OMICRON: Virology, immunopathogenesis, and laboratory diagnosis

EG.5 (Eris) and BA.2.86 (Pirola) two new subvariants of SARS-CoV-2: a new face of old COVID-19

BACKGROUND

The World Health Organization announced the end of the Coronavirus Disease of 2019 (COVID-19) global health emergency on May 5, 2023. However, the reports from different countries indicate an elevation in the number of COVID-19-related hospitalizations and deaths through the last months. The subvariant XBB.1.5 (Kraken) was the cause of 49.1% of COVID-19 cases by the end of January 2023. Although, the subvariant EG.5 (Eris) has surpassed the XBB.1.5 recently. EG.5 is a close subvariant descending from XBB.1.9.2 subvariant of Omicron. EG.5.1 is a sublineage carrying two crucial spike mutations F456L and Q52H. Up to now, it is not well-established whether its infectivity, severity, and immune evasion have shown any change or not. Also, BA.2.86 another subvariant of Omicron descending from BA.2 bears over 30 mutations which could affect its infectivity and transmissibility.

METHODS

Scopus, PubMed, Google Scholar, and Google were searched with six keywords up to 20 November 2023 and highly reliable research and reports were selected to refer to in this article.

PURPOSE

This brief review aims to overview the most reliable data about EG.5 and BA.2.86 based on scientific evidence.

CONCLUSION

Based on the currently available data these two new subvariants have similar features with currently circulating variants of Omicron and are less immune evasive than ancestral SARS-CoV-2.

Neutralization antibody titer and change in 50% protection after the third dose of the COVID-19 vaccine

BACKGROUND

The new COVID-19 variant outbreak is the present global public health problem. The omicron variant of SARS-CoV-2 has several subvariants and causes outbreaks worldwide. Because of the increasing genetic heterogeneity of SARS-CoV-2, it is expected that using COVID-19 immunization to prevent and control disease will be problematic.

AIM

The aim of the study was to study neutralization of antibody titer and change in 50% protection after the third dose of the COVID-19 vaccine.

MATERIALS AND METHODS

In this report, the authors determine the expected neutralization antibody titer against omicron subvariants and the change in 50% protection against infection after the third dose of the immunization.

RESULTS

The change due to subvariant B.4 or B.5 is substantially higher than that due to the other subvariants. The efficacy of using viral vector vaccine boosters is questionable since viral vector COVID-19 boosters fail to generate enough antibodies to achieve the mean convalescent plasma level.

CONCLUSION

Higher antibody levels than the typical convalescent level and that needed for half protective property are still possible with the mRNA vaccine booster shot. In addition, compared to the half-dose regimen, the full-dose regimen produces a higher antibody level. As a booster shot, the mRNA COVID-19 vaccine is recommended.

SARS-CoV-2 variant biology and immune evasion

This chapter discusses the SARS-CoV-2 variants and their immune evasion strategies, shedding light on the dynamic nature of the COVID-19 pandemic. The ecological dynamics and viral evolution of SARS-CoV-2 are explored, considering carriers of infection, individual immunity profiles, and human movement as key factors in the emergence and dissemination of variants. The chapter discusses SARS-CoV-2 mutation, including mutation rate, substitution rate, and recombination, influencing genetic diversity and evolution. Transmission bottlenecks are highlighted as determinants of dominant variants during viral spread. The evolution phases of the pandemic are outlined, from limited early evolution to the emergence of notable changes like the D614G substitution and variants with heavy mutations. Variants of Concern (VOCs), including Alpha, Beta, Gamma, and the recent Omicron variant, are examined, with insights into inter-lineage and intra-lineage dynamics. The origin of VOCs and the Omicron variant is explored, alongside the role of the furin cleavage site (FCS) in variant emergence. The impact of structural and non-structural proteins on viral infectivity is assessed, as well as innate immunity evasion strategies employed by SARS-CoV-2 variants. The chapter concludes by considering future possibilities, including ongoing virus evolution, the need for surveillance, vaccine development, and public health measures.

