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 innovative approaches to combating one of the world’s most persistent health challenges. This Collection seeks to explore scientific, policy, and community-driven advancements aimed at achieving sustainable solutions for malaria elimination and improving the lives of affected populations.

The goal of this Collection is to highlight progress, identify remaining challenges, and showcase actionable strategies to support malaria elimination efforts. Topics of interest include but are not limited to:

Development and deployment of new antimalarial drugs and vaccines

Innovative diagnostic tools and technologies for malaria detection

Community-based interventions to enhance prevention and treatment uptake

Evaluation of insecticide resistance and vector control programs

Policy and governance frameworks to strengthen malaria elimination efforts

Economic and social analyses of malaria programs and their sustainability

Addressing health equity and access disparities in malaria-endemic regions

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.

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.