Viral infection and transmission in a large, well-traced outbreak caused by the SARS-CoV-2 Delta variant

Characterization of a SARS-CoV-2 Infection Model in Golden Hamsters with Diabetes Mellitus

Being widespread across the globe, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) keeps evolving and generating new variants and continuously poses threat to public health, especially to the population with chronic comorbidities. Diabetes mellitus is one of high-risk factors for severe outcome of coronavirus disease 2019 (COVID-19). Establishment of animal models that parallel the clinical and pathological features of COVID-19 complicated with diabetes is thus highly essential. Here, in this study, we constructed leptin receptor gene knockout hamsters with the phenotype of diabetes mellitus (db/db), and revealed that the diabetic hamsters were more susceptible to SARS-CoV-2 and its variants than wild-type hamsters. SARS-CoV-2 and its variants induced a stronger immune cytokine response in the lungs of diabetic hamsters than in wild-type hamsters. Comparative histopathology analyses also showed that infection of SARS-CoV-2 and the variants caused more severe lung tissue injury in diabetic hamsters, and may induce serious complications such as diabetic kidney disease and cardiac lesions. Our findings demonstrated that despite the decreased respiratory pathogenicity, the SARS-CoV-2 variants were still capable of impairing other organs such as kidney and heart in diabetic hamsters, suggesting that the risk of evolving SARS-CoV-2 variants to diabetic patients should never be neglected. This hamster model may help better understand the pathogenesis mechanism of severe COVID-19 in patients with diabetes. It will also aid in development and testing of effective therapeutics and prophylactic treatments against SARS-CoV-2 variants among these high-risk populations.

Structural and Energetic Insights into SARS-CoV-2 Evolution: Analysis of hACE2-RBD Binding in Wild-Type, Delta, and Omicron Subvariants

The evolution of SARS-CoV-2, particularly the emergence of Omicron variants, has raised questions regarding changes in its binding affinity to the human angiotensin-converting enzyme 2 receptor (hACE2). Understanding the impact of mutations on the interaction between the receptor-binding domain (RBD) of the spike protein and hACE2 is critical for evaluating viral transmissibility, immune evasion, and the efficacy of therapeutic strategies. Here, we used molecular dynamics (MD) simulations and binding energy calculations to investigate the structural and energetic differences between the hACE2- RBD complexes of wild-type (WT), Delta, and Omicron subvariants. Our results indicate that the Delta and the first Omicron variants showed the highest and the second-highest binding energy among the variants studied. Furthermore, while Omicron variants exhibit increased structural stability and altered electrostatic potential at the hACE2-RBD interface when compared to the ancestral WT, their binding strength to hACE2 does not consistently increase with viral evolution. Moreover, newer Omicron subvariants like JN.1 exhibit a bimodal conformational strategy, alternating between a high-affinity state for hACE2 and a low-affinity state, which could potentially facilitate immune evasion. These findings suggest that, in addition to enhanced hACE2 binding affinity, other factors, such as immune evasion and structural adaptability, shape SARS-CoV-2 evolution.

The spread of the Delta variant in Catalonia during summer 2021: Modelling and interpretation

BACKGROUND

The emergence of highly transmissible SARS-CoV-2 variants has posed significant challenges to public health efforts worldwide. During the summer of 2021, the Delta variant (B.1.617.2) rapidly displaced the Alpha variant (B.1.1.7) in Catalonia, Spain, leading to a resurgence in infections despite ongoing vaccination campaigns. Understanding the epidemiological drivers of this outbreak is critical for refining future mitigation strategies.

METHODS

We employed a Bayesian age-stratified epidemiological model, incorporating vaccination status and variant-specific transmission dynamics, to analyze the outbreak in Catalonia. The model was calibrated using daily reported cases, hospitalizations, sequencing data, and vaccination coverage across age groups. We inferred contact patterns dynamically to assess their role in the epidemic resurgence and estimated the transmission advantage of the Delta variant over Alpha.

RESULTS

Our analysis revealed that increased social interactions among younger, less vaccinated populations significantly contributed to the surge in infections. The long weekend of Sant Joan (June 23-24) coincided with a peak in contact rates, driving a rise in the reproduction number, particularly among individuals aged 20-29. We estimated that the Delta variant had a 40-60.

CONCLUSIONS

Our findings underscore the critical role of vaccination coverage in mitigating the impact of emerging variants. The combination of increased social interactions and uneven vaccine distribution exacerbated the Delta-driven resurgence. NPIs alone proved insufficient in controlling transmission, highlighting the necessity of targeted vaccination strategies to achieve robust epidemic control. This study provides a framework for assessing future variant-specific threats and informing tailored public health interventions.

Tracking vaccine effectiveness in an evolving pandemic, countering misleading hot takes and epidemiologic fallacies

With the emergence of Omicron during the pandemic and the establishment of antibody waning over time, vaccine effectiveness, especially against infection, declined sharply from the original levels seen after the initial rollout. However, studies have demonstrated that they still provided substantial protection vs severe/fatal disease even with Omicron and after waning. Social media has been rife with reports claiming vaccines provided no benefit and some even claiming they made things worse, often driven by simple presentations of raw observational data using erroneous arguments involving epidemiologic fallacies including the base rate fallacy, Simpson's paradox, and the ecological fallacy and ignoring the extensive bias especially from confounding that is an inherent feature of these data. Similar fallacious arguments have been made by some in promoting vaccination policies, as well. Generally, vaccine effectiveness cannot be accurately estimated from raw population summaries but instead require rigorous, careful studies using epidemiologic designs and statistical analysis tools attempting to adjust for key confounders and sources of bias. This article summarizes what aggregated evidence across studies reveals about effectiveness of the mRNA vaccines as the pandemic has evolved, chronologically summarized with emerging variants and highlighting some of the fallacies and flawed arguments feeding social media-based claims that have obscured society's collective understanding.

Monitoring reported SARS-CoV-2 variants to assess the status of COVID-19 epidemics in the low epidemic state

The reported new confirmed cases of Coronavirus Disease 2019 (COVID-19) nowadays have diminished in their usefulness for assessing the pandemic situation. This study aimed to discover the correlation of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) variants recorded by Nextstrain clade and PANGO lineage and the number of new confirmed cases. Percent stacked area charts were utilized to display their development trends. 31 and 1452 variants were named according to Nextstrain clade and PANGO lineage, respectively. The branch step value maintained a stable increase by linear regression analysis. The changing trend in SARS-CoV-2 variants (PANGO lineage) correlated negatively with the number of new confirmed COVID-19 cases through Spearman rank correlation coefficient (17/06/2020-17/11/2021, ρ=-0.387, P < 0.01; 15/12/2021-11/01/2023, ρ=-0.458, P < 0.01). The proportion and composition of dominant virus variants had regional discrepancies, but some also fluctuated. The speed and quantity of SARS-CoV-2 variants objectively reflect the characteristics of the COVID-19 pandemic and viral dissemination in the population even without valuable data of reported new confirmed cases. The SARS-CoV-2 variation may be a better tool for epidemic monitoring and early-warning in the low epidemic state.

Simian Immunodeficiency Virus-Based Virus-like Particles Are an Efficient Tool to Induce Persistent Anti-SARS-CoV-2 Spike Neutralizing Antibodies and Specific T Cells in Mice

Background/Objectives: Virus-like particles (VLPs) represent an attractive platform for delivering vaccine formulations, combining a high biosafety profile with a potent immune-stimulatory ability. VLPs are non-infectious, non-replicating, self-assembling nanostructures that can be exploited to efficiently expose membrane-tethered glycoproteins such as the SARS-CoV-2 Spike (S) protein, the main target of approved preventive vaccines. Here, we describe the development and preclinical validation of Simian Immunodeficiency Virus (SIV)-based GFP-labeled VLPs displaying S from the B.1.617.2 (Delta) variant (VLP/S-Delta) for inducing persistent anti-SARS-CoV-2 neutralizing antibodies (nAbs) and S-specific T cell responses in mice. Methods: SIV-derived VLP/S-Delta were produced by co-transfecting a plasmid expressing SIVGag-GFP, required for VLP assembly and quantification by flow virometry, a plasmid encoding the Delta S protein deleted in the cytoplasmic tail (CT), to improve membrane binding, and a VSV.G-expressing plasmid, to enhance VLP uptake. Recovered VLPs were titrated by flow virometry and characterized in vitro by transmission electron microscopy (TEM) and confocal microscopy (CLSM). BALB/c mice were immunized intramuscularly with VLP/S-Delta following a prime-boost regimen, and humoral and cellular immune responses were assessed. Results: VLP/S-Delta were efficiently pseudotyped with CT-truncated S-Delta. After BALB/c priming, VLP/S-Delta elicited both specific anti-RBD IgGs and anti-Delta nAbs that significantly increased after the boost and were maintained over time. The prime-boost vaccination induced similar levels of cross-nAbs against the ancestral Wuhan-Hu-1 strain as well as cross-nAbs against Omicron BA.1, BA.2 and BA.4/5 VoCs, albeit at lower levels. Moreover, immunization with VLP/S-Delta induced S-specific IFNγ-producing T cells. Conclusions: These data suggest that SIV-based VLPs are an appropriate delivery system for the elicitation of efficient and sustained humoral and cellular immunity in mice, paving the way for further improvements in the immunogen design to enhance the quality and breadth of immune responses against different viral glycoproteins.

