Experiments on the effects of anti-viral drugs on a "flu-infected" virtual immune system also accurately predicted that lowering the viral load or spread within two days of symptoms enables rapid control of the infection. These results match known limitations of neuraminidase inhibitors like the widely stockpiled Tamiflu and Relenza, which inhibit viral reproduction in infected cells, but are only effective if given soon after infection. The model also predicted that antiviral therapies may be more effective if taken in combination, but only if administered within two days of infection. Unlike chronic HIV infection, the acute nature of influenza means there is a narrow time window during early infection when interfering with viral replication can reduce viral load.
"Heterosubtypic immunity" refers to the ability of human immune defenses primed to fight one strain of flu to provide broad protection should other strains of flu be encountered later. Whether or not a single vaccine can protect against any of the many H1N1 Influenza viruses would depend on this property. The team's model confirmed that heterosubtypic immunity to influenza depends on a specific quality, the number of killer T cells present in the lungs of a given individual at the start of infection. Thus, near-future vaccines against swine flu for instance may work better if designed to evoke local immune memory cells in the lungs, rather than administered through the bloodstream.
In addition, the model argues that a strong antibody response, along with local T cell expansion, will be important to ensure protection against future pandemics. The findings suggest that some unconventional therapies that rapidly boost immune responses might be effective in a worst case scenario of a pandemic influenza virus. One possibility is the treatment of those front line of the epidemic (e.g. healthcare workers) with an injection of the liquid portion of blood (serum) taken from patients who have previously been infected and successfully fought off an influenza virus. This serum would contain antibodies against the virus at hand. Current antiviral treatments only work if given with 48 hours of infection, and vaccines take several weeks to start working, leaving a gap that might be filled by immune sera injection.
Because its genetic makeup is new, little is known about the distribution of preexisiting immunity to current H1N1 "swine" flu across populations, the immune response to the virus or the efficacy of available vaccines. The team in Rochester hopes to contribute to the building of models that simulate swine flu infection across the entire U.S. population to better predict its course.
Along with Wu and Zand, major project contributors included Ha Youn Lee, Sung Yong Park, Jeanne Holden-Wiltse and Hongyu Miao in the Department of Biostatistics and Computational Biology at the Medical Center; David Topham, Joseph Hollenbaugh, Tim Mosmann and Brian Ward within the David H. Smith Center for Vaccine Biology & Immunology and the Department of Microbiology and Immunology; and John Treanor and Xia Jin in the Division of Infectious Diseases within the Department of Medicine. Alan Perelson led a partnering effort at the Los Alamos National Laboratory in New Mexico.
"The right computer model can provide a precise, hands-on way of measuring just how good our theories are about how the system responds to pandemic virus, and how to strengthen our defenses," said Wu.
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