While public health practitioners and first responders work mightily to execute tactics to cope with the current H1N1 flu epidemic, scientists are hard at work developing new models to help us better deal with future flu outbreaks. Over the past week two new studies with potentially path-breaking implications for predicting and perhaps, ultimately, radically mitigating flu outbreaks.

The first study study, led by assistant professor Andrew W. Park of the University of Georgia Odum School of Ecology and in the College of Veterinary Medicine, Athens, Ga., tracked the relationship between the evolution of the virus and immunization rates needed to prevent an outbreak in the population. The paper was published in the Oct. 30 edition of the journal Science.

By measuring the difference between the population’s immunity status and the makeup on emerging vial strains, Park and his associates scientists may become better able to predict the risks of flu epidemics by geographic areas and population clusters.

Working with equine influenza, the research team looked at the likelihood of an influenza outbreak in a population that had all been vaccinated with the same strain of the virus. Their key finding was that outbreaks began occurring when there were two or more amino acid differences and that the size of the outbreak increased with the number of amino acid differences. They also found that large outbreaks were more likely to occur if the virus and the vaccine were from different antigenic clusters, suggesting that a host's immune system perceives the two strains as different. Comparing these results with an earlier human influenza study revealed similar trends.

Another key factor in determining the risk of an outbreak in real populations, according to the researchers, is the individual variation of immunity in the population. Because the virus keeps changing, researchers found, so do the vaccines used against it, causing the immunity of the population to be heterogeneous, with some individuals infected with or vaccinated against last year’s influenza strain, some against strains from previous years, and some have no immunity at all. Park and his colleagues found that the degree of variability of immunity in the population plays a crucial role in determining the risk of an outbreak.

In another study researchers from the National Institute of Allergy and Infectious Diseases (NIAID), part of the National Institutes of Health proposed a new explanation for the evolutionary forces that drive antigenic drift, the process by which influenza viruses evade infection-fighting antibodies by constantly changing the shape of their major surface protein.

Antigenic drift is widely believed to be a primary reason flu vaccines rapidly lose their efficacy and must be updated continually.

After infecting the vaccinated and unvaccinated mice with the 1934 influenza strain, the scientists repeatedly isolated viruses from the lungs of both sets of mice and passed on these viruses to a new set of mice. After the final passage, the researchers sequenced the gene encoding the virus hemagglutinin protein and which time it was revealed that the unvaccinated mice, which lacked vaccine-induced antibodies, had no mutated influenza viruses in their lungs. In contrast, the hemagglutinin gene in virus isolated from vaccinated mice had mutated in a way that increased the ability of the virus to adhere to the receptors it uses to enter lung cells.

Next, the researchers infected a new set of unvaccinated mice with the high-affinity mutant virus strain that had emerged in the first series of experiments. In the absence of antibody pressure, the virus reverted to a low-affinity form and was once again able to easily infect cells and spread.

Based on this experiment researchers proposed a model for antigenic drift in which high- and low-affinity influenza virus mutants alternate. Adults, who have been exposed to many strains of influenza in their lifetime and, correspondingly, have a wide range of antibody responses, which pressures the virus to increase its receptor affinity to escape antibody neutralization. When such high-affinity mutants are passed to children or others who have not been exposed to many influenza strains or who have not been vaccinated against flu, receptor affinity decreases.

The new model predicts that increasing the percentage of the population, especially children, vaccinated against influenza, could slow the rate of antigenic drift and extend the duration of effectiveness of seasonal influenza vaccines.