Influenza Virus Research Studies

This paper reviews mathematical models of influenza-induced host responses, finding that current models fail to capture complex interactions and suggest improvements in modeling virus-resistant cells.

The paper develops a new mathematical model to capture biphasic viral decay in influenza A virus infections, revealing that viral clearance rates change with infected cell density.

INSaFLU automates whole-genome sequencing analysis for influenza surveillance, generating key genetic outputs and enabling mixed infection detection.

This study uses single-cell RNA sequencing to show extreme variation in viral gene transcript production among infected cells, with some cells producing over half their mRNA from virus.

The paper demonstrates a method to forecast seasonal H3N2 influenza incidence by integrating evolutionary changes with an epidemiological model, achieving accurate real-time predictions for the 2016/2017 season.