The changing epidemiology of SARS-CoV-2

Genomic surveillance of SARS-CoV-2 in COVID-19 vaccinated healthcare workers in Lebanon

BACKGROUND

The emergence of SARS-CoV-2 variants including the Delta and Omicron along with waning of vaccine-induced immunity over time contributed to increased rates of breakthrough infection specifically among healthcare workers (HCWs). SARS-CoV-2 genomic surveillance is an important tool for timely detection and characterization of circulating variants as well as monitoring the emergence of new strains. Our study is the first national SARS-CoV-2 genomic surveillance among HCWs in Lebanon.

METHODS

We collected 250 nasopharyngeal swabs from HCWs across Lebanon between December 2021 and January 2022. Data on the date of positive PCR, vaccination status, specific occupation, and hospitalization status of participants were collected. Extracted viral RNA from nasopharyngeal swabs was converted to cDNA, library prepped using the coronaHIT method, followed by whole genome sequencing on the Illumina NextSeq 500 platform.

RESULTS

A total of 133 (57.1%) samples belonging to the Omicron (BA.1.1) sub-lineage were identified, as well as 44 (18.9%) samples belonging to the BA.1 sub-lineage, 28 (12%) belonging to the BA.2 sub-lineage, and only 15 (6.6%) samples belonging to the Delta variant sub-lineage B.1.617.2. These results show that Lebanon followed the global trend in terms of circulating SARS-CoV-2 variants with Delta rapidly replaced by the Omicron variant.

CONCLUSION

This study underscores the importance of continuous genomic surveillance programs in Lebanon for the timely detection and characterization of circulating variants. The latter is critical to guide public health policy making and to timely implement public health interventions.

Targeting RNA G-quadruplex with repurposed drugs blocks SARS-CoV-2 entry

The rapid emergence of SARS-CoV-2 variants of concern, the complexity of infection, and the functional redundancy of host factors, underscore an urgent need for broad-spectrum antivirals against the continuous COVID-19 pandemic, with drug repurposing as a viable therapeutic strategy. Here we report the potential of RNA G-quadruplex (RG4)-targeting therapeutic strategy for SARS-CoV-2 entry. Combining bioinformatics, biochemical and biophysical approaches, we characterize the existence of RG4s in several SARS-CoV-2 host factors. In silico screening followed by experimental validation identify Topotecan (TPT) and Berbamine (BBM), two clinical approved drugs, as RG4-stabilizing agents with repurposing potential for COVID-19. Both TPT and BBM can reduce the protein level of RG4-containing host factors, including ACE2, AXL, FURIN, and TMPRSS2. Intriguingly, TPT and BBM block SARS-CoV-2 pseudovirus entry into target cells in vitro and murine tissues in vivo. These findings emphasize the significance of RG4 in SARS-CoV-2 pathogenesis and provide a potential broad-spectrum antiviral strategy for COVID-19 prevention and treatment.

COVID-19 epidemic and public health interventions in Shanghai, China: Statistical analysis of transmission, correlation and conversion

Background

The Shanghai COVID-19 epidemic is an important example of a local outbreak and of the implementation of normalized prevention and disease control strategies. The precise impact of public health interventions on epidemic prevention and control is unknown.

Methods

We collected information on COVID-19 patients reported in Shanghai, China, from January 30 to May 31, 2022. These newly added cases were classified as local confirmed cases, local asymptomatic infections, imported confirmed cases and imported asymptomatic infections. We used polynomial fitting correlation analysis and illustrated the time lag plot in the correlation analysis of local and imported cases. Analyzing the conversion of asymptomatic infections to confirmed cases, we proposed a new measure of the conversion rate (C _r ). In the evolution of epidemic transmission and the analysis of intervention effects, we calculated the effective reproduction number (R _t ). Additionally, we used simulated predictions of public health interventions in transmission, correlation, and conversion analyses.

Results

(1) The overall level of R _t in the first three stages was higher than the epidemic threshold. After the implementation of public health intervention measures in the third stage, R _t decreased rapidly, and the overall R _t level in the last three stages was lower than the epidemic threshold. The longer the public health interventions were delayed, the more cases that were expected and the later the epidemic was expected to end. (2) In the correlation analysis, the outbreak in Shanghai was characterized by double peaks. (3) In the conversion analysis, when the incubation period was short (3 or 7 days), the conversion rate fluctuated smoothly and did not reflect the effect of the intervention. When the incubation period was extended (10 and 14 days), the conversion rate fluctuated in each period, being higher in the first five stages and lower in the sixth stage.

Conclusion

Effective public health interventions helped slow the spread of COVID-19 in Shanghai, shorten the outbreak duration, and protect the healthcare system from stress. Our research can serve as a positive guideline for addressing infectious disease prevention and control in China and other countries and regions.

Trends in Disease Severity Among Critically Ill Children With Severe Acute Respiratory Syndrome Coronavirus 2: A Retrospective Multicenter Cohort Study in the United States

OBJECTIVES

To describe trends in critical illness from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in children over the course of the COVID-19 pandemic. We hypothesized that PICU admission rates were higher in the Omicron period compared with the original outbreak but that fewer patients needed endotracheal intubation.

DESIGN

Retrospective cohort study.

SETTING

This study took place in nine U.S. PICUs over 3 weeks in January 2022 (Omicron period) compared with 3 weeks in March 2020 (original period).

PATIENTS

Patients less than or equal to 21 years old who screened positive for SARS-CoV-2 infection by polymerase chain reaction or hospital-based rapid antigen test and were admitted to a PICU or intermediate care unit were included.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

A total of 267 patients (239 Omicron and 28 original) were reviewed. Forty-five patients in the Omicron cohort had incidental SARS-CoV-2 and were excluded from analysis. The Omicron cohort patients were younger compared with the original cohort patients (median [interquartile range], 6 yr [1.3-13.3 yr] vs 14 yr [8.3-17.3 yr]; p = 0.001). The Omicron period, compared with the original period, was associated with an average increase in COVID-19-related PICU admissions of 13 patients per institution (95% CI, 6-36; p = 0.008), which represents a seven-fold increase in the absolute number admissions. We failed to identify an association between cohort period (Omicron vs original) and odds of intubation (odds ratio, 0.7; 95% CI, 0.3-1.7). However, we cannot exclude the possibility of up to 70% reduction in intubation.

CONCLUSIONS

COVID-19-related PICU admissions were seven times higher in the Omicron wave compared with the original outbreak. We could not exclude the possibility of up to 70% reduction in use of intubation in the Omicron versus original epoch, which may represent differences in PICU/hospital admission policy in the later period, or pattern of disease, or possibly the impact of vaccination.

Primary and booster vaccination in reducing severe clinical outcomes associated with Omicron Naïve infection

BACKGROUND

Little is known about long-term effectiveness of COVID-19 vaccine in reducing severity and deaths associated with Omicron VOC not perturbed by prior infection and independent of oral anti-viral therapy and non-pharmaceutical (NPI).

METHODS

A retrospective observational cohort study was applied to Taiwan community during the unprecedent large-scale outbreaks of Omicron BA.2 between April and August, 2022. Primary vaccination since March, 2021 and booster vaccination since January, 2022 were offered on population level. Oral Anti-viral therapy was also offered as of mid-May 2022. The population-based effectiveness of vaccination in reducing the risk of moderate and severe cases of and death from Omicron BA.2 with the consideration of NPI and oral anti-viral therapy were assessed by using Bayesian hierarchical models.

RESULTS

The risks of three clinical outcomes associated with Omicron VOC infection were lowest for booster vaccination, followed by primary vaccination, and highest for incomplete vaccination with the consistent trends of being at increased risk for three outcomes from the young people aged 12 years or below until the elderly people aged 75 years or older with 7 age groups. Before the period using oral anti-viral therapy, complete primary vaccination with the duration more than 9 months before outbreaks conferred the statistically significant 47 % (23-64 %) reduction of death, 48 % (30-61 %) of severe disease, and 46 % (95 % CI: 37-54 %) of moderate disease after adjusting for 10-20 % independent effect of NPI. The benefits of booster vaccination within three months were further enhanced to 76 % (95 % CI: 67-86 %), 74 % (95 % CI: 67-80 %), and 61 % (95 % CI: 56-65 %) for three corresponding outcomes. The additional effectiveness of oral anti-viral therapy in reducing moderate disease was 13 % for the booster group and 5.8 % for primary vaccination.

