Characterizing viral clearance kinetics in acute influenza
1
Issued Date
2026-04-30
Resource Type
eISSN
14712970
Scopus ID
2-s2.0-105037562338
Pubmed ID
42057729
Journal Title
Philosophical Transactions of the Royal Society of London Series B Biological Sciences
Volume
381
Issue
1949
Rights Holder(s)
SCOPUS
Bibliographic Citation
Philosophical Transactions of the Royal Society of London Series B Biological Sciences Vol.381 No.1949 (2026)
Suggested Citation
Wongnak P., Seers T., Jittamala P., Imwong M., Schilling W., Watson J., White N.J. Characterizing viral clearance kinetics in acute influenza. Philosophical Transactions of the Royal Society of London Series B Biological Sciences Vol.381 No.1949 (2026). doi:10.1098/rstb.2024.0351 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/116631
Title
Characterizing viral clearance kinetics in acute influenza
Corresponding Author(s)
Other Contributor(s)
Abstract
Pharmacometric assessment of antiviral efficacy in acute influenza informs treatment decisions and pandemic preparedness. We characterized natural viral clearance in acute influenza to guide phase II trial design using simulations based upon observed data. Standardized duplicate oropharyngeal swabs were collected daily over 14 days from 80 untreated low-risk Thai adults, with viral densities measured using quantitative polymerase chain reaction. We evaluated three models to describe viral clearance: exponential, bi-exponential and growth-and-decay. The growth-and-decay model provided the best fit, but the exponential decay model was the most parsimonious. The median viral clearance half-life was 10.3 h (interquartile range (IQR): 6.8-15.4h), varying by influenza type: 9.6 h (IQR: 6.2-13.0 h) for influenza A and 14.0 h (IQR: 10.3-19.3 h) for influenza B. Simulated trials using parameters from the exponential decay model showed that 148 patients per arm provide over 90% power to detect treatments accelerating viral clearance by 40%. Variation in clearance rates strongly impacted the power; doubling this variation would require 232 patients per arm for an antiviral with a 60% effect size. A sampling strategy with four swabs per day reduces the required sample size to 81 per arm while maintaining over 80% power. We recommend this approach to assess and compare current anti-influenza drugs. This article is part of the Theo Murphy meeting issue 'Evaluating anti-infective drugs'.