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Prioritizing COVID-19 vaccination. Part 1: Final size comparison between a single dose and double dose

  • Received: 05 April 2022 Revised: 09 May 2022 Accepted: 16 May 2022 Published: 19 May 2022
  • In response to the coronavirus disease 2019 (COVID-19) pandemic, Japan conducted mass vaccination. Seventy-two million doses of vaccine (i.e., for 36 million people if a double dose is planned per person) were obtained, with initial vaccination of the older population (≡ 65 years). Because of the limited number of vaccines, the government discussed shifting the plan to administering only a single dose so that younger individuals (<65 years) could also be vaccinated with one shot. This study aimed to determine the optimal vaccine distribution strategy using a simple mathematical method. After accounting for age-dependent relative susceptibility after single- and double-dose vaccination (vs and vd, respectively, compared with unvaccinated), we used the age-dependent transmission model to compute the final size for various patterns of vaccine distributions. Depending on the values of vs, the cumulative risk of death would be lower if all 72 million doses were used as a double dose for older people than if a single-dose program was conducted in which half is administered to older people and the other half is administered to adults (i.e., 1,856,000 deaths in the former program and 1,833,000-2,355,000 deaths [depending on the values of vs] in the latter). Even if 90% of older people were vaccinated twice and 100% of adults were vaccinated once, the effective reproduction number would be reduced from 2.50 to1.14. Additionally, the cumulative risk of infection would range from 12.0% to 54.6% and there would be 421,000-1,588,000deaths (depending on the values of vs). If an epidemic appears only after completing vaccination, vaccination coverage using a single-dose program with widespread vaccination among adults will not outperform a double-dose strategy.

    Citation: Tetsuro Kobayashi, Hiroshi Nishiura. Prioritizing COVID-19 vaccination. Part 1: Final size comparison between a single dose and double dose[J]. Mathematical Biosciences and Engineering, 2022, 19(7): 7374-7387. doi: 10.3934/mbe.2022348

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  • In response to the coronavirus disease 2019 (COVID-19) pandemic, Japan conducted mass vaccination. Seventy-two million doses of vaccine (i.e., for 36 million people if a double dose is planned per person) were obtained, with initial vaccination of the older population (≡ 65 years). Because of the limited number of vaccines, the government discussed shifting the plan to administering only a single dose so that younger individuals (<65 years) could also be vaccinated with one shot. This study aimed to determine the optimal vaccine distribution strategy using a simple mathematical method. After accounting for age-dependent relative susceptibility after single- and double-dose vaccination (vs and vd, respectively, compared with unvaccinated), we used the age-dependent transmission model to compute the final size for various patterns of vaccine distributions. Depending on the values of vs, the cumulative risk of death would be lower if all 72 million doses were used as a double dose for older people than if a single-dose program was conducted in which half is administered to older people and the other half is administered to adults (i.e., 1,856,000 deaths in the former program and 1,833,000-2,355,000 deaths [depending on the values of vs] in the latter). Even if 90% of older people were vaccinated twice and 100% of adults were vaccinated once, the effective reproduction number would be reduced from 2.50 to1.14. Additionally, the cumulative risk of infection would range from 12.0% to 54.6% and there would be 421,000-1,588,000deaths (depending on the values of vs). If an epidemic appears only after completing vaccination, vaccination coverage using a single-dose program with widespread vaccination among adults will not outperform a double-dose strategy.



