Synthetic multiantigen MVA vaccine COH04S1 and variant-specific derivatives protect Syrian hamsters from SARS-CoV-2 Omicron subvariants.

Emerging SARS-CoV-2 Omicron subvariants continue to disrupt COVID-19 vaccine efficacy through multiple immune mechanisms including neutralizing antibody evasion. We developed COH04S1, a synthetic modified vaccinia Ankara vector that co-expresses Wuhan-Hu-1-based spike and nucleocapsid antigens. COH04S1 demonstrated efficacy against ancestral virus and Beta and Delta variants in animal models and was safe and immunogenic in a Phase 1 clinical trial. Here, we report efficacy of COH04S1 and analogous Omicron BA.1- and Beta-specific vaccines to protect Syrian hamsters from Omicron subvariants. Despite eliciting strain-specific antibody responses, all three vaccines protect hamsters from weight loss, lower respiratory tract infection, and lung pathology following challenge with Omicron BA.1 or BA.2.12.1. While the BA.1-specifc vaccine affords consistently improved efficacy compared to COH04S1 to protect against homologous challenge with BA.1, all three vaccines confer similar protection against heterologous challenge with BA.2.12.1. These results demonstrate efficacy of COH04S1 and variant-specific derivatives to confer cross-protective immunity against SARS-CoV-2 Omicron subvariants.

Factors Affecting Cultural Competence in a Sample of Nursing Students during the Prolonged COVID-19 Pandemic in Republic of Korea: A Cross-Sectional Study.

Globally, foreign citizens, particularly ethnic and racial minorities, experienced discrimination and received imbalanced medical services and insufficient economic resources during the COVID-19 pandemic. This study aimed to examine the factors that affect the cultural competence of nursing students. This is descriptive cross-sectional study adheres to Strengthening the Reporting of Observational studies in Epidemiology (STROBE) guidelines. A convenience sample of 235 nursing students from two nursing colleges in D city completed an online Google Forms questionnaire from 9 August to 12 August 2022. The self-report questionnaire included a sociodemographic data form, a cultural intelligence scale, an ethnocentrism scale, a global competence scale, and a cultural competence scale. The mean score of cultural competence was 95.39 ± 15.64 (out of 135 points); cultural competence was significantly positively correlated with cultural intelligence and global competence (p < 0.001), and significantly negatively correlated with ethnocentrism (p < 0.001). The factors that significantly affected cultural competence were cultural intelligence (ß = 0.31, p < 0.001) and global competence (ß = 0.37, p < 0.001). The explanatory power of these effects was 47.3%. To improve the cultural competence of nursing students, it is necessary to develop, apply, and evaluate the results of curriculum and programs that can enhance the cultural intelligence and global competence of nursing students.

A Novel Approach of Antiviral Drugs Targeting Viral Genomes.

Outbreaks of viral diseases, which cause morbidity and mortality in animals and humans, are increasing annually worldwide. Vaccines, antiviral drugs, and antibody therapeutics are the most effective tools for combating viral infection. The ongoing coronavirus disease 2019 pandemic, in particular, raises an urgent need for the development of rapid and broad-spectrum therapeutics. Current antiviral drugs and antiviral antibodies, which are mostly specific at protein levels, have encountered difficulties because the rapid evolution of mutant viral strains resulted in drug resistance. Therefore, degrading viral genomes is considered a novel approach for developing antiviral drugs. The current article highlights all potent candidates that exhibit antiviral activity by digesting viral genomes such as RNases, RNA interference, interferon-stimulated genes 20, and CRISPR/Cas systems. Besides that, we introduce a potential single-chain variable fragment (scFv) that presents antiviral activity against various DNA and RNA viruses due to its unique nucleic acid hydrolyzing characteristic, promoting it as a promising candidate for broad-spectrum antiviral therapeutics.

Effects of government policies on the spread of COVID-19 worldwide.

The outbreak of novel COVID-19 disease elicited a wide range of anti-contagion and economic policies like school closure, income support, contact tracing, and so forth, in the mitigation and suppression of the spread of the SARS-CoV-2 virus. However, a systematic evaluation of these policies has not been made. Here, 17 implemented policies from the Oxford COVID-19 Government Response Tracker dataset employed in 90 countries from December 31, 2019, to August 31, 2020, were analyzed. A Poisson regression model was applied to analyze the relationship between policies and daily confirmed cases using a generalized estimating equations approach. A lag is a fixed time displacement in time series data. With that, lagging (0, 3, 7, 10, and 14 days) was also considered during the analysis since the effects of policies implemented on a given day may affect the number of confirmed cases several days after implementation. The countries were divided into three groups depending on the number of waves of the pandemic observed in each country. Through subgroup analysis, we showed that with and without lagging, contact tracing and containment policies were significant for countries with two waves, while closing, economic, and health policies were significant for countries with three waves. Wave-specific analysis for each wave showed that significant health, economic, and containment policies varied across waves of the pandemic. Emergency investment in healthcare was consistently significant among the three groups of countries, while the Stringency index was significant among all waves of the pandemic. These findings may help in making informed decisions regarding whether, which, or when these policies should be intensified or lifted.

Which National Factors Are Most Influential in the Spread of COVID-19?

The outbreak of the novel COVID-19, declared a global pandemic by WHO, is the most serious public health threat seen in terms of respiratory viruses since the 1918 H1N1 influenza pandemic. It is surprising that the total number of COVID-19 confirmed cases and the number of deaths has varied greatly across countries. Such great variations are caused by age population, health conditions, travel, economy, and environmental factors. Here, we investigated which national factors (life expectancy, aging index, human development index, percentage of malnourished people in the population, extreme poverty, economic ability, health policy, population, age distributions, etc.) influenced the spread of COVID-19 through systematic statistical analysis. First, we employed segmented growth curve models (GCMs) to model the cumulative confirmed cases for 134 countries from 1 January to 31 August 2020 (logistic and Gompertz). Thus, each country's COVID-19 spread pattern was summarized into three growth-curve model parameters. Secondly, we investigated the relationship of selected 31 national factors (from KOSIS and Our World in Data) to these GCM parameters. Our analysis showed that with time, the parameters were influenced by different factors; for example, the parameter related to the maximum number of predicted cumulative confirmed cases was greatly influenced by the total population size, as expected. The other parameter related to the rate of spread of COVID-19 was influenced by aging index, cardiovascular death rate, extreme poverty, median age, percentage of population aged 65 or 70 and older, and so forth. We hope that with their consideration of a country's resources and population dynamics that our results will help in making informed decisions with the most impact against similar infectious diseases.

Statistical Estimation of Effects of Implemented Government Policies on COVID-19 Situation in South Korea.

Since the outbreak of novel SARS-COV-2, each country has implemented diverse policies to mitigate and suppress the spread of the virus. However, no systematic evaluation of these policies in their alleviation of the pandemic has been done. We investigate the impact of five indices derived from 12 policies in the Oxford COVID-19 Government Response Tracker dataset and the Korean government's index, which is the social distancing level implemented by the Korean government in response to the changing pandemic situation. We employed segmented Poisson model for this analysis. In conclusion, health and the Korean government indices are most consistently effective (with negative coefficients), while the restriction and stringency indexes are mainly effective with lagging (1~10 days), as intuitively daily confirmed cases of a given day is affected by the policies implemented days before, which shows that a period of time is required before the impact of some policies can be observed. The health index demonstrates the importance of public information campaign, testing policy and contact tracing, while the government index shows the importance of social distancing guidelines in mitigating the spread of the virus. These results imply the important roles of these polices in mitigation of the spread of COVID-19 disease.