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MINI REVIEW article

Front. Public Health

Sec. Infectious Diseases: Epidemiology and Prevention

This article is part of the Research TopicIntelligent Surveillance and Multisource Data Integration: Novel Paradigms for Infectious Disease Monitoring and Early Warning SystemsView all articles

Mobile Phone Data Analyses for Public Health Research: A Scoping Review

Provisionally accepted
Xuening ChengXuening Cheng1Wei JiangWei Jiang2Siyi LiuSiyi Liu3Xuyan LouXuyan Lou1YANG LIYANG LI1Lefan LiuLefan Liu4Molin LiMolin Li1Xuyang WangXuyang Wang5Yan CenYan Cen5Alain ChongAlain Chong1Zhuo ChenZhuo Chen1,6*
  • 1University of Nottingham Ningbo China, Ningbo, China
  • 2Ningbo University of Finance and Economics, Ningbo, China
  • 3Indiana University Kelley School of Business, Bloomington, United States
  • 4University of Birmingham, Birmingham, United Kingdom
  • 5Smartsteps Data Technology Co., Ltd, Beijing, China
  • 6University of Georgia, Athens, United States

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Abstract Mobile phone data provide high-resolution, near real-time measurements of population mobility and have become an increasingly valuable source for public health research, enabling rapid evaluation of policy impacts on human movement and pandemic control. However, the methodological challenges surrounding the extraction, governance, and validation of mobile phone data for the public health community remain insufficiently explored. Following the PRISMA-ScR framework, we conduct a scoping review to synthesize major research themes, opportunities, and challenges in the use of mobile phone data for public health, particularly pandemic-related studies. Our findings highlight limitations in the empirical use of these datasets, including demographic and population coverage, representativeness, and equity issues, as well as the transparency of data extraction and processing. We also provide guidance for future research, including the development of standardized frameworks for data curation and validation, a clear understanding of algorithms that extract mobility information, and rigorous interpretation of mobility metrics.

Keywords: Mobile phone data, Public Health, Mobile signaling data, Population mobility, pandemic

Received: 20 Oct 2025; Accepted: 05 Nov 2025.

Copyright: © 2025 Cheng, Jiang, Liu, Lou, LI, Liu, Li, Wang, Cen, Chong and Chen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Zhuo Chen, zchen1@uga.edu

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Supplementary Material