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Preplanned Studies: Comparative Analysis of Vaccine Inequity and COVID-19 Transmission Amid the Omicron Variant Among Countries — Six Countries, Asia-Pacific Region, 2022

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  • Summary

    What is already known about this topic?

    The coronavirus disease 2019 (COVID-19) persists as a significant global public health crisis. The predominant strain, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), notably the Omicron variant, continues to undergo mutations. While vaccination is heralded as the paramount solution to cease the pandemic, challenges persist in providing equitable access to COVID-19 vaccines.

    What is added by this report?

    The distribution of vaccine coverage exhibited disparities between high-income and middle-income countries, with middle-income countries evidencing lower levels of vaccination. The data further suggested that countries with lesser vaccination levels tended to display a higher case fatality rate. Findings indicated that an increase in population-wide vaccination was effective in mitigating COVID-19 related mortalities.

    What are the implications for public health practice?

    The findings of this research underscore the pressing necessity for equitable access to vaccines to effectively mitigate the COVID-19 pandemic within the Asia-Pacific region.

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  • [1] Mathieu E, Ritchie H, Rodés-Guirao L, Appel C, Giattino C, Hasell J, et al. Coronavirus pandemic (COVID-19) our world in data. 2020. https://ourworldindata.org/coronavirus. [2023-1-13].https://ourworldindata.org/coronavirus
    [2] Zhang ZC, Hao M, Zhang XC, He YF, Chen XS, Taylor EW, et al. Potential of green tea EGCG in neutralizing SARS-CoV-2 Omicron variant with greater tropism toward the upper respiratory tract. Trends Food Sci Technol 2023;132:40-53. http://dx.doi.org/10.1016/j.jpgs.2022.12.012CrossRef
    [3] Higdon MM, Baidya A, Walter KK, Patel MK, Issa H, Espié E, et al. Duration of effectiveness of vaccination against COVID-19 caused by the omicron variant. Lancet Infect Dis 2022;22(8):1114-6. http://dx.doi.org/10.1016/S1473-3099(22)00409-1CrossRef
    [4] Feikin DR, Higdon MM, Abu-Raddad LJ, Andrews N, Araos R, Goldberg Y, et al. Duration of effectiveness of vaccines against SARS-CoV-2 infection and COVID-19 disease: results of a systematic review and meta-regression. Lancet 2022;399(10328):924-44. http://dx.doi.org/10.1016/S0140-6736(22)00152-0CrossRef
    [5] Ledford H. Do vaccines protect against long COVID? What the data say. Nature 2021;599(7886):546-8. http://dx.doi.org/10.1038/d41586-021-03495-2CrossRef
    [6] Yang JL, McClymont H, Wang LP, Vardoulakis S, Hu WB. Epidemic features of COVID-19 and potential impact of hospital strain during the omicron wave - Australia, 2022. China CDC Wkly 2023;5(7):165-9. http://dx.doi.org/10.46234/ccdcw2023.029CrossRef
    [7] Watson OJ, Barnsley G, Toor J, Hogan AB, Winskill P, Ghani AC. Global impact of the first year of COVID-19 vaccination: a mathematical modelling study. Lancet Infect Dis 2022;22(9):1293-302. http://dx.doi.org/10.1016/S1473-3099(22)00320-6CrossRef
    [8] Leung K, Jit M, Leung GM, Wu JT. 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 Reg Health West Pac 2022;21:100389. http://dx.doi.org/10.1016/j.lanwpc.2022.100389CrossRef
    [9] WHO. COVAX: Working for global equitable access to COVID-19 vaccines. https://www.who.int/initiatives/act-accelerator/covax. [2023-1-13].https://www.who.int/initiatives/act-accelerator/covax
    [10] Kunyenje CA, Chirwa GC, Mboma SM, Ng'ambi W, Mnjowe E, Nkhoma D, et al. COVID-19 vaccine inequity in African low-income countries. Front Public Health 2023;11:1087662. http://dx.doi.org/10.3389/fpubh.2023.1087662CrossRef
  • FIGURE 1.  Trends by country during the Omicron period. (A) Full vaccination; (B) Stringency Index; (C) mortality; (D) morbidity; (E) case fatality rate (CFR); (F) mortality fatality index (MFI).

    TABLE 1.  Distribution of vaccination rates over time, by country.

