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This study aims to analyze the neutralization ability against Omicron parental variants in five clusters of individuals with different Coronavirus disease (COVID-19) immunity backgrounds, including individuals receiving a homologous or heterologous vaccine without prior infection, recovered patients with homologous or heterologous vaccination, and recovery patients without vaccination. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) surrogate virus neutralization assay was performed on serum samples. Spearman correlation analysis showed that the percent inhibition against Omicron B.1.1.529 and BA.2 was significantly related to the period of serum collection (r = 0.730 and 0.787, p < 0.001, respectively). Very strong correlation between percent inhibition of neutralizing antibody against Omicron B.1.1.529 and BA.2 variants (rs = 0.973, p < 0.001) was also observed. The neutralizing activity of the sera from recovery patients receiving homologous and heterologous vaccine against the wild-type, B.1.1.529, and BA.2 Omicron variants was significantly higher (p < 0.001) than that of recovery patients without vaccination. This study robustly showed that the breakthrough SARS-CoV-2 Omicron variant in individuals who received homologous and heterologous vaccines had a high level of neutralizing activity against B.1.1.529 and BA.2 parental lineage of XBB subvariants. Therefore, the next-generation COVID-19 vaccine against emerging variants is needed to improve resilience against ongoing variants, particularly for persons who have never been infected. [ABSTRACT FROM AUTHOR]

This research aimed to determine the levels of COVID-19 booster dose vaccinations in Thai populations in areas with environmental risk exposure during the Omicron outbreak. Five of twenty provinces in Thailand were selected by assessing environmental risk exposure for study settings. A total of 1038 people were interviewed by a structured questionnaire. The predicting factors of COVID-19 booster dose vaccinations were analyzed by univariate and multivariate analysis. The results showed that 69.4% (95% CI 66.5–72.1) of the population was vaccinated with COVID-19 booster doses. Multiple logistics regression revealed that the female gender (AOR 1.49, 95% CI 1.11–2.00), all age groups from 38 to 60 years old, all education levels of at least secondary school, high income (AOR 1.16, 95% CI 1.15–2.24), populations having experience with COVID-19 infection (AOR 2.27, 95% CI 2.05–3.76), knowledge of vaccine (AOR 1.78, 95% CI 1.11–2.83), and trusting attitude (AOR 1.76, 95% CI 1.32–2.36) were factors among those more likely to take COVID-19 booster dose vaccinations in high-environmental-risk-exposure areas. Therefore, an effective booster dose campaign with education programs to increase attitudes toward booster vaccinations should be implemented for the resilience of COVID-19 prevention and control. [ABSTRACT FROM AUTHOR]

This study aims to analyze the neutralization ability against Omicron parental variants in five clusters of individuals with different Coronavirus disease (COVID-19) immunity backgrounds, including individuals receiving a homologous or heterologous vaccine without prior infection, recovered patients with homologous or heterologous vaccination, and recovery patients without vaccination. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) surrogate virus neutralization assay was performed on serum samples. Spearman correlation analysis showed that the percent inhibition against Omicron B.1.1.529 and BA.2 was significantly related to the period of serum collection (r = 0.730 and 0.787, p < 0.001, respectively). Very strong correlation between percent inhibition of neutralizing antibody against Omicron B.1.1.529 and BA.2 variants (rs = 0.973, p < 0.001) was also observed. The neutralizing activity of the sera from recovery patients receiving homologous and heterologous vaccine against the wild-type, B.1.1.529, and BA.2 Omicron variants was significantly higher (p < 0.001) than that of recovery patients without vaccination. This study robustly showed that the breakthrough SARS-CoV-2 Omicron variant in individuals who received homologous and heterologous vaccines had a high level of neutralizing activity against B.1.1.529 and BA.2 parental lineage of XBB subvariants. Therefore, the next-generation COVID-19 vaccine against emerging variants is needed to improve resilience against ongoing variants, particularly for persons who have never been infected.

