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. 2012;8(10):e1002741.
doi: 10.1371/journal.pcbi.1002741. Epub 2012 Oct 25.

The role of social contacts and original antigenic sin in shaping the age pattern of immunity to seasonal influenza

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The role of social contacts and original antigenic sin in shaping the age pattern of immunity to seasonal influenza

Adam J Kucharski et al. PLoS Comput Biol. 2012.

Abstract

Recent serological studies of seasonal influenza A in humans suggest a striking characteristic profile of immunity against age, which holds across different countries and against different subtypes of influenza. For both H1N1 and H3N2, the proportion of the population seropositive to recently circulated strains peaks in school-age children, reaches a minimum between ages 35-65, then rises again in the older ages. This pattern is little understood. Variable mixing between different age classes can have a profound effect on disease dynamics, and is hence the obvious candidate explanation for the profile, but using a mathematical model of multiple influenza strains, we see that age dependent transmission based on mixing data from social contact surveys cannot on its own explain the observed pattern. Instead, the number of seropositive individuals in a population may be a consequence of 'original antigenic sin'; if the first infection of a lifetime dominates subsequent immune responses, we demonstrate that it is possible to reproduce the observed relationship between age and seroprevalence. We propose a candidate mechanism for this relationship, by which original antigenic sin, along with antigenic drift and vaccination, results in the age profile of immunity seen in empirical studies.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Comparison of model to data for Australia and Finland .
Grey bars indicate observed seropositivity (proportion with HI titre >40) in each age cohort, with binomial confidence intervals given by black error bars. Blue lines show the age profile of immunity predicted by the best fitting model. The test year is 2005 for Finland and 2009 for Australia. A, proportion seropositive to H1N1/01 (New Cal./99-like strain) in Finland; B, H1N1/New Caledonia/99 in Australia; C, H1N1/Brisbane/07 in Australia; D, H3N2/00 (Panama/99-like) in Finland; E, H3N2/Wisconsin/05 in Australia; F, H3N2/Brisbane/07 in Australia.
Figure 2
Figure 2. Schematic diagram of proposed mechanism behind the age profile of immunity.
Individuals go through four different states as they age: 1) little prior immunity, so seropositivity increases with age and infection, as in a Poisson process; 2) hosts have memory B cells from previous exposures, so novel antibodies to circulating strain are less likely to be made and immunity drops as the strain evolves; 3) the virus has evolved out of the ‘reach’ of OAS, enabling new antibodies to be generated; 4) freedom from OAS, along with vaccination in the elderly, leads to an increase in seropositivity.
Figure 3
Figure 3. Estimated cross-immunity between clusters of strains.
For two clusters of strains formula image and formula image, the level of cross-immunity is given by formula image. Green line, H1N1; blue line, H3N2.

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