The global transmission of new coronavirus variants

Singapore's COVID-19 Genomic Surveillance Programme: Strategies and Insights From a Pandemic Year

BACKGROUND

During the COVID-19 pandemic, genomic surveillance was crucial for monitoring virus spread and identifying variants. Effective surveillance helped understand transmission dynamics. Singapore had success in combating COVID-19 through its surveillance programmes. This paper outlines Singapore's strategy and its impact on public health during the transition to endemicity over 54 weeks from February 2022 to February 2023.

METHODS

In May 2022, Singapore expanded its acute respiratory infections (ARI) surveillance to enhance COVID-19 detection. COVID-19-positive samples from ARI cases were sent to the National Public Health Laboratory for whole genome sequencing (WGS). WGS data informed public health actions based on transmission origins and case severity.

RESULTS

Over 54 weeks, NPHL sequenced 18,918 (73%) samples. Analysis showed 29% imported and 71% local cases. Severe cases accounted for 12% and were mostly elderly, specifically those aged 80 years old and above. Variant analysis identified 11 predominant variants and 288 subvariants. Omicron BA.2, BA.5 and XBB were initially dominant, followed by increased variant heterogeneity. Severe cases mirrored these trends.

CONCLUSION

Genomic surveillance was integral in Singapore's COVID-19 response, guiding timely public health decisions. Effective variant tracking supported proactive measures. The experience underscores the importance of genomic surveillance for future pandemic preparedness and emerging disease detection, emphasising its role in shaping pandemic responses and global health.

Identification of highly conserved surface-exposed peptides of spike protein for multiepitope vaccine design against emerging omicron variants: An immunoinformatic approach

The COVID-19 pandemic, originating in Wuhan in 2019, was caused by SARS-CoV-2, leading to significant global fatalities. Despite the development of vaccines, the virus mutates, creating variants that evade vaccine-induced immunity. To address SARS-CoV-2's evolving nature, a multiepitope vaccine was developed using immunoinformatics approach, specifically targeting the Omicron variant's spike protein. This vaccine includes six CD8 + and eleven CD4 + epitopes selected for their immunogenicity, non-toxicity, and significant conservation among former Variants of Concern (VOCs) and Variants of Interest (VOIs), such as Alpha, Beta, Gamma, Delta, Lambda, Mu, R1, and Zeta, as well as current Variants Under Monitoring (VUMs) like XBB.1.5, XBB.1.16, EG.5, BA.2.86, and JN.1. Notably, certain epitopes like ELLHAPATV and PYRVVVLSFELLHAP were fully conserved across all tested variants in the spike protein's receptor binding domain (RBD). Others, such as NATRFASVYAWNRKR, were fully conserved in all former VOCs and VOIs and 93.33 % in current VUMs, while ERDISTEIYQAGNKP was entirely conserved in current VUMs within the RBD region. The study went on to model, refine, and validate the vaccine prototype's tertiary structure. Docking experiments and molecular dynamic simulations revealed robust and stable interactions with Toll-like receptor 4. Cloning and codon optimization confirmed successful expression in E. coli. Subsequently, the immunological reaction of the multiepitope vaccine demonstrated that the three-time administration of the prototype significantly enhanced the antibody response while decreasing the number of antigens. The designed vaccine's epitopes showed significant combined global population coverage of 100 % with 89.75 % for CD8 + and 99.98 % for CD4 + epitopes and conservation across SARS-CoV-2 variants especially in current monitoring omicron subvariants, supporting its broader applicability and potential efficacy. Although, this promising vaccine candidate needs to undergo clinical trials to determine its effectiveness in neutralising SARS-CoV-2.

Anatolian medicinal plants as potential antiviral agents: bridging traditional knowledge and modern science in the fight against COVID-19 and related viral infections

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was the cause of the coronavirus 2019 (COVID-19), commonly known as the coronavirus pandemic. Since December 2020, COVID-19 vaccines have been extensively administered in numerous countries. In addition to new antiviral medications, the treatment regimen encompasses symptom management. Despite sustained research efforts, the outbreak remains uncontrolled, with affected patients still lacking proper treatment. This review is a valuable asset for researchers and practitioners aiming to delve into the yet unexplored potential of Anatolian flora in the fight against COVID-19 and other viral infections. Numerous medicinal plants in Anatolia, such as thyme, sage, cannabis, oregano, licorice root, and Origanum sp., contain bioactive compounds with proven antiviral properties that have been used in the region for centuries. The rich legacy of traditional Anatolian medicine (TAM), has significantly influenced modern medicine; thus, the profusion of medicinal plants native to Anatolia holds promise for antiviral drug development, making this review essential for researchers and practitioners.

Effect of Regdanvimab on Mortality in Patients Infected with SARS-CoV-2 Delta Variants: A Propensity Score-Matched Cohort Study

INTRODUCTION

Regdanvimab, a monoclonal antibody pharmaceutical, is the first Korean drug approved for treating coronavirus disease 2019 (COVID-19). We analyzed the therapeutic efficacy of regdanvimab in patients with the COVID-19 delta variant infection.

METHODS

We retrospectively reviewed the electronic medical records of patients hospitalized at two Korean tertiary COVID-19 hospitals with COVID-19 delta variant infection between May 26, 2021, and January 30, 2022. To analyze the therapeutic efficacy of regdanvimab, the patients were divided into regdanvimab and non-regdanvimab groups and were 1:1 propensity-score (PS)-matched on age, severity at admission, and COVID-19 vaccination history.

RESULTS

Of 492 patients, 262 (53.3%) and 230 (46.7%) were in the regdanvimab and non-regdanvimab groups, respectively. After PS matching the groups on age, severity at admission, and COVID-19 vaccination history, each group comprised 189 patients. The 30-day hospital mortality rates (0.0% vs. 1.6%, p = 0.030), proportions of patients with exacerbated conditions to severe/critical/died (9.5% vs. 16.4%, p = 0.047), proportions who received oxygen therapy because of pneumonia exacerbation (7.4% vs. 16.4%, p = 0.007), and proportions with a daily National Early Warning Score ≥ 5 from hospital day 2 were significantly lower in the regdanvimab group.

