Moving targets: COVID-19 vaccine efficacy against Omicron subvariants

Silva, Maria Karolaynne da; Fulco, U. L.; Silva, Edilson Dantas da

doi:10.1016/j.ymthe.2022.07.004

Cited by 9 publications

(2 citation statements)

References 15 publications

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“…Some countries had other problems such as vaccine hesitancy, for instance, Bulgaria reported a hesitancy level of 62% and Poland reported a similar issue in older age cohorts [9]. On the other hand, available data by July 2022 suggest that variants of COVID-19 specifically the BA.2, BA.4, and BA.5 subvariants escape neutralizing antibodies to a significant extent, which complicated the transmission of the pandemic [10][11][12][13][14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

Estimation of Near-kink Reproduction Numbers During the Emergent Variants of the COVID-19 Pandemic: Log-quadratic and Forward-imputation Approach

Nakamoto

2023

Preprint

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Background: Sketching the major portraits of the COVID-19 epidemic when variants of the pathogen emerge is critical to inform the dynamics of disease transmission, reproduction (i.e., the average counts of individuals of secondary infections generated by an index individual infected by the virus) strength of the pathogen, and countermeasure strategies. Multiple approaches, including log-linear, EpiEstim (an R package generally utilized to estimate the evolution traits of epidemics), and near-log-linear techniques, have been exploited to evaluate the principal parameters such as basic and effective reproduction numbers of an epidemic outbreak. Objective: This study focuses on the kink corner (i.e., sharp alternation of direction of the transmission curve) presenting differentiated log-quadratic traits where more infectious variants of viruses emerge at the diminishing transmission phase of an infectious disease. Methods: A novel log-quadratic trending framework was proposed to project potentially unidentified cases (i.e., forward imputing approximately one week ahead) of COVID-19 around the kink, where the transmission of the pandemic initially lowered and accelerated subsequently, and exercised with the updated framework of classic EpiEstim and Log-linear model. I first compared the performance near the kink using the proposed technique versus the two traditional models taking into account a variety of levels of transmissibility, data distribution (Weibull, Gamma, and Lognormal distributions), and reporting rates (0.2, 0.4, 0.6, 0.8 and 1.0 respectively). Thereafter I utilized the revised framework on the outbreak data of four settings including Bulgaria, Japan, Poland, and South Korea from June to August 2022. Results: The proposed framework reduced the estimation bias versus traditional EpiEstim and log-linear methods near the kink. The coverage estimates of 95% confidence intervals improved. The proposed forward-imputation method implied generally a consistent ascending trend of effective reproduction number estimation applying to a precipitous transition from diminishing to diverging scenarios versus the irregular zigzagging outcomes in classic methods when more contagious variants of the virus were present in the absence of effective vaccines. Conclusions: The log-quadratic correction accounting for transmissibility, data distribution, reporting rates, sliding windows, and generation intervals improved the basic and effective reproduction numbers estimation at the kink corner versus the classic EpiEstim and log-linear models by refined amendment of curve fitting. This is of concern when essentially the fundamental transmission traits of a pandemic alter expeditiously and countermeasures are needed at the earlier variant phases of the transiting climax with the advancement of the pandemic.

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Section: Introductionmentioning

confidence: 99%

Estimation of Near-kink Reproduction Numbers During the Emergent Variants of the COVID-19 Pandemic: Log-quadratic and Forward-imputation Approach

Nakamoto

2023

Preprint

View full text Add to dashboard Cite

show abstract

“…This includes the current challenge posed by the novel coronavirus 5 . These alarming statistics highlight the need to raise awareness and take action to prevent the spread of these diseases 6 , 7 . Vaccination is an important strategy to prevent these diseases, and immunoinformatics promises to revolutionize the field of vaccine development 8 – 13 .…”

mentioning

confidence: 99%