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When to boost: How dose timing determines the epidemic threshold

Alessandro Celestini1, Francesca Colaiori2,3,*, Stefano Guarino1, Enrico Mastrostefano1, Francesca Pelusi4, and Lena Rebecca Zastrow5

  • 1CNR, Institute for Applied Mathematics, Rome, Italy
  • 2CNR, Institute for Complex Systems, Rome, Italy
  • 3Department of Physics, Sapienza University, Rome, Italy
  • 4CNR, Institute for Applied Mathematics, Naples, Italy
  • 5ISPRA, Department of the Geological Survey of Italy, Rome, Italy

  • *Contact author: francesca.colaiori@cnr.it

Phys. Rev. Research 7, 033125 – Published 6 August, 2025

DOI: https://doi.org/10.1103/cykd-2rjn

Abstract

Most vaccines require multiple doses, the first to induce recognition and antibody production and subsequent doses to boost the primary response and achieve optimal protection. We show that properly prioritizing the administration of first and second doses can shift the epidemic threshold, separating the disease-free from the endemic state and potentially preventing widespread outbreaks. Assuming homogeneous mixing, we prove that at a low vaccination rate, the best strategy is to give absolute priority to first doses. In contrast, for high vaccination rates, we propose a scheduling that outperforms a first-come first-served approach. We identify the threshold that separates these two scenarios and derive the optimal prioritization scheme and interdose interval. Agent-based simulations on real and synthetic contact networks validate our findings. We provide specific guidelines for effective resource allocation, showing that adjusting the timing between the primer and booster significantly impacts epidemic outcomes and can determine whether the disease persists or disappears.

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References (41)

