Using nanopore metagenomics to characterize pathogens in febrile patients from a highland of Western Kenya.

INTRODUCTION

Febrile illness remains a leading cause of morbidity in sub-Saharan Africa despite substantial reductions in malaria transmission. As malaria positive cases decrease, an increasing number of patients with febrile illnesses test negative for Plasmodium infection, leaving their causes unresolved. As a result of the diagnostic gap, patients receive presumptive antimalarial treatment, unnecessary antibiotics and experience delayed therapy.

METHODS

We conducted a nanopore metagenomic next-generation sequencing (mNGS) investigation of 168 archived blood samples collected from febrile patients in Kipsamoite and Kapsisywa sites in Nandi County, a highland region in western Kenya experiencing declining malaria transmission, between 2012 and 2020. The study used exploratory taxonomic profiling to identify microbial DNA/RNA signatures in archived plasma samples and described organisms with known or potential clinical relevance, while classifying detected organisms into common commensal, skin-associated, and environmental taxa. Demographic and clinical data linked to samples were used to fit multivariable logistic regression models to assess associations.

RESULTS

Sequencing revealed substantial microbial heterogeneity, including frequent detection of common skin/environmental taxa, opportunistic organisms, ubiquitous viruses, and a smaller number of organisms with established fever-causing potential. The detections are interpreted as molecular evidence of microbial nucleic acid, not as proof of active infection or fever causality. Malaria-positive subjects had a higher mean number of identified pathogens compared to malaria-negative subjects (3.78 vs. 2.14; p = 0.002), despite a baseline microbial landscape dominated by commensal flora, environmental organisms, and ubiquitous viruses.

DISCUSSION: Nanopore mNGS is a viable tool for identifying non-malarial febrile pathogens in western Kenya. Future efforts must combine systematic sampling with field-deployable contamination controls and causal confirmation frameworks to optimize regional antimicrobial stewardship and surveillance.