ArticleInfluenza and other respiratory viruses2026
Use of Metagenomic Next-Generation Sequencing to Investigate Respiratory Pathogens in Influenza-Negative Nasopharyngeal Swabs From Cameroon's National Influenza Surveillance.
Article in Influenza and other respiratory viruses, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
backgroundIn Cameroon, national influenza surveillance identifies influenza-positive cases, but the causes of non-influenza ARIs remain poorly characterized. We applied metagenomic next-generation sequencing (mNGS) to investigate respiratory pathogens in influenza-negative nasopharyngeal swabs collected through national influenza surveillance.
methodsWe analyzed 199 influenza-negative nasopharyngeal swabs collected between September and December 2023 from patients with influenza-like illness or severe acute respiratory infection. Mixed DNA/RNA libraries were prepared and sequenced on an Illumina NovaSeq platform. Taxonomic classification was performed using METAMIC (v2.0) and SPAdes (V3.15.5) bioinformatic pipelines.
resultsViral sequences were detected in 120/199 samples (60.3%, 95% CI: 53.5%, 67.1%), representing 15 viral species. The most frequent viruses were rhinovirus (43/131), respiratory syncytial virus (33/131), influenza virus, parainfluenza virus and enterovirus. Two non-respiratory viruses (Rotavirus and Papillomavirus) were also detected. Sequencing generated an average of 26.1 million reads per sample, with a mean depth of 870.3 per sample and an average genomic coverage of 82%. Eleven viral co-infections were identified. Several bacterial and fungal genera were also detected.
conclusionOur study shows that mNGS provides a powerful, unbiased approach for characterizing respiratory pathogens in Cameroon, revealing substantial viral diversity among influenza-negative ARI cases. However, cost and bioinformatics capacity remain major barriers to routine implementation. Longitudinal studies and clinical correlation are needed to strengthen interpretation and guide integration of mNGS into national surveillance.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.