Prognostic Factors and Outcomes in Advanced Stage Lung Cancer Patients with COVID-19 Omicron Variant Infection

Background

We study the characteristics and outcomes in lung cancer patients with COVID-19 Omicron variant infection.

Methods

Hospitalized lung cancer patients with advanced-stage disease and laboratory-confirmed COVID-19 Omicron infection were included. Pneumonitis involving at least 25% of lung parenchyma on CT scans, accompanied by symptoms and oxygen saturation below 93%, were criteria for enrollment. Pneumonitis severity was graded using CTCAE v5.0. Treatment included Paxlovid, prednisolone, anticoagulation, and ventilation. Initial data, radiographic findings, and outcomes were compared. Logistic regression was employed to determine risk factors for in-hospital mortality.

Results

Fifteen patients (median age: 65 years; 80.0% males) were included. 73.3% improved and were discharged, 20.0% died, and 6.7% remained intubated. Initial symptoms included cough (100.0%), fever (73.3%), and shortness of breath (53.3%). Symptoms resolved in discharged patients. Median fever duration was 3.5 days, and respiratory symptom recovery took 26 days. Three patients died due to respiratory failure from Omicron pneumonia. Lower oxygen saturation, reduced lymphocyte/neutrophil ratio on day 7, and diffuse bilateral lung lesions were poor prognostic factors.

Conclusion

This study underscores the importance of prompt intervention and early diagnosis for lung cancer patients infected with the COVID-19 Omicron variant. Lower oxygen saturation, decreased lymphocyte/neutrophil ratio on day 7, and diffuse lung lesions on CT scans were associated with worse outcomes. Clinicians should prioritize timely and comprehensive management to improve survival rates in this population.

Decreased NK cell count is a high-risk factor for convulsion in children with COVID-19

BACKGROUND

The neurological symptoms caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are of increasing concern. Convulsions are among the main neurological manifestations reported in children with coronavirus disease-2019 (COVID-19), and cause serious harm to physical and mental health. This study aimed to investigate the risk factors for convulsion in children with COVID-19.

METHODS

This prospective study was conducted at the Children's Hospital of Soochow University. In total, 102 COVID-19 patients with convulsion, 172 COVID-19 patients without convulsion, and 50 healthy controls were enrolled in the study. The children's clinical and laboratory data were analyzed to assess the risk factors for convulsion in COVID-19 patients.

RESULTS

Convulsions occurred in 37.2% of children, mostly those aged 1-3 years, who were hospitalized with the Omicron variant. The neutrophil count, neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), and mean platelet volume-to-platelet ratio (MPR) were significantly higher in the convulsion group than those in the non-convulsion and control groups (P < 0.01). However, the counts of lymphocytes, eosinophils, platelets, lymphocyte subsets, CD3+ T cells, CD4+ T cells, CD8+ T cells, and NK cells were lower in the convulsion group than those in the non-convulsion and control groups (P < 0.01). Multivariate regression analysis indicated that NK cell count (OR = 0.081, 95% CI: 0.010-0.652) and a history of febrile seizure (OR = 10.359, 95% CI: 2.115-50.746) were independent risk factors for the appearance of convulsions in COVID-19.

CONCLUSIONS

History of febrile seizure and decreased NK cell count were high-risk factors for convulsions in COVID-19 patients.

