BMC Global and Public Health is calling for submissions to our Collection on how the integration of advanced data-driven methods in public health policy is rapidly transforming how we understand and respond to global health challenges. This Collection focuses on the application of innovative statistical modelling, machine learning, and geographic information systems (GIS) to inform health policy decisions. By integrating data from surveys and health records with information on social and environmental determinants, researchers can uncover actionable insights that enhance the effectiveness and efficiency of health interventions across diverse populations.

The relevance of these advanced methodologies is underscored by recent advancements in methods for data collection and analysis, which have enabled researchers to create more precise models for predicting disease outbreaks, evaluating health interventions, and addressing health disparities. As public health continues to confront complex issues such as pandemics and non-communicable diseases, the ability to leverage data-driven strategies becomes increasingly vital for crafting evidence-based policies that are responsive to real-world challenges.

Continued research in this area could lead to groundbreaking methodologies that enhance our understanding of health dynamics and improve public health responses. Future advancements may include the development of real-time data analytics for tracking disease spread, enhanced spatial epidemiological models that account for environmental variables, and improved collaboration between data scientists and public health professionals. By further integrating data science with public health, we can pave the way for more effective interventions and ultimately improve health outcomes globally.

We encourage submissions in the following areas, with a particular interest in studies relevant to low- and middle-income countries (LMICs); however, contributions from all settings are welcome, including:

• Applications of Machine Learning in Public Health
• Spatial Epidemiology and Disease Mapping
• Statistical Modeling for Health Policy Decisions
• GIS in Public Health Decision Making
• Evidence-Based Approaches to Infectious and Non-communicable Diseases

This Collection supports and amplifies research related to SDG 3: Good Health and Well-being.

All manuscripts submitted to this journal, including those submitted to collections and special issues, are assessed in line with our editorial policies and the journal’s peer-review process. Reviewers and editors are required to declare competing interests and can be excluded from the peer review process if a competing interest exists.

BMC Global and Public Health is calling for submissions to our Collection on food security, nutrition, and dietary trends. These are interconnected elements that profoundly impact global health and well-being. As the world grapples with rapid population growth, climate change, and economic disparities, the challenges surrounding food access, quality, and sustainability have intensified. This Collection aims to gather diverse research that examines these complex relationships, focusing on how dietary patterns, food availability, and nutritional status influence overall health outcomes. By exploring the multifaceted nature of food systems, this Collection seeks to showcase pathways to achieve improved food security and nutritional health worldwide.

The goal of this Collection is to build a comprehensive body of knowledge that informs policy and practice. We encourage submissions that investigate:

Impact of dietary patterns on health outcomes

Addressing food insecurity through policy

Role of ultra-processed foods in nutrition

Personalized nutrition and dietary therapy

Nutritional supplements for malnutrition

This Collection supports and amplifies research related to SDG 2: Zero Hunger and SDG 3: Good Health and Well-Being.

We encourage work from local, regional, national, and global partnerships and collaboration among multidisciplinary scientists using multiple methodologies. We ask that authors be careful to use non-stigmatizing/preferred language in their manuscripts as outlined in relevant language guidelines for their respective fields.

All manuscripts submitted to this journal, including those submitted to collections and special issues, are assessed in line with our editorial policies and the journal’s peer-review process. Reviewers and editors are required to declare competing interests and can be excluded from the peer review process if a competing interest exists.