The global burden of chronic diseases—encompassing cardiovascular disease, diabetes, obesity, cancer, and other non-communicable conditions—calls for innovative public health strategies. The accelerating adoption of artificial intelligence, data science, mobile technology, and digital health platforms opens new frontiers for population-level monitoring, risk prediction, targeted prevention, and health behavior change.
This Research Topic seeks to advance the intersection of digital technology and public health by gathering novel research and real-world applications that leverage digital tools to address chronic disease prevention, population health surveillance, and health equity. We especially encourage interdisciplinary efforts that connect computer/data science with public health, and interventions that transcend disease silos or are scalable across diverse populations.
We welcome contributions in, but not limited to, the following areas:
- AI/machine learning approaches for anticipating at-risk populations or predicting multi-morbidity - Digital/mobile health tools for promoting healthy behaviors at scale (physical activity, nutrition, smoking cessation) - Data-driven models for chronic disease surveillance or population-level intervention design and evaluation - Equity-focused digital public health: strategies to close gaps in access, prevention, or outcomes via technology - Integration of digital biomarkers, real-world data, and omics for scalable risk stratification - Ethical and policy implications at the interface of technology, privacy, and public health
By promoting interdisciplinary, technology-driven, and public health-impactful research, this Topic will help shape the next generation of global chronic disease prevention and health promotion efforts.
Article types and fees
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Brief Research Report
Clinical Trial
Conceptual Analysis
Data Report
Editorial
FAIR² Data
FAIR² DATA Direct Submission
General Commentary
Hypothesis and Theory
Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.
Article types
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Brief Research Report
Clinical Trial
Conceptual Analysis
Data Report
Editorial
FAIR² Data
FAIR² DATA Direct Submission
General Commentary
Hypothesis and Theory
Methods
Mini Review
Opinion
Original Research
Perspective
Policy and Practice Reviews
Policy Brief
Review
Study Protocol
Systematic Review
Technology and Code
Keywords: chronic disease prevention, digital health, ai in public health, data science, mobile health, health equity, population health surveillance, digital biomarkers, risk prediction
Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
