How immunity shapes the long-term dynamics of influenza H3N2 DOI Creative Commons
Oliver Eales, Freya M. Shearer, James M. McCaw

et al.

PLoS Computational Biology, Journal Year: 2025, Volume and Issue: 21(3), P. e1012893 - e1012893

Published: March 20, 2025

Since its emergence in 1968, influenza A H3N2 has caused yearly epidemics temperate regions. While infection confers immunity against antigenically similar strains, new distinct strains that evade existing regularly emerge (‘antigenic drift’). Immunity at the individual level is complex, depending on an individual's lifetime history. An first with typically elicits greatest response subsequent infections eliciting progressively reduced responses seniority’). The combined effect of individual-level immune and antigenic drift epidemiological dynamics are not well understood. Here we develop integrated modelling framework transmission, immunity, to show how exposure, build-up population shape long-term H3N2. Including seniority model, observe following initial decline after pandemic year, average annual attack rate increases over next 80 years, before reaching equilibrium, greater older age-groups. Our analyses suggest still a growth phase. Further increases, particularly elderly, may be expected coming decades, driving increase healthcare demand due infections.

Language: Английский

How immunity shapes the long-term dynamics of influenza H3N2 DOI Creative Commons
Oliver Eales, Freya M. Shearer, James M. McCaw

et al.

PLoS Computational Biology, Journal Year: 2025, Volume and Issue: 21(3), P. e1012893 - e1012893

Published: March 20, 2025

Since its emergence in 1968, influenza A H3N2 has caused yearly epidemics temperate regions. While infection confers immunity against antigenically similar strains, new distinct strains that evade existing regularly emerge (‘antigenic drift’). Immunity at the individual level is complex, depending on an individual's lifetime history. An first with typically elicits greatest response subsequent infections eliciting progressively reduced responses seniority’). The combined effect of individual-level immune and antigenic drift epidemiological dynamics are not well understood. Here we develop integrated modelling framework transmission, immunity, to show how exposure, build-up population shape long-term H3N2. Including seniority model, observe following initial decline after pandemic year, average annual attack rate increases over next 80 years, before reaching equilibrium, greater older age-groups. Our analyses suggest still a growth phase. Further increases, particularly elderly, may be expected coming decades, driving increase healthcare demand due infections.

Language: Английский

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