COVID-19 Vaccine Prioritisation in Japan and South Korea

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Abstract

Background

Due to a limited initial supply of COVID-19 vaccines, the prioritisation of individuals for vaccination is of utmost importance for public health. Here, we provide the optimal allocation strategy for COVID-19 vaccines according to age in Japan and South Korea.

Methods

Combining national case reports, age-specific contact matrices, and observed periods between each stages of infection (Susceptible-Exposed-Infectious-Quarantined), we constructed a compartmental model. We estimated the age-stratified probability of transmission given contact ( q i ) using Bayesian inference method and simulated different vaccination scenarios to reduce either case numbers or death toll. We also performed sensitivity analyses on the proportion of asymptomatic cases and vaccine efficacy.

Findings

The model inferred age-stratified probability of transmission given contact ( q i ) showed similar age-dependent increase in Japan and South Korea. Assuming the reported COVID-19 vaccine efficacy, our results indicate that Japan and South Korea need to prioritise individuals aged 20–35 years and individuals aged over 60 years, respectively, to minimise case numbers. To minimise the death toll, both countries need to prioritise individuals aged over 75 years. These trends were not changed by proportions of asymptomatic cases and varying vaccine efficacy on individuals under 20 years.

Interpretation

We presented the optimal vaccination strategy for Japan and South Korea. Comparing the results of these countries demonstrates that not only the effective contact rates containing q i but also the age-demographics of current epidemic in Japan (dominance in 20s) and South Korea (dominant cases over 50s) affect vaccine allocation strategy.

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  1. SciScore for 10.1101/2021.04.16.21255649: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    18,19 To capture the changes of contact patterns as a result of social distancing measures, we took into account school closure policies and reduced contact rates at both work and other places using Google mobility data.20-22 In Japan, most schools that had been temporarily closed reopened on June 1, 2020, whereas in South Korea, school attendance has been capped at two-thirds during national distancing level 1, one-thirds during level 2 (except for high schools which remained 2/3), and remote learning only during level 3 throughout 2020 (Figure 1).
    Google
    suggested: (Google, RRID:SCR_017097)

    Results from OddPub: Thank you for sharing your code and data.


    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Moreover, there is a caveat to interpret the qi results, since it could be affected by contact numbers, ϕij. Japan showed much lower qi values for individuals aged below 10 years than South Korea, and we assumed that the different school closure policies could explain the discrepancy; contrary to Japan, South Korea maintained restrictions on the number of students in school and the qi might have decreased as low as Japan if it had not regulated school attendance. In addition, previous studies suggested that older age might contribute to vulnerability to COVID-19 infection, it is possible that biological aspects also affect the value of qi then further investigation would be desirable in this area.30 There are several limitations to this study. First, although the contact matrix is the most important variable in this model, we do not have empirical data for the current mixing patterns. We tried to modify the existing prepandemic contact matrix to make it as realistic as possible, but it might be insufficient to reflect reality. Besides, in the existing Japanese contact matrix, the 20–29 year age group is marginally under-represented, and for South Korean contact matrix, we had to adopt the estimated result, not the measured one, since there was no available national survey data so far.8,18 Secondly, we did not take essential worker status and co-morbidities into consideration for our model. Third, seasonality would undoubtedly affect COVID-19 transmission, but it was hard to i...

    Results from TrialIdentifier: No clinical trial numbers were referenced.


    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


    Results from JetFighter: We did not find any issues relating to colormaps.


    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

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