Using Mobile Data to Understand Urban Mobility Patterns in Freetown, Sierra Leone

Matekenya, Dunstan; Alegre, Xavier; Arroyo, Fatima Arroyo; González, Marta González

doi:10.1596/1813-9450-9519

Cited by 2 publications

(1 citation statement)

References 13 publications

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“…Most of the cases (28) are in Africa, where other sources of high-frequency mobility data with high population coverage are limited. 2 While the premise of mobile phone data's utility is widely acknowledged (Haddad et al, 2014;Blondel et al, 2015), obtaining access to analytics from these data in developing countries remains an uphill battle, as reported in other studies (Matekenya et al, 2021). The challenges have included regulatory restrictions, lengthy processes to obtain government clearances, the need for negotiations on data access agreements, insufficient capacity of data users, high costs, funding gaps, and needs for coordination across actors.…”

Section: Introductionmentioning

confidence: 99%

Challenges and opportunities in accessing mobile phone data for COVID-19 response in developing countries

et al. 2021

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Anonymous and aggregated statistics derived from mobile phone data have proven efficacy as a proxy for human mobility in international development work and as inputs to epidemiological modeling of the spread of infectious diseases such as COVID-19. Despite the widely accepted promise of such data for better development outcomes, challenges persist in their systematic use across countries. This is not only the case for steady-state development use cases such as in the transport or urban development sectors, but also for sudden-onset emergencies such as epidemics in the health sector or natural disasters in the environment sector. This article documents an effort to gain systematized access to and use of anonymized, aggregated mobile phone data across 41 countries, leading to fruitful collaborations in nine developing countries over the course of one year. The research identifies recurring roadblocks and replicable successes, offers lessons learned, and calls for a bold vision for future successes. An emerging model for a future that enables steady-state access to insights derived from mobile big data - such that they are available over time for development use cases - will require investments in coalition building across multiple stakeholders, including local researchers and organizations, awareness raising of various key players, demand generation and capacity building, creation and adoption of standards to facilitate access to data and their ethical use, an enabling regulatory environment and long-term financing schemes to fund these activities.

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Section: Introductionmentioning

confidence: 99%

Challenges and opportunities in accessing mobile phone data for COVID-19 response in developing countries

et al. 2021

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Did Liberal Lockdown Policies Change Spatial Behaviour in Sweden? Mapping Daily Mobilities in Stockholm Using Mobile Phone Data During COVID-19

Shuttleworth,

Toger,

Türk

et al. 2023

Appl. Spatial Analysis

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Sweden had the most liberal lockdown policies in Europe during the Covid-19 pandemic. Relying on individual responsibility and behavioural nudges, their effectiveness was questioned from the perspective of others who responded with legal restrictions on behaviour. In this study, using mobile phone data, we therefore examine daily spatial mobilities in Stockholm to understand how they changed during the pandemic from their pre-pandemic baseline given this background. The analysis demonstrates: that mobilities did indeed change but with some variations according to (a) the residential social composition of places and (b) their locations within the city; that the changes were long lasting; and that the average fall in spatial mobility across the whole was not caused by everybody moving less but instead by more people joining the group of those who stayed close to home. It showed, furthermore, that there were seasonal differences in spatial behaviour as well as those associated with major religious or national festivals. The analysis indicates the value of mobile phone data for spatially fine-grained mobility research but also shows its weaknesses, namely the lack of personal information on important covariates such as age, gender, and education.

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Using Mobile Data to Understand Urban Mobility Patterns in Freetown, Sierra Leone

Cited by 2 publications

References 13 publications

Challenges and opportunities in accessing mobile phone data for COVID-19 response in developing countries

Challenges and opportunities in accessing mobile phone data for COVID-19 response in developing countries

Did Liberal Lockdown Policies Change Spatial Behaviour in Sweden? Mapping Daily Mobilities in Stockholm Using Mobile Phone Data During COVID-19

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