Genomic Surveillance of Respiratory Pathogens: From Molecular Detection to Precision Infection Control

Abstract

Respiratory pathogens remain a major global public health concern due to factors including their genetic diversity, dynamic transmission patterns, and increasing antimicrobial resistance. Conventional molecular diagnostics, particularly polymerase chain reaction (PCR)-based assays, remain essential for rapid and scalable pathogen detection but provide limited information on pathogen evolution, transmission, and resistance mechanisms. Advances in whole-genome sequencing (WGS), targeted sequencing, and metagenomic next-generation sequencing (mNGS) have expanded respiratory pathogen surveillance from targeted detection toward higher-resolution genomic characterization. However, no single technology can adequately address all surveillance objectives. Instead, molecular diagnostics, genomic sequencing, epidemiological investigation, and clinical assessment provide complementary information that can be integrated according to the pathogen, clinical context, and specific public health question. This review examines the evolution of respiratory pathogen surveillance and emphasizes an integrated framework in which different technologies are selected and combined to support pathogen characterization, transmission investigation, antimicrobial resistance surveillance, and preventive decision-making. We further discuss emerging applications of artificial intelligence (AI) for integrating genomic, epidemiological, and clinical data, with potential roles in genomic interpretation, early risk assessment, and precision infection control. Although AI-enhanced surveillance remains largely at the research and validation stage, advances in data integration, model development, and computational infrastructure may enable more predictive and actionable surveillance systems. Overall, the future of respiratory pathogen surveillance will depend not simply on adopting more advanced technologies, but on integrating complementary detection and analytical approaches to transform pathogen detection into actionable evidence for public health decision-making.

The authors' abstract, as published at the source. Pathogens, 2026 · DOI ↗