H5N1 Marker Watch: Antiviral-Resistance and Mammalian-Adaptation Markers in Public U.S. Influenza A(H5N1) Sequences, Alongside CDC Wastewater H5 Detections
Year: 2026
Type: preprint
Abstract: Public genomic and wastewater surveillance data for highly pathogenic avian influenza A(H5N1) in the United States are open, large, and held in systems that do not speak to one another. We describe H5N1 Marker Watch, an open dataset that tabulates published antiviral-resistance and mammalian-adaptation marker positions in publicly deposited U.S. A(H5N1) protein sequences by state, collection year and host group, and places those counts alongside CDC National Wastewater Surveillance System H5 detections for the same state and year. Version 1.0.0 covers 95,582 protein sequences from 18,378 distinct isolates collected between 2022 and 2026 across 52 states and territories, screened at 36 marker positions drawn from WHO and CDC sources, producing 688,287 individual calls, joined to 124,427 wastewater results from 49 states of which 3,010 detected H5. Markers associated with reduced susceptibility to clinically used antivirals are rare: the neuraminidase substitution H275Y, the one substitution WHO identifies as a known clinical resistance marker, appears in 7 of 19,141 covering sequences (0.037%). The mammalian-adaptation picture differs: PB2 E627K rises across the period, from 0.126% of covering sequences in 2022 to 5.18% in the partial year 2026, while two further markers sit at frequencies better read as fixed features of the circulating clade. We report a methodological finding of general relevance: published marker positions arrive in several numbering conventions and some sources list the same site twice under two of them, so every position is validated against a named reference before it is counted. 11 of 36 markers required a numbering translation and 3 proved to be duplicates. Marker status throughout is genotype, not confirmed phenotype; no susceptibility testing was performed or is implied. Data, code and documentation are released openly and the pipeline is built for annual refresh.
Source: Preprints.org
Author: Emmanuel Akhigbe Igbuan
Language: English
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W7224959376