    Variables
    High incomeUpper middle incomeLower middle income
    SingaporeAustraliaMalaysiaThailandIndonesiaVietnam
    One vaccination
    0%Dec-20 (+0 m)Feb-21 (+0 m)Feb-21 (+0 m)Mar-21 (+0 m)Jan-21 (+0 m)Mar-21 (+0 m)
    20%Apr-21 (+4 m)June-21 (+4 m)July-21 (+4 m)Aug-21 (+5 m)Aug-21 (+7 m)Sep-21 (+6 m)
    40%May-21 (+5 m)Aug-21 (+6 m)July-21 (+4 m)Sep-21 (+6 m)Oct-21 (+9 m)Oct-21 (+7 m)
    60%June-21 (+6 m)Sep-21 (+7 m)Aug-21 (+5 m)Nov-21 (+8 m)Jan-22 (+12 m)Nov-21 (+8 m)
    80%Aug-21 (+8 m)Jan-22 (+11 m)Jan-22 (+11 m)Jan-22 (+10 m)
    18 Oct 202294.65%86.58%83.72%79.62% (+19 m)74.62% (+21 m)92.37%
    Full vaccination
    0%Jan-21 (+1 m)Feb-21 (+0 m)Feb-21 (+0 m)Mar-21 (+0 m)Jan-21 (+0 m)Apr-21 (+1 m)
    20%May-21 (+5 m)Aug-21 (+6 m)July-21 (+5 m)Sep-21 (+6 m)Oct-21 (+9 m)Oct-21 (+7 m)
    40%July-21 (+7 m)Sep-21 (+7 m)Aug-21 (+6 m)Oct-21 (+7 m)Dec-21 (+11 m)Dec-21 (+9 m)
    60%Aug-21 (+8 m)Oct-21 (+8 m)Sep-21 (+7 m)Dec-21 (+9 m)Apr-22 (+15 m)Dec-21 (+9 m)
    80%Nov-21 (+11 m)Mar-22 (+13 m)May-22 (+15 m)Apr-22 (+13 m)
    18 Oct 202293.92%84.04%81.96%74.70% (+19 m)62.41% (+21 m)86.57%
    Boosters
    0%Sep-21 (+9 m)Oct-21 (+8 m)Sep-21 (+7 m)Aug-21 (+5 m)Feb-22 (+13 m)Feb-22 (+11 m)
    20%Nov-21 (+11 m)Jan-22 (+11 m)Jan-22 (+11 m)Jan-22 (+10 m)July-22 (+18 m)
    40%Dec-21 (+12 m)Feb-22 (+12 m)Feb-22 (+12 m)Jun-22 (+20 m)Mar-22 (+14 m)
    60%Feb-22 (+14 m)June-22 (+15 m)
    80%Aug-22 (+20 m)
    18 Oct 202281.13%55.03% (+20 m)49.92% (+20 m)44.89% (+19 m)23.30% (+21 m)71.62% (+19 m)
    Note: The distribution of time is represented in terms of months since the initiation of the vaccine rollout. “−” means unavailable; “m” means month.
    Download: CSV

    TABLE 2.  Association between full vaccination status and measures of disease severity including MFI, CFR, mortality, and morbidity during the Omicron variant period.

    Full vaccinationBeta coefficientsAverage marginal effects
    β (95% CI)P-valueAME (95% CI), %P-value
    Mortality fatality index
    Level 1ReferenceReference
    Level 20.94 (0.60, 1.28)<0.0014.98 (3.31, 6.65)<0.001
    Level 30.55 (0.13, 0.97)0.0012.12 (0.82, 3.41)0.001
    Level 40.68 (0.11, 1.25)0.0193.06 (0.57, 2.55)0.016
    Case fatality rate
    Level 1ReferenceReference
    Level 21.00 (0.68, 1.33)<0.0010.36 (0.22, 0.49)<0.001
    Level 31.26 (0.88, 1.64)<0.0010.48 (0.29, 0.66)<0.001
    Level 41.46 (0.99, 1.93)<0.0011.34 (0.66, 2.02)<0.001
    Mortality
    Level 1ReferenceReference
    Level 22.05 (1.78, 2.33)<0.00110.55 (7.61, 13.49)<0.001
    Level 31.71 (1.34, 2.07)<0.0015.33 (2.45, 8.22)<0.001
    Level 42.18 (1.63, 2.73)<0.00111.88 (4.65, 19.10)0.001
    Morbidity
    Level 1ReferenceReference
    Level 21.47 (1.26, 1.69)<0.0014.97 (3.86, 6.09)<0.001
    Level 31.55 (1.25, 1.85)<0.0014.54 (3.12, 5.96)<0.001
    Level 42.47 (1.94, 2.99)<0.00119.85 (13.00, 26.71)<0.001
    Note: 1) The model has been adjusted for factors including a 28-day lag for full vaccination, a 14-day lag for Stringency Index, booster shots, population density, gross domestic product, the number of hospital beds per thousand, the proportion of the population aged 65 years and older, and the reproduction rate. 2) The full vaccination rate is regarded as a categorical variable that is divided into four levels. Level 1 signifies a full vaccination rate higher than 90%, level 2 denotes a rate between 80% and 90%, level 3 indicates a rate from 70% to 80%, and level 4 represents a full vaccination rate below 70%.
    “−” means unavailable.
    Abbreviation: CFR=case fatality rate; MFI=mortality fatality index; AME=average marginal effects; β=beta coefficients; CI=confidence interval.
    Download: CSV

