The field of genetic epidemiology has been revolutionized by recent advancements in next-generation sequencing technologies, as well as the development of sophisticated bioinformatic tools and mathematical algorithms applied to genomics. These innovations have enhanced our ability to understand disease epidemiology more effectively, addressing the complexity of genetic components involved in public health. Although substantial progress has been made, a need for refined analysis methods remains important.

This research topic aims to showcase research on innovative methodologies in genetic and genomics that are relevant to public and global health. Both wet and dry lab studies following general ethical requirements and standard scientific rigor are covered. Methodologies are considered if they provide high-quality data to better understand or contribute to fill important gaps.

We welcome articles addressing, but not limited to, the following themes:

- Original or optimized software or pipelines

- New or improved genetic metric,

- Innovative or cost-effective sequencing methods and library preparations

- Affordable and/or portable genomic tools that can be implemented for large-scale studies in resource-limited settings

- Evaluation of tool performance highlighting key areas for improvement

- Creative ideas or opinions to advance any aspect of the broad field of genetic epidemiology

Articles may include studies on disease spatial or temporal distribution, pathogen genetic relatedness and connectivity, population structure and dynamics, disease origins and importation, pathogen genetic diversity to understand vaccine failure or immune evasion, emergence and spread of drug resistance markers, transmission intensity of diseases, genomic signatures of selection pressures, vector genetic diversity and insecticide resistance for vector-born diseases, and genetic impacts of disease control or elimination interventions.

Are you interested in contributing a manuscript to this Research Topic?

Advances in Genetic and Genomic Tools for Epidemiological Research