Topic Editors

Department of Epidemiology and Biostatistics, School of Public Health, University of Maryland, College Park, MD 20742, USA
Department of Epidemiology and Biostatistics, School of Public Health, University of Maryland, College Park, MD 20742, USA

The Use of Big Data in Public Health Research and Practice

Abstract submission deadline
31 October 2025
Manuscript submission deadline
31 December 2025
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Topic Information

Dear Colleagues,

We are organizing a Topic on the use of big data to inform health research and practice. To enable decision-making, it is important to obtain timely data on the determinants of health and well-being. Big data can often be operational or “organic” data generated for non-research purposes, including social media, news feeds, Google Street View images, online reviews, blogs, electronic health records, pharmacy records, and billing records. This Topic is focused on innovative ways that big data are leveraged for health research and practice. Some possible submission ideas are listed below; however, submissions addressing other related topics are also welcomed:

  • Use of electronic health records, billing data, and pharmacy data to understand individualized risk factors and treatment success; 
  • Characterization of built environments with big data derived from various sources (e.g., Street View images and remote sensing imagery data) as well as their impact on health; 
  • Using various user-generated content (e.g., GPS data, accelerometer data, users’ review data, social media data, and web search data) to study individual behaviors and social/cultural environments as well as their impacts on people’s health; 
  • Development of new methods or tools (e.g., natural language processing, machine learning, database management, high-performance computing, data mining, cloud computing, computer vision, visualization, geographic information systems, and spatial analysis) for big-data-based health research; 
  • Use of big data in COVID-19-related research; 
  • Application or development of causal inference methods for big data;
  • Investigating and addressing data quality and uncertainty issues;
  • Blending and integration of big data from different sources.

Dr. Quynh C. Nguyen
Dr. Thu T. Nguyen
Topic Editors


  • big data
  • artificial intelligence
  • machine learning
  • deep learning
  • data science
  • natural language processing
  • computer vision
  • chat GPT

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
5.2 8.0 2009 17.9 Days CHF 2900 Submit
International Journal of Environmental Research and Public Health
- 7.3 2004 29.6 Days CHF 2500 Submit
ISPRS International Journal of Geo-Information
3.4 6.9 2012 35.5 Days CHF 1700 Submit
Machine Learning and Knowledge Extraction
3.9 6.3 2019 19.9 Days CHF 1800 Submit
Smart Cities
6.4 11.2 2018 20.2 Days CHF 2000 Submit is a multidiscipline platform providing preprint service that is dedicated to sharing your research from the start and empowering your research journey.

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Published Papers

This Topic is now open for submission.
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