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

the go-to for data storage when COVID-19 impeded the acquisition of additional server capacity. In terms of analytics, although there was a tool for producing standardized mobility statistics available on the GitHub repository, we chose to write our own script. This was to accommodate the system parameters on PURA’s premises. Since much of the analytical work was done through remote access, it was restricted by network capacity and could be interrupted by electrical outages. This required breaking computationally intensive tasks into multiple steps with intermediate results, so that any interruption would only disrupt the current computation and not the whole script.

# **7. Conclusion**

In this paper, we demonstrate the uses of four indicators for examining how interventions and events under COVID-19 are reflected in the patterns of phone usage, population distributions, levels of mobility, and population flows. Results show that CDR aggregates are relevant for capturing changes in these indicators, which continued to vary over a few months. It indicates that CDR data provide timely and granular population statistics that can complement conventional statistics.

The use of CDR data in the context of COVID-19 in The Gambia demonstrates the hidden potential of big data, including CDR data, to inform decision making. Due to lack of investments in statistical systems, severe data deprivations are likely to remain a challenge for governments, the private sector, and civil society, and this approach offers an opportunity to leapfrog, and exploit data which is available in real-time, highly localized, and at relatively low cost. However, the use of CDR data will require future investments into the institutional and organizational framework of national statistical systems, including improvements of IT infrastructure and technical and statistical capacity. The analysis also demonstrates that CDR data are unlikely to substitute traditional data, such as administrative and survey data, as linkages between telecommunication data and individual level and household characteristics need to satisfy strict technical and ethical requirements.

This application focuses on a well-defined use case, and further work is necessary to scale up the existing structure and ensure interoperability. This paper demonstrates that the analysis of CDR data can support decision making during a crisis situation. This scaling up will require a commitment to include the analysis of CDR data into the standard set of planning instruments, including for the allocation of human capacity and financing.

Future work in The Gambia will build on the existing partnership and experience. While valuable, CDR data on its own can only offer limited insights. We propose to build on this analysis by overlaying it with additional data sets. This includes validation of observed patterns against mobility data from Facebook. We also propose to overlay the mobility trends against price data to infer whether shifts in population drove food prices up in rural areas relative to urban areas. Finally, we would draw on recently available survey data, including the 2019 migration survey, to unpack the correlation between ward level mobility metrics and underlying patterns of internal migration. Notably, did the areas that depend most on internal migrants see a large number of returns? This would allow us to infer how the COVID19 induced lockdown differentially impacted vulnerable populations in rural and per-urban areas.

From a policy perspective, the future analysis of CDR data could inform urban planning, particularly investments into infrastructures such as roads, schools, and hospitals. In addition, the private sector has also shown interest in using this information to better understand commuting and clustering patterns in order to exploit untapped market potential.

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