Time-dependent vaccine efficacy estimation quantified by a mathematical model (original) (raw)

Abstract

In this paper we calculate the variation of the estimated vaccine efficacy (VE) due to the time-dependent force of infection resulting from the difference between the moment the Clinical Trial (CT) begins and the peak in the outbreak intensity. Using a simple mathematical model we tested the hypothesis that the time difference between the moment the CT begins and the peak in the outbreak intensity determines substantially different values for VE. We exemplify the method with the case of the VE efficacy estimation for one of the vaccines against the new coronavirus SARS-CoV-2.

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References (28)

  1. Scheppler L, De Clercq N, McGoldrick M, Dias J. Regulatory Harmonization and Streamlining of Clinical Trial Applications globally should lead to faster clinical development and earlier access to life-saving vaccines. Vaccine. 2021;.
  2. Bellomo N, Bingham R, Chaplain MA, Dosi G, Forni G, Knopoff DA, et al. A multiscale model of virus pandemic: Heterogeneous interactive entities in a globally connected world. Mathematical Models and Methods in Applied Sciences. 2020; 30(08):1591-1651. https://doi.org/10.1142/s0218202520500323 PMID: 35309741
  3. Bellomo N, Burini D, Dosi G, Gibelli L, Knopoff D, Outada N, et al. What is life? A perspective of the mathematical kinetic theory of active particles. Mathematical Models and Methods in Applied Sciences. 2021; 31(09):1821-1866. https://doi.org/10.1142/S0218202521500408
  4. Delany I, Rappuoli R, De Gregorio E. Vaccines for the 21st century. EMBO molecular medicine. 2014; 6 (6):708-720. https://doi.org/10.1002/emmm.201403876 PMID: 24803000
  5. World Health Organization, Global Immunization Vision and Strategy 2006-2015; 2016.
  6. Orenstein WA, Bernier RH, Dondero TJ, Hinman AR, Marks JS, Bart KJ, et al. Field evaluation of vac- cine efficacy. Bulletin of the World Health Organization. 1985; 63(6):1055. PMID: 3879673
  7. Mao HH, Chao S. Advances in vaccines. Current Applications of Pharmaceutical Biotechnology. 2019; p. 155-188. https://doi.org/10.1007/10\_2019\_107
  8. Garon JR, Orenstein WA. Understanding the host-pathogen interaction saves lives: lessons from vac- cines and vaccinations. Current Opinion in Immunology. 2015; 36:8-13. https://doi.org/10.1016/j.coi. 2015.04.003 PMID: 25974089
  9. Lal H, Cunningham AL, Godeaux O, Chlibek R, Diez-Domingo J, Hwang SJ, et al. Efficacy of an adju- vanted herpes zoster subunit vaccine in older adults. New England Journal of Medicine. 2015; 372 (22):2087-2096. https://doi.org/10.1056/NEJMoa1501184 PMID: 25916341
  10. Malkin EM, Durbin AP, Diemert DJ, Sattabongkot J, Wu Y, Miura K, et al. Phase 1 vaccine trial of Pvs25H: a transmission blocking vaccine for Plasmodium vivax malaria. Vaccine. 2005; 23(24):3131- 3138. https://doi.org/10.1016/j.vaccine.2004.12.019 PMID: 15837212
  11. Villa LL, Costa RL, Petta CA, Andrade RP, Ault KA, Giuliano AR, et al. Prophylactic quadrivalent human papillomavirus (types 6, 11, 16, and 18) L1 virus-like particle vaccine in young women: a randomised double-blind placebo-controlled multicentre phase II efficacy trial. The lancet oncology. 2005; 6(5):271- 278. https://doi.org/10.1016/S1470-2045(05)70101-7 PMID: 15863374
  12. Perrett K, Winter A, Kibwana E, Jin C, John T, Yu L, et al. Antibody persistence after serogroup C meningococcal conjugate immunization of United Kingdom primary-school children in 1999-2000 and response to a booster: a phase 4 clinical trial. Clinical Infectious Diseases. 2010; 50(12):1601-1610. https://doi.org/10.1086/652765 PMID: 20459323