Modeling-based design of adaptive control strategy for the effective preparation of 'Disease X'

This study aims at exploring a general and adaptive control strategy to confront the rapid evolution of an emerging infectious disease ('Disease X'), drawing lessons from the management of COVID-19 in China. We employ a dynamic model incorporating age structures and vaccination statuses, which is calibrated using epidemic data. We therefore estimate the cumulative infection rate (CIR) during the first epidemic wave of Omicron variant after China relaxed its zero-COVID policy to be 82.9% (95% CI: 82.3%, 83.5%), with a case fatality rate (CFR) of 0.25% (95% CI: 0.248%, 0.253%). We further show that if the zero-COVID policy had been eased in January 2022, the CIR and CFR would have decreased to 81.64% and 0.205%, respectively, due to a higher level of immunity from vaccination. However, if we ease the zero-COVID policy during the circulation of Delta variant from June 2021, the CIR would decrease to 74.06% while the CFR would significantly increase to 1.065%. Therefore, in the face of a 'Disease X', the adaptive strategies should be guided by multiple factors, the 'zero-COVID-like' policy could be a feasible and effective way for the control of a variant with relative low transmissibility. However, we should ease the strategy as the virus matures into a new variant with much higher transmissibility, particularly when the population is at a high level of immunity.

Tracing Emergence of SARS-CoV-2 Variants: Insights from Comprehensive Assessment Using Reverse Transcription Polymerase Chain Reaction and Whole Genome Sequencing

The emergence and evolution of SARS-CoV-2 variants, such as Delta and Omicron, pose significant challenges to pandemic management. This study evaluated the effectiveness of reverse-transcription polymerase chain reaction (RT-PCR) and whole-genome sequencing (WGS) in detecting and characterizing SARS-CoV-2 variants using 624 samples collected in South Korea from mid-2021 to mid-2022. Two RT-PCR genotyping assays demonstrated a high concordance rate (90.4%) in identifying the Delta variant during its dominance. In contrast, WGS revealed extensive genetic diversity among Omicron sub-lineages, identifying 29 distinct sub-lineages, including two South Korea-specific variants (BA.1.1.5 and BA.2.3.8). Clustering analysis of WGS data highlighted distinct groupings of BA.1, BA.2, and BA.5 sub-lineages, with overlap in shared mutations suggesting evolutionary convergence. Sub-lineage diversity expanded during rapid transmission phases and subsequently consolidated as dominant lineages emerged. These findings highlight the complementary strengths of RT-PCR and WGS and underscore the importance of integrating these methodologies for effective variant monitoring and public health response.

A modeling study to define guidelines for antigen screening in schools and workplaces to mitigate COVID-19 outbreaks

BACKGROUND

In-person interaction offers invaluable benefits to people. To guarantee safe in-person activities during a COVID-19 outbreak, effective identification of infectious individuals is essential. In this study, we aim to analyze the impact of screening with antigen tests in schools and workplaces on identifying COVID-19 infections.

METHODS

We assess the effectiveness of various screening test strategies with antigen tests in schools and workplaces through quantitative simulations. The primary outcome of our analyses is the proportion of infected individuals identified. The transmission process at the population level is modeled using a deterministic compartmental model. Infected individuals are identified through screening tests or symptom development. The time-varying sensitivity of antigen tests and infectiousness is determined by a viral dynamics model. Screening test strategies are characterized by the screening schedule, sensitivity of antigen tests, screening duration, timing of screening initiation, and available tests per person.

RESULTS

Here, we show that early and frequent screening is the key to maximizing the effectiveness of the screening program. For example, 44.5% (95% CI: 40.8-47.5) of infected individuals are identified by daily testing, whereas it is only 33.7% (95% CI: 30.5-37.3) when testing is performed at the end of the program duration. If high sensitivity antigen tests (Detection limit: 6.3 × 10 4 copies/mL) are deployed, it reaches 69.3% (95% CI: 66.5-72.5).

CONCLUSIONS

High sensitivity antigen tests, high frequency screening tests, and immediate initiation of screening tests are important to safely restart educational and economic activities in-person. Our computational framework is useful for assessing screening programs by incorporating situation-specific factors.

Patterns of Isoform Variation for N Gene Subgenomic mRNAs in Betacoronavirus Transcriptomes

The nucleocapsid (N) protein is the most expressed protein in later stages of SARS-CoV-2 infection with several important functions. It is translated from a subgenomic mRNA (sgmRNA) formed by template switching during transcription. A recently described translation initiation site (TIS) with a CTG codon in the leader sequence (TIS-L) is out of frame with most structural and accessory genes including the N gene and may act as a translation suppressor. We analyzed multiple sequenced samples infected by SARS-CoV-2 and found that any single variant of this virus produces multiple isoforms of the N sgmRNA. The main isoform starting at TIS-L is out of frame, but two secondary dominant isoforms (present in nearly all samples) were found to restore the reading frame and likely involved in the regulation of N protein production. Analysis of sequenced samples infected by other coronaviruses revealed that such isoforms are also produced in their transcriptomes. In SARS-CoV, they restore the reading frame for a putative TIS (also a CTG codon) in the same relative position as in SARS-CoV-2. Positions of junction breakpoints relative to stem loop 3 in the 5'-UTR suggest similar mechanisms in SARS-CoV, SARS-CoV-2, and OC43, but not in MERS-CoV. These observations may be pertinent for antisense-based antiviral strategies.

Differential Impact of Spike Protein Mutations on SARS-CoV-2 Infectivity and Immune Evasion: Insights from Delta and Kappa Variants

SARS-CoV-2 continues to pose a global health challenge due to its high transmissibility and mutability, with new variants emerging that potentially undermine vaccination and therapeutic efforts. Mutations in the spike protein, particularly in the receptor-binding domain (RBD), significantly influence viral transmissibility and immune escape. However, the complex interplay of these mutations and their combined effects on viral fitness remain to be analyzed. In this study, we investigated the functional impact of key mutations found in the Delta and Kappa variants of SARS-CoV-2. Using pseudovirus assays, we demonstrated that the T478K and L452R mutations characteristic of the Delta variant primarily enhance viral infectivity, with minimal effect on antibody-mediated neutralization. Conversely, the E484Q mutation of the Kappa variant, alone or in combination with L452R, significantly improved evasion of antibody-mediated neutralization but appeared to compromise viral fitness and infectivity. Notably, contrary to previous reports, we found that the P681R mutation contributed neither to increased infectivity nor immune evasion at least in the assay system employed in this study. Our findings suggest that the Delta variant's global dominance over the Kappa variant may be attributed to its superior infectivity and transmissibility rather than enhanced immune evasion capabilities. These results provide valuable insights into the functional consequences of spike protein mutations and may aid in predicting the emergence and spread of future SARS-CoV-2 variants. Such understanding is crucial for enhancing public health preparedness and informing the development of next-generation vaccines and therapeutics.

Multi-Organ Spread and Intra-Host Diversity of SARS-CoV-2 Support Viral Persistence, Adaptation, and a Mechanism That Increases Evolvability

Intra-host diversity is an intricate phenomenon related to immune evasion, antiviral resistance, and evolutionary leaps along transmission chains. SARS-CoV-2 intra-host variation has been well-evidenced from respiratory samples. However, data on systemic dissemination and diversification are relatively scarce and come from immunologically impaired patients. Here, the presence and variability of SARS-CoV-2 were assessed among 71 tissue samples obtained from multiple organs including lung, intestine, heart, kidney, and liver from 15 autopsies with positive swabs and no records of immunocompromise. The virus was detected in most organs in the majority of autopsies. All organs presented intra-host single nucleotide variants (iSNVs) with low, moderate, and high abundances. The iSNV abundances observed within different organs indicate that the virus can mutate at one host site and subsequently spread to other parts of the body. In agreement with previous data from respiratory samples, our lung samples presented no more than 10 iSNVs each. But interestingly, when analyzing different organs we were able to detect between 11 and 45 iSNVs per case. Our results indicate that SARS-CoV-2 can replicate, and evolve in a compartmentalized manner, in different body sites, which agrees with the "viral reservoir" theory. We elaborate on how compartmentalized evolution in multiple organs may contribute to SARS-CoV-2 evolving so rapidly despite the virus having a proofreading mechanism.

Real-time estimates of the emergence and dynamics of SARS-CoV-2 variants of concern: A modeling approach

The emergence of SARS-CoV-2 variants of concern (VOCs) punctuated the dynamics of the COVID-19 pandemic in multiple occasions. The stages subsequent to their identification have been particularly challenging due to the hurdles associated with a prompt assessment of transmissibility and immune evasion characteristics of the newly emerged VOC. Here, we retrospectively analyze the performance of a modeling strategy developed to evaluate, in real-time, the risks posed by the Alpha and Omicron VOC soon after their emergence. Our approach utilized multi-strain, stochastic, compartmental models enriched with demographic information, age-specific contact patterns, the influence of non-pharmaceutical interventions, and the trajectory of vaccine distribution. The models' preliminary assessment about Omicron's transmissibility and immune evasion closely match later findings. Additionally, analyses based on data collected since our initial assessments demonstrate the retrospective accuracy of our real-time projections in capturing the emergence and subsequent dominance of the Alpha VOC in seven European countries and the Omicron VOC in South Africa. This study shows the value of relatively simple epidemic models in assessing the impact of emerging VOCs in real time, the importance of timely and accurate data, and the need for regular evaluation of these methodologies as we prepare for future global health crises.