CONCLUSIONS

We showed that regdanvimab reduced the exacerbation rates of conditions and mortality in patients with the COVID-19 delta variant infection. Thus, it is recommended to streamline the drug approval system during epidemics of new variant viruses to improve the availability and usage of therapeutics for patients. To facilitate this, relevant institutional support is required.

An overview for monitoring and prediction of pathogenic microorganisms in the atmosphere

Corona virus disease 2019 (COVID-19) has exerted a profound adverse impact on human health. Studies have demonstrated that aerosol transmission is one of the major transmission routes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Pathogenic microorganisms such as SARS-CoV-2 can survive in the air and cause widespread infection among people. Early monitoring of pathogenic microorganism transmission in the atmosphere and accurate epidemic prediction are the frontier guarantee for preventing large-scale epidemic outbreaks. Monitoring of pathogenic microorganisms in the air, especially in densely populated areas, may raise the possibility to detect viruses before people are widely infected and contain the epidemic at an earlier stage. The multi-scale coupled accurate epidemic prediction system can provide support for governments to analyze the epidemic situation, allocate health resources, and formulate epidemic response policies. This review first elaborates on the effects of the atmospheric environment on pathogenic microorganism transmission, which lays a theoretical foundation for the monitoring and prediction of epidemic development. Secondly, the monitoring technique development and the necessity of monitoring pathogenic microorganisms in the atmosphere are summarized and emphasized. Subsequently, this review introduces the major epidemic prediction methods and highlights the significance to realize a multi-scale coupled epidemic prediction system by strengthening the multidisciplinary cooperation of epidemiology, atmospheric sciences, environmental sciences, sociology, demography, etc. By summarizing the achievements and challenges in monitoring and prediction of pathogenic microorganism transmission in the atmosphere, this review proposes suggestions for epidemic response, namely, the establishment of an integrated monitoring and prediction platform for pathogenic microorganism transmission in the atmosphere.

Susceptible-Infected-Susceptible type COVID-19 spread with collective effects

Many models developed to forecast and attempt to understand the COVID-19 pandemic are highly complex, and few take collective behavior into account. As the pandemic progressed individual recurrent infection was observed and simpler susceptible-infected type models were introduced. However, these do not include mechanisms to model collective behavior. Here, we introduce an extension of the SIS model that accounts for collective behavior and show that it has four equilibria. Two of the equilibria are the standard SIS model equilibria, a third is always unstable, and a fourth where collective behavior and infection prevalence interact to produce either node-like or oscillatory dynamics. We then parameterized the model using estimates of the transmission and recovery rates for COVID-19 and present phase diagrams for fixed recovery rate and free transmission rate, and both rates fixed. We observe that regions of oscillatory dynamics exist in both cases and that the collective behavior parameter regulates their extent. Finally, we show that the system exhibits hysteresis when the collective behavior parameter varies over time. This model provides a minimal framework for explaining oscillatory phenomena such as recurring waves of infection and hysteresis effects observed in COVID-19, and other SIS-type epidemics, in terms of collective behavior.

A deterministic compartmental model for the transition between variants in the spread of Covid-19 in Italy

We propose a deterministic epidemic model to describe the transition between two variants of the same virus, through the combination of a series of realistic mechanisms such as partial cross immunity, waning immunity for vaccinated individuals and a novel data-based algorithm to describe the average immunological status of the population. The model is validated on the evolution of Covid-19 in Italy, during the period in which the transition between Delta and Omicron variant occurred, with very satisfactory agreement with the experimental data. According to our model, if the vaccine efficacy had been equal against Delta and Omicron variant infections, the transition would have been smoothed and the epidemic would have gone extinct. This circumstance confirms the fundamental role of vaccines in combating the epidemic, and the importance of identifying vaccines capable of intercepting new variants.

COVID-19 in 16 West African Countries: An Assessment of the Epidemiology and Genetic Diversity of SARS-CoV-2 after Four Epidemic Waves

West Africa faced the COVID-19 pandemic in early March 2020 and, as of March 31, 2022, had more than 900,000 confirmed cases and more than 12,000 deaths. During this period, SARS-CoV-2 genomes evolved genetically, resulting in the emergence of distinct lineages. This review was conducted to provide the epidemiological profile of COVID-19, the mutational profile of SARS-CoV-2, and the dynamics of its lineages in the 16 west African countries by analyzing data from 33 studies and seven situation reports. For a more complete representation of the epidemiology and genetic diversity of SARS-CoV-2, we used reliable public data in addition to eligible studies. As of March 31, 2022, the 16 west African countries experienced four epidemic waves with variable intensities. Higher mortality was noted during the third wave with a case fatality rate (CFR) of 1.9%. After these four epidemic waves, Liberia recorded the highest CFR (4.0%), whereas Benin had the lowest CFR (0.6%). Through mutational analysis, a high genetic heterogeneity of the genomes was observed, with a predominance of mutations in the spike protein. From this high mutational rate, different lineages emerged. Our analysis of the evolutionary diversity allowed us to count 205 lineages circulating in west Africa. This study has provided a good representation of the mutational profile and the prevalence of SARS CoV-2 lineages beyond the knowledge of the global epidemiology of the 16 African countries.

Protection against Severe Illness versus Immunity-Redefining Vaccine Effectiveness in the Aftermath of COVID-19

Anti-SARS-CoV-2 vaccines have played a pivotal role in reducing the risk of developing severe illness from COVID-19, thus helping end the COVID-19 global public health emergency after more than three years. Intriguingly, as SARS-CoV-2 variants emerged, individuals who were fully vaccinated did get infected in high numbers, and viral loads in vaccinated individuals were as high as those in the unvaccinated. However, even with high viral loads, vaccinated individuals were significantly less likely to develop severe illness; this begs the question as to whether the main effect of anti-SARS-CoV-2 vaccines is to confer protection against severe illness or immunity against infection. The answer to this question is consequential, not only to the understanding of how anti-SARS-CoV-2 vaccines work, but also to public health efforts against existing and novel pathogens. In this review, we argue that immune system sensitization-desensitization rather than sterilizing immunity may explain vaccine-mediated protection against severe COVID-19 illness even when the SARS-CoV-2 viral load is high. Through the lessons learned from COVID-19, we make the case that in the disease's aftermath, public health agencies must revisit healthcare policies, including redefining the term "vaccine effectiveness."