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Comparative Analysis of Vaccine Inequity and COVID-19 Transmission Amid the Omicron Variant Among Countries — Six Countries, Asia-Pacific Region, 2022

View author affiliations

Summary

What is already known about this topic?

The coronavirus disease 2019 (COVID-19) persists as a significant global public health crisis. The predominant strain, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), notably the Omicron variant, continues to undergo mutations. While vaccination is heralded as the paramount solution to cease the pandemic, challenges persist in providing equitable access to COVID-19 vaccines.

What is added by this report?

The distribution of vaccine coverage exhibited disparities between high-income and middle-income countries, with middle-income countries evidencing lower levels of vaccination. The data further suggested that countries with lesser vaccination levels tended to display a higher case fatality rate. Findings indicated that an increase in population-wide vaccination was effective in mitigating COVID-19 related mortalities.

What are the implications for public health practice?

The findings of this research underscore the pressing necessity for equitable access to vaccines to effectively mitigate the COVID-19 pandemic within the Asia-Pacific region.

  • 1. School of Public Health and Social Work, Queensland University of Technology, Brisbane, Australia
  • 2. College of Earth and Environmental Sciences, Lanzhou University, Lanzhou City, Gansu Province, China
  • 3. School of Mathematical Sciences, Queensland University of Technology, Brisbane, Australia
  • 4. Centre for Data Science, Queensland University of Technology, Brisbane, Australia
  • 5. Division of Infectious Diseases, Chinese Center for Diseases Control and Prevention, Beijing, China
  • Corresponding authors:

    Wenbiao Hu, w2.hu@qut.edu.au

    Liping Wang, wanglp@chinacdc.cn

    Online Date: August 18 2023
    Issue Date: August 18 2023
    doi: 10.46234/ccdcw2023.139
  • Coronavirus disease 2019 (COVID-19) has emerged as a global public health crisis, with equitable access to vaccines representing a significant challenge. Our study aimed to investigate vaccine inequity and the relationship between vaccination and COVID-19 transmission during the Omicron variant period, focusing specifically on six countries within the Asia-Pacific region. We applied Joinpoint regression modeling to analyze the transmission trends of COVID-19, and the beta regression model was employed to explore the impacts of vaccination on daily mortality, morbidity, case fatality rate (CFR), and mortality fatality index (MFI). As of October 18, 2022, the fully vaccinated population percentages in Singapore, Australia, Malaysia, Thailand, Indonesia, and Vietnam were 93.90%, 84.04%, 81.95%, 74.70%, 62.38%, and 86.42%, respectively. When compared with countries boasting a full vaccination coverage rate exceeding 90%, those countries with rates below 70% exhibited increased mortality by an average of 11.88%, morbidity by 19.85%, MFI by 3.06%, and CFR by 1.34%. Clearly, vaccine coverage is uneven throughout the Asia-Pacific region. Elevated levels of population vaccination have been shown to be effective in preventing COVID-19-related deaths. Thus, our findings underscore the pressing need for more uniform vaccine access to efficiently manage and mitigate the ongoing COVID-19 pandemic.