Rapid detection of SARS-CoV-2 variants by molecular-clamping technology-based RT-qPCR

Given the challenges that SARS-CoV-2 variants have caused in terms of rapid spread and reduced vaccine efficacy, a rapid and cost-effective assay that can detect new and emerging variants is greatly needed worldwide. We have successfully applied the xenonucleic acid-based molecular-clamping technology to develop a multiplex reverse-transcription quantitative real-time PCR assay for SARS-CoV-2 multivariant detection. The assay was used to test 649 nasopharyngeal swab samples that were collected for clinical diagnosis or surveillance. The assay was able to correctly identify all 36 Delta variant samples as it accurately detected the D614G, T478K, and L452R mutations. In addition, the assay was able to correctly identify all 34 Omicron samples by detecting the K417N, T478K, N501Y, and D614G mutations. This technique reliably detects a variety of variants and has an analytical sensitivity of 100 copies/mL. In conclusion, this novel assay can serve as a rapid and cost-effective tool to facilitate large-scale detection of SARS-CoV-2 variants.

IMPORTANCE

We have developed a multiplex reverse-transcription quantitative real-time PCR (RT-qPCR) testing platform for the rapid detection of SARS-CoV-2 variants using the xenonucleic acid (XNA)-based molecular-clamping technology. The XNA-based RT-qPCR assay can achieve high sensitivity with a limit of detection of about 100 copies/mL for variant detection which is much better than the next-generation sequencing (NGS) assay. Its turnaround time is about 4 hours with lower cost and a lot of Clinical Laboratory Improvement Amendments (CLIA) labs own the instrument and meet skillset requirements. This assay provides a rapid, reliable, and cost-effective testing platform for rapid detection and monitoring of known and emerging SARS-CoV-2 variants. This testing platform can be adopted by laboratories that perform routine SARS-CoV-2 PCR testing, providing a rapid and cost-effective method in lieu of NGS-based assays, for detecting, differentiating, and monitoring SARS-CoV-2 variants. This assay is easily scalable to any new variant(s) should it emerge.

One Year of Wastewater Surveillance in South Africa Supporting COVID-19 Clinical Findings Across Two Waves of Infection

Wastewater-based epidemiology (WBE) has been an important tool for the detection of COVID-19 outbreaks. The retrospective analysis of COVID-19 data is vital to understand the spread and impact of the virus as well as to inform future planning and response efforts. In this study, we evaluated the SARS-CoV-2 RNA levels in wastewater from 21 wastewater treatment plants (WWTPs) in the City of Cape Town (South Africa) over a period of 12 months and compared the (inactive) SARS-CoV-2 viral RNA in wastewater between wave 2 (November 2020 to January 2021) and wave 3 (June 2021 to September 2021). The SARS-CoV-2 RNA expression was quantified in wastewater using quantitative real-time PCR (qRT-PCR) by targeting the nucleocapsid (N) gene, and the resultant signal was normalized to the WWTP design capacity and catchment size. Our findings show that the maximum SARS-CoV-2 RNA signal was significantly higher in wave 3 than in wave 2 (p < 0.01). The duration of wave 3 (15 weeks) was longer than that of wave 2 (10 weeks), and the wastewater surveillance data supported the clinical findings, as evidenced by the two distinct waves. Furthermore, the data demonstrated the importance of long-term wastewater surveillance as a key indicator of changing trends.

Attojoule Hexagonal Boron Nitride-Based Memristor for High-Performance Neuromorphic Computing

In next-generation neuromorphic computing applications, the primary challenge lies in achieving energy-efficient and reliable memristors while minimizing their energy consumption to a level comparable to that of biological synapses. In this work, hexagonal boron nitride (h-BN)-based metal-insulator-semiconductor (MIS) memristors operating is presented at the attojoule-level tailored for high-performance artificial neural networks. The memristors benefit from a wafer-scale uniform h-BN resistive switching medium grown directly on a highly doped Si wafer using metal-organic chemical vapor deposition (MOCVD), resulting in outstanding reliability and low variability. Notably, the h-BN-based memristors exhibit exceptionally low energy consumption of attojoule levels, coupled with fast switching speed. The switching mechanisms are systematically substantiated by electrical and nano-structural analysis, confirming that the h-BN layer facilitates the resistive switching with extremely low high resistance states (HRS) and the native SiOx on Si contributes to suppressing excessive current, enabling attojoule-level energy consumption. Furthermore, the formation of atomic-scale conductive filaments leads to remarkably fast response times within the nanosecond range, and allows for the attainment of multi-resistance states, making these memristors well-suited for next-generation neuromorphic applications. The h-BN-based MIS memristors hold the potential to revolutionize energy consumption limitations in neuromorphic devices, bridging the gap between artificial and biological synapses.

Ni3C/Ni3S2 Heterojunction Electrocatalyst for Efficient Methanol Oxidation via Dual Anion Co-modulation Strategy

Enhancing active states on the catalyst surface by modulating the adsorption-desorption properties of reactant species is crucial to optimizing the electrocatalytic activity of transition metal-based nanostructured materials. In this work, an efficient optimization strategy is proposed by co-modulating the dual anions (C and S) in Ni3C/Ni3S2, the heterostructured electrocatalyst, which is prepared via a simple hot-injection method. The presence of Ni3C/Ni3S2 heterojunctions accelerates the charge carrier transfer and promotes the generation of active sites, enabling the heterostructured electrocatalyst to achieve current densities of 10/100 mA cm-2 at 1.37 V/1.53 V. The Faradaic efficiencies for formate production coupled with hydrogen evolution approach 100%, accompanied with a stability record of 350 h. Additionally, operando electrochemical impedance spectroscopy (EIS), in situ Raman spectroscopy, and density functional theory (DFT) calculations further demonstrate that the creation of Ni3C/Ni3S2 heterointerfaces originating from dual anions' (C and S) differentiation is effective in adjusting the d-band center of active Ni atoms, promoting the generation of active sites, as well as optimizing the adsorption and desorption of reaction intermediates. This dual anions co-modulation strategy to stable heterostructure provides a general route for constructing high-performance transition metal-based electrocatalysts.

Early pulmonary fibrosis-like changes between delta and pre-delta periods in patients with severe COVID-19 pneumonia on mechanical ventilation

It remains unclear whether pulmonary fibrosis-like changes differ in patients with different SARS-CoV-2 variants. This study aimed to compare pulmonary fibrotic changes between two SARS-CoV-2 variant periods (delta vs. pre-delta) in critically ill patients with SARS-CoV-2 pneumonia. Clinical data and chest CT images of patients with SARS-CoV-2 pneumonia receiving mechanical ventilation were collected from 10 hospitals in South Korea over two periods: delta (July-December, 2021; n = 64) and pre-delta (February, 2020-June, 2021; n = 120). Fibrotic changes on chest CT were evaluated through visual assessment. Of 184 patients, the mean age was 64.6 years, and 60.5% were ale. Fibrosis-like changes on chest CT (median 51 days from enrollment to follow up CT scan, interquartile range 27-76 days) were identified in 75.3%. Delta group showed more fibrosis-like changes (≥ 2) (69.8% vs. 43.1%, P = 0.001) and more frequent reticulation and architectural distortion+/-parenchymal band than pre-delta group. Even after propensity score matching with clinical variables, delta group had more severe (≥ 2) fibrosis-like changes (71.4% vs. 38.8%, P = 0.001), and more frequent reticulation and architectural distortion+/-parenchymal band than pre-delta group. Our data suggest that critically ill patients with SARS-CoV-2 in delta period had more severe pulmonary fibrosis-like changes than those in pre-delta period.

Genomic epidemiology reveals the variation and transmission properties of SARS-CoV-2 in a single-source community outbreak

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused the coronavirus disease 2019 (COVID-19) pandemic, which is still a global public health concern. During March 2022, a rapid and confined single-source outbreak of SARS-CoV-2 was identified in a community in Nanjing municipal city. Overall, 95 individuals had laboratory-confirmed SARS-CoV-2 infection. The whole genomes of 61 viral samples were obtained, which were all members of the BA.2.2 lineage and clearly demonstrated the presence of one large clade, and all the infections could be traced back to the original index case. The most distant sequence from the index case presented a difference of 4 SNPs, and 118 intrahost single-nucleotide variants (iSNVs) at 74 genomic sites were identified. Some minor iSNVs can be transmitted and subsequently rapidly fixed in the viral population. The minor iSNVs transmission resulted in at least two nucleotide substitutions among all seven SNPs identified in the outbreak, generating genetically diverse populations. We estimated the overall transmission bottleneck size to be 3 using 11 convincing donor-recipient transmission pairs. Our study provides new insights into genomic epidemiology and viral transmission, revealing how iSNVs become fixed in local clusters, followed by viral transmission across the community, which contributes to population diversity.

Shift in Demographic Involvement and Clinical Characteristics of COVID-19 From Wild-Type SARS-CoV-2 to the Delta Variant in the Indian Population: In Silico Analysis

BACKGROUND

The Delta variant (B.1.617.2) was considered the most dangerous SARS-CoV-2 strain; however, in-depth studies on its impact based on demographic and clinical characteristics of COVID-19 are scarce.

