Quantifying influenza vaccine efficacy and antigenic distance

Gupta, Vishal; Earl, David J.; Deem, Michael W.

doi:10.1016/j.vaccine.2006.01.010

Cited by 142 publications

(305 citation statements)

References 44 publications

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“…We demonstrated that the informatics framework PREDAC we developed can effectively infer antigenic clusters from HA sequences, and thus can provide a very important tool in the influenza surveillance and vaccine strain recommendation when coupled with large-scale HA sequencing. Previously, many computational approaches were designed to either predict antigenic variants 18,[30][31][32][33][34][35][36] or to model evolutionary patterns for the H3N2 virus [19][20][21]23,24 . In our study, the prediction of antigenic variants and the modeling of antigenic evolutionary patterns are integrated into one computational framework, PREDAC.…”

Section: Discussionmentioning

confidence: 99%

Mapping of H3N2 influenza antigenic evolution in China reveals a strategy for vaccine strain recommendation

et al. 2012

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one of the primary efforts in influenza vaccine strain recommendation is to monitor through gene sequencing the viral surface protein haemagglutinin (HA) variants that lead to viral antigenic changes. Here we have developed a computational method, denoted as PREDAC, to predict antigenic clusters of influenza A (H3n2) viruses with high accuracy from viral HA sequences. Application of PREDAC to large-scale HA sequence data of H3n2 viruses isolated from diverse regions of mainland China identified 17 antigenic clusters that have dominated for at least one season between 1968 and 2010. By tracking the dynamics of the dominant antigenic clusters, we not only find that dominant antigenic clusters change more frequently in China than in the united states/Europe, but also characterize the antigenic patterns of seasonal H3n2 viruses within China. Furthermore, we demonstrate that the coupling of large-scale HA sequencing with PREDAC can significantly improve vaccine strain recommendation for China.

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Section: Discussionmentioning

confidence: 99%

Mapping of H3N2 influenza antigenic evolution in China reveals a strategy for vaccine strain recommendation

et al. 2012

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“…Each antigenic unit difference in distance between strains increases susceptibility by 7% (Fig. 1C) [1,36,39].…”

Section: Modeling Approach and Choice Of Parametersmentioning

confidence: 99%

“…where c = 0.07 is a constant for converting antigenic distance to a risk of infection [1,36,39]. Each infection mutates to a new antigenic phenotype at a rate µ mutations per day.…”

Section: Model Overviewmentioning

confidence: 99%

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The beneficial effects of vaccination on the evolution of seasonal influenza

Wen

Malani

Cobey

2017

Preprint

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Although vaccines against seasonal influenza are designed to protect against currently circulating strains, they may also affect the emergence of antigenically divergent strains and thereby change the rate of antigenic evolution. Such evolutionary effects could change the benefits that vaccines confer to vaccinated individuals and the host population (i.e. private and social benefits). To investigate vaccinations potential evolutionary impacts, we simulated the dynamics of an influenza-like pathogen in an annually vaccinated host population. On average, vaccination decreased the cumulative amount of antigenic evolution of the viral population and the incidence of disease. Vaccination at a 5% random annual vaccination rate (48% cumulative vaccine coverage after 20 years) decreased cumulative evolution by 56% and incidence by 76%. To understand how the evolutionary effects of vaccination might affect its private and social benefits over multiple seasons, we fit linear panel models to simulated infection and vaccination histories. Including the evolutionary effects of vaccination lowered the private benefits by 14% but increased the social benefits by 30% (at a 5% annual vaccination rate) compared to when evolutionary effects were ignored. Thus, in the long term, vaccines' private benefits may be lower and social benefits may be greater than predicted by current measurements of vaccine impact, which do not capture long-term evolutionary effects. These results suggest that conventional vaccines against seasonal influenza could greatly reduce the burden of disease by slowing antigenic evolution like universal vaccines. Furthermore, vaccination's evolutionary effects compound a collective action problem, highlighting the importance on social policies concerning vaccination.

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“…Clinical symptoms associated with infection include high fever, headaches, cough, sore throat, runny nose and muscle ache that resolve within several days. Other associated complications of influenza infections include viral pneumonia, secondary bacterial pneumonia, airway inflammation [9,10]. Nasopharyngeal samples are used for the isolation of the virus while using serum samples serological diagnosis can be carried out [3][4][5].…”

Section: Introductionmentioning

confidence: 99%

Seroconversion and immunogenicity evaluation of seasonal influenza vaccine in mice model

2016

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Influenza virus is epidemiologically very important due to the antigenic variations occurring in it. In present study isolation and identification of influenza virus was attempted from Kasauli and adjoining areas. 71 clinical samples i.e. throat washings were processed and inoculated into the eggs for virus isolation. The isolated strains of H3N2, H1N1 and Influenza B were identified, purified and passaged in eggs. The harvested virus was inactivated by 0.03 % formalin and three formulations of crude, inactivated, whole virus monovalent vaccine for H3N2, H1N1 and influenza B as well as a trivalent vaccine was prepared. The immunogenicity study of the vaccine was performed in the mouse model by using varying dilutions of four types of vaccines for a period of 40 days. The impact of booster dose was also analyzed in the study. A significant seroconversion was observed in the mice sera verifying that the monovalent and trivalent lots of influenza vaccine were antigenically effective based on the serological tests.

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Quantifying influenza vaccine efficacy and antigenic distance

Cited by 142 publications

References 44 publications

Mapping of H3N2 influenza antigenic evolution in China reveals a strategy for vaccine strain recommendation

Mapping of H3N2 influenza antigenic evolution in China reveals a strategy for vaccine strain recommendation

The beneficial effects of vaccination on the evolution of seasonal influenza

Seroconversion and immunogenicity evaluation of seasonal influenza vaccine in mice model

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