Table 1 presents the summary of country cases where institutional frameworks and analytical pipelines provided timely analysis for informing decision as well as reduced response burden in disasters. In Nepal, the first report on population inflows to each region was released 13 days after the earthquake—this was made possible by the existing collaboration framework, which aimed to support preparedness and response to humanitarian disasters through analysis of CDR data (Wilson et al. 2016). In Vanuatu, at the time of volcanic eruptions in 2018, there was already an institutional framework in place for analyzing the effects of previous disasters. It enabled timely insights into population displacement for the government as well as humanitarian agencies (UN Global Pulse 2014). In The Gambia, the existing framework explored the use of CDR data to create an evidence base for policy and project design in the context of economic and social development. The spread of COVID-19 has prompted interest in internal mobility, altering the development objective of this partnership (Arai et al. 2021). Sierra Leone, Guinea, and Liberia collaborated to develop a data pipeline, which facilitated timely information exchange on cross-border movements among the neighboring countries (ITU, n.d.). In Turkey, a real-time analytics platform was developed to provide analytical insights to the government disaster response team which helped zero in on the number of people affected by disasters nationwide (GSMA, 2019). In Mozambique, a semi-automated software tool was installed on the premise of the ICT regulator to detect disaster-driven displacements and returns, providing results in a practical and timely manner; in this case, past mobile data was analyzed to assess the sensitivity and accuracy of the displacement monitoring system for future use. This toolkit was also installed in Ghana to support the COVID-19 response effort.
These examples demonstrate that efforts on establishing an institutional framework and system building between the data producer and use could contribute to strengthening preparedness to respond to a timely data demand under disasters. Appendix 1 highlights the experiences of several countries in establishing institutional frameworks and data pipeline. Each country case provides insights on their approaches as well as the key steps that can be considered for developing institutional frameworks and data pipelines, and areas for improvements.
Table 1. Benefits of institutional frameworks and data pipelines: selected country cases
Guinea, Liberia Sierra Leone
Regulators, MNOs, ITU, University of Tokyo
MNO, UN Global Pulse
NSO, regulator, MNOs, World Bank, University of Tokyo
MNO, NSO, Flowminder
Regulator, disaster management agency, Flowminder
MNO, NIPH, University of Oslo, Norwegian Computing Centre
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