OBJECTIVE

We aimed to investigate the shift in demographic and clinical characteristics of the COVID-19 pandemic with the emergence of the SARS-CoV-2 Delta variant compared with the wild-type (WT) strain (B.1).

METHODS

A cross-sectional study of COVID-19 cases in the Indian population caused by the WT strain (B.1) and Delta variant of SARS-CoV-2 was performed. The viral genomic sequence metadata containing demographic, vaccination, and patient status details (N=9500, NDelta=6238, NWT=3262) were statistically analyzed.

RESULTS

With the Delta variant, in comparison with the WT strain, a higher proportion of young individuals (<20 years) were infected (0-9 years: Delta: 281/6238, 4.5% vs B.1: 75/3262, 2.3%; 10-19 years: Delta: 562/6238, 9% vs B.1: 229/3262, 7%; P<.001). The proportion of women contracting infection increased (Delta: 2557/6238, 41% vs B.1: 1174/3262, 36%; P<.001). However, it decreased for men (Delta: 3681/6238, 59% vs B.1: 2088/3262, 64%; P<.001). An increased proportion of the young population developed symptomatic illness and were hospitalized (Delta: 27/262, 10.3% vs B.1: 5/130, 3.8%; P=.02). Moreover, an increased proportion of the women (albeit not men) from the young (Delta: 37/262, 14.1% vs B.1: 4/130, 3.1%; P<.001) and adult (Delta: 197/262, 75.2% vs B.1: 72/130, 55.4%; P<.001) groups developed symptomatic illness and were hospitalized. The mean age of men and women who contracted infection (Delta: men=37.9, SD 17.2 years; women=36.6, SD 17.6 years; P<.001; B.1: men=39.6, SD 16.9 years; women=40.1, SD 17.4 years; P<.001) as well as developing symptoms or being hospitalized (Delta: men=39.6, SD 17.4 years; women=35.6, SD 16.9 years, P<.001; B.1: men=47, SD 18 years; women=49.5, SD 20.9 years, P<.001) were considerably lower with the Delta variant than the B.1 strain. The total mortality was about 1.8 times higher with the Delta variant than with the WT strain. With the Delta variant, compared with B.1, mortality decreased for men (Delta: 58/85, 68% vs B.1: 15/20, 75%; P<.001); in contrast, it increased for women (Delta: 27/85, 32% vs B.1: 5/20, 25%; P<.001). The odds of death increased with age, irrespective of sex (odds ratio 3.034, 95% CI 1.7-5.2, P<.001). Frequent postvaccination infections (24/6238) occurred with the Delta variant following complete doses.

CONCLUSIONS

The increased involvement of young people and women, the lower mean age for illness, higher mortality, and frequent postvaccination infections were significant epidemiological concerns with the Delta variant.

COVID-19 mutations: An overview

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) belongs to the genus Beta coronavirus and the family of Coronaviridae. It is a positive-sense, non-segmented single-strand RNA virus. Four common types of human coronaviruses circulate globally, particularly in the fall and winter seasons. They are responsible for 10%-30% of all mild upper respiratory tract infections in adults. These are 229E, NL63 of the Alfacoronaviridae family, OC43, and HKU1 of the Betacoronaviridae family. However, there are three highly pathogenic human coronaviruses: SARS-CoV-2, Middle East respiratory syndrome coronavirus, and the latest pandemic caused by the SARS-CoV-2 infection. All viruses, including SARS-CoV-2, have the inherent tendency to evolve. SARS-CoV-2 is still evolving in humans. Additionally, due to the development of herd immunity, prior infection, use of medication, vaccination, and antibodies, the viruses are facing immune pressure. During the replication process and due to immune pressure, the virus may undergo mutations. Several SARS-CoV-2 variants, including the variants of concern (VOCs), such as B.1.1.7 (Alpha), B.1.351 (Beta), B.1.617/B.1.617.2 (Delta), P.1 (Gamma), and B.1.1.529 (Omicron) have been reported from various parts of the world. These VOCs contain several important mutations; some of them are on the spike proteins. These mutations may lead to enhanced infectivity, transmissibility, and decreased neutralization efficacy by monoclonal antibodies, convalescent sera, or vaccines. Mutations may also lead to a failure of detection by molecular diagnostic tests, leading to a delayed diagnosis, increased community spread, and delayed treatment. We searched PubMed, EMBASE, Covariant, the Stanford variant Database, and the CINAHL from December 2019 to February 2023 using the following search terms: VOC, SARS-CoV-2, Omicron, mutations in SARS-CoV-2, etc. This review discusses the various mutations and their impact on infectivity, transmissibility, and neutralization efficacy.

SARS-CoV-2 Delta and Omicron variants resist spike cleavage by human airway trypsin-like protease

Soluble host factors in the upper respiratory tract can serve as the first line of defense against SARS-CoV-2 infection. In this study, we described the identification and function of a human airway trypsin-like protease (HAT), capable of reducing the infectivity of ancestral SARS-CoV-2. Further, in mouse models, HAT analogue expression was upregulated by SARS-CoV-2 infection. The antiviral activity of HAT functioned through the cleavage of the SARS-CoV-2 spike glycoprotein at R682. This cleavage resulted in inhibition of the attachment of ancestral spike proteins to host cells, which inhibited the cell-cell membrane fusion process. Importantly, exogenous addition of HAT notably reduced the infectivity of ancestral SARS-CoV-2 in vivo. However, HAT was ineffective against the Delta variant and most circulating Omicron variants, including the BQ.1.1 and XBB.1.5 subvariants. We demonstrate that the P681R mutation in Delta and P681H mutation in the Omicron variants, adjacent to the R682 cleavage site, contributed to HAT resistance. Our study reports what we believe to be a novel soluble defense factor against SARS-CoV-2 and resistance of its actions in the Delta and Omicron variants.

Comprehensive contact tracing during an outbreak of alpha-variant SARS-CoV-2 in a rural community reveals less viral genomic diversity and higher household secondary attack rates than expected

Sequencing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes throughout the COVID-19 pandemic has generated a wealth of data on viral evolution across populations, but only a few studies have so far explored SARS-CoV-2 evolution across large connected transmission networks. Here, we couple data from SARS-CoV-2 sequencing with contact tracing data from an outbreak with a single origin in a rural Norwegian community where samples from all exposed persons were collected prospectively. A total of 134 nasopharyngeal samples were positive by PCR. Among the 121 retrievable genomes, 81 were identical to the genome of the introductor, thus demonstrating that genomics beyond clustering genotypically similar viral genomes to confirm relatedness offers limited additional value to manual contact tracing. In the cases where mutations were discovered, five small genetic clusters were identified. We observed a household secondary attack rate of 77%, with 92% of household members infected among households with secondary transmission, suggesting that SARS-CoV-2 introduction into large families is likely to affect all household members.

IMPORTANCE

In outbreak investigations, obtaining a full overview of infected individuals within a population is seldom achieved. We here present an example where a single introduction of B1.1.7 SARS-CoV-2 within a rural community allowed for tracing of the virus from an introductor via dissemination through larger gatherings into households. The outbreak occurred before widespread vaccination, allowing for a "natural" outbreak development with community lockdown. We show through sequencing that the virus can infect up to five consecutive persons without gaining mutations, thereby showing that contact tracing seems more important than sequencing for local outbreak investigations in settings with few alternative introductory transmission pathways. We also show how larger households where a child introduced transmission appeared more likely to promote further spread of the virus compared to households with an adult as the primary introductor.

Molecular epidemiology and population immunity of SARS-CoV-2 in Guangdong (2022-2023) following a pivotal shift in the pandemic

The SARS-CoV-2 Omicron variant sparked the largest wave of infections worldwide. Mainland China eased its strict COVID-19 measures in late 2022 and experienced two nationwide Omicron waves in 2023. Here, we investigated lineage distribution and virus evolution in Guangdong, China, 2022-2023 by comparing 5813 local viral genomes with the datasets from other regions of China and worldwide. Additionally, we conducted three large-scale serological surveys involving 1696 participants to measure their immune response to the BA.5 and XBB.1.9 before and after the corresponding waves. Our findings revealed the Omicron variants, mainly the BA.5.2.48 lineage, causing infections in over 90% of individuals across different age groups within a month. This rapid spread led to the establishment of widespread immunity, limiting the virus's ability to further adaptive mutation and dissemination. While similar immune responses to BA.5 were observed across all age groups after the initial wave, children aged 3 to 11 developed a stronger cross immune response to the XBB.1.9 strain, possibly explaining their lower infection rates in the following XBB.1 wave. Reinfection with Omicron XBB.1 variant triggered a more potent neutralizing immune response among older adults. These findings highlight the impact of age-specific immune responses on viral spread in potential future waves.

The public health impact of COVID-19 variants of concern on the effectiveness of contact tracing in Vermont, United States

Case investigation and contact tracing (CICT) are public health measures that aim to break the chain of pathogen transmission. Changes in viral characteristics of COVID-19 variants have likely affected the effectiveness of CICT programs. We estimated and compared the cases averted in Vermont when the original COVID-19 strain circulated (Nov. 25, 2020-Jan. 19, 2021) with two periods when the Delta strain dominated (Aug. 1-Sept. 25, 2021, and Sept. 26-Nov. 20, 2021). When the original strain circulated, we estimated that CICT prevented 7180 cases (55% reduction in disease burden), compared to 1437 (15% reduction) and 9970 cases (40% reduction) when the Delta strain circulated. Despite the Delta variant being more infectious and having a shorter latency period, CICT remained an effective tool to slow spread of COVID-19; while these viral characteristics did diminish CICT effectiveness, non-viral characteristics had a much greater impact on CICT effectiveness.