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    [1] K. L. Prem, Y. Liu, T. W. Russell, A. J. Kucharski, R. M. Eggo, N. Davies, et.al., The effect of control strategies to reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China: A modelling study, Lancet Public Health, 5 (2020), e261–e270. https://doi.org/10.1016/S2468-2667(20)30073-6 doi: 10.1016/S2468-2667(20)30073-6
    [2] B. L. Dickens, J. R. Koo, J. T. Lim, M. Park, S. Quaye, H. Sun, et. al., Modelling lockdown and exit strategies for COVID-19 in Singapore, Lancet Regional Health – Western Pacific, 1 (2020) 100004. https://doi.org/10.1016/j.lanwpc.2020.100004 doi: 10.1016/j.lanwpc.2020.100004
    [3] E. Mahase, Covid-19: Novavax vaccine efficacy is 86% against UK variant and 60% against South African variant, BMJ, 372 (2021), n296. https://doi.org/10.1136/bmj.n296 doi: 10.1136/bmj.n296
    [4] G. Persad, M. E. Peek, E. J. Emanuel, Fairly prioritizing groups for access to COVID-19 vaccines, JAMA, 324 (2020), 1601–1602. https://doi.org/10.1001/jama.2020.18513 doi: 10.1001/jama.2020.18513
    [5] K. Liu, Y. Lou, Optimizing COVID-19 vaccination programs during vaccine shortages, Infect Dis. Model, 7 (2022), 286–298. https://doi.org/10.1016/j.idm.2022.02.002 doi: 10.1016/j.idm.2022.02.002
    [6] P. C. Jentsch, M. Anand, C. T. Bauch, Prioritising COVID-19 vaccination in changing social and epidemiological landscapes: A mathematical modelling study, Lancet Infect. Dis., 3099 (2021), 00057-8. https://doi.org/10.1016/S1473-3099(21)00057-8 doi: 10.1016/S1473-3099(21)00057-8
    [7] G. Persad, E. J. Emanuel, S. Sangenito, A. Glickman, S. Phillips, E. A. Largent, Public perspectives on COVID-19 vaccine prioritization, JAMA Netw. Open, 4 (2021), e217943. https://doi.org/10.1001/jamanetworkopen.2021.7943 doi: 10.1001/jamanetworkopen.2021.7943
    [8] E. Rumpler, M. J. Feldman, M. T. Bassett, M. Lipsitch, Equitable COVID-19 vaccine prioritization: Front-line workers or 65–74 year olds?, preprint, medRxiv, no. 2022.02.03.22270414. https://doi.org/10.1101/2022.02.03.22270414
    [9] L. A. C. Chapman, P. Shukla, I. Rodríguez-Barraquer, P. B. Shete, T. M. León, K. Bibbins-Domingo, et al., Risk factor targeting for vaccine prioritization during the COVID-19 pandemic, Sci. Rep., 12 (2022), 3055. https://doi.org/10.1038/s41598-022-06971-5 doi: 10.1038/s41598-022-06971-5
    [10] S. Epstein, K. Ayers, B. K. Swenor, COVID-19 vaccine prioritisation for people with disabilities, Lancet Public Health, 6 (2021), e361. https://doi.org/10.1016/S2468-2667(21)00093-1 doi: 10.1016/S2468-2667(21)00093-1
    [11] S. Han, J. Cai, J. Yang, J. Zhang, Q. Wu, W. Zheng, et al., Time-varying optimization of COVID-19 vaccine prioritization in the context of limited vaccination capacity, Nat. Commun., 12 (2021), 4673. https://doi.org/10.1038/s41467-021-24872-5 doi: 10.1038/s41467-021-24872-5
    [12] E. K. Lee, Z. L. Li, Y. K. Liu, J. LeDuc, Strategies for vaccine prioritization and mass dispensing, Vaccines (Basel), 9 (2021), 506. https://doi.org/10.3390/vaccines9050506 doi: 10.3390/vaccines9050506
    [13] H. Tatapudi, R. Das, T. K. Das, Impact of vaccine prioritization strategies on mitigating COVID-19: An agent-based simulation study using an urban region in the United States, BMC Med. Res. Methodol., 21 (2021), 272. https://doi.org/10.1186/s12874-021-01458-9 doi: 10.1186/s12874-021-01458-9
