Bull, Koelle, and Antia proposed that the rapid waning of immunity in the respiratory tract is the key driver of antigenic evolution in respiratory viruses: because recovered hosts pass through a long phase of partial immunity that no longer protects against antigenically different strains, abundant partially immune hosts give an immune-escape variant - even one bearing a transmission fitness cost - a population-wide advantage, predicting successive emergence and replacement of antigenic variants. Their analysis, however, covers only the initial invasion of a single escape variant into an equilibrium of an endemic wild-type virus, with a single step of waning and no recall responses. The open problem is to extend this mechanism to the long-term eco-evolutionary dynamics of antigenically evolving respiratory viruses - gradual waning, immune recall, compensatory mutations that offset the fitness costs of escape - using empirically grounded parameters for waning and for escape costs, and to determine whether it quantitatively reproduces the observed long-term patterns of antigenic drift (successive variant replacement, ladder-like phylogenies, phylodynamics) while being discriminated against alternative mechanisms such as mutational tolerance and immunodominance.

Background

Many respiratory viruses - influenza A and B viruses, SARS-CoV-2, respiratory syncytial virus (RSV), seasonal coronaviruses - reinfect people repeatedly, whereas systemic viruses such as measles induce lifelong immunity and show almost no antigenic change. Antigenic drift is the stepwise accumulation of mutations in viral surface proteins (for influenza, chiefly the hemagglutinin protein, the main target of neutralizing antibodies) that allow the virus to evade previously acquired antibody immunity; antigenic cartography - the mapping of viruses into a two-dimensional antigenic space using antibody measurements - showed that influenza A(H3N2) evolves as a succession of antigenically distinct clusters that emerge and replace one another (Smith et al. 2004). Phylodynamics is the study of how epidemic dynamics and pathogen evolutionary dynamics shape each other, visible in phylogenetic trees; influenza A(H3N2)'s tree is characteristically ladder-like, with one trunk lineage persisting as side branches die out, a pattern Koelle et al. (2006) modeled as "epochal" evolution driven by rare selectively favored antigenic mutations, and Grenfell et al. (2004) unified with epidemiology in general terms. What selects for antigenic change in mucosal respiratory viruses but not in systemic ones has remained contested: candidate mechanisms include mutational tolerance (many antibody-contact positions can mutate with only small functional cost, as measured for influenza hemagglutinin by Thyagarajan and Bloom 2014) and immunodominance (the immune response concentrating on few epitopes that are then easy to escape by single mutations). Bull, Koelle, and Antia (2025) proposed a different, population-level driver: waning immunity. In their ordinary-differential-equation model, hosts recovered from a wild-type virus move from full immunity through partial immunity (rates γ1\gamma_1, γ2\gamma_2) back to susceptibility; a partially immune host is protected against the wild-type virus but can be infected by an antigenically different escape variant. An invasion analysis - asking whether a mutant, introduced at the wild-type endemic equilibrium, grows - shows that when partially immune hosts are abundant enough, the escape variant invades even though it pays a transmission fitness cost cc and cannot infect fully immune hosts. They argue this explains both why respiratory (and other mucosal, non-systemic) viruses undergo antigenic evolution while systemic viruses do not, and why antigenic variants emerge and replace one another. The published analysis is deliberately minimal, and the authors state its limits explicitly: the quantitative parameters governing waning of immunity in the respiratory tract and the fitness costs of immune escape are poorly known; the model has a single class of partial immunity rather than gradual waning, and ignores recall responses (the reactivation of memory immunity on re-exposure), which requires quantitative measures of immune efficacy separating susceptibility to infection from onward transmission; only the initial invasion of one escape variant is analyzed, so the model cannot predict the timescale of antigenic evolution or the long-run outcome of successive replacement versus diversification, and compatibility with observed antigenic drift and phylodynamic patterns is untested; and the waning mechanism has not been quantitatively compared with alternatives such as mutational tolerance or immunodominance. Several adjacent frameworks exist but do not answer the question: Park et al. (2024) built a general pathogen invasion theory for strain co-circulation and replacement; Nielsen et al. (2025) derived an analytic stochastic framework for the risk and timing of emergence of a single immune-escape variant (a population-level "phylodynamic curve"); Barrat-Charlaix and Neher (2024) modeled escape-variant growth in a dynamic, immunologically diverse host population with waning immunity, explaining quasi-neutral trajectories of high-frequency influenza variants; and Figgins and Bedford (2026) connected SARS-CoV-2 variant frequency dynamics to transmissibility and immune escape for forecasting. None of these implements the waning-immunity escape mechanism with gradual waning and compensatory evolution and tests it against long-term antigenic drift data across respiratory viruses.

Problem Statement

Determine whether waning immunity, as the driver of immune-escape variant invasion established by Bull, Koelle, and Antia for respiratory viruses, can account for the observed long-term antigenic evolution of these viruses once the analysis is extended beyond the initial invasion of a single escape variant. Concretely: (1) extend the waning-immunity transmission model from a single class of partial immunity to gradual waning and immune recall responses, distinguishing immune efficacy against susceptibility to infection from efficacy against onward transmission, and characterize when the mechanism generates successive emergence and replacement of antigenic variants (with compensatory mutations mitigating the fitness costs of escape) rather than antigenic diversification or stasis, and on what timescale; (2) ground the waning rates (particularly for the respiratory tract) and escape fitness costs in empirical measurements; and (3) test the resulting model quantitatively against observed long-term patterns - antigenic-cluster replacement, ladder-like phylogenies, and phylodynamics - for major respiratory viruses such as influenza A(H3N2), SARS-CoV-2, and RSV, comparing the waning-immunity mechanism against alternatives such as mutational tolerance and immunodominance. These components serve one overarching objective: a quantitatively validated, mechanistic account of whether and how waning immunity drives the long-term antigenic drift of respiratory viruses. The three components above are jointly required. An answer may take the form of a model-and-data demonstration, an analytic characterization of the long-term dynamics, or a rigorous demonstration that the mechanism cannot reproduce the observed patterns under empirically admissible parameters; each form must still address all three components.