Development of a SARS-CoV-2 viral dynamic model for patients with COVID-19 based on the amount of viral RNA and viral titer

The target-cell limited model, which is one of the mathematical modeling approaches providing a quantitative understanding of viral dynamics, has been applied to describe viral RNA profiles of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in previous studies. However, these models have been developed mainly using patient data from the early phase of the pandemic. Furthermore, no reports focused on the profiles of the viral titer. In this study, the dynamics of both viral RNA and viral titer were characterized using data reflecting the current clinical situation in which the Omicron variant has become epidemic and vaccines for SARS-CoV-2 have become available. Consecutive data for 5212 viral RNA levels and 5216 viral titers were obtained from 720 patients with coronavirus disease 2019 (COVID-19) in a phase II/III study for ensitrelvir. Our model assumed that productively infected cells would produce only infectious viruses, which could be transformed into non-infectious viruses, and has been used to describe the dynamics of both viral RNA levels and viral titer. The time from infection to symptom onset (tinf) of unvaccinated patients was estimated to be 3.0 days, which was shorter than that of the vaccinated patients. The immune-related parameter as a power function for the vaccinated patients was 1.1 times stronger than that for the unvaccinated patients. Our model allows the prediction of the viral dynamics in patients with COVID-19 from the time of infection to symptom onset. Vaccination status was identified as a factor influencing tinf and the immune function.

Revisiting the ethnomedicinal, ethnopharmacological, phytoconstituents and phytoremediation of the plant Solanum viarum Dunal

Solanum viarum, a perennial shrub, belongs to the family Solanaceae known for its therapeutic value worldwide. As a beneficial remedial plant, it is used for treating several disorders like dysentery, diabetes, inflammation, and respiratory disorders. Phytochemistry studies of this plant have shown the presence of steroidal glycoside alkaloids, including solasonine, solasodine, and solamargine. It also has flavonoids, saponins, minerals, and other substances. S. viarum extracts and compounds possess a variety of pharmacological effects, including antipyretic, antioxidant, antibacterial, insecticidal, analgesic, and anticancer activity. Most of the heavy metals accumulate in the aerial sections of the plant which is considered a potential phytoremediation, a highly effective method for the treatment of metal-polluted soils. We emphasize the forgoing outline of S. viarum, as well as its ethnomedicinal and ethnopharmacological applications, the chemistry of its secondary metabolites, and heavy metal toxicity. In addition to describing the antitumor activity of compounds and their mechanisms of action isolated from S. viarum, liabilities are also explained and illustrated, including any significant chemical or metabolic stability and toxicity risks. A comprehensive list of information was compiled from Science Direct, PubMed, Google Scholar, and Web of Science using different key phrases (traditional use, ethnomedicinal plants, western Himalaya, Himachal Pradesh, S viarum, and biological activity). According to the findings of this study, we hope that this review will inspire further studies along the drug discovery pathway of the chemicals extracted from the plant of S. viarum. Further, this review shows that ethnopharmacological information from ethnomedicinal plants can be a promising approach to drug discovery for cancer and diabetes.

A Targeted LC-MRM3 Proteomic Approach for the Diagnosis of SARS-CoV-2 Infection in Nasopharyngeal Swabs

Since its first appearance, severe acute respiratory syndrome coronavirus 2 quickly spread around the world and the lack of adequate PCR testing capacities, especially during the early pandemic, led the scientific community to explore new approaches such as mass spectrometry (MS). We developed a proteomics workflow to target several tryptic peptides of the nucleocapsid protein. A highly selective multiple reaction monitoring-cubed (MRM3) strategy provided a sensitivity increase in comparison to conventional MRM acquisition. Our MRM3 approach was first tested on an Amsterdam public health cohort (alpha-variant, 760 participants) detecting viral nucleocapsid protein peptides from nasopharyngeal swabs samples presenting a cycle threshold value down to 35 with sensitivity and specificity of 94.2% and 100.0%, without immunopurification. A second iteration of the MS-diagnostic test, able to analyze more than 400 samples per day, was clinically validated on a Leiden-Rijswijk public health cohort (delta-variant, 2536 participants) achieving 99.9% specificity and 93.1% sensitivity for patients with cycle threshold values up to 35. In this manuscript, we also developed and brought the first proof of the concept of viral variant monitoring in a complex matrix using targeted MS.

SARS-CoV-2: pathogenesis, therapeutics, variants, and vaccines

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), emerged in December 2019 with staggering economic fallout and human suffering. The unique structure of SARS-CoV-2 and its underlying pathogenic mechanism were responsible for the global pandemic. In addition to the direct damage caused by the virus, SARS-CoV-2 triggers an abnormal immune response leading to a cytokine storm, culminating in acute respiratory distress syndrome and other fatal diseases that pose a significant challenge to clinicians. Therefore, potential treatments should focus not only on eliminating the virus but also on alleviating or controlling acute immune/inflammatory responses. Current management strategies for COVID-19 include preventative measures and supportive care, while the role of the host immune/inflammatory response in disease progression has largely been overlooked. Understanding the interaction between SARS-CoV-2 and its receptors, as well as the underlying pathogenesis, has proven to be helpful for disease prevention, early recognition of disease progression, vaccine development, and interventions aimed at reducing immunopathology have been shown to reduce adverse clinical outcomes and improve prognosis. Moreover, several key mutations in the SARS-CoV-2 genome sequence result in an enhanced binding affinity to the host cell receptor, or produce immune escape, leading to either increased virus transmissibility or virulence of variants that carry these mutations. This review characterizes the structural features of SARS-CoV-2, its variants, and their interaction with the immune system, emphasizing the role of dysfunctional immune responses and cytokine storm in disease progression. Additionally, potential therapeutic options are reviewed, providing critical insights into disease management, exploring effective approaches to deal with the public health crises caused by SARS-CoV-2.

B cell somatic hypermutation following COVID-19 vaccination with Ad26.COV2.S

The viral vector-based COVID-19 vaccine Ad26.COV2.S has been recommended by the WHO since 2021 and has been administered to over 200 million people. Prior studies have shown that Ad26.COV2.S induces durable neutralizing antibodies (NAbs) that increase in coverage of variants over time, even in the absence of boosting or infection. Here, we studied humoral responses following Ad26.COV2.S vaccination in individuals enrolled in the initial Phase 1/2a trial of Ad26.COV2.S in 2020. Through 8 months post vaccination, serum NAb responses increased to variants, including B.1.351 (Beta) and B.1.617.2 (Delta), without additional boosting or infection. The level of somatic hypermutation, measured by nucleotide changes in the VDJ region of the heavy and light antibody chains, increased in Spike-specific B cells. Highly mutated mAbs from these sequences neutralized more SARS-CoV-2 variants than less mutated comparators. These findings suggest that the increase in NAb breadth over time following Ad26.COV2.S vaccination is mediated by affinity maturation.

Estimated relative potential for airborne SARS-CoV-2 transmission in a day care centre

We estimated the hourly probability of airborne severe acute respiratory coronavirus 2 (SARS-CoV-2) transmission and further the estimated number of persons at transmission risk in a day care centre by calculating the inhaled dose for airborne pathogens based on their concentration, exposure time and activity. Information about the occupancy and activity of the rooms was collected from day care centre personnel and building characteristics were obtained from the design values. The generation rate of pathogens was calculated as a product of viral load of the respiratory fluids and the emission of the exhaled airborne particles, considering the prevalence of the disease and the activity of the individuals. A well-mixed model was used in the estimation of the concentration of pathogens in the air. The Wells-Riley model was used for infection probability. The approach presented in this study was utilised in the identification of hot spots and critical events in the day care centre. Large variation in the infection probabilities and estimated number of persons at transmission risk was observed when modelling a normal day at the centre. The estimated hourly infection probabilities between the worst hour in the worst room and the best hour in the best room varied in the ratio of 100:1. Similarly, the number of persons at transmission risk between the worst and best cases varied in the ratio 1000:1. Although there are uncertainties in the input values affecting the absolute risk estimates the model proved to be useful in ranking and identifying the hot spots and events in the building and implementing effective control measures.