Geospatial analysis in the United States reveals the changing roles of temperature on COVID-19 transmission

Environmental factors are known to affect outbreak patterns of infectious disease, but their impacts on the spread of COVID-19 along with the evolution of this relationship over time intervals and in different regions are unclear. This study utilized 3 years of data on COVID-19 cases in the continental United States from 2020 to 2022 and the corresponding weather data. We used regression analysis to investigate weather impacts on COVID-19 spread in the mainland United States and estimate the changes of these impacts over space and time. Temperature exhibited a significant and moderately strong negative correlation for most of the US while relative humidity and precipitation experienced mixed relationships. By regressing temperature factors with the spreading rate of waves, we found temperature change can explain over 20% of the spatial-temporal variation in the COVID-19 spreading, with a significant and negative response between temperature change and spreading rate. The pandemic in the continental United States during 2020-2022 was characterized by seven waves, with different transmission rates and wave peaks concentrated in seven time periods. When repeating the analysis for waves in the seven periods and nine climate zones, we found temperature impacts evolve over time and space, possibly due to virus mutation, changes in population susceptibility, social behavior, and control measures. Temperature impacts became weaker in 6 of 9 climate zones from the beginning of the epidemic to the end of 2022, suggesting that COVID-19 has increasingly adapted to wider weather conditions.

Modeling the drivers of oscillations in COVID-19 data on college campuses

PURPOSE

Incorporating human behavior in a disease model can explain the oscillations in COVID-19 data which occur more rapidly than can be explained by variants alone on college campuses.

METHODS

Dampened oscillations emerge by supplementing a simple disease model with a risk assessment function, which depends on the current number of infected individuals in the student population and the institutional public health policies. After accounting for a rapid disease impulse due to social gatherings, we achieve sustained oscillations that follow the trend of 2020/2021 COVID-19 data as reported on the COVID-19 dashboards of US post-secondary institutions.

RESULTS

This adjustment to the epidemiological model can provide an intuitive way of understanding rapid oscillations based on human risk perception and institutional policies. More risk-averse communities experience lower disease-level equilibria and less oscillations within the system, while communities that are less responsive to changes in the number of infected individuals exhibit larger amplitude and frequency of the oscillations.

CONCLUSIONS

Community risk assessment plays an important role in COVID-19 management in college settings. Improving the ability of individuals to rapidly and conservatively respond to changes in community disease levels may help assist in self-regulating these oscillations to levels well below thresholds for emergency management.

Role of Natural Products in the Management of COVID-19: A Saudi Arabian Perspective

The coronavirus disease of 2019 (COVID-19) pandemic has resulted in an unprecedented circumstance that has never previously occurred. This has caused the Saudi Arabian people to recognize the necessity of preventive measures and explore alternative systems, such as using natural products (NPs), for treating their infection. Therefore, the specific objectives of this study were to explore the factors that influence the selection of NPs for COVID-19 management and to know the outcome of using NPs in COVID-19 infection management. This observational cross-sectional study was conducted in Saudi Arabia between February and April 2022. The validated pretested questionnaire was distributed among different regions of the country via a purposive snowball sampling procedure. Both descriptive statistics and stepwise regression analyses were carried out to evaluate the parameters related to the use of medicinal plants for the prevention of COVID-19 and the treatment of respiratory symptoms during the pandemic. The data obtained were statistically analyzed using IBM SPSS Statistics for Windows, version 25 (IBM Corp., Armonk, NY, USA). Of the 677 participants, 65% reported using NPs for themselves or family members during COVID-19. Utilizing NPs is always given priority by a significant (p < 0.001) percentage of survey respondents. Further, a highly significant (p < 0.001) percentage of participants felt that using NPs reduced their COVID-19 symptoms without having any remarkable (p < 0.001) adverse effects. Family and friends (59%) were the most frequent sources of information about utilizing NPs, followed by personal experience (41%). Honey (62.7%) and ginger (53.8%) were the most utilized NP among participants. Moreover, black seeds, garlic and turmeric were used by 40.5%, 37.7% and 26.3% of the surveyors, respectively. Those who used NPs before COVID-19 were 72.9% more likely to use them during COVID-19. NPs are more likely to be used by 75% of people who live in the central part of the country and whose families prefer it. This is true even if other factors are considered, such as the practice of using NPs along with traditional therapies and the fact that some participants' families prefer it. Our findings show that NPs were commonly used to treat COVID-19 infection among Saudi Arabian residents. Close friends and family members mainly encouraged the use of NPs. Overall, the use of NPs was high among those who participated in our study; such practices are strongly impacted by society. It is essential to promote extensive studies to improve the recognition and accessibility of these products. Authorities should also educate the people about the benefits and risks of using commonly used NPs, especially those reported in this study.

Unsupervised machine learning framework for discriminating major variants of concern during COVID-19

Due to the high mutation rate of the virus, the COVID-19 pandemic evolved rapidly. Certain variants of the virus, such as Delta and Omicron emerged with altered viral properties leading to severe transmission and death rates. These variants burdened the medical systems worldwide with a major impact to travel, productivity, and the world economy. Unsupervised machine learning methods have the ability to compress, characterize, and visualize unlabelled data. This paper presents a framework that utilizes unsupervised machine learning methods to discriminate and visualize the associations between major COVID-19 variants based on their genome sequences. These methods comprise a combination of selected dimensionality reduction and clustering techniques. The framework processes the RNA sequences by performing a k-mer analysis on the data and further visualises and compares the results using selected dimensionality reduction methods that include principal component analysis (PCA), t-distributed stochastic neighbour embedding (t-SNE), and uniform manifold approximation projection (UMAP). Our framework also employs agglomerative hierarchical clustering to visualize the mutational differences among major variants of concern and country-wise mutational differences for selected variants (Delta and Omicron) using dendrograms. We also provide country-wise mutational differences for selected variants via dendrograms. We find that the proposed framework can effectively distinguish between the major variants and has the potential to identify emerging variants in the future.

