Math can improve flu shot, experts say

Mathematical modeling can improve the effectiveness of influenza vaccine, according to experts at Rice University – where such a model has existed for more than 15 years – and its Baker Institute for Public Policy.

Michael Deem, John W. Cox Professor of Biochemical Engineering and Genetics at Rice; Melia Bonomo, Ph.D. candidate in physics and astronomy at the university; and Kirstin Matthews, a research scientist in science and technology policy at the Baker Institute's Center for Health and Biosciences, presented their views in a new guidance document titled "Improving the Effectiveness of the Annual Vaccine Against Cancer." influenza".

Seasonal flu is the cause of 49 million illnesses and 79,000 deaths in the United States each year since 2010. To combat its consequences, the Center for Disease Control and Prevention (CDC) recommends to all children and adults in good health to be vaccinated against the flu every year. In 2017-18, 58% of healthy children (aged 6 months to 17 years) and only 37% of adults received the vaccine. About 80 percent of pediatric influenza deaths during this season were unvaccinated children.

"To develop a vaccine before the start of the influenza season in the fall, scientists must start in early January," the authors wrote. "The current CDC method involves scientists vaccinating ferrets with several candidate vaccines, then extracting ferret antibodies to estimate which vaccine was most effective against the dominant viruses of the previous influenza season." method has been used since almost However, it has been proven that it was inconsistent in predicting the efficacy of vaccines in humans, particularly with the recent fast-mutating A (H3N2) viruses. In addition, experiments with ferrets take time and are expensive. "

In contrast, mathematical models, including a model developed by Rice more than 15 years ago, allow scientists to calculate how well influenza vaccine matches infectious viruses. The Rice model, called pEpitope, evaluates the effectiveness of the vaccine. It has proven effective for influenza A (H3N2), A (H1N1) and B vaccines. According to Rice scientists, for the 2018-2019 influenza season, the effectiveness of the vaccine will be 20 to 40 % higher than the majority of A (H3N2) viruses.

"Public health researchers are often slow to change," the authors wrote. "Despite the fact that Rice's pEpitope model has been in existence for more than 15 years, it's unclear why CDC still has to leverage it to develop their seasonal influenza flu vaccine." The model of experiments already conducted with the ferret will strengthen the current decision-making process for immunization.

"This mathematical modeling technique can quickly reduce the number of viruses that would be good candidates for the vaccine during a given influenza season," they continued. "This can be used to verify that the vaccine virus does not mutate during the manufacturing process.The pEpitope model is also inexpensive because it does not require any specialized equipment.Finally, it is extremely fast and takes a few seconds to analyze the 39; potential efficacy of a vaccine against thousands of infective viruses in a given geographical area. "

The authors stated that the CDC should strengthen its current protocols for the selection of vaccine candidates using all available predictive models. "This will improve the overall effectiveness of the influenza vaccine and possibly the coverage rate," they wrote. "Scientists hope that with increased efficiency, they will also be able to improve immunization coverage rates, which remains far from the 70% target of the project" Healthy People for 2020 "This work could improve the selection and education of vaccine strains by providing a tool accessible to researchers and scientific citizens."

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More information:
Improving the Influenza Vaccine: www.bakerinstitute.org/researc…Indicating Influenza Vaccines /