CONCLUSIONS

We corroborated population effectiveness of primary vaccination and its booster vaccination, independent of oral anti-viral therapy and NPI, in reducing severe clinical outcomes associated with Omicron BA.2 naïve infection population.

Stability of SARS-CoV-2 in cold-chain transportation environments and the efficacy of disinfection measures

Background

Low temperature is conducive to the survival of COVID-19. Some studies suggest that cold-chain environment may prolong the survival of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and increase the risk of transmission. However, the effect of cold-chain environmental factors and packaging materials on SARS-CoV-2 stability remains unclear.

Methods

This study aimed to reveal cold-chain environmental factors that preserve the stability of SARS-CoV-2 and further explore effective disinfection measures for SARS-CoV-2 in the cold-chain environment. The decay rate of SARS-CoV-2 pseudovirus in the cold-chain environment, on various types of packaging material surfaces, i.e., polyethylene plastic, stainless steel, Teflon and cardboard, and in frozen seawater was investigated. The influence of visible light (wavelength 450 nm-780 nm) and airflow on the stability of SARS-CoV-2 pseudovirus at -18°C was subsequently assessed.

Results

Experimental data show that SARS-CoV-2 pseudovirus decayed more rapidly on porous cardboard surfaces than on nonporous surfaces, including polyethylene (PE) plastic, stainless steel, and Teflon. Compared with that at 25°C, the decay rate of SARS-CoV-2 pseudovirus was significantly lower at low temperatures. Seawater preserved viral stability both at -18°C and with repeated freeze-thaw cycles compared with that in deionized water. Visible light from light-emitting diode (LED) illumination and airflow at -18°C reduced SARS-CoV-2 pseudovirus stability.

Conclusion

Our studies indicate that temperature and seawater in the cold chain are risk factors for SARS-CoV-2 transmission, and LED visible light irradiation and increased airflow may be used as disinfection measures for SARS-CoV-2 in the cold-chain environment.

When green enters a room: A scoping review of epidemiological studies on indoor plants and mental health

BACKGROUND

Increasing numbers of epidemiological studies are investigating the association between outdoor greenery and various health outcomes. However, in the case of indoor plants, although experimental studies seem relatively abundant, epidemiological studies remain scarce, and research considering the mental health effects is even more limited. Thus, we aim to identify and summarise the relevant epidemiological studies on indoor plant exposure and mental health via this scoping review, thereby presenting the current state of knowledge and research niches.

METHODS

PubMed and PsycINFO were systematically searched for epidemiological studies on indoor plant exposure and mental health, including mental and behavioural disorders, quality of life, and cognitive function. The publication period was from the inception of these two databases to 22nd June 2022. We extracted information on exposure to indoor plants and mental health-related outcomes from the relevant studies.

RESULTS

The systematic search yielded 1186 unique results. Six studies met the inclusion criteria and were finally included in this scoping review. All included studies were Europe-based cross-sectional studies on mental and behavioural disorders. One study was conducted in 2015 and investigated the office environment, whereas the other five were conducted during the COVID-19 pandemic and focused on the home environment. Despite considerable heterogeneity in outcome assessments and indoor plant exposure metrics, all six studies generally reported beneficial associations between having indoor plants and mental health, such as reducing stress, depressive symptoms, and negative emotions.

CONCLUSIONS

Epidemiological evidence on exposure to indoor plants and mental health is currently limited. In general, favourable effects of indoor plants are supported, although most relevant studies were conducted in the context of COVID-19. Before conducting more studies to explore the associations, data collection methods must be refined with more elaborate designs that allow for the measurement of more comprehensive metrics of indoor plants.

REGISTRATION

Open Science Framework, osf.io/5xr6b.

Likelihood-Free Dynamical Survival Analysis applied to the COVID-19 epidemic in Ohio

The Dynamical Survival Analysis (DSA) is a framework for modeling epidemics based on mean field dynamics applied to individual (agent) level history of infection and recovery. Recently, the Dynamical Survival Analysis (DSA) method has been shown to be an effective tool in analyzing complex non-Markovian epidemic processes that are otherwise difficult to handle using standard methods. One of the advantages of Dynamical Survival Analysis (DSA) is its representation of typical epidemic data in a simple although not explicit form that involves solutions of certain differential equations. In this work we describe how a complex non-Markovian Dynamical Survival Analysis (DSA) model may be applied to a specific data set with the help of appropriate numerical and statistical schemes. The ideas are illustrated with a data example of the COVID-19 epidemic in Ohio.

Frequently Asked Questions on Coronavirus Disease 2019 Vaccination for Hematopoietic Cell Transplantation and Chimeric Antigen Receptor T-Cell Recipients From the American Society for Transplantation and Cellular Therapy and the American Society of Hematology

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), disproportionately affects immunocompromised and elderly patients. Not only are hematopoietic cell transplantation (HCT) and chimeric antigen receptor (CAR) T-cell recipients at greater risk for severe COVID-19 and COVID-19-related complications, but they also may experience suboptimal immune responses to currently available COVID-19 vaccines. Optimizing the use, timing, and number of doses of the COVID-19 vaccines in these patients may provide better protection against SARS-CoV-2 infection and better outcomes after infection. To this end, current guidelines for COVID-19 vaccination in HCT and CAR T-cell recipients from the American Society of Transplantation and Cellular Therapy Transplant Infectious Disease Special Interest Group and the American Society of Hematology are provided in a frequently asked questions format.

Pathogen diversity in meta-population networks

The pathogen diversity means that multiple strains coexist, and widely exist in the biology systems. The new mutation of SARS-CoV-2 leading to worldwide pathogen diversity is a typical example. What are the main factors of inducing the pathogen diversity? Previous studies indicated the pathogen mutation is the most important reason for inducing the pathogen diversity. The traffic network and gene network are crucial in shaping the dynamics of pathogen contagion, while their roles for the pathogen diversity still lacking a theoretical study. To this end, we propose a reaction-diffusion process of pathogens with mutations on meta-population networks, which includes population movement and strain mutation. We extend the Microscopic Markov Chain Approach (MMCA) to describe the model. Traffic networks make pathogen diversity more likely to occur in cities with lower infection densities. The likelihood of pathogen diversity is low in cities with short effective distances in the traffic network. Star-type gene network is more likely to lead to pathogen diversity than lattice-type and chain-type gene networks. When pathogen localization is present, infection is localized to strains that are at the endpoints of the gene network. Both the increased probability of movement and mutation promote pathogen diversity. The results also show that the population tends to move to cities with short effective distances, resulting in the infection density is high.

Religious pluralism and the ethics of healthcare

Democratic societies that separate church and state face major challenges in accommodating religious convictions. This applies especially to determining healthcare policies. Building on our prior work on the demands and limits of religious accommodation in democratic societies, we propose a set of ethical standards that can guide societies in meeting this challenge. In applying and defending these standards, we explore three topics: vaccine resistance, abortion, and concerns about rights to healthcare. We clarify these and other issues of religious accommodation and propose ethical standards for approaching these and other problems.

Functional evolution of SARS-CoV-2 spike protein: Maintaining wide host spectrum and enhancing infectivity via surface charge of spike protein

The SARS-CoV-2 virus, which causes the COVID-19, is rapidly accumulating mutations to adapt to the hosts. We collected SARS-CoV-2 sequence data from the end of 2019 to January 2023 to analyze for their evolutionary features during the pandemic. We found that most of the SARS-CoV-2 genes are undergoing negative purifying selection, while the spike protein gene (S-gene) is undergoing rapid positive selection. From the original strain to the alpha, delta and omicron variant types, the Ka/Ks of the S-gene increases, while the Ka/Ks within one variant type decreases over time. During the evolution, the codon usage did not evolve towards optimal translation and protein expression. In contrast, only S-gene mutations showed a remarkable trend on accumulating more positive charges. This facilitates the infection via binding human ACE2 for cell entry and binding furin for cleavage. Such a functional evolution emphasizes the survival strategy of SARS-CoV-2, and indicated new druggable target to contain the viral infection. The nearly fully positively-charged interaction surfaces indicated that the infectivity of SARS-CoV-2 virus may approach a limit.