Comparative Computational Analysis of Spike Protein Structural Stability in SARS-CoV-2 Omicron Subvariants

The continuous emergence of new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants with multiple spike (S) protein mutations pose serious threats to current coronavirus disease 2019 (COVID-19) therapies. A comprehensive understanding of the structural stability of SARS-CoV-2 variants is vital for the development of effective therapeutic strategies as it can offer valuable insights into their potential impact on viral infectivity. S protein mediates a virus' attachment to host cells by binding to angiotensin-converting enzyme 2 (ACE2) through its receptor-binding domain (RBD), and mutations in this protein can affect its stability and binding affinity. We analyzed S protein structural stability in various Omicron subvariants computationally. Notably, the S protein sequences analyzed in this work were obtained directly from our own sample collection. We evaluated the binding free energy between S protein and ACE2 in several complex forms. Additionally, we measured distances between the RBD of each chain in S protein to analyze conformational changes. Unlike most of the prior studies, we analyzed full-length S protein-ACE2 complexes instead of only RBD-ACE2 complexes. Omicron subvariants including BA.1, BA.2, BA.2.12.1, BA.4/BA.5, BA.2.75, BA.2.75_K147E, BA.4.6 and BA.4.6_N658S showed enhanced stability compared to wild type, potentially due to distinct S protein mutations. Among them, BA.2.75 and BA.4.6_N658S exhibited the highest and lowest level of stability, respectively.

The CD19+ B cell as a marker for the febrile children infected with influenza A and Omicron variant

H3N2 and Omicron are common pathogens of respiratory infections in children. This study aimed to explore dynamic changes of lymphocyte subsets and the diagnostic value of CD19+ B cell in children infected with influenza A and Omicron. One hundred and sixty-five in-patients with H3N2, 175 in-patients with Omicron variant, and 50 age-matched healthy children from Children's Hospital of Soochow University were included in this study. The participants underwent 13 respiratory pathogens by DNA polymerase chain reaction (PCR), sputum culture, severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) DNA PCR, routine blood, and lymphocyte subset assays within 24 h of admission. The neutrophils, neutrophil-to-lymphocyte ratio, and monocyte-to-lymphocyte ratio in the H3N2 and Omicron groups were significantly higher than in the control groups (p < 0.05). However, the lymphocytes and eosinophils in the H3N2 and Omicron groups were lower than the control groups (p < 0.05). The CD3+ T cell, CD3+ CD4+ T cell, CD3+ CD8+ T cell, CD3- CD19+ B cell, and natural killer cell were lower in the H3N2 and Omicron groups than in the control group (p < 0.05). The CD3- CD19+ cell in the Omicron group was higher than that in the H3N2 group but lower than that in the control group (p < 0.05). In addition, CD3- CD19+ cell had good diagnostic value for H3N2 (area under the receiver operating characteristic curve = 0.902, p < 0.05). The children with H3N2 were more likely to have lower lymphocytes than children with Omicron. Additionally, B-cell count had good diagnostic value for H3N2.

From Alpha to Omicron: How Different Variants of Concern of the SARS-Coronavirus-2 Impacted the World

SARS-CoV-2, the virus that causes COVID-19, is prone to mutations and the generation of genetic variants. Since its first outbreak in 2019, SARS-CoV-2 has continually evolved, resulting in the emergence of several lineages and variants of concern (VOC) that have gained more efficient transmission, severity, and immune evasion properties. The World Health Organization has given these variants names according to the letters of the Greek Alphabet, starting with the Alpha (B.1.1.7) variant, which emerged in 2020, followed by the Beta (B.1.351), Gamma (P.1), Delta (B.1.617.2), and Omicron (B.1.1.529) variants. This review explores the genetic variation among different VOCs of SARS-CoV-2 and how the emergence of variants made a global impact on the pandemic.

Exploring the Syndecan-Mediated Cellular Internalization of the SARS-CoV-2 Omicron Variant