    [14] R. Strodel, L. Dayton, H. M. Garrison-Desany, G. Eber, C. Beyrer, J. Arscott, et al., COVID-19 vaccine prioritization of incarcerated people relative to other vulnerable groups: An analysis of state plans, PLoS One, 16 (2021), e0253208. https://doi.org/10.1371/journal.pone.0253208 doi: 10.1371/journal.pone.0253208
    [15] K. M. Bubar, K. Reinholt, S. M. Kissler, M. Lipsitch, S. Cobey, Y. H. Grad, et al., Model-informed COVID-19 vaccine prioritization strategies by age and serostatus, Science, 371 (2021), 916–921. https://doi.org/10.1126/science.abe6959 doi: 10.1126/science.abe6959
    [16] J. H. Buckner, G. Chowell, M. R. Springborn, Dynamic prioritization of COVID-19 vaccines when social distancing is limited for essential workers, Proc. Natl. Acad. Sci. U. S. A., 118 (2021), e2025786118. https://doi.org/10.1073/pnas.2025786118 doi: 10.1073/pnas.2025786118
    [17] H. Nishiura, K. Iwata, A simple mathematical approach to deciding the dosage of vaccine against pandemic H1N1 influenza, Euro. Surveill., 14 (2009), 1–5. https://doi.org/10.2807/ese.14.45.19396-en doi: 10.2807/ese.14.45.19396-en
    [18] M. A. Billah, M. M. Miah, M. N. Khan, Reproductive number of coronavirus: A systematic review and meta-analysis based on global level evidence, PLoS One, 15 (2020), e0242128. https://doi.org/10.1371/journal.pone.0242128 doi: 10.1371/journal.pone.0242128
    [19] A. T. Levin, W. P. Hanage, N. Owusu-Boaitey, K. B. Cochran, S. P. Walsh, G. Meyerowitz-Katz, Assessing the age specificity of infection fatality rates for COVID-19: Systematic review, meta-analysis, and public policy implications, Eur. J. Epidemiol., 35 (2020), 1123–1138. https://doi.org/10.1007/s10654-020-00698-1 doi: 10.1007/s10654-020-00698-1
    [20] L. Munasinghe, Y. Asai, H. Nishiura, Quantifying heterogeneous contact patterns in Japan: A social contact survey, Theor. Biol. Med. Model., 16 (2019), 6. https://doi.org/10.1186/s12976-019-0102-8 doi: 10.1186/s12976-019-0102-8
    [21] E. Mahase, Covid-19: Reports from Israel suggest one dose of Pfizer vaccine could be less effective than expected, BMJ, 372 (2021), n217. https://doi.org/10.1136/bmj.n217 doi: 10.1136/bmj.n217
    [22] H. Nishiura, Tracking Public Health and Social Measures, in World Health Organization, 2021, work in progress.
    [23] N. Dagan, N. Barda, E. Kepten, O. Miron, S. Perchik, M. A. Katz, et al., BNT162b2 mRNA Covid-19 vaccine in a nationwide mass vaccination setting, N. Engl. J. Med., 384 (2021), 1412–1423. https://doi.org/10.1056/NEJMoa2101765 doi: 10.1056/NEJMoa2101765
    [24] S. J. B. Hanley, E. Yoshioka, Y. Ito, R. Kishi, HPV vaccination crisis in Japan, Lancet, 385 (2015), 2571. https://doi.org/10.1016/S0140-6736(15)61152-7 doi: 10.1016/S0140-6736(15)61152-7
    [25] S. Moore, E. M. Hill, M. J. Tildesley, L. Dyson, M. J. Keeling, Vaccination and non-pharmaceutical interventions for COVID-19: A mathematical modelling study, Lancet Infect. Dis., 3099 (2021), 793–802. https://doi.org/10.1016/S1473-3099(21)00143-2 doi: 10.1016/S1473-3099(21)00143-2
    [26] J. Wise, Covid-19: The E484K mutation and the risks it poses, BMJ, 372 (2021), n359. https://doi.org/10.1136/bmj.n359 doi: 10.1136/bmj.n359
    [27] T. Burki, Understanding variants of SARS-CoV-2, Lancet, 397 (2021), 462. https://doi.org/10.1016/S0140-6736(21)00298-1 doi: 10.1016/S0140-6736(21)00298-1
    [28] D. A. Collier, A. De Marco, I. A. T. M. Ferreira, B. Meng, R. Datir, A. C. Walls, et. al., Sensitivity of SARS-CoV-2 B.1.1.7 to mRNA vaccine-elicited antibodies, Nature, 593 (2021), 136–141. https://doi.org/10.1038/s41586-021-03412-7 doi: 10.1038/s41586-021-03412-7
