Respiratory pathogen detections varied across Jiangsu in 2025

A multicenter epidemiological study of 28,736 respiratory specimens collected from patients with acute respiratory tract infections across 13 regions of Jiangsu Province, China, found frequent bacterial and viral detections, with multiple organisms detected in 68.7% of specimens. The analysis used targeted metagenomic next-generation sequencing, or tNGS, during January–December 2025. At least one respiratory organism was detected in all 28,736 specimens, but the researchers cautioned that the platform’s high analytical sensitivity does not mean every detection represented clinically significant infection.

Bacteria were detected in 72.4% of specimens and viruses in 66.6%. Atypical pathogens were found in 6.3%, and other pathogens in 3.2%. The five most frequently detected organisms were Haemophilus influenzae , detected in 26.4% of specimens; Streptococcus pneumoniae , at 23.0%; Moraxella catarrhalis , at 21.1%; Staphylococcus aureus , at 18.4%; and Acinetobacter baumannii , at 13.1%.

The most prevalent mixed-detection combination was H. influenzae together with S. pneumoniae . Mixed detections occurred in 73.5% of specimens from children aged 1–4 years, compared with 46.2% among people aged 60 years or older. The study also reported statistically significant differences in pathogen-detection distributions across age groups, with a chi-square statistic of 412.7 and a two-tailed p value below 0.001.

Detection patterns also varied geographically and seasonally. Comparisons among the 13 Jiangsu regions produced a chi-square statistic of 189.3, while the seasonal comparison yielded 48.2; both had two-tailed p values below 0.001. These tests identified differences in the distributions of detections within the 2025 sampling period, but they did not establish that any organism was increasing or decreasing over time.

The study therefore describes differences among age groups, regions and seasons rather than long-term trends. The researchers classified detected organisms into bacteria, viruses, atypical pathogens and other pathogens, then stratified the results by age, geographical region, season and whether a specimen contained a single organism or a mixture of organisms. The findings reflect the capabilities and limitations of tNGS, a clinical platform designed to provide relatively unbiased and comprehensive pathogen detection.

Detecting an organism in a respiratory specimen does not by itself prove that the organism caused the patient’s symptoms or that the patient had an active infection. The authors specifically noted that high analytical sensitivity can produce detections that are not clinically significant, and they identified colonization and selection bias as limitations. The specimens came from patients seeking care for acute respiratory tract infections rather than from a population-representative sample, so the percentages describe detections in the tested clinical specimens rather than the prevalence of active respiratory infection in all residents of Jiangsu.

Overall, the study provides a large-scale snapshot of the respiratory organisms detected in clinical samples across the province in 2025, with frequent mixed detections and differences associated with age, location and season, while requiring cautious interpretation of individual results.

Subject of Research: Respiratory pathogen detection patterns in clinical specimens from Jiangsu, China

Article Title: Metagenomic sequencing analysis of respiratory pathogens in the Jiangsu region of China: a multicenter epidemiological study (2025)

Article References: Mao, Y., Li, Z., Li, Z., Pan, Y., Gao, J., Zhang, M., Zhang, M., & Sun, J. (2026). Metagenomic sequencing analysis of respiratory pathogens in the Jiangsu region of China: a multicenter epidemiological study (2025). BMC Infectious Diseases. https://doi.org/10.1186/s12879-026-14352-w

Image Credits: AI Generated

DOI: 10.1186/s12879-026-14352-w

Keywords: respiratory infections, metagenomic sequencing, tNGS, pathogen detection, Jiangsu, mixed detections, bacterial pathogens, viral epidemiology, seasonal variation, clinical specimens, Metagenomic, sequencing