The past, present and future of tuberculosis treatment

Tuberculosis (TB) is an ancient infectious disease. Before the availability of effective drug therapy, it had high morbidity and mortality. In the past 100 years, the discovery of revolutionary anti-TB drugs such as streptomycin, isoniazid, pyrazinamide, ethambutol and rifampicin, along with drug combination treatment, has greatly improved TB control globally. As anti-TB drugs were widely used, multidrug-resistant (MDR) and extensively drug-resistant (XDR) strains of Mycobacterium tuberculosis emerged due to acquired genetic mutations, and this now presents a major problem for effective treatment. Genes associated with drug resistance have been identified, including katG mutations in isoniazid resistance, rpoB mutations in rifampin resistance, pncA mutations in pyrazinamide resistance, and gyrA mutations in quinolone resistance. The major mechanisms of drug resistance include loss of enzyme activity in prodrug activation, drug target alteration, overexpression of drug target, and overexpression of the efflux pump. During the disease process, Mycobacterium tuberculosis may reside in different microenvironments where it is expose to acidic pH, low oxygen, reactive oxygen species and anti-TB drugs, which can facilitate the development of non-replicating persisters and promote bacterial survival. The mechanisms of persister formation may include toxin-antitoxin (TA) modules, DNA protection and repair, protein degradation such as trans-translation, efflux, and altered metabolism. In recent years, the use of new anti-TB drugs, repurposed drugs, and their drug combinations has greatly improved treatment outcomes in patients with both drug-susceptible TB and MDR/XDR-TB. The importance of developing more effective drugs targeting persisters of Mycobacterium tuberculosis is emphasized. In addition, host-directed therapeutics using both conventional drugs and herbal medicines for more effective TB treatment should also be explored. In this article, we review historical aspects of the research on anti-TB drugs and discuss the current understanding and treatments of drug resistant and persistent tuberculosis to inform future therapeutic development.

Immunological Studies to Understand Hybrid/Recombinant Variants of SARS-CoV-2

The zoonotic SARS-CoV-2 virus was present before the onset of the pandemic. It undergoes evolution, adaptation, and selection to develop variants that gain high transmission rates and virulence, resulting in the pandemic. Structurally, the spike protein of the virus is required for binding to ACE2 receptors of the host cells. The gene coding for the spike is known to have a high propensity of mutations, as a result generating numerous variants. The variants can be generated by random point mutations or recombination during replication. However, SARS-CoV-2 can also produce hybrid variants on co-infection of the host by two distinct lineages of the virus. The genomic sequences of the two variants undergo recombination to produce the hybrid variants. Additionally, these sub-variants also contain numerous mutations from both the parent variants, as well as some novel mutations unique to the hybrids. The hybrid variants (XD, XE, and XF) can be identified through numerous techniques, such as peak PCR, NAAT, and hybrid capture SARS-CoV-2 NGS (next generation sequencing) assay, etc., but the most accurate approach is genome sequencing. There are numerous immunological diagnostic assays, such as ELISA, chemiluminescence immunoassay, flow-cytometry-based approaches, electrochemiluminescence immunoassays, neutralization assays, etc., that are also designed and developed to provide an understanding of the hybrid variants, their pathogenesis, and other reactions. The objective of our study is to comprehensively analyze the variants of SARS-CoV-2, especially the hybrid variants. We have also discussed the techniques available for the identification of hybrids, as well as the immunological assays and studies for analyzing the hybrid variants.

Rapid and Unamplified Detection of SARS-CoV-2 RNA via CRISPR-Cas13a-Modified Solution-Gated Graphene Transistors

The disease caused by severe acute respiratory syndrome coronavirus, SARS-CoV-2, is termed COVID-19. Even though COVID-19 has been out for more than two years, it is still causing a global pandemic. Due to the limitations of sample collection, transportation, and kit performance, the traditional reverse transcription-quantitative polymerase chain reaction (RT-qPCR) method has a long detection period and high testing costs. An increased risk of infection is inevitable, since many patients may not be diagnosed in time. The CRISPR-Cas13a system can be designed for RNA identification and knockdown, as a promising platform for nucleic acid detection. Here, we designed a solution-gated graphene transistor (SGGT) biosensor based on the CRISPR-Cas13a system. Using the gene-targeting capacity of CRISPR-Cas13a and gate functionalization via multilayer modification, SARS-CoV-2 nucleic acid sequences can be quickly and precisely identified without the need for amplification or fluorescence tagging. The limit of detection (LOD) in both buffer and serum reached the aM level, and the reaction time was about 10 min. The results of the detection of COVID-19 clinical samples from throat swabs agree with RT-PCR. In addition, the interchangeable gates significantly minimize the cost and time of device fabrication. In a nutshell, our biosensor technology is broadly applicable and will be suitable for point-of-care (POC) testing.

Dynamics of COVID-19 progression and the long-term influences of measures on pandemic outcomes

The pandemic progression is a dynamic process, in which measures yield outcomes, and outcomes in turn influence subsequent measures and outcomes. Due to the dynamics of pandemic progression, it is challenging to analyse the long-term influence of an individual measure in the sequence on pandemic outcomes. To demonstrate the problem and find solutions, in this article, we study the first wave of the pandemic-probably the most dynamic period-in the Nordic countries and analyse the influences of the Swedish measures relative to the measures adopted by its neighbouring countries on COVID-19 mortality, general mortality, COVID-19 incidence, and unemployment. The design is a longitudinal observational study. The linear regressions based on the Poisson distribution or the binomial distribution are employed for the analysis. To show that analysis can be timely conducted, we use table data available during the first wave. We found that the early Swedish measure had a long-term and significant causal effect on public health outcomes and a certain degree of long-term mitigating causal effect on unemployment during the first wave, where the effect was measured by an increase of these outcomes under the Swedish measures relative to the measures adopted by the other Nordic countries. This information from the first wave has not been provided by available analyses but could have played an important role in combating the second wave. In conclusion, analysis based on table data may provide timely information about the dynamic progression of a pandemic and the long-term influence of an individual measure in the sequence on pandemic outcomes.

In Silico Prediction of Hub Genes Involved in Diabetic Kidney and COVID-19 Related Disease by Differential Gene Expression and Interactome Analysis

Diabetic kidney disease (DKD) is a frequently chronic kidney pathology derived from diabetes comorbidity. This condition has irreversible damage and its risk factor increases with SARS-CoV-2 infection. The prognostic outcome for diabetic patients with COVID-19 is dismal, even with intensive medical treatment. However, there is still scarce information on critical genes involved in the pathophysiological impact of COVID-19 on DKD. Herein, we characterize differential expression gene (DEG) profiles and determine hub genes undergoing transcriptional reprogramming in both disease conditions. Out of 995 DEGs, we identified 42 shared with COVID-19 pathways. Enrichment analysis elucidated that they are significantly induced with implications for immune and inflammatory responses. By performing a protein-protein interaction (PPI) network and applying topological methods, we determine the following five hub genes: STAT1, IRF7, ISG15, MX1 and OAS1. Then, by network deconvolution, we determine their co-expressed gene modules. Moreover, we validate the conservancy of their upregulation using the Coronascape database (DB). Finally, tissue-specific regulation of the five predictive hub genes indicates that OAS1 and MX1 expression levels are lower in healthy kidney tissue. Altogether, our results suggest that these genes could play an essential role in developing severe outcomes of COVID-19 in DKD patients.

Clinical features of elderly patients with COVID-19 in Wuhan, China

BACKGROUND

Elderly patients with coronavirus disease 2019 (COVID-19) who have comorbidities, frailty or profound disabilities experience poor outcomes. We analyzed the clinical characteristics of elderly patients from Wuhan who had COVID-19 during the early stages of the pandemic.

AIM

To identify factors affecting the early mortality of elderly patients with COVID-19.

METHODS

The records of 234 patients who were 65-years-old or more and were hospitalized in Wuhan Huoshenshan Hospital from February 4 to March 4, 2020 were reviewed. All patients had confirmed COVID-19 and the final date of follow-up was April 4, 2020.

