Nanopore Adaptive Sampling for Real-Time Pathogen Metagenomics in Febrile Illness Cohorts Across Four Nigerian Geopolitical Zones: Algorithm Development and Deployment Validation

Febrile illness in Nigeria is caused by a diverse array of bacterial, viral, and parasitic pathogens that frequently defy accurate diagnosis based on clinical features alone, while current laboratory capacity remains insufficient to apply comprehensive molecular testing at population scale. Nanopore adaptive sampling, which enables real-time computational selection of target sequences for preferential sequencing, offers a transformative approach to metagenomic pathogen discovery in complex clinical specimens. This dissertation develops novel adaptive sampling algorithms and validates their deployment for real-time febrile illness pathogen metagenomics across clinical sites in four Nigerian geopolitical zones. Clinical serum and cerebrospinal fluid (CSF) samples from 200 febrile patients with undetermined etiology were prospectively enrolled at sites in Kano (Northwest), Abuja (North Central), Port Harcourt (South-South), and Enugu (Southeast). Metagenomic libraries were prepared using a rapid extraction and transposase-based library protocol (Rapid Sequencing Kit SQK-RBK114). Sequencing was performed on Oxford Nanopore MinION devices using ReadFish adaptive sampling software with a pathogen-targeted reference panel. A novel algorithm (NigeriaPathoSampler) was developed that dynamically updates pathogen target probability weights based on real-time base-call streaming results, improving depth at low-abundance target loci. NigeriaPathoSampler achieved 4.2-fold on-target enrichment over non-adaptive sequencing. Thirty-one distinct pathogen species were identified across the cohort, with 18% of cases carrying co-infections. Six samples yielded viral genome sequences with less than 10% database identity to known species, flagged as novel virus candidates requiring further characterization. The NigeriaPathoSampler algorithm represents an original computational contribution to low-resource infectious disease metagenomics. Keywords: nanopore adaptive sampling, pathogen metagenomics, febrile illness, algorithm development, Nigeria.