Comparison of AstraZeneca and sinopharm vaccines as boosters in protection against COVID-19 infection

BACKGROUND

As the global number of confirmed cases rises past 640 million, vaccination remains the most effective measure in controlling COVID-19. Studies have shown that two doses of vaccination can significantly reduce hospitalization and mortality rates among patients, but the effectiveness of booster doses is also important. We aimed to evaluate the role played by the type of the 3rd dose of vaccination by comparing the safety and efficacy of two common vaccination histories differing only in the 3rd received dose.

METHODS

We conducted a cross-sectional study on patients with respiratory symptoms suspected of having SARS-CoV-2 infection using Real-time PCR. We also collected information on the age, gender, and type of vaccine received for the third dose.

RESULTS

Out of 346 cases with respiratory symptoms, 120 cases tested positive for SARS-CoV-2 and had received two doses of Sinopharm and a different booster dose of either AZD1222 (AstraZeneca) or BIBP (Sinopharm). Among these 120 patients, vaccination with AZD1222 as a booster dose resulted in fewer symptoms compared to those vaccinated with three doses of BIBP.

CONCLUSIONS

Our study demonstrates that booster doses can help reduce hospitalization and the severity of infection, and it appears that a combination of different vaccines may be effective against severe COVID-19 infection.

The influence of meteorological factors on COVID-19 spread in Italy during the first and second wave

The relation between meteorological factors and COVID-19 spread remains uncertain, particularly with regard to the role of temperature, relative humidity and solar ultraviolet (UV) radiation. To assess this relation, we investigated disease spread within Italy during 2020. The pandemic had a large and early impact in Italy, and during 2020 the effects of vaccination and viral variants had not yet complicated the dynamics. We used non-linear, spline-based Poisson regression of modeled temperature, UV and relative humidity, adjusting for mobility patterns and additional confounders, to estimate daily rates of COVID-19 new cases, hospital and intensive care unit admissions, and deaths during the two waves of the pandemic in Italy during 2020. We found little association between relative humidity and COVID-19 endpoints in both waves, whereas UV radiation above 40 kJ/m² showed a weak inverse association with hospital and ICU admissions in the first wave, and a stronger relation with all COVID-19 endpoints in the second wave. Temperature above 283 K (10 °C/50 °F) showed a strong non-linear negative relation with COVID-19 endpoints, with inconsistent relations below this cutpoint in the two waves. Given the biological plausibility of a relation between temperature and COVID-19, these data add support to the proposition that temperature above 283 K, and possibly high levels of solar UV radiation, reduced COVID-19 spread.

Effect of religious fatalism and concern about new variants on the acceptance of COVID-19 vaccines

Introduction

To protect public health, it is important that the population be vaccinated against COVID-19; however, certain factors can affect vaccine acceptance.

Objective

The objective of this study was to determine whether religious fatalism and concern about new variants have a significant effect on the acceptance of COVID-19 vaccines.

Methodology

An explanatory study was conducted with 403 adults of legal age captured through non-probabilistic convenience sampling in vaccination centers in the 13 health networks of the Regional Health Directorate of Puno, Peru. Data were collected through a brief scale of religious fatalism, a scale of acceptance of vaccines against COVID-19 and a scale of concern about a new variant of COVID-19.

Results

The proposed model obtained an adequate fit. There was a negative effect of religious fatalism on vaccine acceptance, a positive effect of fatalism on vaccine rejection, a positive effect of concern about new variants on the acceptance of vaccines, and a positive effect of concern about new variants on vaccine rejection.

Conclusion

These findings provide evidence for the usefulness of considering both religious fatalism and concern about new variants affect the intention to receive the COVID-19 vaccine in adults in southern Peru.

Genomic epidemiology of SARS-CoV-2 infections in The Gambia: an analysis of routinely collected surveillance data between March, 2020, and January, 2022

BACKGROUND

COVID-19, caused by SARS-CoV-2, is one of the deadliest pandemics of the past 100 years. Genomic sequencing has an important role in monitoring of the evolution of the virus, including the detection of new viral variants. We aimed to describe the genomic epidemiology of SARS-CoV-2 infections in The Gambia.

METHODS

Nasopharyngeal or oropharyngeal swabs collected from people with suspected cases of COVID-19 and international travellers were tested for SARS-CoV-2 with standard RT-PCR methods. SARS-CoV-2-positive samples were sequenced according to standard library preparation and sequencing protocols. Bioinformatic analysis was done using ARTIC pipelines and Pangolin was used to assign lineages. To construct phylogenetic trees, sequences were first stratified into different COVID-19 waves (waves 1-4) and aligned. Clustering analysis was done and phylogenetic trees constructed.

FINDINGS

Between March, 2020, and January, 2022, 11 911 confirmed cases of COVID-19 were recorded in The Gambia, and 1638 SARS-CoV-2 genomes were sequenced. Cases were broadly distributed into four waves, with more cases during the waves that coincided with the rainy season (July-October). Each wave occurred after the introduction of new viral variants or lineages, or both, generally those already established in Europe or in other African countries. Local transmission was higher during the first and third waves (ie, those that corresponded with the rainy season), in which the B.1.416 lineage and delta (AY.34.1) were dominant, respectively. The second wave was driven by the alpha and eta variants and the B.1.1.420 lineage. The fourth wave was driven by the omicron variant and was predominantly associated with the BA.1.1 lineage.

INTERPRETATION

More cases of SARS-CoV-2 infection were recorded in The Gambia during peaks of the pandemic that coincided with the rainy season, in line with transmission patterns for other respiratory viruses. The introduction of new lineages or variants preceded epidemic waves, highlighting the importance of implementing well structured genomic surveillance at a national level to detect and monitor emerging and circulating variants.

FUNDING

Medical Research Unit The Gambia at London School of Hygiene & Tropical Medicine, UK Research and Innovation, WHO.

The global dynamic transmissibility of COVID-19 and its influencing factors: an analysis of control measures from 176 countries

OBJECTIVE

To summarise the dynamic characteristics of COVID-19 transmissibility; To analyse and quantify the effect of control measures on controlling the transmissibility of COVID-19; To predict and compare the effectiveness of different control measures.