RESULTS

There were 163 cases of mild disease (69.66%), 39 cases of severe disease (16.67%) and 32 cases of critical disease (13.68%). Twenty-nine patients died within 1 mo (12.40%), all of whom had critical disease. Surviving patients and deceased patients had no significant differences in age or chronic diseases. Overall, the most common symptoms were fever (65.4%), dry cough (57.3%), fatigue (47.4%) and shortness of breath (41%). The deceased patients had higher levels of multiple disease markers (C-reactive protein, D-dimer, lactate dehydrogenase, alanine amino transferase, aspartate aminotransferase, creatinine kinase and creatinine kinase-MB) and higher incidences of lymphocytopenia and hypoproteinemia.

CONCLUSION

This single-center study of elderly patients from Wuhan, China who were hospitalized with COVID-19 indicated that age and chronic diseases were not associated with mortality. Hypertension, diabetes and cardiovascular disease were the most common comorbidities and the most common symptoms were fever, dry cough, fatigue and shortness of breath. Lymphocytopenia, increased levels of D-dimer and other markers indicative of damage to the heart, kidneys or liver were associated with an increased risk of death.

Responses to COVID-19 Threats: an Evolutionary Psychological Analysis

Responses to COVID-19 public health interventions have been lukewarm. For example, only 64% of the US population has received at least two vaccinations. Because most public health interventions require people to behave in ways that are evolutionarily novel, evolutionary psychological theory and research on mismatch theory, the behavioral immune system, and individual differences can help us gain a better understanding of how people respond to public health information. Primary sources of threat information during the pandemic (particularly in early phases) were geographic differences in morbidity and mortality statistics. We argue that people are unlikely to respond to this type of evolutionarily novel information, particularly under conditions of high uncertainty. However, because individual differences affect threat perceptions, some individual differences will be associated with threat responses. We conducted two studies (during Phase 1 and 2 years later), using data from primarily public sources. We found that state-level COVID-19 morbidity and mortality rates had no relationship with mental health symptoms (an early indicator of how people were responding to the pandemic), suggesting that people-in general-were not attending to this type of information. This result is consistent with the evolutionary psychological explanation that statistical information is likely to have a weak effect on the behavioral immune system. We also found that individual differences (neuroticism, IQ, age, and political ideology) affected how people responded to COVID-19 threats, supporting a niche-picking explanation. We conclude with suggestions for future research and suggestions for improving interventions and promoting greater compliance.

Surveillance of SARS-CoV-2 in nine neighborhood sewersheds in Detroit Tri-County area, United States: Assessing per capita SARS-CoV-2 estimations and COVID-19 incidence

Wastewater-based epidemiology (WBE) has been suggested as a useful tool to predict the emergence and investigate the extent of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this study, we screened appropriate population biomarkers for wastewater SARS-CoV-2 normalization and compared the normalized SARS-CoV-2 values across locations with different demographic characteristics in southeastern Michigan. Wastewater samples were collected between December 2020 and October 2021 from nine neighborhood sewersheds in the Detroit Tri-County area. Using reverse transcriptase droplet digital polymerase chain reaction (RT-ddPCR), concentrations of N1 and N2 genes in the studied sites were quantified, with N1 values ranging from 1.92 × 102 genomic copies/L to 6.87 × 103 gc/L and N2 values ranging from 1.91 × 102 gc/L to 6.45 × 103 gc/L. The strongest correlations were observed with between cumulative COVID-19 cases per capita (referred as COVID-19 incidences thereafter), and SARS-CoV-2 concentrations normalized by total Kjeldahl nitrogen (TKN), creatinine, 5-hydroxyindoleacetic acid (5-HIAA) and xanthine when correlating the per capita SARS-CoV-2 and COVID-19 incidences. When SARS-CoV-2 concentrations in wastewater were normalized and compared with COVID-19 incidences, the differences between neighborhoods of varying demographics were reduced as compared to differences observed when comparing non-normalized SARS-CoV-2 with COVID-19 cases. This indicates when studying the disease burden in communities of different demographics, accurate per capita estimation is of great importance. The study suggests that monitoring selected water quality parameters or biomarkers, along with RNA concentrations in wastewater, will allow adequate data normalization for spatial comparisons, especially in areas where detailed sanitary sewage flows and contributing populations in the catchment areas are not available. This opens the possibility of using WBE to assess community infections in rural areas or the developing world where the contributing population of a sample could be unknown.

Structural Analysis of the Spike Protein of SARS-CoV-2 Variants and Other Betacoronaviruses Using Molecular Dynamics

A structural analysis over various spike proteins from three highly pathogenic Betacoronavirus was done to understand their structural differences. The proteins were modeled using crystal structures from SARS-CoV, MERS-CoV, and other Betacoronavirus that infect bats and pangolins. The group was split in two sets; the first set corresponds to the non-mutated spike proteins, while the second set corresponds to mutated spike variants alpha, beta, gamma, delta, omicron and mu; five of them classified as variants of concern and the last one as variant of interest. A conformational space exploration was carried out for every protein by using molecular dynamic simulations. Root mean square fluctuations, principal component and cross-correlation analysis were carried out over the dynamics to analyze the flexibility and rigidity of every protein in comparison to the wild type Spike protein from the SARS-CoV-2. The obtained results indicate that the proteins, which are not spread among humans, have smooth movements compared to those of SARS-CoV-2 and its variants. In addition, a relationship between the speed of the virulence and the movement of the protein can explain the behavior of delta and omicron variants.

Long-term validation of a reverse transcription loop-mediated isothermal amplification (RT-LAMP) assay for the rapid detection of SARS-CoV-2 from March 2020 to October 2021 in Central Africa, Gabon

BACKGROUND

Despite the development of several methods for diagnosing COVID-19, long-term validation of such methods remains limited. In the early phase of the COVID-19 pandemic, we developed a rapid and sensitive diagnostic method based on reverse transcription loop-mediated isothermal amplification (RT-LAMP) methodology, which is suitable for point-of-care application or for use in resource-limited settings to detect SARS-CoV-2. To assess the applicability of the RT-LAMP assay technique to resource-limited regions, such as rural areas in Africa, and to verify the usability of the method against various SARS-CoV-2 variants, the method was validated using clinical samples collected longitudinally during the pandemic.

METHODOLOGY/PRINCIPAL FINDINGS

First, the sensitivity of the RT-LAMP assay for detecting 10 SARS-CoV-2 variants was evaluated using viral RNA samples extracted from cell culture with a portable battery-supported device, resulting in the successful detection of 20-50 copies of the viral genome within 15 min, regardless of the variant. COVID-19 positive samples collected in Gabon between March 2020 and October 2021 were used to evaluate the sensitivity of the assay and to calculate the copy number of the SARS-CoV-2 genome. More than 292 copies of the viral genome were detected with 100% probability within 15 min in almost all tests.

CONCLUSIONS

This long-term validation study clearly demonstrated the applicability of the RT-LAMP assay for the clinical diagnosis of COVID-19 in resource-limited settings of Africa, such as rural areas in Gabon. The results show the potential of the assay as a promising COVID-19 diagnostic method, especially in rural and remote regions located far from the official diagnosis facilities in urban or semi-urban areas.

A variant-proof SARS-CoV-2 vaccine targeting HR1 domain in S2 subunit of spike protein

The emerging SARS-CoV-2 variants, commonly with many mutations in S1 subunit of spike (S) protein are weakening the efficacy of the current vaccines and antibody therapeutics. This calls for the variant-proof SARS-CoV-2 vaccines targeting the more conserved regions in S protein. Here, we designed a recombinant subunit vaccine, HR121, targeting the conserved HR1 domain in S2 subunit of S protein. HR121 consisting of HR1-linker1-HR2-linker2-HR1, is conformationally and functionally analogous to the HR1 domain present in the fusion intermediate conformation of S2 subunit. Immunization with HR121 in rabbits and rhesus macaques elicited highly potent cross-neutralizing antibodies against SARS-CoV-2 and its variants, particularly Omicron sublineages. Vaccination with HR121 achieved near-full protections against prototype SARS-CoV-2 infection in hACE2 transgenic mice, Syrian golden hamsters and rhesus macaques, and effective protection against Omicron BA.2 infection in Syrian golden hamsters. This study demonstrates that HR121 is a promising candidate of variant-proof SARS-CoV-2 vaccine with a novel conserved target in the S2 subunit for application against current and future SARS-CoV-2 variants.

