Policy-Ready Genomic Intelligence from Limited Resources: Open-Source SARS-CoV-2 Surveillance, Ankara

• Published in: European journal of public health Vol. 35; no. Supplement_4
• Main Author: Öntaş, E
• Format: Journal Article
• Language: English
• Published: Oxford Oxford University Press 01.10.2025
• Subjects: Borders; Cost sharing; COVID-19; Data; Datasets; Flow mapping; Gene sequencing; Genomes; Genomics; Global health; Health surveillance; Intelligence; Mutation; Open source software; Outbreaks; Pandemics; Pipelines; Public health; Real time; Resources; Sampling; Security; Severe acute respiratory syndrome coronavirus 2; Surveillance; Viral diseases; Ankara Turkey; Turkey
• ISSN: 1101-1262; 1464-360X; 1464-360X
• DOI: 10.1093/eurpub/ckaf161.1024

Rapid viral evolution challenges pandemic control and highlights the need for sustainable global surveillance. In many low-resource settings, restricted sequencing capacity and limited data-sharing frameworks delay timely action. We evaluated whether openly shared genomic data and fully open-source analytic pipelines can generate actionable evidence despite these constraints. A cross-sectional genomic surveillance study analysed 45 SARS-CoV-2 whole-genome sequences from Ankara (BioProject PRJNA687366). Reads were processed on Galaxy EU (fastp/MultiQC>BWA-MEM>MarkDuplicates/Samtools); variants were called with LoFreq, annotated by SnpEff, and converted to consensus sequences with bcftools. Lineages and clades were assigned using Pangolin and Nextstrain, and contextualised globally via Outbreak.info. Mutation counts and impact categories were summarised. Limited sample size and single-city sourcing were recognised sources of potential sampling bias. Open-source analysis uncovered mutations in key regions, including spike and RdRp genes, relevant to transmissibility and immune escape. Using Nextstrain, each genome was mapped to clades (e.g.20A-20C) and lineages (e.g.B.1.1.28, B.1.469). Phylogenetic placement revealed multiple introductions into Ankara and export links to neighbouring countries. All analyses were completed in < 2 h on free cloud resources, proving feasibility without proprietary software. Outbreak.info flow maps highlighted likely transmission routes and hotspots, informing isolation and travel policy. Thus, shared genomes and free pipelines provide actionable evidence despite limited local capacity. Even a modest, publicly shared dataset -analysed with open-source tools- can yield timely, policy-relevant genomic intelligence at minimal cost. Expanding national mandates for real-time sequence sharing and cultivating open-analytics capacity will accelerate early warning, thus enhance cross-border One Health collaboration, and reinforce global health security. Key messages • Open-source genomic data and tools enable rapid variant tracking where resources are limited, reinforcing global health security. • Even small publicly shared datasets guide timely interventions; scaling data sharing is vital for One Health surveillance.