METHODS

We used the basic reproduction number ([Formula: see text]) to measure the transmissibility of COVID-19, the transmissibility of COVID-19 and control measures of 176 countries and regions from January 1, 2020 to May 14, 2022 were included in the study. The dynamic characteristics of COVID-19 transmissibility were summarised through descriptive research and a Dynamic Bayesian Network (DBN) model was constructed to quantify the effect of control measures on controlling the transmissibility of COVID-19.

RESULTS

The results show that the spatial transmissibility of COVID-19 is high in Asia, Europe and Africa, the temporal transmissibility of COVID-19 increases with the epidemic of Beta and Omicron strains. Dynamic Bayesian Network (DBN) model shows that the transmissibility of COVID-19 is negatively correlated with control measures. Restricting population mobility has the strongest effect, nucleic acid testing (NAT) has a strong effect, and vaccination has the weakest effect.

CONCLUSION

Strict control measures are essential for controlling the COVID-19 outbreak; Restricting population mobility and nucleic acid testing (NAT) have significant impacts on controlling the COVID-19 transmissibility, while vaccination has no significant impact. In light of these findings, future control measures may include the widespread use of new NAT technology and the promotion of booster immunization.

A Statistical Synopsis of COVID-19 Components and Descriptive Analysis of Their Socio-Economic and Healthcare Aspects in Bangladesh Perspective

The aim of the work is to analyze the socio-economic and healthcare aspects that arise in the contemporary COVID-19 situation from Bangladesh perspective. We elaborately discuss the successive COVID-19 occurrences in Bangladesh with consequential information. The components associated with the COVID-19 commencement and treatment policy with corresponding features and their consequences are patently delineated. The effect of troublesome issues related to the treatment is detailed with supporting real-time data. We elucidate the applications of modern technologies advancement in epidemiological aspects and their existent compatibility in Bangladesh. We statistically analyze the real-time data through figurative and tabular approaches. Some relevant measures of central tendency and dispersion are utilized to explore the data structure and its observable specifications. For a clear manifestation, Z- scores of the COVID-19 components are analyzed through the Box-Whisker plot. We have discovered that the gathered data exhibit features that are unsatisfactory for the normal distribution, are highly positively skewed, and are predominated by the earliest occurrences. Infections and deaths were initially lower than the global average, but they drastically rose in the first quarter of 2021 and persisted for the remainder of the year. Substantial preventive results were produced by the region-wisetime-worthy moves. In the fourth quarter of 2021, the infections and deaths noticeably decreased, and the number of recoveries was highly significant. In the middle of 2022, a lethal rise in infections was observed in Bangladesh and that was quickly stabilized, and the pandemic ingredients were under control. According to our assessment, some concluding remarks are made at the end of this work.

Risk of death, hospitalization and intensive care unit admission by SARS-CoV-2 variants in Peru: a retrospective study

OBJECTIVES

Peru has had the highest death toll from the pandemic worldwide; however, it is not clear what the effects of the different variants on these outcomes are. The study aimed to evaluate the risk of death, hospitalization, and intensive care unit (ICU) admission rates of COVID-19 according to the SARS-CoV-2 variants detected in Peru from March 2020-February 2022.

METHODS

Retrospective study using open-access databases were published by the Peruvian Ministry of Health. Databases of genomic sequencing, death, COVID-19 cases, hospitalization and ICU, and vaccination were used. Crude and adjusted Cox proportional hazards regressions with clustered variances were modeled to calculate the hazard ratio (HR) of outcomes by variant.

RESULTS

Lambda variant had the highest risk of death (HR 1.92, 95% CI 1.37-2.68), whereas the Delta variant had the lowest risk (HR 0.50, 95% CI 0.31-0.82). Mu variant had the highest risk of hospitalization (HR: 2.39, 95% CI 1.56-3.67), Omicron the lowest (HR 0.45, 95%CI 0.23-0.90), and Gamma had the highest ICU admission rate (HR 1.95, 95%CI 1.40-2.71).

CONCLUSION

SARS-CoV-2 variants showed distinctive risks of clinical outcomes, which could have implications for the management of infected persons during the pandemic.

Scientific evidence on the origin of SARS-CoV-2

Even reaching the end of the year 2022, there is still a controversy on the origin of the SARS-CoV-2 virus. This Virtual Special Issue (VSI), focused on the "Scientific evidence on the origin of SARS-CoV-2", was launched some months ago with the aim of stimulating the submission of new high quality scientific research papers on the matter, to shed light on it. As indicated in the call for papers, the Editors involved in the VSI were aware of the difficulties of presenting concluding facts on that issue, however, bearing in mind that some teams of researchers had started investigations regarding this subject, a VSI like this (searching for stimulating the scientific controversy while requiring scientific evidence), could help to elucidate complicated aspects, going a step ahead in this way. The Editors made a call encouraging interested teams of researchers having solid results to submit high quality manuscripts dealing with this crucial theme. We thought -and we still think-that it is of maximum interest for the scientific community, as well as for the whole society, now and probably for the future. The VSI have received 50 submissions, which could be considered a limited number highlighting the difficulties of elaborating new high-quality manuscripts providing solid evidence on the matter. After a careful peer-review, those manuscripts considered to reach the highest scientific value were accepted for publication. The Editors think that the set of papers included in this VSI constitute interesting and high-quality contributions, providing further scientific knowledge on this issue. In this editorial piece, the Editors make some comments on the papers published, including some additional reflections.

Efficient Tracing of the SARS-CoV-2 Omicron Variants in Santa Barbara County Using a Rapid Quantitative Reverse Transcription PCR Assay

The emergence of the SARS-CoV-2 Omicron variant in 2021 is associated with a global surge of cases in late 2021 and early 2022. Identifying the introduction of novel SARS-CoV-2 variants to a population is imperative to inform decisions by clinicians and public health officials. Here, we describe a quantitative reverse transcription PCR-based assay (RT-qPCR) targeting unique mutations in the Omicron BA.1/BA1.1 and BA.2 viral genomes. This assay accurately and precisely detect the presence of these Omicron variants in patient samples in less than four hours. Using this assay, we tested 270 clinical samples and detected the introduction of Omicron BA.1/BA1.1 and BA.2 in the Santa Barbara County (SBC) population in December 2021 and February 2022, respectively. Identifying Omicron variants using this RT-qPCR assay showed complete concordance with whole viral genome sequencing; both assays indicated that Omicron was the dominant variant in SB County. Our data substantiate that RT-qPCR-based virus detection assays offer a fast and inexpensive alternative to NGS for virus variant-specific detection approach, which allows streamlining the detection of Omicron variants in patient samples.