Porous charged polymer nanosheets formed via microplastic removal from frozen ice for virus filtration and detection

We developed a method for producing porous charged polymer nanosheets using frozen ice containing microplastics. Upon assessing SARS-CoV-2 filtration using nanosheets with 100 nm-sized pores, a high rejection rate of 96% was achieved. The charged surfaces of nanosheets further enabled the electrophoretic capture of the virus using a portable battery with additional real-time sensing capability.

Epidemiological Characteristics of Deaths from COVID-19 in Peru during the Initial Pandemic Response

BACKGROUND AND AIM

Peru is the country with the highest mortality rate from COVID-19 globally, so the analysis of the characteristics of deaths is of national and international interest. The aim was to determine the epidemiological characteristics of deaths from COVID-19 in Peru from 28 March to 21 May 2020.

METHODS

Deaths from various sources were investigated, including the COVID-19 Epidemiological Surveillance and the National System of Deaths (SINADEF). In all, 3851 deaths that met the definition of a confirmed case and had a positive result of RT-PCR or rapid test IgM/IgG, were considered for the analysis. We obtained the epidemiological variables and carried out an analysis of time defined as the pre-hospital time from the onset of symptoms to hospitalization, and hospital time from the date of hospitalization to death.

RESULTS

Deaths were more frequent in males (72.0%), seniors (68.8%) and residents of the region of Lima (42.7%). In 17.8% of cases, the death occurred out-of-hospital, and 31.4% had some comorbidity. The median of pre-hospital time was 7 days (IQR: 4.0-9.0) and for the hospital time was 5 days (IQR: 3.0-9.0). The multivariable analysis with Poisson regression with robust variance found that the age group, comorbidity diagnosis and the region of origin significantly influenced pre-hospital time; while sex, comorbidity diagnosis, healthcare provider and the region of origin significantly influenced hospital time.

CONCLUSION

Deaths occurred mainly in males, seniors and on the coast, with considerable out-of-hospital deaths. Pre-hospital time was affected by age group, the diagnosis of comorbidities and the region of origin; while, hospital time was influenced by gender, the diagnosis of comorbidities, healthcare provider and the region of origin.

New Surveillance Metrics for Alerting Community-Acquired Outbreaks of Emerging SARS-CoV-2 Variants Using Imported Case Data: Bayesian Markov Chain Monte Carlo Approach

BACKGROUND

Global transmission from imported cases to domestic cluster infections is often the origin of local community-acquired outbreaks when facing emerging SARS-CoV-2 variants.

OBJECTIVE

We aimed to develop new surveillance metrics for alerting emerging community-acquired outbreaks arising from new strains by monitoring the risk of small domestic cluster infections originating from few imported cases of emerging variants.

METHODS

We used Taiwanese COVID-19 weekly data on imported cases, domestic cluster infections, and community-acquired outbreaks. The study period included the D614G strain in February 2020, the Alpha and Delta variants of concern (VOCs) in 2021, and the Omicron BA.1 and BA.2 VOCs in April 2022. The number of cases arising from domestic cluster infection caused by imported cases (Dci/Imc) per week was used as the SARS-CoV-2 strain-dependent surveillance metric for alerting local community-acquired outbreaks. Its upper 95% credible interval was used as the alert threshold for guiding the rapid preparedness of containment measures, including nonpharmaceutical interventions (NPIs), testing, and vaccination. The 2 metrics were estimated by using the Bayesian Monte Carlo Markov Chain method underpinning the directed acyclic graphic diagram constructed by the extra-Poisson (random-effect) regression model. The proposed model was also used to assess the most likely week lag of imported cases prior to the current week of domestic cluster infections.

RESULTS

A 1-week lag of imported cases prior to the current week of domestic cluster infections was considered optimal. Both metrics of Dci/Imc and the alert threshold varied with SARS-CoV-2 variants and available containment measures. The estimates were 9.54% and 12.59%, respectively, for D614G and increased to 14.14% and 25.10%, respectively, for the Alpha VOC when only NPIs and testing were available. The corresponding figures were 10.01% and 13.32% for the Delta VOC, but reduced to 4.29% and 5.19% for the Omicron VOC when NPIs, testing, and vaccination were available. The rapid preparedness of containment measures guided by the estimated metrics accounted for the lack of community-acquired outbreaks during the D614G period, the early Alpha VOC period, the Delta VOC period, and the Omicron VOC period between BA.1 and BA.2. In contrast, community-acquired outbreaks of the Alpha VOC in mid-May 2021, Omicron BA.1 VOC in January 2022, and Omicron BA.2 VOC from April 2022 onwards, were indicative of the failure to prepare containment measures guided by the alert threshold.

CONCLUSIONS

We developed new surveillance metrics for estimating the risk of domestic cluster infections with increasing imported cases and its alert threshold for community-acquired infections varying with emerging SARS-CoV-2 strains and the availability of containment measures. The use of new surveillance metrics is important in the rapid preparedness of containment measures for averting large-scale community-acquired outbreaks arising from emerging imported SARS-CoV-2 variants.

Selective sweeps in SARS-CoV-2 variant competition

The main mathematical result in this paper is that change of variables in the ordinary differential equation (ODE) for the competition of two infections in a Susceptible-Infected-Removed (SIR) model shows that the fraction of cases due to the new variant satisfies the logistic differential equation, which models selective sweeps. Fitting the logistic to data from the Global Initiative on Sharing All Influenza Data (GISAID) shows that this correctly predicts the rapid turnover from one dominant variant to another. In addition, our fitting gives sensible estimates of the increase in infectivity. These arguments are applicable to any epidemic modeled by SIR equations.

Infectiousness of SARS-CoV-2 breakthrough infections and reinfections during the Omicron wave

SARS-CoV-2 breakthrough infections in vaccinated individuals and reinfections among previously infected individuals have become increasingly common. Such infections highlight a broader need to understand the contribution of vaccination, including booster doses, and natural immunity to the infectiousness of persons with SARS-CoV-2 infections, especially in high-risk populations with intense transmission such as prisons. Here, we show that both vaccine-derived and naturally acquired immunity independently reduce the infectiousness of persons with Omicron variant SARS-CoV-2 infections in a prison setting. Analyzing SARS-CoV-2 surveillance data from December 2021 to May 2022 across 35 California state prisons with a predominately male population, we estimate that unvaccinated Omicron cases had a 36% (95% confidence interval (CI): 31-42%) risk of transmitting infection to close contacts, as compared to 28% (25-31%) risk among vaccinated cases. In adjusted analyses, we estimated that any vaccination, prior infection alone, and both vaccination and prior infection reduced an index case's risk of transmitting infection by 22% (6-36%), 23% (3-39%) and 40% (20-55%), respectively. Receipt of booster doses and more recent vaccination further reduced infectiousness among vaccinated cases. These findings suggest that although vaccinated and/or previously infected individuals remain highly infectious upon SARS-CoV-2 infection in this prison setting, their infectiousness is reduced compared to individuals without any history of vaccination or infection, underscoring some benefit of vaccination to reduce but not eliminate transmission.

Antigenic escape is accelerated by the presence of immunocompromised hosts

The repeated emergence of SARS-CoV-2 escape mutants from host immunity has obstructed the containment of the current pandemic and poses a serious threat to humanity. Prolonged infection in immunocompromised patients has received increasing attention as a driver of immune escape, and accumulating evidence suggests that viral genomic diversity and emergence of immune-escape mutants are promoted in immunocompromised patients. However, because immunocompromised patients comprise a small proportion of the host population, whether they have a significant impact on antigenic evolution at the population level is unknown. We consider an evolutionary epidemiological model that combines antigenic evolution and epidemiological dynamics. Applying this model to a heterogeneous host population, we study the impact of immunocompromised hosts on the evolutionary dynamics of pathogen antigenic escape from host immunity. We derived analytical formulae of the speed of antigenic evolution in heterogeneous host populations and found that even a small number of immunocompromised hosts in the population significantly accelerates antigenic evolution. Our results demonstrate that immunocompromised hosts play a key role in viral adaptation at the population level and emphasize the importance of critical care and surveillance of immunocompromised hosts.

Impact of Early Pandemic SARS-CoV-2 Lineages Replacement with the Variant of Concern P.1 (Gamma) in Western Bahia, Brazil

BACKGROUND

The correct understanding of the epidemiological dynamics of COVID-19, caused by the SARS-CoV-2, is essential for formulating public policies of disease containment.

