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Age profile of immunity to influenza: Effect of original antigenic sin

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  • Kucharski, Adam J.
  • Gog, Julia R.

Abstract

When multiple infections are possible during an individual’s lifetime, as with influenza, a host’s history of infection and immunity will determine the result of future exposures. In turn, the suite of varying individual infection histories will shape the population level dynamics of the disease. Exploring the consequences of precisely how immunity is acquired using mathematical models has proven challenging though: if n strains have circulated previously, there are 2n combinations of past infection to consider. However, by using an age-structured mathematical model of a disease with multiple strains, we can examine the population immune profile without explicitly keeping track of all possible infection histories. This framework allows previously unknown consequences of assumptions about immune acquisition to be observed. In particular, we see that ‘original antigenic sin’ can reduce immunity in some age groups: these immune blind spots could be responsible for the unexpectedly high severity of certain past influenza epidemics.

Suggested Citation

  • Kucharski, Adam J. & Gog, Julia R., 2012. "Age profile of immunity to influenza: Effect of original antigenic sin," Theoretical Population Biology, Elsevier, vol. 81(2), pages 102-112.
  • Handle: RePEc:eee:thpobi:v:81:y:2012:i:2:p:102-112
    DOI: 10.1016/j.tpb.2011.12.006
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    References listed on IDEAS

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    1. Adams, Ben & Sasaki, Akira, 2009. "Antigenic distance and cross-immunity, invasibility and coexistence of pathogen strains in an epidemiological model with discrete antigenic space," Theoretical Population Biology, Elsevier, vol. 76(3), pages 157-167.
    2. Andrew Rambaut & Oliver G. Pybus & Martha I. Nelson & Cecile Viboud & Jeffery K. Taubenberger & Edward C. Holmes, 2008. "The genomic and epidemiological dynamics of human influenza A virus," Nature, Nature, vol. 453(7195), pages 615-619, May.
    3. Jens Wrammert & Kenneth Smith & Joe Miller & William A. Langley & Kenneth Kokko & Christian Larsen & Nai-Ying Zheng & Israel Mays & Lori Garman & Christina Helms & Judith James & Gillian M. Air & J. D, 2008. "Rapid cloning of high-affinity human monoclonal antibodies against influenza virus," Nature, Nature, vol. 453(7195), pages 667-671, May.
    4. Neil M. Ferguson & Alison P. Galvani & Robin M. Bush, 2003. "Ecological and immunological determinants of influenza evolution," Nature, Nature, vol. 422(6930), pages 428-433, March.
    5. Sergey Kryazhimskiy & Ulf Dieckmann & Simon A Levin & Jonathan Dushoff, 2007. "On State-Space Reduction in Multi-Strain Pathogen Models, with an Application to Antigenic Drift in Influenza A," PLOS Computational Biology, Public Library of Science, vol. 3(8), pages 1-1, August.
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    Cited by:

    1. Frédéric M Hamelin & Linda J S Allen & Vrushali A Bokil & Louis J Gross & Frank M Hilker & Michael J Jeger & Carrie A Manore & Alison G Power & Megan A Rúa & Nik J Cunniffe, 2019. "Coinfections by noninteracting pathogens are not independent and require new tests of interaction," PLOS Biology, Public Library of Science, vol. 17(12), pages 1-25, December.
    2. Nie, Yanyi & Zhong, Xiaoni & Lin, Tao & Wang, Wei, 2023. "Pathogen diversity in meta-population networks," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
    3. Fahlena, Hilda & Kusdiantara, Rudy & Nuraini, Nuning & Soewono, Edy, 2022. "Dynamical analysis of two-pathogen coinfection in influenza and other respiratory diseases," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).

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