The Impact of Demographic, Clinical Characteristics and the Various COVID-19 Variant Types on All-Cause Mortality: A Case-Series Retrospective Study

(1) Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has rapidly evolved into a pandemic affecting virtually every country in the world. We evaluated the demographic, clinical, laboratory, and all-cause mortality of moderate and severe COVID-19 patients admitted to a tertiary care hospital in Oman during the different COVID-19 waves and variant types. (2) Methods: A case-series retrospective study was carried out between 12 March 2020 and 30 June 2022. All adults over the age of 18 with laboratory-confirmed COVID-19 were enrolled. Analyses were performed using univariate and multivariate statistics. (3) Results: A total of 1462 confirmed cases enrolled with the mean age of the cohort was 55 ± 17 years with significant differences among the groups (p = 0.006). A total of 63% and 80% of the patients were males and citizens of Oman, respectively. Patients infected with the Alpha COVID-19 variant type were more likely to have acute respiratory distress syndrome (ARDS) (p < 0.001), stay longer in the hospital (p < 0.001), and get admitted to the intensive care unit (ICU) (p < 0.001). At the same time, those who had the Omicron COVID-19 type were more likely to have renal impairment (p < 0.001) and less likely to be associated with non-invasive ventilation (NIV) (p = 0.001) compared with other COVID-19 variant types. The Delta (adjusted odds ratio (aOR), 1.8; 95% confidence interval (CI): 1.22−2.66; p = 0.003) and Omicron (aOR, 1.88; 95% CI: 1.09−3.22; p = 0.022) COVID-19 variant types were associated with higher all-cause mortality when compared to the initial COVID-19 variant. Old age (aOR, 1.05; 95% CI: 1.04−1.06; p < 0.001), the presence of respiratory disease (aOR, 1.58; 95% CI: 1.02−2.44; p = 0.04), ICU admission (aOR, 3.41; 95% CI: 2.16−5.39; p < 0.001), lower eGFR (aOR, 1.61; 95% CI: 1.17−2.23; p = 0.004), and ARDS (aOR, 5.75; 95% CI: 3.69−8.98; p < 0.001) were also associated with higher mortality while NIV requirements were associated with lower odds of dying (aOR, 0.65; 95% CI: 0.46−0.91; p = 0.012). (4) Conclusions: Alpha and Delta variants were associated with a longer hospital stay, need for intensive care, mechanical ventilation, and increased mortality. Old age, cardiac renal dysfunction were commonly associated with Omicron variants. Large-scale national studies to further assess the risk factors for mortality related to COVID-19 waves are warranted.

Aptamer-Gated Mesoporous Silica Nanoparticles for N Protein Triggered Release of Remdesivir and Treatment of Novel Coronavirus (2019-nCoV)

Since the 2019-nCoV outbreak was first reported, hundreds of millions of people all over the world have been infected. There is no doubt that improving the cure rate of 2019-nCoV is one of the most effective means to deal with the current serious epidemic. At present, Remdesivir (RDV) has been clinically proven to be effective in the treatment of SARS-CoV-2. However, the uncertain side effects make it important to reduce the use of drugs while ensuring the self-healing effect. We report an approach here with targeted therapy for the treatment of SARS-CoV-2 and other coronaviruses illness. In this study, mesoporous silica was used as the carrier of RDV, the nucleocapsid protein (N protein) aptamer was hybridized with the complementary chain, and the double-stranded DNA was combined with gold nanoparticles as the gates of mesoporous silica pores. When the RDV-loaded mesoporous silica is incubated with the N protein, aptamer with gold nanoparticles dissociate from the complementary DNA oligonucleotide on the mesoporous silica surface and bind to the N protein. The releasing of RDV was determined by detecting the UV-vis absorption peak of RDV in the solution. These results show that the RDV delivery system designed in this work has potential clinical application for the treatment of 2019-nCoV.

A comparative overview of SARS-CoV-2 and its variants of concern

In December 2019, the severe acute respiratory syndrome 2 (SARS-CoV-2) coronavirus outbreak began in Wuhan, China, and quickly spread to practically every corner of the globe, killing millions of people. SARS-CoV-2 produced numerous variants, five of which have been identified as variants of concern (VOC) by the World Health Organization (WHO) (Alpha, Beta, Gamma, Delta, and Omicron). We conducted a comparative epidemiological analysis of SARS-CoV-2 and its VOC in this paper. We compared the effects of various spike (S) protein mutations in SARS-CoV-2 and its VOC on transmissibility, illness severity, hospitalization risk, fatality rate, immunological evasion, and vaccine efficacy in this review. We also looked into the clinical characteristics of patients infected with SARS-CoV-2 and its VOC.

Filtration efficiency of N95 filtering facepiece respirators during multi-cycles of '8-hour simulated donning + disinfection'

BACKGROUND

Aerosol-borne diseases such as COVID-19 may outbreak occasionally in various regions of the world, inevitably resulting in short-term shortage and corresponding reuse of disposable respirators.

AIM

To investigate the effective disinfection methods, reusable duration and frequency of N95 respirators.

METHODS

Based on the self-built respirator simulation test system, and under combinations of experimental conditions of three N95 respirators × 0-200 nm NaCl aerosols × three simulated breathing flow rates (15, 50 and 85 L/min) × two disinfection methods (dry heating and ultraviolet (UV) radiation), this study continuously measured the changes in filtration efficiency of all respirators during multi-cycles of '8-h simulated donning + disinfection' until the penetration reached ≥5%.