METHODS

In this study, we constructed a picture of the epidemiological dynamics of COVID-19 in a Brazilian population of almost 17000 patients in 15 months. We specifically studied the fluctuations of COVID-19 cases and deaths due to COVID-19 over time according to host gender, age, viral load, and genetic variants.

RESULTS

As the main results, we observed that the numbers of COVID-19 cases and deaths due to COVID-19 fluctuated over time and that men were the most affected by deaths, as well as those of 60 or more years old. We also observed that individuals between 30- and 44-years old were the most affected by COVID-19 cases. In addition, the viral loads in the patients' nasopharynx were higher in the early symptomatic period. We found that early pandemic SARS-CoV-2 lineages were replaced by the variant of concern (VOC) P.1 (Gamma) in the second half of the study period, which led to a significant increase in the number of deaths.

CONCLUSIONS

The results presented in this study are helpful for future formulations of efficient public policies of COVID-19 containment.

Teaching undergraduate physical chemistry lab with kinetic analysis of COVID-19 in the United States

A physical chemistry lab for undergraduate students described in this report is about applying kinetic models to analyze the spread of COVID-19 in the United States and obtain the reproduction numbers. The susceptible-infectious-recovery (SIR) model and the SIR-vaccinated (SIRV) model are explained to the students and are used to analyze the COVID-19 spread data from U.S. Centers for Disease Control and Prevention (CDC). The basic reproduction number R 0 and the real-time reproduction number R t of COVID-19 are extracted by fitting the data with the models, which explains the spreading kinetics and provides a prediction of the spreading trend in a given state. The procedure outlined here shows the differences between the SIR model and the SIRV model. The SIRV model considers the effect of vaccination which helps explain the later stages of the ongoing pandemic. The predictive power of the models is also shown giving the students some certainty in the predictions they made for the following months.

Vaccine models predict rules for updating vaccines against evolving pathogens such as SARS-CoV-2 and influenza in the context of pre-existing immunity

Currently, vaccines for SARS-CoV-2 and influenza viruses are updated if the new vaccine induces higher antibody-titers to circulating variants than current vaccines. This approach does not account for complex dynamics of how prior immunity skews recall responses to the updated vaccine. We: (i) use computational models to mechanistically dissect how prior immunity influences recall responses; (ii) explore how this affects the rules for evaluating and deploying updated vaccines; and (iii) apply this to SARS-CoV-2. Our analysis of existing data suggests that there is a strong benefit to updating the current SARS-CoV-2 vaccines to match the currently circulating variants. We propose a general two-dose strategy for determining if vaccines need updating as well as for vaccinating high-risk individuals. Finally, we directly validate our model by reanalysis of earlier human H5N1 influenza vaccine studies.

Editorial: Rebound COVID-19 and Cessation of Antiviral Treatment for SARS-CoV-2 with Paxlovid and Molnupiravir

One of the most recently described clinical associations with SARS-CoV-2 infection is rebound COVID-19, which occurs between five and eight days following the cessation of antiviral treatment. Most case reports of rebound COVID-19 have been associated with cessation of treatment with the combined oral antiviral agent nirmatrelvir/ritonavir (Paxlovid). On 24 May 2022, the US Centers for Disease Control and Prevention (CDC) issued a Health Alert Network (HAN) Health Advisory update for patients, healthcare providers, and public health departments on COVID-19 rebound or recurrence of COVID-19. However, population data from the US showed no significant differences in the risk of developing rebound COVID-19 between patients treated with Paxlovid and Molnupiravir. The mechanisms of rebound COVID-19 remain unclear but may involve the development of resistance to the antiviral drug, impaired immunity to the virus, or insufficient drug dosing. A further explanation may be the persistence of a high viral load of SARS-CoV-2 in individuals who are no longer symptomatic. This Editorial aims to provide an update on what is known about rebound COVID-19 and the current public health implications.

Comparative Assessment of Severe Acute Respiratory Syndrome Coronavirus 2 Variants in the Ferret Model

The continued spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in humans necessitates evaluation of variants for enhanced virulence and transmission. We used the ferret model to perform a comparative analysis of four SARS-CoV-2 strains, including an early pandemic isolate from the United States (WA1), and representatives of the Alpha, Beta, and Delta lineages. While Beta virus was not capable of pronounced replication in ferrets, WA1, Alpha, and Delta viruses productively replicated in the ferret upper respiratory tract, despite causing only mild disease with no overt histopathological changes. Strain-specific transmissibility was observed; WA1 and Delta viruses transmitted in a direct contact setting, whereas Delta virus was also capable of limited airborne transmission. Viral RNA was shed in exhaled air particles from all inoculated animals but was highest for Delta virus. Prior infection with SARS-CoV-2 offered varied protection against reinfection with either homologous or heterologous variants. Notable genomic variants in the spike protein were most frequently detected following WA1 and Delta virus infection.

SARS-CoV-2 Spike Proteins and Cell-Cell Communication Inhibits TFPI and Induces Thrombogenic Factors in Human Lung Microvascular Endothelial Cells and Neutrophils: Implications for COVID-19 Coagulopathy Pathogenesis

In SARS-CoV-2-infected humans, disease progression is often associated with acute respiratory distress syndrome involving severe lung injury, coagulopathy, and thrombosis of the alveolar capillaries. The pathogenesis of these pulmonary complications in COVID-19 patients has not been elucidated. Autopsy study of these patients showed SARS-CoV-2 virions in pulmonary vessels and sequestrated leukocytes infiltrates associated with endotheliopathy and microvascular thrombosis. Since SARS-CoV-2 enters and infects target cells by binding its spike (S) protein to cellular angiotensin-converting enzyme 2 (ACE2), and there is evidence that vascular endothelial cells and neutrophils express ACE2, we investigated the effect of S-proteins and cell-cell communication on primary human lung microvascular endothelial cells (HLMEC) and neutrophils expression of thrombogenic factors and the potential mechanisms. Using S-proteins of two different SARS-CoV-2 variants (Wuhan and Delta), we demonstrate that exposure of HLMEC or neutrophils to S-proteins, co-culture of HLMEC exposed to S-proteins with non-exposed neutrophils, or co-culture of neutrophils exposed to S-proteins with non-exposed HLMEC induced transcriptional upregulation of tissue factor (TF), significantly increased the expression and secretion of factor (F)-V, thrombin, and fibrinogen and inhibited tissue factor pathway inhibitor (TFPI), the primary regulator of the extrinsic pathway of blood coagulation, in both cell types. Recombinant (r)TFPI and a thiol blocker (5,5'-dithio-bis-(2-nitrobenzoic acid)) prevented S-protein-induced expression and secretion of Factor-V, thrombin, and fibrinogen. Thrombomodulin blocked S-protein-induced expression and secretion of fibrinogen but had no effect on S-protein-induced expression of Factor-V or thrombin. These results suggests that following SARS-CoV-2 contact with the pulmonary endothelium or neutrophils and endothelial-neutrophil interactions, viral S-proteins induce coagulopathy via the TF pathway and mechanisms involving functional thiol groups. These findings suggest that using rTFPI and/or thiol-based drugs could be a viable therapeutic strategy against SARS-CoV-2-induced coagulopathy and thrombosis.

A replication-competent smallpox vaccine LC16m8Δ-based COVID-19 vaccine

Viral vectors are a potent vaccine platform for inducing humoral and T-cell immune responses. Among the various viral vectors, replication-competent ones are less commonly used for coronavirus disease 2019 (COVID-19) vaccine development compared with replication-deficient ones. Here, we show the availability of a smallpox vaccine LC16m8Δ (m8Δ) as a replication-competent viral vector for a COVID-19 vaccine. M8Δ is a genetically stable variant of the licensed and highly effective Japanese smallpox vaccine LC16m8. Here, we generated two m8Δ recombinants: one harbouring a gene cassette encoding the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike (S) glycoprotein, named m8Δ-SARS2(P7.5-S)-HA; and one encoding the S protein with a highly polybasic motif at the S1/S2 cleavage site, named m8Δ-SARS2(P7.5-S_HN)-HA. M8Δ-SARS2(P7.5-S)-HA induced S-specific antibodies in mice that persisted for at least six weeks after a homologous boost immunization. All eight analysed serum samples displayed neutralizing activity against an S-pseudotyped virus at a level similar to that of serum samples from patients with COVID-19, and more than half (5/8) also had neutralizing activity against the Delta/B.1.617.2 variant of concern. Importantly, most serum samples also neutralized the infectious SARS-CoV-2 Wuhan and Delta/B.1.617.2 strains. In contrast, immunization with m8Δ-SARS2(P7.5-S_HN)-HA elicited significantly lower antibody titres, and the induced antibodies had less neutralizing activity. Regarding T-cell immunity, both m8Δ recombinants elicited S-specific multifunctional CD8⁺ and CD4⁺ T-cell responses even after just a primary immunization. Thus, m8Δ provides an alternative method for developing a novel COVID-19 vaccine.