  1. WHO, Interim recommendations for use of the Moderna mRNA-1273 vaccine against COVID-19, https://www.who.int/publications/i/item/WHO-2019-nCoV-vaccines-SAGE-recommendation-mRNA-1273-2021.3 (2021).
  2. WHO, Interim recommendations for use of the PfizerBioNTech COVID-19 vaccine, BNT162b2, under Emergency Use Listing, https://www.who.int/publications/i/item/WHO-2019-nCoV-vaccines-SAGE_recommendation-BNT162b2-2021.1 (2021).
  3. JCVI statement, Optimising the COVID-19 vaccination programme for maximum short-term impact, https://www.gov.uk/government/publications/prioritising-the-first-covid-19-vaccine-dose-jcvi-statement/optimising-the-covid-19-vaccination-programme-for-maximum-short-term-impact#:∼:text=The%20committee%20supports%20a%202,12%20weeks%20for%20both%20vaccines (2021).
  4. M. Voysey, S. A. Costa Clemens, S. A. Madhi, L. Y. Weckx, P. M. Folegatti, P. K. Aley, B. Angus, V. L. Baillie, S. L. Barnabas, Q. E. Bhorat et al., Single-dose administration and the influence of the timing of the booster dose on immunogenicity and efficacy of ChAdOx1 nCoV-19 (AZD1222) vaccine: A pooled analysis of four randomised trials, The Lancet 397, 881 (2021).
  5. S. R. Kadire, R. M. Wachter, and N. Lurie, Delayed second dose versus standard regimen for COVID-19 vaccination, N. Engl. J. Med. 384, e28 (2021).
  6. M. Halloran, M. Haber, I. M. Longini, and C. J. Struchiner, Direct and indirect effects in vaccine efficacy and effectiveness, Am. J. Epidemiol. 133, 323 (1991).
  7. Z. Wang, C. T. Bauch, S. Bhattacharyya, A. d'Onofrio, P. Manfredi, M. Perc, N. Perra, M. Salathé, and D. Zhao, Statistical physics of vaccination, Phys. Rep. 664, 1 (2016).
  8. J. Wallinga, M. Van Boven, and M. Lipsitch, Optimizing infectious disease interventions during an emerging epidemic, Proc. Natl. Acad. Sci. USA 107, 923 (2010).
  9. N. Perra, Non-pharmaceutical interventions during the COVID-19 pandemic: A review, Phys. Rep. 913, 1 (2021).
  10. R. Balderrama, J. Peressutti, J. P. Pinasco, F. Vazquez, and C. S. D. L. Vega, Optimal control for a SIR epidemic model with limited quarantine, Sci. Rep. 12, 12583 (2022).
  11. R. Pastor-Satorras and C. Castellano, The advantage of self-protecting interventions in mitigating epidemic circulation at the community level, Sci. Rep. 12, 15950 (2022).
  12. J. A. Moreno López, D. Mateo, A. Hernando, S. Meloni, and J. J. Ramasco, Critical mobility in policy making for epidemic containment, Sci. Rep. 15, 3055 (2025).
  13. P. Castioni, S. Gómez, C. Granell, and A. Arenas, Rebound in epidemic control: How misaligned vaccination timing amplifies infection peaks, npj Complexity 1, 20 (2024).
  14. J. Medlock and A. P. Galvani, Optimizing influenza vaccine distribution, Science 325, 1705 (2009).
  15. G. Pontrelli, G. Cimini, M. Roversi, A. Gabrielli, G. Salina, S. Bernardi, F. Rocchi, A. Simonetti, C. Giaquinto, P. Rossi, and F. S. Labini, Prioritizing the first doses of SARS-CoV-2 vaccine to save the elderly: The case study of Italy, Front. Public Health 9, 684760 (2021).
  16. N. Gozzi, M. Chinazzi, J. T. Davis, K. Mu, A. Pastore Y Piontti, M. Ajelli, N. Perra, and A. Vespignani, Anatomy of the first six months of COVID-19 vaccination campaign in Italy, PLoS Comput. Biol. 18, e1010146 (2022).
  17. J. Wei, P. C. Matthews, N. Stoesser, I. Diamond, R. Studley, E. Rourke, D. Cook, J. I. Bell, J. N. Newton, J. Farrar et al., SARS-CoV-2 antibody trajectories after a single COVID-19 vaccination with and without prior infection, Nat. Commun. 13, 3748 (2022).
  18. Y. Goldberg, M. Mandel, Y. M. Bar-On, O. Bodenheimer, L. S. Freedman, N. Ash, S. Alroy-Preis, A. Huppert, and R. Milo, Protection and waning of natural and hybrid immunity to SARS-CoV-2, N. Engl. J. Med. 386, 2201 (2022).
  19. V. Hall, S. Foulkes, F. Insalata, P. Kirwan, A. Saei, A. Atti, E. Wellington, J. Khawam, K. Munro, M. Cole et al., Protection against SARS-CoV-2 after Covid-19 vaccination and previous infection, N. Engl. J. Med. 386, 1207 (2022).
  20. T. Cerqueira-Silva et al., Effectiveness of CoronaVac, ChAdOx1 nCoV-19, BNT162b2, and Ad26.COV2.S among individuals with previous SARS-CoV-2 infection in Brazil: A test-negative, case-control study, Lancet Infect. Dis. 22, 791 (2022).