SARS-CoV-2 variants evolve to rely more on heparan sulfate (HS) for viral attachment and subsequent infection. In our earlier work, we demonstrated that the Delta variant's spike protein binds more strongly to HS compared to WT SARS-CoV-2, leading to enhanced cell internalization via syndecans (SDCs), a family of transmembrane HS proteoglycans (HSPGs) facilitating the cellular entry of the original strain. Using our previously established ACE2- or SDC-overexpressing cellular models, we now compare the ACE2- and SDC-dependent cellular uptake of heat-inactivated WT SARS-CoV-2 with the Delta and Omicron variants. Internalization studies with inactivated virus particles showed that ACE2 overexpression could not compensate for the loss of HS in Omicron's internalization, suggesting that this variant primarily uses HSPGs to enter cells. Although SDCs increased the internalization of all three viruses, subtle differences could be detected between their SDC isoform preferences. The Delta variant particularly benefitted from SDC1, 2, and 4 overexpression for cellular entry, while SDC4 had the most prominent effect on Omicron internalization. The SDC4 knockdown (KD) in Calu-3 cells reduced the cellular uptake of all three viruses, but the inhibition was the most pronounced for Omicron. The polyanionic heparin also hindered the cellular internalization of all three viruses with a dominant inhibitory effect on Omicron. Omicron's predominant HSPG affinity, combined with its preference for the universally expressed SDC4, might account for its efficient transmission yet reduced pathogenicity.

Recovery from olfactory and gustatory dysfunction following COVID-19 acquired during Omicron BA.1 wave in Italy

BACKGROUND

Despite alterations in the sense of smell and taste have dominated the symptoms of SARS-CoV-2 infection, the prevalence and the severity of self-reporting COVID-19 associated olfactory and gustatory dysfunction has dropped significantly with the advent of the Omicron BA.1 subvariant. However, data on the evolution of Omicron-related chemosensory impairment are still lacking.

OBJECTIVE

The aim of the present study was to estimate the prevalence and the recovery rate of self-reported chemosensory dysfunction 6-month after SARS-CoV-2 infection acquired during the predominance of the Omicron BA.1 subvariant in Italy.

METHODS

Prospective observational study based on the sino-nasal outcome tool 22 (SNOT-22), item "sense of smell or taste" and additional outcomes conducted in University hospitals and tertiary referral centers in Italy.

RESULTS

Of 338 patients with mild-to-moderate COVID-19 completing the baseline survey, 294 (87.0 %) responded to the 6-month follow-up interview. Among them, 101 (34.4 %) and 4 (1.4 %) reported an altered sense of smell or taste at baseline and at 6 months, respectively. Among the 101 patients with COVID-19-associated smell or taste dysfunction during the acute phase of the disease, 97 (96.0 %) reported complete resolution at 6 months. The duration of smell or taste impairment was significantly shorter in vaccinated patients (p = 0.007).

CONCLUSIONS

Compared with that observed in subjects infected during the first wave of the pandemic, the recovery rate from chemosensory dysfunctions reported in the present series of patients infected during the predominance of the Omicron BA.1 subvariant was more favorable with a shorter duration being positively influenced by vaccination.

Novel receptor, mutation, vaccine, and establishment of coping mode for SARS-CoV-2: current status and future

Since the outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its resultant pneumonia in December 2019, the cumulative number of infected people worldwide has exceeded 670 million, with over 6.8 million deaths. Despite the marketing of multiple series of vaccines and the implementation of strict prevention and control measures in many countries, the spread and prevalence of SARS-CoV-2 have not been completely and effectively controlled. The latest research shows that in addition to angiotensin converting enzyme II (ACE2), dozens of protein molecules, including AXL, can act as host receptors for SARS-CoV-2 infecting human cells, and virus mutation and immune evasion never seem to stop. To sum up, this review summarizes and organizes the latest relevant literature, comprehensively reviews the genome characteristics of SARS-CoV-2 as well as receptor-based pathogenesis (including ACE2 and other new receptors), mutation and immune evasion, vaccine development and other aspects, and proposes a series of prevention and treatment opinions. It is expected to provide a theoretical basis for an in-depth understanding of the pathogenic mechanism of SARS-CoV-2 along with a research basis and new ideas for the diagnosis and classification, of COVID-19-related disease and for drug and vaccine research and development.

