Researchers from the University of Rochester, Rochester, NY, developed a mathematical model to predict immune responses to infection with influenza A viruses, which include novel viruses such as the emergent 2009 influenza A (H1N1). The mathematical model predicts that antiviral therapy is most effective in reducing the spread of the virus when given within 2 days after infection.
According to a press announcement from the National Institute of Allergy and Infectious Diseases (NIAID), which funded the project, the model examines the contributions of specific sets of immune cells in fighting influenza A virus. Additionally, the model helps predict when antiviral therapy would be most effective during the immune response to viral infection.
According to the researchers, their mathematical model generates immune response scenarios reflecting multiple variables, including the pathogenicity of the virus, numbers of responding B and T cells, and function of antigen-presenting cells in the lungs and lymph nodes. The model suggests that prolonged viral infection limits the production of T cells and inhibits antigen presentation to immune cells.
The accuracy of the model was tested in mice infected with influenza A virus. The researchers now plan to apply the model to human populations and continue to improve the model as more data become available.
The project appears in the Journal of Virology.