    The dataset used in our study is sourced from Our World in Data (1). The analysis focuses on six Asia-Pacific countries with relatively comprehensive data at various income levels: Australia and Singapore (high-income), Thailand and Malaysia (upper-middle-income), and Indonesia and Vietnam (lower-middle-income). The study spans from the establishment of the Omicron variant’s 100% share in each country to October 18, 2022. Abstraction of definitions pertaining to COVID-19 vaccination, COVID-19 outcomes, and governmental response can be obtained from the Supplementary Methods. A beta regression model was adopted to investigate the association between full vaccination and variables such as daily mortality, morbidity, CFR, and MFI using the logit link model. Both the beta coefficients (β) and the 95% confidence interval (95% CI) were calculated. Model accuracy was ensured by assessing the distribution of residuals. The joinpoint regression model was utilized to discern trends over a period of time.

    Statistical significance was defined by a two-sided test with P values less than 0.05. All statistical computations were performed using R software (version 4.1.3; R Foundation for Statistical Computing, Vienna, Austria) and the NCI Joinpoint Regression Program (version 4.9.1.0; National Cancer Institute: Rockville, MD, USA).

    Supplementary Table S1 delineates the distribution of cases, deaths, and full vaccinations. Throughout the designated COVID-19 period (Table 1), Singapore was the inaugural country to initiate vaccinations, while Vietnam and Thailand were the last.

    Variables
    High incomeUpper middle incomeLower middle income
    SingaporeAustraliaMalaysiaThailandIndonesiaVietnam
    One vaccination
    0%Dec-20 (+0 m)Feb-21 (+0 m)Feb-21 (+0 m)Mar-21 (+0 m)Jan-21 (+0 m)Mar-21 (+0 m)
    20%Apr-21 (+4 m)June-21 (+4 m)July-21 (+4 m)Aug-21 (+5 m)Aug-21 (+7 m)Sep-21 (+6 m)
    40%May-21 (+5 m)Aug-21 (+6 m)July-21 (+4 m)Sep-21 (+6 m)Oct-21 (+9 m)Oct-21 (+7 m)
    60%June-21 (+6 m)Sep-21 (+7 m)Aug-21 (+5 m)Nov-21 (+8 m)Jan-22 (+12 m)Nov-21 (+8 m)
    80%Aug-21 (+8 m)Jan-22 (+11 m)Jan-22 (+11 m)Jan-22 (+10 m)
    18 Oct 202294.65%86.58%83.72%79.62% (+19 m)74.62% (+21 m)92.37%
    Full vaccination
    0%Jan-21 (+1 m)Feb-21 (+0 m)Feb-21 (+0 m)Mar-21 (+0 m)Jan-21 (+0 m)Apr-21 (+1 m)
    20%May-21 (+5 m)Aug-21 (+6 m)July-21 (+5 m)Sep-21 (+6 m)Oct-21 (+9 m)Oct-21 (+7 m)
    40%July-21 (+7 m)Sep-21 (+7 m)Aug-21 (+6 m)Oct-21 (+7 m)Dec-21 (+11 m)Dec-21 (+9 m)
    60%Aug-21 (+8 m)Oct-21 (+8 m)Sep-21 (+7 m)Dec-21 (+9 m)Apr-22 (+15 m)Dec-21 (+9 m)
    80%Nov-21 (+11 m)Mar-22 (+13 m)May-22 (+15 m)Apr-22 (+13 m)
    18 Oct 202293.92%84.04%81.96%74.70% (+19 m)62.41% (+21 m)86.57%
    Boosters
    0%Sep-21 (+9 m)Oct-21 (+8 m)Sep-21 (+7 m)Aug-21 (+5 m)Feb-22 (+13 m)Feb-22 (+11 m)
    20%Nov-21 (+11 m)Jan-22 (+11 m)Jan-22 (+11 m)Jan-22 (+10 m)July-22 (+18 m)
    40%Dec-21 (+12 m)Feb-22 (+12 m)Feb-22 (+12 m)Jun-22 (+20 m)Mar-22 (+14 m)
    60%Feb-22 (+14 m)June-22 (+15 m)
    80%Aug-22 (+20 m)
    18 Oct 202281.13%55.03% (+20 m)49.92% (+20 m)44.89% (+19 m)23.30% (+21 m)71.62% (+19 m)
    Note: The distribution of time is represented in terms of months since the initiation of the vaccine rollout. “−” means unavailable; “m” means month.

    Table 1.  Distribution of vaccination rates over time, by country.

