Metagenomic sequencing is useful in quickly identifying the pathogens circulating in the community, especially for respiratory infections. Analysing and interpreting molecular and epidemiological data require specialist knowledge, skills and abilities. On the other hand, a human-readable report could aid in making evidence-based public health policies. In this study, the use of generative artificial intelligence (GenAI) to bridge the gap between the two was evaluated. Molecular data generated were taxonomically classified through a bioinformatics pipeline and were then combined with epidemiological data to create a report with actionable insights using GenAI. Acknowledging its limitations, the study results showed that this approach was feasible and could be scaled up in the future and expanded to study transmission dynamics of other infections.
Kwan et al. (Mon,) studied this question.