ArticleThe Lancet. Digital health2020
Measuring mobility to monitor travel and physical distancing interventions: a common framework for mobile phone data analysis.
Article in The Lancet. Digital health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
53 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Modern sources of controls in case-control studies.American journal of epidemiology · 2025Article
- The limitations of mobile phone data for measuring movement patterns of populations at risk of malaria.Malaria journal · 2025Observational
- Bias in mobility datasets drives divergence in modeled outbreak dynamics.Communications medicine · 2025Article
- Mobile phone data analyses for public health research: a scoping review.Frontiers in public health · 2025Article
- Evaluating the COVID-19 vaccination program in Japan, 2021 using the counterfactual reproduction number.Scientific reports · 2023Article
- A standardised differential privacy framework for epidemiological modeling with mobile phone data.PLOS digital health · 2023Article
- Checkpoint Travel Numbers as a Proxy Variable in Population-Based Studies During the COVID-19 Pandemic: Validation Study.JMIR public health and surveillance · 2023Article
- A Stochastic Mobility-Driven Spatially Explicit SEIQRD covid-19 Model with VOCs, Seasonality, and Vaccines.Applied mathematical modelling · 2023Article
- Estimation of mobility and population in Spain during different phases of the COVID-19 pandemic from mobile phone data.Scientific reports · 2023Article
- Quantifying human mobility resilience to the COVID-19 pandemic: A case study of Beijing, China.Sustainable cities and society · 2023Article
- Mobile Phone Data: A Survey of Techniques, Features, and Applications.Sensors (Basel, Switzerland) · 2023Review
- Article
- Deriving neighborhood-level diet and physical activity measurements from anonymized mobile phone location data for enhancing obesity estimation.International journal of health geographics · 2022Article
- Connecting the dots: understanding how human mobility shapes TB epidemics.Trends in microbiology · 2022Review
- Article
- Mapping urban physical distancing constraints, sub-Saharan Africa: a case study from Kenya.Bulletin of the World Health Organization · 2022Article
- Socio-economic disparities in activity-travel behavior adaptation during the COVID-19 pandemic in North Carolina.Transport policy · 2022Article
- Impact of COVID-19 on Community Participation and Mobility in Young Adults with Autism Spectrum Disorders.Journal of autism and developmental disorders · 2022Article
- The Disparity and Dynamics of Social Distancing Behaviors in Japan: Investigation of Mobile Phone Mobility Data.JMIR medical informatics · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
A surge of interest has been noted in the use of mobility data from mobile phones to monitor physical distancing and model the spread of severe acute respiratory syndrome coronavirus 2, the virus that causes COVID-19. Despite several years of research in this area, standard frameworks for aggregating and making use of different data streams from mobile phones are scarce and difficult to generalise across data providers. Here, we examine aggregation principles and procedures for different mobile phone data streams and describe a common syntax for how aggregated data are used in research and policy. We argue that the principles of privacy and data protection are vital in assessing more technical aspects of aggregation and should be an important central feature to guide partnerships with governments who make use of research products.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.