    As of October 18, 2022, the percentage of the population that had received the complete vaccination protocol in Singapore, Australia, Malaysia, Thailand, Indonesia, and Vietnam was 93.92%, 84.04%, 81.96%, 74.70%, 62.41%, and 86.57%, respectively. The highest fully vaccinated rate was reported in Singapore, and the lowest in Indonesia (Figure 1A). According to Supplementary Table S2, Indonesia demonstrated the greatest increase in full vaccination rates amongst the six countries. Government response indicators shone brightest in Malaysia, whereas Australia showed the lowest (Figure 1B).

    Figure 1. 

    Trends by country during the Omicron period. (A) Full vaccination; (B) Stringency Index; (C) mortality; (D) morbidity; (E) case fatality rate (CFR); (F) mortality fatality index (MFI).

    As outlined in Figure 1, Australia and Singapore observed lower CFR but higher morbidity and mortality, whereas the inverse trend was noted in Indonesia and Thailand. Additionally, Thailand, Indonesia, and Australia reported higher MFI while Singapore, Malaysia, and Vietnam reported lower MFI.

    Increasing trends in cumulative morbidity, mortality, CFR, and MFI were noted across these six countries (Supplementary Tables S3S6).

    We employed residual simulation and the Akaike information criterion to evaluate model fitness. Compared with level 1 at full vaccination (Table 2), mortality increased by an average of 10.55%, 5.33%, and 11.88%, morbidity increased by an average of 4.97%, 4.54%, and 19.85%, CFR increased by an average of 0.36%, 0.48%, and 1.34%, MFI increased by an average of 4.98%, 2.12%, and 3.06% in levels 2-4, respectively.

    Full vaccinationBeta coefficientsAverage marginal effects
    β (95% CI)P-valueAME (95% CI), %P-value
    Mortality fatality index
    Level 1ReferenceReference
    Level 20.94 (0.60, 1.28)<0.0014.98 (3.31, 6.65)<0.001
    Level 30.55 (0.13, 0.97)0.0012.12 (0.82, 3.41)0.001
    Level 40.68 (0.11, 1.25)0.0193.06 (0.57, 2.55)0.016
    Case fatality rate
    Level 1ReferenceReference
    Level 21.00 (0.68, 1.33)<0.0010.36 (0.22, 0.49)<0.001
    Level 31.26 (0.88, 1.64)<0.0010.48 (0.29, 0.66)<0.001
    Level 41.46 (0.99, 1.93)<0.0011.34 (0.66, 2.02)<0.001
    Mortality
    Level 1ReferenceReference
    Level 22.05 (1.78, 2.33)<0.00110.55 (7.61, 13.49)<0.001
    Level 31.71 (1.34, 2.07)<0.0015.33 (2.45, 8.22)<0.001
    Level 42.18 (1.63, 2.73)<0.00111.88 (4.65, 19.10)0.001
    Morbidity
    Level 1ReferenceReference
    Level 21.47 (1.26, 1.69)<0.0014.97 (3.86, 6.09)<0.001
    Level 31.55 (1.25, 1.85)<0.0014.54 (3.12, 5.96)<0.001
    Level 42.47 (1.94, 2.99)<0.00119.85 (13.00, 26.71)<0.001
    Note: 1) The model has been adjusted for factors including a 28-day lag for full vaccination, a 14-day lag for Stringency Index, booster shots, population density, gross domestic product, the number of hospital beds per thousand, the proportion of the population aged 65 years and older, and the reproduction rate. 2) The full vaccination rate is regarded as a categorical variable that is divided into four levels. Level 1 signifies a full vaccination rate higher than 90%, level 2 denotes a rate between 80% and 90%, level 3 indicates a rate from 70% to 80%, and level 4 represents a full vaccination rate below 70%.
    “−” means unavailable.
    Abbreviation: CFR=case fatality rate; MFI=mortality fatality index; AME=average marginal effects; β=beta coefficients; CI=confidence interval.

    Table 2.  Association between full vaccination status and measures of disease severity including MFI, CFR, mortality, and morbidity during the Omicron variant period.

    • In this study, six representative countries from the Asia-Pacific region categorized by economic tiers were analyzed to investigate the correlation between immunization and COVID-19 results. The findings suggest that countries with high-income scales exhibit higher rates of complete vaccination, early commencement of vaccination programs, and lower CFR. Additionally, a notable increase in both CFR and MFI was seen in countries with lower vaccination rates in comparison to the country with the highest rate of full vaccination.