    [29] D. Planas, T. Bruel, L. Grzelak, F. Guivel-Benhassine, I. Staropoli, F. Porrot, et al., Sensitivity of infectious SARS-CoV-2 B.1.1.7 and B.1.351 variants to neutralizing antibodies, Nat. Med., 27 (2021), 917–924. https://doi.org/10.1038/s41591-021-01318-5 doi: 10.1038/s41591-021-01318-5
    [30] A. Muik, A. K. Wallisch, B. Sänger, K. A. Swanson, J. Mühl, W. Chen, et al., Neutralization of SARS-CoV-2 lineage B.1.1.7 pseudovirus by BNT162b2 vaccine–elicited human sera, Science, 371 (2021), 1152–1153. https://doi.org/10.1126/science.abg6105 doi: 10.1126/science.abg6105
    [31] P. Wang, M. S. Nair, L. Liu, S. Iketani, Y. Luo, Y. Guo, et al., Antibody Resistance of SARS-CoV-2 Variants B.1.351 and B.1.1.7, Nature, 593 (2021), 130–135. https://doi.org/10.1038/s41586-021-03398-2 doi: 10.1038/s41586-021-03398-2
    [32] D. Zhou, W. Dejnirattisai, P. Supasa, C. Liu, A. J. Mentzer, H. M. Ginn, et al., Evidence of escape of SARS-CoV-2 variant B.1.351 from natural and vaccine-induced sera, Cell, 184 (2021), 2348–2361. https://doi.org/10.1016/j.cell.2021.02.037 doi: 10.1016/j.cell.2021.02.037
    [33] K. Leung, M. Jit, G. M. Leung, J. T. Wu, The allocation of COVID-19 vaccines and antivirals against emerging SARS-CoV-2 variants of concern in East Asia and Pacific region: A modelling study, Lancet Regional Health – Western Pacific, 21 (2022), 100389. https://doi.org/10.1016/j.lanwpc.2022.100389 doi: 10.1016/j.lanwpc.2022.100389
    [34] C. C. John, V. Ponnusamy, S. K. Chandrasekaran, R. Nandakumar, A survey on mathematical, machine learning and deep learning models for COVID-19 transmission and diagnosis, IEEE Rev. Biomed. Eng., 15 (2022), 325–340. https://doi.org/10.1109/RBME.2021.3069213 doi: 10.1109/RBME.2021.3069213
    [35] S. M. Saadat, Z. R. Tehrani, J. Logue, M. Newman, M. B. Frieman, A. D. Harris, et al., Binding and neutralization antibody titers after a single vaccine dose in health care workers previously infected with SARS-CoV-2, JAMA, 325 (2021), 1467–1469. https://doi.org/10.1001/jama.2021.3341 doi: 10.1001/jama.2021.3341
    [36] COVID-19 Dashboard, the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University, 2021. Available From: https://gisanddata.maps.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6 (accessed Mar. 30, 2021).
    [37] COVID-19 Advisory Board, Ministry of Health, Labor and Welfare (in Japanese), From https://www.mhlw.go.jp/stf/seisakunitsuite/bunya/0000121431_00216.html (accessed Apr. 30, 2021).
    [38] I. Locatelli, B. Trächsel, V. Rousson, Estimating the basic reproduction number for COVID-19 in Western Europe, PLoS One, 16 (2021), 1–9. https://doi.org/10.1371/journal.pone.0248731 doi: 10.1371/journal.pone.0248731
    [39] Z. Zhuang, S. Zhao, Q. Lin, P. Cao, Y. Lou, L. Yang, et al., Preliminary estimates of the reproduction number of the coronavirus disease (COVID-19) outbreak in Republic of Korea and Italy by 5 March 2020, Int. J. Infect. Dis., 95 (2020), 308–310. https://doi.org/10.1016/j.ijid.2020.04.044 doi: 10.1016/j.ijid.2020.04.044
    [40] M. Al-Raeei, The basic reproduction number of the new coronavirus pandemic with mortality for India, the Syrian Arab Republic, the United States, Yemen, China, France, Nigeria and Russia with different rate of cases, Clin. Epidemiol. Glob. Heal., 9 (2021), 147–149. https://doi.org/10.1016/j.cegh.2020.08.005 doi: 10.1016/j.cegh.2020.08.005
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