Using Public-Private Data to Understand Compliance with Mobility Restrictions in Sierra Leone
During the early stages of the pandemic, lockdowns and mobility restrictions became indispensable tools to flatten the curve and ease pressure on healthcare systems worldwide. However, guaguing adherence to evolving public policies was tricky, especially in the Global South where decision-makers can lack access to data and capacity to analyze it in a timely way.
In a novel collaboration between MIT researchers, government officials and a telecom operator in Sierra Leone created metrics from raw data, providing decision-makers unprecedented insights into how nationwide restrictions were affecting mobility.
A book chapter about this project, “Using Public-Private Data to Understand Compliance with Mobility Restrictions in Sierra Leone” by Innocent Ndubuisi-Obi, Jr. and five co-authors, is just one of 29 in the new edited volume Urban Informatics and Future Cities, published in conjunction with the Computation in Urban Planning and Urban Management (CUPUM) conference held virtually in June 2021.
CUPUM is a unique global community of scholars that has met biannually since being inaugurated in 1989 in Hong Kong. Thanks to the decision to rotate the conference to locations around the globe and an international board, these conferences feature cutting-edge computational methods, tools, and research with a broad international reach illustrated by the chapters to this timely book, which are drawn from the best papers presented at the CUPUM 2021 conference.
The Sierra Leone case study is just one of the contributions dealing with COVID-19.
Another, “Smart Governance and COVID-19 Control in Wuhan, China,” written by Huaxiong Jiang and two co-authors, documents the many ways advanced technology was used to combat the outbreak in Wuhan. Unlike conventional accounts that stress tracking apps and monitoring, the authors argue that social media platforms, used to organize ad-hoc food delivery and social support, were some of the most consequential uses of technology.
Other chapters also demonstrate a combination of local urban expertise with technical skill, including a novel walkability index for tourism in Melbourne (Ch. 13), the analysis of Flickr photos to gauge population response to disaster in Tokyo (Ch. 9), and an analysis showing commercial cellphone data may beat conventional travel surveys for inclusion in Benton Harbor, Michigan (Ch. 8).
The introduction provides a quick review of the book’s scope, themes, and brief summaries of the chapters.
The volume’s main technical themes are big data, planning support systems, and analysis and modeling. Substantively, the chapters address topics in transportation, disasters and resilience, and walkability and tourism. Reflecting the diversity of topics and methods of interest to the CUPUM community, the book has chapters of interest to a wide range of scholars working on urban computational research.
Planning is already underway for the next CUPUM event to be hosted by McGill University in Montreal, and a call for submissions will be published for that event in September 2022.
Robert Goodspeed
Abstract of the book chapter "Using Public-Private Data to Understand Compliance with Mobility Restrictions in Sierra Leone":
This research investigates the potential for using call detail records (CDRs) data to determine public compliance to two government mandated confinement measures in Sierra Leone: a three day lockdown and fourteen day inter district travel restriction during the first wave of the COVID19 pandemic in April 2020. We use a distance-based mobility indicator, the average distance travelled per district per day to determine compliance to government mandates. The measure is used to proxy the change in mobility compared to a baseline period for both inter- and intra-district trips in Sierra Leone. Our results show significant compliance across all districts in Sierra Leone. We also show that the intensity of compliance is influenced by poverty and population. Our work demonstrates how using CDR-based mobility analysis was carried out in Sierra Leone during the COVID19 crisis to aid policy makers in understanding the effectiveness of their COVID19 mitigation measures.
