Background In the face of a sudden outbreak of COVID-19, it is essential to promote health communication, especially to reduce communication inequality. The paper targeted China to investigate whether social structural factors (education level and urban-rural differences) lead to the knowledge gap of COVID-19. Also, this paper examined whether media use, interpersonal communication, public communication, and perceived salience of information can influence the knowledge gap of COVID-19. Furthermore, this paper explored the strategies to promote communication equality. Methods An online survey on COVID-19 knowledge and its influencing factors was conducted in February 2020, with a valid sample of 981 participants. The dependent variable was the total score of knowledge related to COVID-19. In addition to demographic variables such as education level and residence, the main explanatory variables include four independent variables: the use of different media (print media, radio, television, Internet), interpersonal communication, public communication, and perceived salience of information. This paper utilized descriptive statistics, correlation analysis, and hierarchical multiple regression analysis for data processing. Results Descriptive statistics indicated that the Internet was the most frequent source of information for participants to obtain COVID-19 knowledge (M = 6.28, SD = 1.022). Bi-variate analysis and regression analysis presented that education level, Internet media use, and perceived salience of information predicted the difference in knowledge level. Hierarchical multiple regression showed that Internet media use significantly predicted differences in the level of knowledge related to COVID-19 among groups with different education levels. Conclusions This study found a COVID-19 knowledge gap among the Chinese public, especially the digital knowledge gap. Education level, perceived salience of information, and internet media use can significantly predict the difference in COVID-19 knowledge level. In contrast, the use of traditional media such as newspaper, radio, and television, public communication, and interpersonal communication did not improve knowledge level. Internet media use and education level have an interactive effect on the formation of a COVID-19 knowledge gap. That is, online media use will expand the COVID-19 knowledge gap between groups with different education levels.

Vaccination is critical for controlling the COVID-19 pandemic. However, the progress of COVID-19 vaccination varies from different countries, and global vaccine inequity has been a worldwide public health issue. This study collected data from the Our World in Data COVID-19 vaccination data set between 13 December 2020 and 1 January 2022. The measurement reflecting the pandemic situation included New cases, New deaths, Hospital patients, ICU patients, and the Reproduction rate. Indicators for measuring the vaccination coverage included Total vaccinations per hundred and People vaccinated per hundred. The Human Development Index (HDI) measured the country’s development level. Findings indicated that countries with higher HDI have more adequate vaccine resources, and global vaccine inequity exists. The study also found that vaccination significantly mitigates the pandemic, and reaching 70% immunization coverage can further control the epidemic. In addition, the emergence of Omicron variants makes the COVID-19 epidemic situation even worse, suggesting the importance and necessity of addressing vaccine inequity. The globe will face a greater challenge in controlling the pandemic if lower-vaccinated countries do not increase their vaccination coverage. Addressing the issue of vaccine inequity needs the cooperation of HIC, LMIC, public health departments, and vaccine producers. Moreover, the media has to contribute to effective public health communication by raising public perceptions of the COVID-19 pandemic, vaccination, and vaccine inequity.

Given the drawbacks of implementing multivariate analysis for mapping multiple traits in genome-wide association study (GWAS), principal component analysis (PCA) has been widely used to generate independent 'super traits' from the original multivariate phenotypic traits for the univariate analysis. However, parameter estimates in this framework may not be the same as those from the joint analysis of all traits, leading to spurious linkage results. In this paper, we propose to perform the PCA for residual covariance matrix instead of the phenotypical covariance matrix, based on which multiple traits are transformed to a group of pseudo principal components. The PCA for residual covariance matrix allows analyzing each pseudo principal component separately. In addition, all parameter estimates are equivalent to those obtained from the joint multivariate analysis under a linear transformation. However, a fast least absolute shrinkage and selection operator (LASSO) for estimating the sparse oversaturated genetic model greatly reduces the computational costs of this procedure. Extensive simulations show statistical and computational efficiencies of the proposed method. We illustrate this method in a GWAS for 20 slaughtering traits and meat quality traits in beef cattle. Heredity (2014) 113, 526-532; doi:10.1038/hdy.2014.57; published online 2 July 2014 INTRODUCTIONWith the advance of high-throughput genotyping technology, the paradigm of mapping quantitative trait locus (QTL) based on the linkage analysis of sparse genetic markers has gradually shifted to genome-wide association studies (GWAS) based on thousands and thousands of single-nucleotide polymorphisms (SNPs). On the other hand, association studies tend to involve more than one quantitative traits or complex diseases located in different regions of chromosomes, allowing the investigation of common genetic risk factors underlying multiple traits. Although these traits could be analyzed separately with univariate genetic model, statistical methods and algorithms have been developed for simultaneously analyzing multiple

Introduction: On December 31, 2020, the Chinese government announced that the domestic coronavirus disease-2019 (COVID-19) vaccines have obtained approval for conditional marketing and are free for vaccination. This release drove the attention of the public and intense debates on social media, which reflected public attitudes to the domestic vaccine. This study examines whether the public concerns and public attitudes to domestic COVID-19 vaccines changed after the official announcement.Methods: This article used big data analytics in the research, including semantic network and sentiment analysis. The purpose of the semantic network is to obtain the public concerns about domestic vaccines. Sentiment analysis reflects the sentiments of the public to the domestic vaccines and the emotional changes by comparing the specific sentiments shown on the posts before and after the official announcement.Results: There exists a correlation between the public concerns about domestic vaccines before and after the official announcement. According to the semantic network analysis, the public concerns about vaccines have changed after the official announcement. The public focused on the performance issues of the vaccines before the official approval, but they cared more about the practical issues of vaccination after that. The sentiment analysis showed that both positive and negative emotions increased among the public after the official announcement. “Good” was the most increased positive emotion and indicated great public appreciation for the production capacity and free vaccination. “Fear” was the significantly increased negative emotion and reflected the public concern about the safety of the vaccines.Conclusion: The official announcement of the approval for marketing improved the Chinese public acceptance of the domestic COVID-19 vaccines. In addition, safety and effectiveness are vital factors influencing public vaccine hesitancy.

Infectious bursal disease virus (IBDV) is an immunosuppressive pathogen causing enormous economic losses to the poultry industry across the globe. As a double-stranded RNA virus, IBDV undergoes genetic mutation or recombination in replication during circulation among flocks, leading to the generation and spread of variant or recombinant strains. In particular, the recent emergence of variant IBDV causes severe immunosuppression in chickens, affecting the efficacy of other vaccines. It seems that the genetic mutation of IBDV during the battle against host response is an effective strategy to help itself to survive. Therefore, a comprehensive understanding of the viral genome diversity will definitely help to develop effective measures for prevention and control of infectious bursal disease (IBD). In recent years, considerable progress has been made in understanding the relation of genetic mutation and genomic recombination of IBDV to its pathogenesis using the reverse genetic technique. Therefore, this review focuses on our current genetic insight into the IBDV’s genetic typing and viral genomic variation.