. (2020) : The Hidden Potential of Call Detail Records in The Gambia.

A workshop in February 2020 was instrumental to initiate a partnership on “Big Data for Development” that evolved around ownership and sustainability. A joint vision and a clearly specified use case to focus the analysis on internal migration helped to coordinate expectations, and build capacity using a practical example. Moreover, a broader audience during the initial workshop - involving stakeholders from the private sector, ministries and agencies, academia, civil society, and development partners - confirmed the demand and interest for access and analysis of CDR data. During this discussion, it was instrumental to convince the MNO to join this initiative as they are collecting and providing the CDR data. Their agreement was based on the idea that training would also enhance their inhouse capacity to analyze CDR data to improve their business operations and enhance customer relations. The workshop also offered a forum to discuss any institutional, organizational, or technical challenges, and showcase how other countries have dealt with these concerns.

Once COVID-19 hit The Gambia in March 2020, all parties agreed to revisit the focus of the collaboration and explore the use of CDR data to respond to the health and economic crisis. In light of limited testing and health facilities, the government announced a national health emergency with profound restrictions on human mobility (Hale et al, 2020). As part of this dialog it became clear that prolonged social distancing would bear a high cost for households and firms (Gottlieb, Grobovsek, Poschke, & Saltiel, 2020), and there was interest to create an evidence base for smart containment measures. Based on successful applications in other countries, the analysis then focused on the use of CDR data to understand patterns of human mobility during COVID-19.

# **B. Strengthening technical capacity**

In addition to building a consensus about the analysis of CDR data, the partners agreed to strengthen technical capacity and ensure knowledge transfer. Crucially, rather than building a system from scratch, efforts were directed at strengthening existing data collection protocols between the MNO and the PURA to include the necessary indicators. As part of its mandate to monitor the quality of calls, PURA already had put in place a centralized repository of data, plugged into the respective MNOs systems, and updated in real-time. After securing the necessary approvals, the team worked with the system administrator to include additional indicators as part of this routine monitoring for use in the analysis. This minimized the reporting burden on MNOs, facilitating compliance. To ensure an additional level of security, the data collected for this project was firewalled and stored on a separate server on the premises, with remote access strictly limited to key researchers and system administrators. Capacity building in the preparation and analysis of CDR data also built trust and offered an opportunity to discuss lessons learned from other countries. It helped to establish a platform to continue the work during the following month when all interactions between the counterparts in The Gambia and the team of researchers shifted online.

Throughout the partnership, PURA played a crucial role in working closely with the MNOs to obtain access to the CDR data. The regulator for telecommunication services used its convening power to discuss with MNOs data sharing while upholding national and international standards for data privacy. Two out of four MNOs agreed to provide access to their CDR data. After training in one-way encryption using a 160-bit hash function, they provided anonymized data to the regulator. In accordance with national regulatory requirements, the regulator set up a secure File Transfer Protocol (FTP), and all data was stored on-premise on a dedicated server. Aggregation of the data was conducted through highly restricted remote access into the server, which constrained computational capacity but kept the data secure and confidential. The team working remotely only had access to aggregate indicators for analysis which precluded any possibility of de-anonymizing the data.

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