Novel mutation N588 residue in the NS1 protein of feline parvovirus greatly augments viral replication

Feline parvovirus (FPV) infection is highly fatal in felines. NS1, which is a key nonstructural protein of FPV, can inhibit host innate immunity and promote viral replication, which is the main reason for the severe pathogenicity of FPV. However, the mechanism by which the NS1 protein disrupts host immunity and regulates viral replication is still unclear. Here, we identified an FPV M1 strain that is regulated by the NS1 protein and has more pronounced suppression of innate immunity, resulting in robust replication. We found that the neutralization titer of the FPV M1 strain was significantly lower than that of the other strains. Moreover, FPV M1 had powerful replication ability, and the FPV M1-NS1 protein had heightened efficacy in repressing interferon-stimulated genes (ISGs) expression. Subsequently, we constructed an FPV reverse genetic system, which confirmed that the N588 residue of FPV M1-NS1 protein is a key amino acid that bolsters viral proliferation. Recombinant virus containing N588 also had stronger ability to inhibit ISGs, and lower ISGs levels promoted viral replication and reduced the neutralization titer of the positive control serum. Finally, we confirmed that the difference in viral replication was abolished in type I IFN receptor knockout cell lines. In conclusion, our results demonstrate that the N588 residue of the NS1 protein is a critical amino acid that promotes viral proliferation by increasing the inhibition of ISGs expression. These insights provide a reference for studying the relationship between parvovirus-mediated inhibition of host innate immunity and viral replication while facilitating improved FPV vaccine production.IMPORTANCEFPV infection is a viral infectious disease with the highest mortality rate in felines. A universal feature of parvovirus is its ability to inhibit host innate immunity, and its ability to suppress innate immunity is mainly accomplished by the NS1 protein. In the present study, FPV was used as a viral model to explore the mechanism by which the NS1 protein inhibits innate immunity and regulates viral replication. Studies have shown that the FPV-NS1 protein containing the N588 residue strongly inhibits the expression of host ISGs, thereby increasing the viral proliferation titer. In addition, the presence of the N588 residue can increase the proliferation titer of the strain 5- to 10-fold without affecting its virulence and immunogenicity. In conclusion, our findings provide new insights and guidance for studying the mechanisms by which parvoviruses suppress innate immunity and for developing high-yielding FPV vaccines.

Characterizing Infections in Two Epidemic Waves of SARS-CoV-2 Omicron Variants: A Cohort Study in Guangzhou, China

BACKGROUND

After the adjustment of COVID-19 epidemic policy, mainland China experienced two consecutive waves of Omicron variants within a seven-month period. In Guangzhou city, as one of the most populous regions, the viral infection characteristics, molecular epidemiology, and the dynamic of population immunity are still elusive.

METHODS

We launched a prospective cohort study in the Guangdong Provincial CDC from December 2022 to July 2023. Fifty participants who received the same vaccination regimen and had no previous infection were recruited.

RESULTS

90% of individuals were infected with Omicron BA.5* variants within three weeks in the first wave. Thirteen cases (28.26%) experienced infection with XBB.1* variants, occurring from 14 weeks to 21 weeks after the first wave. BA.5* infections exhibited higher viral loads in nasopharyngeal sites compared to oropharyngeal sites. Compared to BA.5* infections, the XBB.1* infections had significantly milder clinical symptoms, lower viral loads, and shorter durations of virus positivity. The infection with the BA.5* variant elicited varying levels of neutralizing antibodies against XBB.1* among different individuals, even with similar levels of BA.5* antibodies. The level of neutralizing antibodies specific to XBB.1* determined the risk of reinfection.

CONCLUSIONS

The rapid large-scale infections of the Omicron variants have quickly established herd immunity among the population in mainland China. In the future of the COVID-19 epidemic, a lower infection rate but a longer duration can be expected. Given the large population size and ongoing diversified herd immunity, it remains crucial to closely monitor the molecular epidemiology of SARS-CoV-2 for the emergence of new variants of concern in this region. Additionally, the timely evaluation of the immune status across different age groups is essential for informing future vaccination strategies and intervention policies.

Synchronous Diagnosis of Respiratory Viruses Variants via Receptonics Based on Modeling Receptor-Ligand Dynamics

The transmission and pathogenesis of highly contagious fatal respiratory viruses are increasing, and the need for an on-site diagnostic platform has arisen as an issue worldwide. Furthermore, as the spread of respiratory viruses continues, different variants have become the dominant circulating strains. To prevent virus transmission, the development of highly sensitive and accurate on-site diagnostic assays is urgently needed. Herein, a facile diagnostic device is presented for multi-detection based on the results of detailed receptor-ligand dynamics simulations for the screening of various viral strains. The novel bioreceptor-treated electronics (receptonics) device consists of a multichannel graphene transistor and cell-entry receptors conjugated to N-heterocyclic carbene (NHC). An ultrasensitive multi-detection performance is achieved without the need for sample pretreatment, which will enable rapid diagnosis and prevent the spread of pathogens. This platform can be applied for the diagnosis of variants of concern in clinical respiratory virus samples and primate models. This multi-screening platform can be used to enhance surveillance and discriminate emerging virus variants before they become a severe threat to public health.

Single-molecule force stability of the SARS-CoV-2-ACE2 interface in variants-of-concern

Mutations in SARS-CoV-2 have shown effective evasion of population immunity and increased affinity to the cellular receptor angiotensin-converting enzyme 2 (ACE2). However, in the dynamic environment of the respiratory tract, forces act on the binding partners, which raises the question of whether not only affinity but also force stability of the SARS-CoV-2-ACE2 interaction might be a selection factor for mutations. Using magnetic tweezers, we investigate the impact of amino acid substitutions in variants of concern (Alpha, Beta, Gamma and Delta) and on force-stability and bond kinetic of the receptor-binding domain-ACE2 interface at a single-molecule resolution. We find a higher affinity for all of the variants of concern (>fivefold) compared with the wild type. In contrast, Alpha is the only variant of concern that shows higher force stability (by 17%) compared with the wild type. Using molecular dynamics simulations, we rationalize the mechanistic molecular origins of this increase in force stability. Our study emphasizes the diversity of contributions to the transmissibility of variants and establishes force stability as one of the several factors for fitness. Understanding fitness advantages opens the possibility for the prediction of probable mutations, allowing a rapid adjustment of therapeutics, vaccines and intervention measures.

Analysis of the COVID-19 model with self-protection and isolation measures affected by the environment

Since the global outbreak of COVID-19, the virus has continuously mutated and can survive in the air for long periods of time. This paper establishes and analyzes a model of COVID-19 with self-protection and quarantine measures affected by viruses in the environment to investigate the influence of viruses in the environment on the spread of the outbreak, as well as to develop a rational prevention and control measure to control the spread of the outbreak. The basic reproduction number was calculated and Lyapunov functions were constructed to discuss the stability of the model equilibrium points. The disease-free equilibrium point was proven to be globally asymptotically stable when $ R_0 < 1 $, and the endemic equilibrium point was globally asymptotically stable when $ R_0 > 1 $. The model was fitted using data from COVID-19 cases in Chongqing between November 1 to November 25, 2022. Based on the numerical analysis, the following conclusion was obtained: clearing the virus in the environment and strengthening the isolation measures for infected people can control the epidemic to a certain extent, but enhancing the self-protection of individuals can be more effective in reducing the risk of being infected and controlling the transmission of the epidemic, which is more conducive to the practical application.

Risk factors for SARS-CoV-2 transmission during a movie theater outbreak in Incheon in the Republic of Korea, November 2021: a retrospective study

BACKGROUND

We examined factors contributing to the transmission of an acute respiratory virus within multi-use facilities, focusing on an outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in a movie theater in the Republic of Korea.

METHODS

This retrospective cohort study involved a descriptive analysis of 48 confirmed cases. Logistic regression was applied to a cohort of 80 theater attendees to identify risk factors for infection. The infection source and transmission route were determined through gene sequencing data analysis.

RESULTS

Of the 48 confirmed cases, 35 were theater attendees (72.9%), 10 were family members of attendees (20.8%), 2 were friends (4.2%), and 1 was an employee (2.1%). Among the 80 individuals who attended the 3rd to 5th screenings of the day, 35 became infected, representing a 43.8% attack rate. Specifically, 28 of the 33 third-screening attendees developed confirmed SARSCoV-2, constituting an 84.8% attack rate. Furthermore, 11 of the 12 cases epidemiologically linked to the theater outbreak were clustered monophyletically within the AY.69 lineage. At the time of the screening, 35 individuals (72.9%) had received 2 vaccine doses. However, vaccination status did not significantly influence infection risk. Multivariate analysis revealed that close contacts had a 15.9-fold higher risk of infection (95% confidence interval, 4.37-78.39) than casual contacts.

CONCLUSION

SARS-CoV-2 transmission occurred within the theater, and extended into the community, via a moviegoer who attended the 3rd screening during the viral incubation period after contracting the virus from a family member. This study emphasizes the importance of adequate ventilation in theaters.

Trajectory of COVID-19 response and management strategy in China: scientific rationale driven strategy adjustments

The pneumonia caused by novel coronavirus SARS-CoV-2 infection in early December 2019, which was later named coronavirus disease 2019 (COVID-19) by the World Health Organization (WHO), rapidly spread across the world. China has made extraordinary efforts to this unprecedented pandemic, put its response and control at a very high level of infectious disease management (Category B but with measures for Category A), given top priority to the people and their lives, and balanced the pandemic control and socio-economic development. After more than three years' fighting against this disease, China downgraded the management of COVID-19 to Category B infectious disease on January 8, 2023 and the WHO declared the end of public health emergency on May 5, 2023. However, the ending of pandemic does not mean that the disease is no longer a health threat. Experiences against COVID-19 from China and the whole world should be learned to prepare well for the future public health emergencies. This article gives a systematic review of the trajectory of COVID-19 development in China, summarizes the critical policy arrangements and provides evidence for the adjustment during policy making process, so as to share experiences with international community and contribute to the global health for all humanity.

Impact of closed-off management due to COVID-19 rebound on maternal depression during pregnancy

BACKGROUND

This study aimed to assess the impacts of closed-off measures with different strictness levels (lockdown, partial lockdown and non-lockdown) and geographic proximity to patients with coronavirus disease 2019 (COVID-19) on prenatal depression during an epidemic rebound of COVID-19.