FINDINGS

Multi-cycles of dry heating and UV radiation treatments on the reused (i.e., multiple 8-h donning) N95 respirators had a minimal effect (<0.5%) on the respirator filtration efficiency, and even at 85 L/min, all tested N95 respirators were able to maintain filtration efficiencies ≥95% for at least 30 h or four reuse cycles of '8-h donning + disinfection', while a lower breathing flow rate (15 L/min) plus the exhalation valve could further extend the N95 respirator's usability duration up to 140 h or 18 reuse cycles of '8-h donning + disinfection'. As the respirator wearing time extended, aerosol penetration slowly increased in a quadratic function with a negative second-order coefficient, and the penetration increment during each cycle of 8-h donning was less than 0.9%.

CONCLUSION

Multi-cycles of N95 respirator reuse in combination with dry heating or UV irradiation disinfection are feasible.

Contrasting Epidemiology and Population Genetics of COVID-19 Infections Defined by Multilocus Genotypes in SARS-CoV-2 Genomes Sampled Globally

Since its emergence in 2019, SARS-CoV-2 has spread and evolved globally, with newly emerged variants of concern (VOCs) accounting for more than 500 million COVID-19 cases and 6 million deaths. Continuous surveillance utilizing simple genetic tools is needed to measure the viral epidemiological diversity, risk of infection, and distribution among different demographics in different geographical regions. To help address this need, we developed a proof-of-concept multilocus genotyping tool and demonstrated its utility to monitor viral populations sampled in 2020 and 2021 across six continents. We sampled globally 22,164 SARS-CoV-2 genomes from GISAID (inclusion criteria: available clinical and demographic data). They comprised two study populations, “2020 genomes” (N = 5959) sampled from December 2019 to September 2020 and “2021 genomes” (N = 16,205) sampled from 15 January to 15 March 2021. All genomes were aligned to the SARS-CoV-2 reference genome and amino acid polymorphisms were called with quality filtering. Thereafter, 74 codons (loci) in 14 genes including orf1ab polygene (N = 9), orf3a, orf8, nucleocapsid (N), matrix (M), and spike (S) met the 0.01 minimum allele frequency criteria and were selected to construct multilocus genotypes (MLGs) for the genomes. At these loci, 137 mutant/variant amino acids (alleles) were detected with eight VOC-defining variant alleles, including N KR203&204, orf1ab (I265, F3606, and L4715), orf3a H57, orf8 S84, and S G614, being predominant globally with > 35% prevalence. Their persistence and selection were associated with peaks in the viral transmission and COVID-19 incidence between 2020 and 2021. Epidemiologically, older patients (≥20 years) compared to younger patients (<20 years) had a higher risk of being infected with these variants, but this association was dependent on the continent of origin. In the global population, the discriminant analysis of principal components (DAPC) showed contrasting patterns of genetic clustering with three (Africa, Asia, and North America) and two (North and South America) continental clusters being observed for the 2020 and 2021 global populations, respectively. Within each continent, the MLG repertoires (range 40−199) sampled in 2020 and 2021 were genetically differentiated, with ≤4 MLGs per repertoire accounting for the majority of genomes sampled. These data suggested that the majority of SARS-CoV-2 infections in 2020 and 2021 were caused by genetically distinct variants that likely adapted to local populations. Indeed, four GISAID clade-defined VOCs - GRY (Alpha), GH (Beta), GR (Gamma), and G/GK (Delta variant) were differentiated by their MLG signatures, demonstrating the versatility of the MLG tool for variant identification. Results from this proof-of-concept multilocus genotyping demonstrates its utility for SARS-CoV-2 genomic surveillance and for monitoring its spatiotemporal epidemiology and evolution, particularly in response to control interventions including COVID-19 vaccines and chemotherapies.

Exploring the risk factors of COVID-19 Delta variant in the USA based on Bayesian spatio-temporal analysis

The transmission of coronavirus disease‐2019 (COVID‐19) epidemic is a global emergency, which is worsened by the genetic mutations of SARS‐CoV‐2. However, till date, few statistical studies have researched the COVID‐19 spread patterns in terms of the variant cases. Hence, this paper aims to explore the associated risk factors of Delta variant, the most contagious strain of COVID‐19. The study collected the state‐level COVID‐19 Delta variant cases in the United States during a 12‐week period and included potential environmental, socioeconomic, and public prevention factors as independent variables. Instead of regarding the covariate effects as constant, this paper proposes a flexible Bayesian hierarchical model with spatio‐temporally varying coefficients to account for data heterogeneity. The method enables us to cluster the states into distinctive groups based on the temporal trends of the coefficients and simultaneously identify significant risk factors for each cluster. The findings contribute novel insight into the dynamics of covariate effects on the COVID‐19 Delta variant over space and time, which could help the government develop targeted prevention measures for vulnerable regions based on the selected risk factors.

A Multivalent Vaccine Based on Ferritin Nanocage Elicits Potent Protective Immune Responses against SARS-CoV-2 Mutations

The SARS-CoV-2 pandemic has created a global public crisis and heavily affected personal lives, healthcare systems, and global economies. Virus variants are continuously emerging, and, thus, the pandemic has been ongoing for over two years. Vaccines were rapidly developed based on the original SARS-CoV-2 (Wuhan-Hu-1) to build immunity against the coronavirus disease. However, they had a very low effect on the virus' variants due to their low cross-reactivity. In this study, a multivalent SARS-CoV-2 vaccine was developed using ferritin nanocages, which display the spike protein from the Wuhan-Hu-1, B.1.351, or B.1.429 SARS-CoV-2 on their surfaces. We show that the mixture of three SARS-CoV-2 spike-protein-displaying nanocages elicits CD4+ and CD8+ T cells and B-cell immunity successfully in vivo. Furthermore, they generate a more consistent antibody response against the B.1.351 and B.1.429 variants than a monovalent vaccine. This leads us to believe that the proposed ferritin-nanocage-based multivalent vaccine platform will provide strong protection against emerging SARS-CoV-2 variants of concern (VOCs).

Determinants of COVID-19 skepticism and SARS-CoV-2 vaccine hesitancy: findings from a national population survey of U.S. adults

BACKGROUND

The enduring presence of COVID-19 skepticism and SARS-CoV-2 vaccine hesitancy is an ongoing impediment to the global response effort to the current pandemic. This study seeks to identify determinants of skepticism and vaccine hesitancy in U.S. adults.