  21. R. Pastor-Satorras and A. Vespignani, Immunization of complex networks, Phys. Rev. E 65, 036104 (2002).
  22. N. Gozzi, M. Chinazzi, N. E. Dean, I. M. Longini, Jr., M. E. Halloran, N. Perra, and A. Vespignani, Estimating the impact of COVID-19 vaccine inequities: A modeling study, Nat. Commun. 14, 3272 (2023).
  23. P. Klepac, R. Laxminarayan, and B. T. Grenfell, Synthesizing epidemiological and economic optima for control of immunizing infections, Proc. Natl. Acad. Sci. USA 108, 14366 (2011).
  24. S. M. Moghadas, T. N. Vilches, K. Zhang, S. Nourbakhsh, P. Sah, M. C. Fitzpatrick, and A. P. Galvani, Evaluation of COVID-19 vaccination strategies with a delayed second dose, PLoS Biol. 19, e3001211 (2021).
  25. L. Souto Ferreira, O. Canton, R. L. P. Da Silva, S. Poloni, V. Sudbrack, M. E. Borges, C. Franco, F. M. D. Marquitti, J. C. De Moraes, M. A. D. S. M. Veras, R. A. Kraenkel, and R. M. Coutinho, Assessing the best time interval between doses in a two-dose vaccination regimen to reduce the number of deaths in an ongoing epidemic of SARS-CoV-2, PLoS Comput. Biol. 18, e1009978 (2022).
  26. Z. Wang, G. Röst, and S. M. Moghadas, Deviation from the recommended schedule: Optimal dosing interval for a two-dose vaccination programme, R. Soc. Open Sci. 11, 231971 (2024).
  27. P. Castioni and A. Arenas, Network-driven vaccination strategies for preventing rebound dynamics in metapopulation epidemic control, Phys. Rev. E 111, 064315 (2025).
  28. C. M. Saad-Roy, S. E. Morris, C. J. E. Metcalf, M. J. Mina, R. E. Baker, J. Farrar, E. C. Holmes, O. G. Pybus, A. L. Graham, S. A. Levin, B. T. Grenfell, and C. E. Wagner, Epidemiological and evolutionary considerations of SARS-CoV-2 vaccine dosing regimes, Science 372, 363 (2021).
  29. N. Imai, T. Rawson, E. S. Knock, R. Sonabend, Y. Elmaci, P. N. Perez-Guzman, L. K. Whittles, D. T. Kanapram, K. A. M. Gaythorpe, W. Hinsley et al., Quantifying the effect of delaying the second COVID-19 vaccine dose in England: a mathematical modelling study, Lancet Public Health 8, e174 (2023).
  30. See Supplemental Material at http://link.aps.org/supplemental/10.1103/cykd-2rjn for details about the nature of the phase transition, stability in the endemic phase, and properties of the networks numerical simulations.
  31. E. N. Gilbert, Random graphs, Ann. Math. Stat. 30, 1141 (1959).
  32. I. Z. Kiss, J. C. Miller, and P. L. Simon, Mathematics of epidemics on networks, Cham: Springer 598, 31 (2017).
  33. J. C. Miller and T. Ting, Eon (epidemics on networks): A fast, flexible python package for simulation, analytic approximation, and analysis of epidemics on networks, J. Open Source Software 4, 1731 (2019).
  34. J. Leskovec and A. Krevl, SNAP Datasets: Stanford large network dataset collection, http://snap.stanford.edu/data (2014).
  35. B. Klimt and Y. Yang, Introducing the enron corpus, in CEAS, Vol. 4 (2004), p. 1, https://www.ceas.cc/papers-2004/168.pdf.
  36. M. Á. Serrano, D. Krioukov, and M. Boguná, Self-similarity of complex networks and hidden metric spaces, Phys. Rev. Lett. 100, 078701 (2008).
  37. R. S. Sander, G. S. Costa, and S. C. Ferreira, Sampling methods for the quasistationary regime of epidemic processes on regular and complex networks, Phys. Rev. E 94, 042308 (2016).
  38. G. S. Costa and S. C. Ferreira, Simple quasistationary method for simulations of epidemic processes with localized states, Comput. Phys. Commun. 267, 108046 (2021).
  39. P. Shu, W. Wang, M. Tang, and Y. Do, Numerical identification of epidemic thresholds for susceptible-infected-recovered model on finite-size networks, Chaos 25, 063104 (2015).
  40. C. M. Buckner, L. Kardava, O. El Merhebi, S. R. Narpala, L. Serebryannyy, B. C. Lin, W. Wang, X. Zhang, F. Lopes de Assis, S. E. M. Kelly et al., Interval between prior SARS-CoV-2 infection and booster vaccination impacts magnitude and quality of antibody and b cell responses, Cell 185, 4333 (2022).
  41. A. Celestini, F. Colaiori, S. Guarino, E. Mastrostefano, F. Pelusi, and L. R. Zastrow, When to boost: How dose timing determines the epidemic threshold (V.0), Zenodo (2025), https://doi.org/10.5281/zenodo.15657089.

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