      The Omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) demonstrates greater transmissibility, increased upper respiratory tract prevalence, and lower disease severity compared to previous variants (2). Despite the decrease in disease severity, Omicron’s rapid transmission rates persist as a significant obstacle to pandemic control. The administration of booster doses has been shown to enhance defense against severe COVID-19 during the Omicron surge, with elevated antibody levels sustained for the initial four months post-vaccination (3). Yet, the effectiveness of vaccines appears to diminish over time (4). In summary, while vaccines have significantly curtailed the severity and death rate from COVID-19, they do not offer absolute protection from infection, with cases of “long COVID” prevalent even amidst those who experienced mild or asymptomatic cases of the virus (5). Particularly vulnerable to severe outcomes, including hospitalization and death from COVID-19, are older adults, especially those contending with multiple chronic illnesses, notably cardiovascular or respiratory conditions, or dementia (6).

      This study reveals that lower-income countries exhibit lower rates of complete vaccination and later initiation of the vaccination process. This highlights the disparity in vaccine coverage within the Asia-Pacific region and underscores the urgent need for rectification. Our models indicate that by raising the full vaccination rate from less than 70% to more than 90% as accomplished in Indonesia, the MFI decreased by 19.90% and the CFR declined by 8.02%. Consistent with our findings, Watson et al. (7) pointed out that COVID-19 vaccinations have significantly influenced the pandemic’s trajectory. However, limited vaccine accessibility in economically disadvantaged countries has restricted its benefits, reinforcing the urgency for global vaccine equality and comprehensive coverage. The primary global objective should remain focused on amplifying vaccination coverage across the world’s eligible populace, giving special regard to individuals at an elevated risk of severe illness, such as older demographics, cardiac patients, and individuals with dementia (8). This is a significant global concern as stated by COVAX, the World Health Organization’s initiative promoting global equality of COVID-19 vaccine access, which maintains that until all individuals are protected, no one is truly safe (9). Several stratagems to ensure equalized COVID-19 vaccine coverage have been proposed, including expansion of the COVAX facility, waivers for intellectual property rights, amplified manufacturing capabilities within economically disadvantaged nations, reinforced and improved health infrastructure, and implementation of extensive COVID-19 vaccination initiatives (10). In the future, prioritizing and enhancing routine vaccination schedules within high-risk areas of low- and mid-income nations will abet improved control of future pandemics by addressing vaccine scarcity and unequal accessibility.

      In the present study, the severity of COVID-19 across six representative countries was evaluated using an array of outcome measures, including mortality, morbidity, CFR, and MFI. An infectious disease’s burden is not solely determined by its case and death counts but also significantly impacted by the total population. Mortality is assessed based on both the number of deaths and the total target population, while CFR factors in the number of cases and deaths. The MFI, a more comprehensive indicator developed for this study, integrates case and death counts with the total targeted population to evaluate COVID-19’s severity. As a general metric, the MFI presents a valuable tool for evaluating and comparing the burden of COVID-19 across various regions. The data analyzed in this study pertain to a period when the Omicron variant represented 100% of COVID-19 cases, thus presenting a picture of the ongoing prevalence of this variant relative to studies featuring earlier variants.

      However, some limitations warrant consideration. First, given that reporting of the SARS-CoV-2 variant appears every two weeks, the timing of Omicron’s dominance may be inaccurately represented. Second, the disparity in vaccine types and disease surveillance reporting systems across different countries could potentially bias the results. Third, the beta regression model displayed some underdispersion — an inherent trait of such models — which, while not significantly detracting from our conclusions, invites a more conservative interpretation of hypothesis tests. Furthermore, the existing study lacks data from asymptomatic, mild, moderate, severe, critical, and fatal cases, a spectrum that future research should consider in order to enhance the MFI’s efficiency and accuracy. Despite controlling for potential confounding variables, some factors not accounted for in this research, such as vaccine type, could potentially impact COVID-19 transmission. Thus, caution must be exercised when interpreting the study results.

    • No conflicts of interest.

    • The work of the team from Our World in Data. HEAL (Healthy Environments And Lives) National Research Network, National Health and Medical Research Council (Grant No. 2008937), the China Scholarship Council (CSC), and the Centre for Data Science.

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