METHODS

Data are from the Values and Beliefs of the American Public Survey, conducted in 2021 by the Gallup Organization in conjunction with Baylor University. The survey used stratified random probability sampling of the U.S. adult population (N = 1222). Outcome measures were respective single items assessing COVID-19 skepticism and SARS-CoV-2 vaccine hesitancy. Exposure variables included political, religious, and sociodemographic indicators, and moderators assessed personal history of COVID-19 and losing a relative or close friend to COVID-19.

RESULTS

Skepticism and vaccine hesitancy were strongly associated with conservative and Republican political preference and conservative religious beliefs, and less so with socioeconomic status. Personal experience with COVID-19 did not mitigate the effect of politics on skepticism and barely reduced the odds for hesitancy. Results confirm that attitudes toward COVID-19 are politically and religiously conditioned, and are especially a product of conservative political preference.

CONCLUSION

Skepticism about COVID-19 and hesitancy regarding SARS-CoV-2 vaccination are highest among the political and religious right. Efforts to increase immunization through public education may be inadequate; resistance appears ideological. Other solutions may need to be considered, which risk widespread pushback both politically and religiously motivated.

Genetic diversity of SARS-CoV-2 infections in Ghana from 2020-2021

The COVID-19 pandemic is one of the fastest evolving pandemics in recent history. As such, the SARS-CoV-2 viral evolution needs to be continuously tracked. This study sequenced 1123 SARS-CoV-2 genomes from patient isolates (121 from arriving travellers and 1002 from communities) to track the molecular evolution and spatio-temporal dynamics of the SARS-CoV-2 variants in Ghana. The data show that initial local transmission was dominated by B.1.1 lineage, but the second wave was overwhelmingly driven by the Alpha variant. Subsequently, an unheralded variant under monitoring, B.1.1.318, dominated transmission from April to June 2021 before being displaced by Delta variants, which were introduced into community transmission in May 2021. Mutational analysis indicated that variants that took hold in Ghana harboured transmission enhancing and immune escape spike substitutions. The observed rapid viral evolution demonstrates the potential for emergence of novel variants with greater mutational fitness as observed in other parts of the world.

The Impact of Lockdown, Patient Classification, and the Large-Scale Case Screening on the Spread of the Coronavirus Disease 2019 (COVID-19) in Hubei

The coronavirus disease (COVID-19) which emerged in Wuhan, China, in December 2019, is widely controlled now in China. However, the global epidemic is still severe. To study and comment on Hubei's approaches for responding to the disease, the paper considered some factors such as suspected cases (part of them are influenza patients or common pneumonia patients, etc.), quarantine, patient classification (three types), clinically diagnosed cases, and lockdown of Wuhan and Hubei. After that, the paper established an SELIHR model based on the surveillance data of Hubei published by the Hubei Health Commission from 10 January 2020 to 30 April 2020 and used the fminsearch optimization method to estimate the optimal parameters of the model. We obtained the basic reproduction number ℛ 0 = 3.1571 from 10 to 22 January. ℛ 0 was calculated as 2.0471 from 23 to 27 January. From 28 January to 30 April, ℛ 0 = 1.5014. Through analysis, it is not hard to find that the patients without classification during the period of confirmed cases will result in the cumulative number of cases in Hubei to increase. In addition, regarding the lockdown measures implemented by Hubei during the epidemic, our simulations also show that if the lockdown time of either Hubei or Wuhan is advanced, it will effectively curb the spread of the epidemic. If the lockdown measures are not taken, the total cumulative number of cases will increase substantially. From the results of the study, it can be concluded that the lockdown, patient classification, and the large-scale case screening are essential to slow the spread of COVID-19, which can provide references for other countries or regions.

The Impact and Evaluation of the COVID-19 Pandemic on the Teaching of Biology from the Perspective of Slovak School Teachers

The closing of schools due to COVID-19 was a critical incident that should have caused a rethinking of education in our country. Among the many changes that this crisis has brought, one is fully remote teaching. Our research focuses on a comparison of the changes between on-site and remote forms of biology teaching, the opinions and feelings of teaching staff across all the institutional levels, and their opinions regarding the usage of online teaching tools in the future. The research shows that teachers have used both time-tested teaching aids and modern technology to generate an environment that would be as close to on-site teaching as possible. Similarly, the teachers with longer teaching experience had felt a greater degree of stress during the remote teaching period. Teachers of primary and tertiary schools agree that they can imagine having a combined form of education in the future but that the practical classes of biology must be completed on-site. On the other hand, most secondary school teachers want to preserve only the on-site form of teaching. Our study provides information on the current state of coping with the pandemic situation in Slovakia from teachers’ perspectives.

Comparison of clinical features and perinatal outcomes between pre-variant and post-variant periods in pregnant women with SARS-CoV-2: analysis of 1935 cases

Purpose

To compare the clinical features and perinatal outcomes of pregnant women with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the pre-variant and post-variant periods.

Methods

This prospective cohort study includes pregnant women with SARS-CoV-2 who were followed-up at Ankara City Hospital between 11, March 2020 and 15, September 2021. Demographic features, clinical characteristics and pregnancy outcomes were compared between the pre-variant (n = 1416) and post-variant (n = 519) groups.

Results

The rates of severe and critical cases significantly increased in the post-variant group (9.7% vs 2%, p < 0.001). The rates of respiratory support (26.8% vs 7.3%, p < 0.001), ICU admission (12.9% vs 1.8%, p < 0.001) and maternal mortality (2.9% vs 0.4%, p < 0.001) were significantly higher in the post-variant group. A significant increase was observed for pregnancy complications in the post-variant group (45.6% vs 18.8%, p = 0.007). The rates of preterm delivery (26.4% vs 4.4%, p < 0.001) and NICU admission (34% vs 18.8%, p < 0.001) were significantly higher in the post-variant group. Positive, weak, statistically significant correlations were observed between the post-variant period, disease severity and maternal mortality (r = 0.19, r = 0.12 and p < 0.001).

Conclusion

Post-variant COVID-19 period was associated with a severe course of the disease and increased rates of adverse obstetric outcomes in pregnant patients.