  13. Halloran ME, Struchiner CJ, Longini IM Jr. Study designs for evaluating different efficacy and effective- ness aspects of vaccines. American journal of epidemiology. 1997; 146(10):789-803. https://doi.org/ 10.1093/oxfordjournals.aje.a009196 PMID: 9384199
  14. Halloran ME, Longini IM, Struchiner CJ, Longini IM. Design and analysis of vaccine studies. vol. 18. Springer; 2010.
  15. Kaslow DC. Force of infection: a determinant of vaccine efficacy? NPJ Vaccines. 2021; 6(1):1-7.
  16. Vynnycky E, White R. An introduction to infectious disease modelling. Oxford University Press; 2010.
  17. Massad E, Coutinho F, Burattini M, Amaku M. Estimation of R0 from the initial phase of an outbreak of a vector-borne infection. Tropical Medicine & International Health. 2010; 15(1):120-126. PMID: 19891761
  18. Albani VVL, Velho RM, Zubelli JP. Estimating, Monitoring, and Forecasting the Covid-19 Epidemics: A Spatio-Temporal Approach Applied to NYC Data. Scientific Reports. 2021; p. 9089. https://doi.org/10\. 1038/s41598-021-88281-w PMID: 33907222
  19. Albani VVL, Loria J, Massad E, Zubelli JP. COVID-19 Underreporting and its Impact on Vaccination Strategies. BMC Infectious Diseases. 2021; 21:1111. https://doi.org/10.1186/s12879-021-06780-7 PMID: 34711190
  20. Albani V, Loria J, Massad E, Zubelli JP. The Impact of COVID-19 Vaccination Delay: A Data-Driven Modelling Analysis for Chicago and New York City. Vaccine. 2021; 39(41):6088-6094. https://doi.org/ 10.1016/j.vaccine.2021.08.098 PMID: 34507859
  21. Amaku M, Covas DT, Coutinho FAB, Azevedo RS, Massad E. Modelling the impact of delaying vaccina- tion against SARS-CoV-2 assuming unlimited vaccine supply. Theoretical Biology and Medical Model- ling. 2021; 18(1):1-11. https://doi.org/10.1186/s12976-021-00143-0 PMID: 34325717
  22. Campos EL, Cysne RP, Madureira AL, Mendes GL. Multi-generational SIR modeling: Determination of parameters, epidemiological forecasting and age-dependent vaccination policies. Infectious Disease Modelling. 2021; 6:751-765. https://doi.org/10.1016/j.idm.2021.05.003 PMID: 34127952
  23. Hodgson SH, Mansatta K, Mallett G, Harris V, Emary KR, Pollard AJ. What defines an efficacious COVID-19 vaccine? A review of the challenges assessing the clinical efficacy of vaccines against SARS-CoV-2. The Lancet Infectious Diseases. 2021; 21(2):e26-e35. https://doi.org/10.1016/S1473- 3099(20)30773-8 PMID: 33125914
  24. Blackwelder WC. Sample size and power for prospective analysis of relative risk. Statistics in Medicine. 1993; 12(7):691-698. https://doi.org/10.1002/sim.4780120708 PMID: 8511445
  25. Martcheva M. An introduction to mathematical epidemiology. vol. 61. Springer; 2015.
  26. Struchiner CJ, Halloran ME, Brunet RC, Ribeiro J, Massad E. Malaria vaccines: lessons from field trials. Cadernos de Sau ´de Pu ´blica. 1994; 10:S310-S326. https://doi.org/10.1590/S0102- 311X1994000800009 PMID: 15042221
  27. Struchiner C, Halloran M. Randomization and baseline transmission in vaccine field trials. Epidemiology & Infection. 2007; 135(2):181-194. https://doi.org/10.1017/S0950268806006716 PMID: 17291359
  28. Hay JA, Kennedy-Shaffer L, Kanjilal S, Lennon NJ, Gabriel SB, Lipsitch M, et al. Estimating epidemio- logic dynamics from cross-sectional viral load distributions. Science. 2021; 373(6552):eabh0635. https://doi.org/10.1126/science.abh0635 PMID: 34083451