References

  1. Bull JJ, Koelle K, Antia R (2025) Waning immunity drives respiratory virus evolution and reinfection. Evolution, Medicine, and Public Health 13(1):101–110. DOI: 10.1093/emph/eoaf002. https://doi.org/10.1093/emph/eoaf002 (preprint bioRxiv 2024.07.23.604867, DOI: 10.1101/2024.07.23.604867)
  2. Park SW, Cobey S, Metcalf CJE, Levine JM, Grenfell BT (2024) Predicting pathogen mutual invasibility and co-circulation. Science 386:175–179. DOI: 10.1126/science.adq0072. https://doi.org/10.1126/science.adq0072
  3. Nielsen BF, Saad-Roy CM, Metcalf CJE, Viboud C, Grenfell BT (2025) Eco-evolutionary dynamics of pathogen immune-escape: deriving a population-level phylodynamic curve. Journal of the Royal Society Interface 22(225):20240675. DOI: 10.1098/rsif.2024.0675. https://doi.org/10.1098/rsif.2024.0675
  4. Barrat-Charlaix P, Neher RA (2024) Eco-evolutionary dynamics of adapting pathogens and host immunity. eLife 13:RP97350. DOI: 10.7554/eLife.97350. https://doi.org/10.7554/eLife.97350
  5. Saha A, Ahmed H, Hirst C, Koelle K, Handel A, Teunis P, Antia R (2025) Quantifying the waning of humoral immunity. Immunity 58(12):3144–3152. DOI: 10.1016/j.immuni.2025.11.007. https://doi.org/10.1016/j.immuni.2025.11.007
  6. Maurer DP, Vu M, Schmidt AG (2025) Antigenic drift expands influenza viral escape pathways from recalled humoral immunity. Immunity 58(3):716–727. DOI: 10.1016/j.immuni.2025.02.006. https://doi.org/10.1016/j.immuni.2025.02.006
  7. Perofsky AC, Huddleston J, Hansen CL, Barnes JR, Rowe T, Xu X, Kondor R, Wentworth DE, Lewis N, Whittaker L, Ermetal B, Harvey R, Galiano M, Daniels RS, McCauley JW, Fujisaki S, Nakamura K, Kishida N, Watanabe S, Hasegawa H, Sullivan SG, Barr IG, Subbarao K, Krammer F, Bedford T, Viboud C (2024) Antigenic drift and subtype interference shape A(H3N2) epidemic dynamics in the United States. eLife 13:RP91849. DOI: 10.7554/eLife.91849. https://doi.org/10.7554/eLife.91849
  8. Figgins MD, Bedford T (2026) Frequency dynamics predict viral fitness, antigenic relationships and epidemic growth. eLife. DOI: 10.7554/eLife.111948. https://doi.org/10.7554/eLife.111948
  9. Gutierrez MA, Page CK, Tompkins SM, Rohani P (2026) Strain coexistence and competition for pathogens with asymmetric cross-immunity and waning immunity. bioRxiv preprint. DOI: 10.64898/2026.08.03.26359614. https://doi.org/10.64898/2026.08.03.26359614
  10. Good MR, Lemus-Reyes JI, Guthmiller JJ (2026) Influenza virus antigenic drift: balancing fitness and immune evasion. Annual Review of Virology. DOI: 10.1146/annurev-virology-100424-103728. https://doi.org/10.1146/annurev-virology-100424-103728
  11. Rubin IN, Bushman M, Lipsitch M, Hanage WP (2026) Seasonal forcing and waning immunity drive the sub-annual periodicity of the COVID-19 epidemic. PLOS Pathogens 22(4):e1014169. DOI: 10.1371/journal.ppat.1014169. https://doi.org/10.1371/journal.ppat.1014169
  12. Koelle K, Cobey S, Grenfell B, Pascual M (2006) Epochal evolution shapes the phylodynamics of interpandemic influenza A (H3N2) in humans. Science 314:1898–1903. DOI: 10.1126/science.1132745. https://doi.org/10.1126/science.1132745
  13. Smith DJ, Lapedes AS, de Jong JC, Bestebroer TM, Rimmelzwaan GF, Osterhaus ADME, Fouchier RAM (2004) Mapping the antigenic and genetic evolution of influenza virus. Science 305:371–376. DOI: 10.1126/science.1097211. https://doi.org/10.1126/science.1097211
  14. Grenfell BT, Pybus OG, Gog JR, Wood JLN, Daly JM, Mumford JA, Holmes EC (2004) Unifying the epidemiological and evolutionary dynamics of pathogens. Science 303:327–332. DOI: 10.1126/science.1090727. https://doi.org/10.1126/science.1090727
  15. Thyagarajan B, Bloom JD (2014) The inherent mutational tolerance and antigenic evolvability of influenza hemagglutinin. eLife 3:e03300. DOI: 10.7554/eLife.03300. https://doi.org/10.7554/eLife.03300