METHODS

This was a cross-sectional web-based survey including 880 pregnant women. Depressive symptoms were measured by Self-Rating Depression Scale (SDS) and geographic proximity was calculated using Geographic Information Systems. Linear and logistic regression were used to assess the associations of closed-off measures and geographic proximity with SDS scores and depressive symptoms. Restricted cubic splines were used to model non-linear associations between geographic proximity and depression symptoms.

RESULTS

Compared with those living in non-lockdown areas, women in lockdown areas had higher SDS scores (adjusted β: 3.51, 95% CI: 1.80, 5.21) and greater risk of depressive symptoms (adjusted OR: 4.00, 95% CI: 2.18, 7.35), but evidence for partial lockdown was not obvious. A progressive increase in the risk of depressive symptoms was found with decreasing distance to COVID-19 patients when geographic proximity was <8 kilometers. Compared to those in the 5th quintile of geographic proximity, women in the first, second and third quintiles had at least 6 times higher risk of depressive symptoms.

CONCLUSIONS

Pregnant women under strict closed-off management during COVID-19 epidemic have high risk of depression. A specific range around the residences of reported COVID-19 patients should be underlined as potential clustering of high prenatal depression levels. Our findings highlight the importance of enhancing mental health management during the COVID-19 epidemic for pregnant women.

Asymmetric Schottky Barrier-Generated MoS2/WTe2 FET Biosensor Based on a Rectified Signal

Field-effect transistor (FET) biosensors can be used to measure the charge information carried by biomolecules. However, insurmountable hysteresis in the long-term and large-range transfer characteristic curve exists and affects the measurements. Noise signal, caused by the interference coefficient of external factors, may destroy the quantitative analysis of trace targets in complex biological systems. In this report, a "rectified signal" in the output characteristic curve, instead of the "absolute value signal" in the transfer characteristic curve, is obtained and analyzed to solve these problems. The proposed asymmetric Schottky barrier-generated MoS2/WTe2 FET biosensor achieved a 105 rectified signal, sufficient reliability and stability (maintained for 60 days), ultra-sensitive detection (10 aM) of the Down syndrome-related DYRK1A gene, and excellent specificity in base recognition. This biosensor with a response range of 10 aM-100 pM has significant application potential in the screening and rapid diagnosis of Down syndrome.

Characteristics, outcome, duration of hospitalization, and cycle threshold of patients with COVID-19 referred to four hospitals in Babol City: a multicenter retrospective observational study on the fourth, fifth, and sixth waves

BACKGROUND

The aim of the present study was to compare the epidemiological patterns of severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) infections, hospitalizations, deaths, and duration of hospitalization during the fourth, fifth and sixth epidemic waves of coronavirus disease 2019 (COVID-19) in Iran.

METHODS

A multicenter retrospective observational study was conducted on hospitalized patients in four hospitals in the Babol district of northern Iran. The study periods were during the fourth, fifth, and sixth waves of the epidemic in Iran, (March 2021 to March 2022). A total of 13,312 patients with suspected COVID-19 were included. Patient demographics, medical history, length of hospital stay, and clinical outcomes were obtained from the hospital information system. Data on the cycle threshold (Ct) and SARS-CoV2 variant were collected for SARS-CoV2-positive cases.

RESULTS

The highest number of hospitalized patients was reported during the fifth (Delta) wave (5231; 39.3%), while the lowest number of hospitalized patients was reported during the sixth (Omicron) wave (2143; 16.1%). In total, 6459 (48.5%) out of 13,312 hospitalized patients with suspected COVID-19 had a positive rRT-PCR result. The fifth (Delta) wave had the highest number of SARS-CoV2 rRT-PCR-positive hospitalized patients (3573, 55.3%), while the sixth (Omicron) wave had the lowest number (835, 12.9%). Moreover, 238 (3.7%) patients with laboratory-confirmed COVID-19 died. The hospital mortality rate was 6.8% in the fourth (Alpha) wave, which reduced to 2.7 and 3.5% in the fifth (Delta) and sixth (Omicron) waves, respectively (p < 0.001).

CONCLUSIONS

This is the most comprehensive study evaluating the epidemiologic characteristics of laboratory-confirmed SARS-CoV2 cases in Iran during the Alpha, Delta, and Omicron waves. The highest number of SARS-CoV2-positive hospitalized patients was in the fifth wave of COVID-19 (dominance of the Delta variant), while the sixth wave (dominance of the Omicron variant) had the lowest number. Comorbidities were similar, and cardiovascular disease, diabetes, kidney disease, and hypertension were the main risk factors in all waves.

Transmission Bottleneck Size Estimation from De Novo Viral Genetic Variation

Sequencing of viral infections has become increasingly common over the last decade. Deep sequencing data in particular have proven useful in characterizing the roles that genetic drift and natural selection play in shaping within-host viral populations. They have also been used to estimate transmission bottleneck sizes from identified donor-recipient pairs. These bottleneck sizes quantify the number of viral particles that establish genetic lineages in the recipient host and are important to estimate due to their impact on viral evolution. Current approaches for estimating bottleneck sizes exclusively consider the subset of viral sites that are observed as polymorphic in the donor individual. However, these approaches have the potential to substantially underestimate true transmission bottleneck sizes. Here, we present a new statistical approach for instead estimating bottleneck sizes using patterns of viral genetic variation that arise de novo within a recipient individual. Specifically, our approach makes use of the number of clonal viral variants observed in a transmission pair, defined as the number of viral sites that are monomorphic in both the donor and the recipient but carry different alleles. We first test our approach on a simulated dataset and then apply it to both influenza A virus sequence data and SARS-CoV-2 sequence data from identified transmission pairs. Our results confirm the existence of extremely tight transmission bottlenecks for these 2 respiratory viruses.

Comparative analysis of SARS-CoV-2 variants Alpha (B.1.1.7), Gamma (P.1), Zeta (P.2) and Delta (B.1.617.2) in Vero-E6 cells: ultrastructural characterization of cytopathology and replication kinetics

This study compares the effects of virus-cell interactions among SARS-CoV-2 variants of concern (VOCs) isolated in Brazil in 2021, hypothesizing a correlation between cellular alterations and mortality and between viral load and transmissibility. For this purpose, reference isolates of Alpha, Gamma, Zeta, and Delta variants were inoculated into monolayers of Vero-E6 cells. Viral RNA was quantified in cell supernatants by RT‒PCR, and infected cells were analyzed by Transmission Electron Microscopy (TEM) for qualitative and quantitative evaluation of cellular changes 24, 48, and 72 hours postinfection (hpi). Ultrastructural analyses showed that all variants of SARS-CoV-2 altered the structure and function of mitochondria, nucleus, and rough endoplasmic reticulum of cells. Monolayers infected with the Delta variant showed the highest number of modified cells and the greatest statistically significant differences compared to those of other variants. Viral particles were observed in the cytosol and the cell membrane in 100 % of the cells at 48 hpi. Alpha showed the highest mean particle diameter (79 nm), and Gamma and Delta were the smallest (75 nm). Alpha and Gamma had the highest particle frequency per field at 48 hpi, while the same was observed for Zeta and Delta at 72 hpi and 24 hpi, respectively. The cycle threshold of viral RNA varied among the target protein, VOC, and time of infection. The findings presented here demonstrate that all four VOCs evaluated caused ultrastructural changes in Vero-E6 cells, which were more prominent when infection occured with the Delta variant.

Association of COVID with Mycosis in General

BACKGROUND

The COVID-19 pandemic caused by SARS-CoV-2 is a respiratory disease which created havoc worldwide, was accompanied by another peculiar, otherwise rare, secondary fungal infection Mucormycosis which was observed at exceptionally high incidence in India during the second wave of COVID-19. The article explores possible links between the two infectious diseases to understand a higher-than-normal occurrence of Mucormycosis in COVID-19 patients. Coronavirus enters the patients through ACE-2 and many other receptors like- NRP-1, TfR, CD-126, and CD-26. Virus bind to cells possessing these receptors and affect their proper functioning, disturbing homeostatic metabolism and resulting in conditions like hyperglycemia, Diabetic Ketoacidosis (DKA), low serum pH, iron overload, anemia, hypoxia, and immunosuppression as explained in the article. All these outcomes provide a very supportive environment for the attack and spread of Mucormycosis fungi. The major receptor for Mucormycosis in humans is the GRP-78. Its expression is upregulated by coronavirus entry and by hyperferritinemia, hyperglycemia, and acidic conditions prevalent in COVID patients, thus providing an easy entry for the fungal species. Upregulation of GRP-78 furthermore damages pancreatic β-cells and intensifies hyperglycemia, showing quite a synergic relationship. Inordinate rise of Mucormycosis cases in India might be explained by facts like- India possessing a large proportion of diabetic patients, emergence of a very deadly strain of coronavirus- Delta strain, higher doses of steroids and antibodies used to treat patients against this strain, overburdened health care services, sudden much higher need of oxygen supply and use of industrial oxygen could explain the Mucormycosis outbreak observed in India during the second wave of COVID-19.

OBJECTIVE

The present review discusses the functional interdependence between COVID-19 and Mucormycosis and summarizes the possible synergic links between COVID and Mucormycosis.

