{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,12]],"date-time":"2026-08-12T06:30:46Z","timestamp":1786516246827,"version":"build-2736575974"},"reference-count":54,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,8,12]],"date-time":"2026-08-12T00:00:00Z","timestamp":1786492800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Cell. Infect. Microbiol."],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>\n                      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\n                      <jats:italic>Plasmodium<\/jats:italic>\n                      infection, leaving their causes unresolved. As a result of the diagnostic gap, patients receive presumptive antimalarial treatment, unnecessary antibiotics and experience delayed therapy.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fcimb.2026.1884846","type":"journal-article","created":{"date-parts":[[2026,8,12]],"date-time":"2026-08-12T05:55:34Z","timestamp":1786514134000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Using nanopore metagenomics to characterize pathogens in febrile patients from a highland of Western Kenya"],"prefix":"10.3389","volume":"16","author":[{"given":"Felix M.","family":"Pabon-Rodriguez","sequence":"first","affiliation":[{"name":"Department of Biostatistics and Health Data Science, Indiana University School of Medicine","place":["Indianapolis, IN, United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"George","family":"Ayodo","sequence":"additional","affiliation":[{"name":"Centre for Community Health and Wellbeing, Jaramogi Oginga University of Science and Technology","place":["Bondo, Kenya"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,8,12]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1155\/jotm\/4081643","article-title":"Spatial and temporal distribution of febrile illnesses in Uganda: Case studies of brucellosis, malaria and typhoid fever (2016\u20132023)","volume":"4081643","author":"Aceng","year":"2025","journal-title":"J. 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