Nano-multilamellar lipid vesicles promote the induction of SARS-CoV-2 immune responses by a protein-based vaccine formulation

The development of safe and effective vaccine formulations against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) represents a hallmark in the history of vaccines. Here we report a COVID-19 subunit vaccine based on a SARS-CoV-2 Spike protein receptor binding domain (RBD) incorporated into nano-multilamellar vesicles (NMV) associated with monophosphoryl lipid A (MPLA). The results based on immunization of C57BL/6 mice demonstrated that recombinant antigen incorporation into NMVs improved antibody and T-cell responses without inducing toxic effects under both in vitro and in vivo conditions. Administration of RBD-NMV-MPLA formulations modulated antigen avidity and IgG subclass responses, whereas MPLA incorporation improved the activation of CD4⁺/CD8⁺ T-cell responses. In addition, immunization with the complete vaccine formulation reduced the number of doses required to achieve enhanced serum virus-neutralizing antibody titers. Overall, this study highlights NMV/MPLA technology, displaying the performance improvement of subunit vaccines against SARS-CoV-2, as well as other infectious diseases.

Inflammatory pathways in COVID-19: Mechanism and therapeutic interventions

The 2019 coronavirus disease (COVID-19) pandemic has become a global crisis. In the immunopathogenesis of COVID-19, SARS-CoV-2 infection induces an excessive inflammatory response in patients, causing an inflammatory cytokine storm in severe cases. Cytokine storm leads to acute respiratory distress syndrome, pulmonary and other multiorgan failure, which is an important cause of COVID-19 progression and even death. Among them, activation of inflammatory pathways is a major factor in generating cytokine storms and causing dysregulated immune responses, which is closely related to the severity of viral infection. Therefore, elucidation of the inflammatory signaling pathway of SARS-CoV-2 is important in providing otential therapeutic targets and treatment strategies against COVID-19. Here, we discuss the major inflammatory pathways in the pathogenesis of COVID-19, including induction, function, and downstream signaling, as well as existing and potential interventions targeting these cytokines or related signaling pathways. We believe that a comprehensive understanding of the regulatory pathways of COVID-19 immune dysregulation and inflammation will help develop better clinical therapy strategies to effectively control inflammatory diseases, such as COVID-19.

Professional Student Education and Training During the COVID-19 Pandemic

Introduction

The ongoing COVID-19 pandemic has presented numerous challenges to education at all levels, but has been particularly challenging for professional schools and other educational sectors that require intensive hands-on training. Those institutions have had to deploy and continuously adapt new learning strategies in response to an ever-changing pandemic landscape over the past two years, while at the same time meeting the rigorous proficiency standards for their students.

Methods

This communication describes how two professional schools at Oregon State University, the College of Pharmacy and the Carlson College of Veterinary Medicine, pivoted in response to the COVID-19 pandemic to ensure continuity in student training. The adaptations included technological solutions, physical distancing, barriers, reduced group size and scheduling changes in the curriculum, and enhanced personal protective equipment.

Results

The available evidence suggest that the biosafety measures implemented to reduce the risk of COVID-19 in the hands-on educational setting appear to have been effective in preventing transmission during classroom and experiential learning activities. Professional licensing exam scores for the students of both colleges remain as high as pre-pandemic values, suggesting that the implemented changes in instruction did not have a detrimental impact on student learning. The scores will need to be monitored for several more years before firm conclusions can be drawn.

Discussion

Both colleges implemented creative solutions to the delivery of hands-on pedagogy that sought to balance risk of infection and the necessity to master critical skills that can only be acquired by active learning.

COVID-19 pandemic dynamics in South Africa and epidemiological characteristics of three variants of concern (Beta, Delta, and Omicron)

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOCs) have been key drivers of new coronavirus disease 2019 (COVID-19) pandemic waves. To better understand variant epidemiologic characteristics, here we apply a model-inference system to reconstruct SARS-CoV-2 transmission dynamics in South Africa, a country that has experienced three VOC pandemic waves (i.e. Beta, Delta, and Omicron BA.1) by February 2022. We estimate key epidemiologic quantities in each of the nine South African provinces during March 2020 to February 2022, while accounting for changing detection rates, infection seasonality, nonpharmaceutical interventions, and vaccination. Model validation shows that estimated underlying infection rates and key parameters (e.g. infection-detection rate and infection-fatality risk) are in line with independent epidemiological data and investigations. In addition, retrospective predictions capture pandemic trajectories beyond the model training period. These detailed, validated model-inference estimates thus enable quantification of both the immune erosion potential and transmissibility of three major SARS-CoV-2 VOCs, that is, Beta, Delta, and Omicron BA.1. These findings help elucidate changing COVID-19 dynamics and inform future public health planning.

Saliva for molecular detection of SARS‐CoV ‐2 in preschool and school‐age children

SARS‐CoV‐2 diagnosis is a cornerstone for the management of coronavirus disease 2019 (COVID‐19). Numerous studies have assessed saliva performance over nasopharyngeal sampling (NPS), but data in young children are still rare. We explored saliva performance for SARS‐CoV‐2 detection by RT‐PCR according to the time interval from initial symptoms or patient serological status. We collected 509 NPS and saliva paired samples at initial diagnosis from 166 children under 12 years of age (including 57 children under 6), 106 between 12 and 17, and 237 adults. In children under 12, overall detection rate for SARS‐CoV‐2 was comparable in saliva and NPS, with an overall agreement of 89.8%. Saliva sensitivity was significantly lower than that of NPS (77.1% compared to 95.8%) in pre‐school and school‐age children but regained 96% when considering seronegative children only. This pattern was also observed to a lesser degree in adolescents but not in adults. Sensitivity of saliva was independent of symptoms, in contrary to NPS, whose sensitivity decreased significantly in asymptomatic subjects. Performance of saliva is excellent in children under 12 at early stages of infection. This reinforces saliva as a collection method for early and unbiased SARS‐CoV‐2 detection and a less invasive alternative for young children.

Differences Between Omicron Infections and Fever Outpatients: Comparison of Clinical Manifestations and Initial Routine Hematology Indicators

Purpose

We evaluated the differences between patients with SARS-CoV-2 Omicron variant infections and Fever outpatients, so that prevention and control measures can be taken in time.

Patients and Methods

This study retrospectively analyzed 65 patients with SARS-CoV-2 Omicron variant. Sixty-nine age- and sex-matched Fever outpatients were enrolled during the same period of time. We also reanalyzed data from 81 SARS-CoV-2 Wild-Type-infected patients. We compared the clinical characteristics and initial indexes of routine tests among the 3 groups.

Results

A total of 93.8% of the patients with Omicron infections had clinical symptoms, and the major symptoms were cough, fever and pharyngalgia. Pharyngalgia was a specific manifestation in Omicron group compared to Wild-Type group. The white blood cell of the Omicron group was lower than that of the Fever group [5.0 (3.6–6.1) vs 10.1 (7.6–12.9) ×10⁹/L, P < 0.001]. The neutrophil count in Omicron group was lower than that in Fever and Wild-Type group [2.6 (1.8–3.9) vs 8.1 (5.9–10.9), P < 0.001; 2.6 (1.8–3.9) vs 3.4 (2.5–4.7) ×10⁹/L, P < 0.001]. The white blood cell and neutrophil counts were lower in Omicron group than in the Fever group. The top 5 major symptoms were fever, cough, pharyngalgia, headache and expectoration.