Omicron, the latest SARS-CoV-2 Variant of Concern (VOC), first appeared in Africa in November 2021. At present, the question of whether a new VOC will out-compete the currently predominant variant is important for governments seeking to determine if current surveillance strategies and responses are appropriate and reasonable. Based on both virus genomes and daily-confirmed cases, we compare the additive differences in growth rates and reproductive numbers ( R 0 ) between VOCs and their predominant variants through a Bayesian framework and phylo-dynamics analysis. Faced with different variants, we evaluate the effects of current policies and vaccinations against VOCs and predominant variants. The model also predicts the date on which a VOC may become dominant based on simulation and real data in the early stage. The results suggest that the overall additive difference in growth rates of B.1.617.2 and predominant variants was 0.44 (95% confidence interval, 95% CI: −0.38, 1.25) in February 2021, and that the VOC had a relatively high R 0 . The additive difference in the growth rate of BA.1 in the United Kingdom was 6.82 times the difference between Delta and Alpha, and the model successfully predicted the dominating process of Alpha, Delta and Omicron. Current vaccination strategies remain similarly effective against Delta compared to the previous variants. Our model proposes a reliable Bayesian framework to predict the spread trends of VOCs based on early-stage data, and evaluates the effects of public health policies, which may help us better prepare for the upcoming Omicron variant, which is now spreading at an unprecedented speed. [ABSTRACT FROM AUTHOR]

This research aimed to determine the levels of COVID-19 booster dose vaccinations in Thai populations in areas with environmental risk exposure during the Omicron outbreak. Five of twenty provinces in Thailand were selected by assessing environmental risk exposure for study settings. A total of 1038 people were interviewed by a structured questionnaire. The predicting factors of COVID-19 booster dose vaccinations were analyzed by univariate and multivariate analysis. The results showed that 69.4% (95% CI 66.5–72.1) of the population was vaccinated with COVID-19 booster doses. Multiple logistics regression revealed that the female gender (AOR 1.49, 95% CI 1.11–2.00), all age groups from 38 to 60 years old, all education levels of at least secondary school, high income (AOR 1.16, 95% CI 1.15–2.24), populations having experience with COVID-19 infection (AOR 2.27, 95% CI 2.05–3.76), knowledge of vaccine (AOR 1.78, 95% CI 1.11–2.83), and trusting attitude (AOR 1.76, 95% CI 1.32–2.36) were factors among those more likely to take COVID-19 booster dose vaccinations in high-environmental-risk-exposure areas. Therefore, an effective booster dose campaign with education programs to increase attitudes toward booster vaccinations should be implemented for the resilience of COVID-19 prevention and control.

Omicron, the latest SARS-CoV-2 Variant of Concern (VOC), first appeared in Africa in November 2021. At present, the question of whether a new VOC will out-compete the currently predominant variant is important for governments seeking to determine if current surveillance strategies and responses are appropriate and reasonable. Based on both virus genomes and daily-confirmed cases, we compare the additive differences in growth rates and reproductive numbers (R0) between VOCs and their predominant variants through a Bayesian framework and phylo-dynamics analysis. Faced with different variants, we evaluate the effects of current policies and vaccinations against VOCs and predominant variants. The model also predicts the date on which a VOC may become dominant based on simulation and real data in the early stage. The results suggest that the overall additive difference in growth rates of B.1.617.2 and predominant variants was 0.44 (95% confidence interval, 95% CI: −0.38, 1.25) in February 2021, and that the VOC had a relatively high R0. The additive difference in the growth rate of BA.1 in the United Kingdom was 6.82 times the difference between Delta and Alpha, and the model successfully predicted the dominating process of Alpha, Delta and Omicron. Current vaccination strategies remain similarly effective against Delta compared to the previous variants. Our model proposes a reliable Bayesian framework to predict the spread trends of VOCs based on early-stage data, and evaluates the effects of public health policies, which may help us better prepare for the upcoming Omicron variant, which is now spreading at an unprecedented speed.