CONCLUSION

The receptors and metabolic pathways affected by COVID-19 result in severe physiological conditions- hyperglycemia, DKA, anemia, iron overload, immunosuppression, and hypoxia. All these conditions not only increase the expression of GRP-78, the major receptor for entry of fungi but also play a crucial role in providing quality media for Mucormycosis fungus to establish and grow. Hence explains the fungal epidemic observed in India during the second wave of COVID-19 in India.

A Survey of Fear for Others, Fear for Self, and Pandemic Anxiety Predicting Intention to Take the First Booster Vaccine to Combat COVID-19

This study examined the impact of fear and anxiety on the intent to take the first COVID-19 booster vaccine. The objective of this study is to provide guidance for messaging campaigns of public health practitioners. A survey approach provided insights about individuals' emotions of fear and anxiety related to adopting the first booster vaccine for the Coronavirus disease 2019 (COVID-19).

METHODS

Three independent variables were considered in their ability to predict the intent to take the first COVID-19 booster vaccine (BINT): Fear for Others (FOTH), Fear for SELF (FSELF), and COVID-19 Anxiety (CANX).

RESULTS

The confirmatory factor analysis supported an underlying three-factor solution for three central emotions in this study. A path analysis indicated significant direct effects for FOTH and FSELF in the prediction of BINT. The interdependent nature of these variables on the intent to get the first booster vaccine also was indicated by significant indirect effects.

DISCUSSION

Fear should be more precisely refined to include the fear for others (FOTH) beyond consideration of the fear for self (FSELF) from the impact of COVID-19.

CONCLUSIONS

FOTH and FSELF were demonstrated to be direct predictors of BINT. CANX was only found to be significant as part of indirect effects impacting BINT. Future investigation should be given to the mediating role of anxiety with FOTH and FSELF as the context changes.

Computational Modeling Insights into Extreme Heterogeneity in COVID-19 Nasal Swab Data

Throughout the COVID-19 pandemic, an unprecedented level of clinical nasal swab data from around the globe has been collected and shared. Positive tests have consistently revealed viral titers spanning six orders of magnitude! An open question is whether such extreme population heterogeneity is unique to SARS-CoV-2 or possibly generic to viral respiratory infections. To probe this question, we turn to the computational modeling of nasal tract infections. Employing a physiologically faithful, spatially resolved, stochastic model of respiratory tract infection, we explore the statistical distribution of human nasal infections in the immediate 48 h of infection. The spread, or heterogeneity, of the distribution derives from variations in factors within the model that are unique to the infected host, infectious variant, and timing of the test. Hypothetical factors include: (1) reported physiological differences between infected individuals (nasal mucus thickness and clearance velocity); (2) differences in the kinetics of infection, replication, and shedding of viral RNA copies arising from the unique interactions between the host and viral variant; and (3) differences in the time between initial cell infection and the clinical test. Since positive clinical tests are often pre-symptomatic and independent of prior infection or vaccination status, in the model we assume immune evasion throughout the immediate 48 h of infection. Model simulations generate the mean statistical outcomes of total shed viral load and infected cells throughout 48 h for each "virtual individual", which we define as each fixed set of model parameters (1) and (2) above. The "virtual population" and the statistical distribution of outcomes over the population are defined by collecting clinically and experimentally guided ranges for the full set of model parameters (1) and (2). This establishes a model-generated "virtual population database" of nasal viral titers throughout the initial 48 h of infection of every individual, which we then compare with clinical swab test data. Support for model efficacy comes from the sampling of infection dynamics over the virtual population database, which reproduces the six-order-of-magnitude clinical population heterogeneity. However, the goal of this study is to answer a deeper biological and clinical question. What is the impact on the dynamics of early nasal infection due to each individual physiological feature or virus-cell kinetic mechanism? To answer this question, global data analysis methods are applied to the virtual population database that sample across the entire database and de-correlate (i.e., isolate) the dynamic infection outcome sensitivities of each model parameter. These methods predict the dominant, indeed exponential, driver of population heterogeneity in dynamic infection outcomes is the latency time of infected cells (from the moment of infection until onset of viral RNA shedding). The shedding rate of the viral RNA of infected cells in the shedding phase is a strong, but not exponential, driver of infection. Furthermore, the unknown timing of the nasal swab test relative to the onset of infection is an equally dominant contributor to extreme population heterogeneity in clinical test data since infectious viral loads grow from undetectable levels to more than six orders of magnitude within 48 h.

COVID-19 vaccination strategies in settings with limited rollout capacity: a mathematical modelling case study in Sierra Leone

BACKGROUND

COVID-19 vaccine coverage in low- and middle-income countries continues to be challenging. As supplies increase, coverage is increasingly becoming determined by rollout capacity.

METHODS

We developed a deterministic compartmental model of COVID-19 transmission to explore how age-, risk-, and dose-specific vaccine prioritisation strategies can minimise severe outcomes of COVID-19 in Sierra Leone.

RESULTS

Prioritising booster doses to older adults and adults with comorbidities could reduce the incidence of severe disease by 23% and deaths by 34% compared to the use of these doses as primary doses for all adults. Providing a booster dose to pregnant women who present to antenatal care could prevent 38% of neonatal deaths associated with COVID-19 infection during pregnancy. The vaccination of children is not justified unless there is sufficient supply to not affect doses delivered to adults.

CONCLUSIONS

Our paper supports current WHO SAGE vaccine prioritisation guidelines (released January 2022). Individuals who are at the highest risk of developing severe outcomes should be prioritised, and opportunistic vaccination strategies considered in settings with limited rollout capacity.

Humoral and cellular immunity against diverse SARS-CoV-2 variants

Since the outbreak of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in late 2019, the virus has rapidly spread worldwide. This has led to an unprecedented global pandemic, marked by millions of COVID-19 cases and a significant number of fatalities. Over a relatively short period, several different vaccine platforms are developed and deployed for use globally to curb the pandemic. However, the genome of SARS-CoV-2 continuously undergoes mutation and/or recombination, resulting in the emergence of several variants of concern (VOC). These VOCs can elevate viral transmission and evade the neutralizing antibodies induced by vaccines, leading to reinfections. Understanding the impact of the SARS-CoV-2 genomic mutation on viral pathogenesis and immune escape is crucial for assessing the threat of new variants to public health. This review focuses on the emergence and pathogenesis of VOC, with particular emphasis on their evasion of neutralizing antibodies. Furthermore, the memory B cell, CD4+, and CD8+ T cell memory induced by different COVID-19 vaccines or infections are discussed, along with how these cells recognize VOC. This review summarizes the current knowledge on adaptive immunology regarding SARS-CoV-2 infection and vaccines. Such knowledge may also be applied to vaccine design for other pathogens.

Substitution spectra of SARS-CoV-2 genome from Pakistan reveals insights into the evolution of variants across the pandemic

Changing morbidity and mortality due to COVID-19 across the pandemic has been linked with factors such as the emergence of SARS-CoV-2 variants and vaccination. Mutations in the Spike glycoprotein enhanced viral transmission and virulence. We investigated whether SARS-CoV-2 mutation rates and entropy were associated COVID-19 in Pakistan, before and after the introduction of vaccinations. We analyzed 1,705 SARS-CoV-2 genomes using the Augur phylogenetic pipeline. Substitution rates and entropy across the genome, and in the Spike glycoprotein were compared between 2020, 2021 and 2022 (as periods A, B and C). Mortality was greatest in B whilst cases were highest during C. In period A, G clades were predominant, and substitution rate was 5.25 × 10-4 per site per year. In B, Delta variants dominated, and substitution rates increased to 9.74 × 10-4. In C, Omicron variants led to substitution rates of 5.02 × 10-4. Genome-wide entropy was the highest during B particularly, at Spike E484K and K417N. During C, genome-wide mutations increased whilst entropy was reduced. Enhanced SARS-CoV-2 genome substitution rates were associated with a period when more virulent SARS-CoV-2 variants were prevalent. Reduced substitution rates and stabilization of genome entropy was subsequently evident when vaccinations were introduced. Whole genome entropy analysis can help predict virus evolution to guide public health interventions.

Reproduction number projection for the COVID-19 pandemic

The recently derived Hybrid-Incidence Susceptible-Transmissible-Removed (HI-STR) prototype is a deterministic compartment model for epidemics and an alternative to the Susceptible-Infected-Removed (SIR) model. The HI-STR predicts that pathogen transmission depends on host population characteristics including population size, population density and social behaviour common within that population.

The HI-STR prototype is applied to the ancestral Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV2) to show that the original estimates of the Coronavirus Disease 2019 (COVID-19) basic reproduction number $\mathcal{R}_{0}$ R 0 for the United Kingdom (UK) could have been projected onto the individual states of the United States of America (USA) prior to being detected in the USA.

The Imperial College London (ICL) group’s estimate of $\mathcal{R}_{0}$ R 0 for the UK is projected onto each USA state. The difference between these projections and the ICL’s estimates for USA states is either not statistically significant on the paired Student t-test or not epidemiologically significant.

The SARS-CoV2 Delta variant’s $\mathcal{R}_{0}$ R 0 is also projected from the UK to the USA to prove that projection can be applied to a Variant of Concern (VOC). Projection provides both a localised baseline for evaluating the implementation of an intervention policy and a mechanism for anticipating the impact of a VOC before local manifestation.