Conclusion

There are differences between the patients with Omicron infections and Fever outpatients, both in clinical manifestations and initial routine hematology indicators. We hope to provide some clues for early identification combined with a history of living in the epidemic area.

Clinical and Pulmonary CT Characteristics of Patients Infected With the SARS-CoV-2 Omicron Variant Compared With Those of Patients Infected With the Alpha Viral Strain

Background

Omicron has become the dominant variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) globally. We aimed to compare the clinical and pulmonary computed tomography (CT) characteristics of the patients infected with SARS-CoV-2 Omicron with those of patients infected with the Alpha viral strain.

Methods

Clinical profiles and pulmonary CT images of 420 patients diagnosed with coronavirus disease-2019 (COVID-19) at Ningbo First Hospital between January 2020 and April 2022 were collected. Demographic characteristics, symptoms, and imaging manifestations of patients infected with the SARS-CoV-2 Omicron variant were compared with those of patients infected with the Alpha strain.

Results

A total of 38 patients were diagnosed to be infected with the Alpha strain of SARS-CoV-2, whereas 382 patients were thought to be infected with the Omicron variant. Compared with patients infected with the Alpha strain, those infected with the Omicron variant were younger, and a higher proportion of men were infected (P < 0.001). Notably, 93 (24.3%) of the patients infected with Omicron were asymptomatic, whereas only two (5.3%) of the patients infected with the Alpha strain were asymptomatic. Fever (65.8%), cough (63.2%), shortness of breath (21.1%), and diarrhea (21.1%) were more common in patients infected with the SARS-CoV-2 Alpha strain, while runny nose (24.1%), sore throat (31.9%), body aches (13.6%), and headache (12.3%) were more common in patients with the Omicron variant. Compared with 33 (86.84%) of 38 patients infected with the Alpha strain, who had viral pneumonia on pulmonary CT images, only 5 (1.3%) of 382 patients infected with the Omicron variant had mild foci. In addition, the distribution of opacities in the five patients was unilateral and centrilobular, whereas most patients infected with the Alpha strain had bilateral involvement and multiple lesions in the peripheral zones of the lung.

Conclusion

The SARS-CoV-2 Alpha strain mainly affects the lungs, while Omicron is confined to the upper respiratory tract in patients with COVID-19.

COVID-19: Omicron - the latest, the least virulent, but probably not the last variant of concern of SARS-CoV-2

The Omicron variant rapidly became the dominant SARS-CoV-2 strain in South Africa and elsewhere. This review explores whether this rise was due to an increased transmission of the variant or its escape from population immunity by an extensively mutated spike protein. The mutations affected the structure of the spike protein leading to the loss of neutralization by most, but not all, therapeutic monoclonal antibodies. Omicron also shows substantial immune escape from serum antibodies in convalescent patients and vaccinees. A booster immunization increased, however, the titre and breadth of antiviral antibody response. The cellular immune response against Omicron was largely preserved explaining a satisfying protection of boosted vaccinees against severe infections. Clinicians observed less severe infection with Omicron, but other scientists warned that this must not necessarily reflect less intrinsic virulence. However, in animal experiments with mice and hamsters, Omicron infections also displayed a lesser virulence than previous VOCs and lung functions were less compromised. Cell biologists demonstrated that Omicron differs from Delta by preferring the endocytic pathway for cell entry over fusion with the plasma membrane which might explain Omicron's distinct replication along the respiratory tract compared with Delta. Omicron represents a distinct evolutionary lineage that deviated from the mainstream of evolving SARS-CoV-2 already in mid-2020 raising questions about where it circulated before getting widespread in December 2021. The role of Omicron for the future trajectory of the COVID-19 pandemic is discussed.

COVID-19 pandemic dynamics in South Africa and epidemiological characteristics of three variants of concern (Beta, Delta, and Omicron)

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOCs) have been key drivers of new coronavirus disease 2019 (COVID-19) pandemic waves. To better understand variant epidemiologic characteristics, here we apply a model-inference system to reconstruct SARS-CoV-2 transmission dynamics in South Africa, a country that has experienced three VOC pandemic waves (i.e. Beta, Delta, and Omicron). We estimate key epidemiologic quantities in each of the nine South African provinces during March 2020 â€" Feb 2022, while accounting for changing detection rates, infection seasonality, nonpharmaceutical interventions, and vaccination. Model validation shows that estimated underlying infection rates and key parameters (e.g., infection-detection rate and infection-fatality risk) are in line with independent epidemiological data and investigations. In addition, retrospective predictions capture pandemic trajectories beyond the model training period. These detailed, validated model-inference estimates thus enable quantification of both the immune erosion potential and transmissibility of three major SARS-CoV-2 VOCs, i.e., Beta, Delta, and Omicron. These findings help elucidate changing COVID-19 dynamics and inform future public health planning.

Molecular characteristics, immune evasion, and impact of SARS-CoV-2 variants

The persistent COVID-19 pandemic since 2020 has brought an enormous public health burden to the global society and is accompanied by various evolution of the virus genome. The consistently emerging SARS-CoV-2 variants harboring critical mutations impact the molecular characteristics of viral proteins and display heterogeneous behaviors in immune evasion, transmissibility, and the clinical manifestation during infection, which differ each strain and endow them with distinguished features during populational spread. Several SARS-CoV-2 variants, identified as Variants of Concern (VOC) by the World Health Organization, challenged global efforts on COVID-19 control due to the rapid worldwide spread and enhanced immune evasion from current antibodies and vaccines. Moreover, the recent Omicron variant even exacerbated the global anxiety in the continuous pandemic. Its significant evasion from current medical treatment and disease control even highlights the necessity of combinatory investigation of the mutational pattern and influence of the mutations on viral dynamics against populational immunity, which would greatly facilitate drug and vaccine development and benefit the global public health policymaking. Hence in this review, we summarized the molecular characteristics, immune evasion, and impacts of the SARS-CoV-2 variants and focused on the parallel comparison of different variants in mutational profile, transmissibility and tropism alteration, treatment effectiveness, and clinical manifestations, in order to provide a comprehensive landscape for SARS-CoV-2 variant research.

Prevalence and risk factors for postinfectious cough in discharged patients with coronavirus disease 2019 (COVID-19)

Background

Cough is one of the most common symptoms of coronavirus disease 2019 (COVID-19). However, the prevalence of persistent cough in recovered patients with COVID-19 during a longer follow-up remained unknown. This study aims to investigate the prevalence, and risk factors for postinfectious cough in COVID-19 patients after discharge.

Methods

We conducted a follow-up study for 129 discharged patients with laboratory-confirmed COVID-19 in two large hospitals located in Hubei Province, China from January 2020 to December 2020. Baseline demographics, comorbidities and smoking history were extracted from the medical record. Current symptoms and severity were recorded by a uniform questionnaire. Spirometry, diffuse function and chest computed tomography (CT) were performed on part of patients who were able to return to the outpatient department at follow-up.

Results

The median (interquartile range) follow-up time was 8.1 (7.9-8.5) months after discharge. The mean (standard deviation) age was 51.5 (14.9) years and 57 (44.2%) were male. A total of 27 (20.9%) patients had postinfectious cough (>3 weeks), 6 patients (4.7%) had persistent cough by the end of follow-up, including 3 patients with previous chronic respiratory diseases or current smoking. Other symptoms included dyspnea (6, 4.7%), sputum (4, 3.1%), fatigue (4, 3.1%), and anorexia (4, 3.1%) by the end of follow-up. Thirty-six of 41 (87.8%) patients showed impaired lung function or diffuse function, and 39 of 50 (78.0%) patients showed abnormal CT imaging. Patients with postinfectious cough demonstrated more severe and more frequent cough during hospitalization (P<0.001), and more chronic respiratory diseases (P=0.01). In multivariate logistic regression analysis, digestive symptoms during hospitalization [odds ratio (OR) 2.95, 95% confidence interval (CI): 1.10-7.92] and current smoking (OR 6.95, 95% CI: 1.46-33.14) were significantly associated with postinfectious cough of COVID-19.

Conclusions

A small part of patients developed postinfectious cough after recovery from COVID-19, few patients developed chronic cough in spite of a higher proportion of impaired lung function and abnormal lung CT image. Current smoking and digestive symptoms during hospitalization were risk factors for postinfectious cough in COVID-19.