Predicting omicron pneumonia severity and outcome: a single-center study in Hangzhou, China

Background

In December 2022, there was a large Omicron epidemic in Hangzhou, China. Many people were diagnosed with Omicron pneumonia with variable symptom severity and outcome. Computed tomography (CT) imaging has been proven to be an important tool for COVID-19 pneumonia screening and quantification. We hypothesized that CT-based machine learning algorithms can predict disease severity and outcome in Omicron pneumonia, and we compared its performance with the pneumonia severity index (PSI)-related clinical and biological features.

Methods

Our study included 238 patients with the Omicron variant who have been admitted to our hospital in China from 15 December 2022 to 16 January 2023 (the first wave after the dynamic zero-COVID strategy stopped). All patients had a positive real-time polymerase chain reaction (PCR) or lateral flow antigen test for SARS-CoV-2 after vaccination and no previous SARS-CoV-2 infections. We recorded patient baseline information pertaining to demographics, comorbid conditions, vital signs, and available laboratory data. All CT images were processed with a commercial artificial intelligence (AI) algorithm to obtain the volume and percentage of consolidation and infiltration related to Omicron pneumonia. The support vector machine (SVM) model was used to predict the disease severity and outcome.

Results

The receiver operating characteristic (ROC) area under the curve (AUC) of the machine learning classifier using PSI-related features was 0.85 (accuracy = 87.40%, p < 0.001) for predicting severity while that using CT-based features was only 0.70 (accuracy = 76.47%, p = 0.014). If combined, the AUC was not increased, showing 0.84 (accuracy = 84.03%, p < 0.001). Trained on outcome prediction, the classifier reached the AUC of 0.85 using PSI-related features (accuracy = 85.29%, p < 0.001), which was higher than using CT-based features (AUC = 0.67, accuracy = 75.21%, p < 0.001). If combined, the integrated model showed a slightly higher AUC of 0.86 (accuracy = 86.13%, p < 0.001). Oxygen saturation, IL-6, and CT infiltration showed great importance in both predicting severity and outcome.

Conclusion

Our study provided a comprehensive analysis and comparison between baseline chest CT and clinical assessment in disease severity and outcome prediction in Omicron pneumonia. The predictive model accurately predicts the severity and outcome of Omicron infection. Oxygen saturation, IL-6, and infiltration in chest CT were found to be important biomarkers. This approach has the potential to provide frontline physicians with an objective tool to manage Omicron patients more effectively in time-sensitive, stressful, and potentially resource-constrained environments.

Blood Biomarkers from the Emergency Department Disclose Severe Omicron COVID-19-Associated Outcomes

Background: Since its outbreak, Coronavirus disease 2019 (COVID-19), a life-threatening respiratory illness, has rapidly become a public health emergency with a devastating social impact. Lately, the Omicron strain is considered the main variant of concern. Routine blood biomarkers are, indeed, essential for stratifying patients at risk of severe outcomes, and a huge amount of data is available in the literature, mainly for the previous variants. However, only a few studies are available on early routine biochemical blood biomarkers for Omicron-afflicted patients. Thus, the aim and novelty of this study were to identify routine blood biomarkers detected at the emergency room for the early prediction of severe morbidity and/or mortality. Methods: 449 COVID-19 patients from Sapienza University Hospital of Rome were divided into four groups: (1) the emergency group (patients with mild forms who were quickly discharged); (2) the hospital ward group (patients that after the admission in the emergency department were hospitalized in a COVID-19 ward); (3) the intensive care unit (ICU) group (patients that after the admission in the emergency department required intensive assistance); (4) the deceased group (patients that after the admission in the emergency department had a fatal outcome). Results: ANOVA and ROC data showed that high-sensitivity troponin-T (TnT), fibrinogen, glycemia, C-reactive protein, lactate dehydrogenase, albumin, D-dimer myoglobin, and ferritin for both men and women may predict lethal outcomes already at the level of the emergency department. Conclusions: Compared to previous Delta COVID-19 parallel emergency patterns of prediction, Omicron-induced changes in TnT may be considered other early predictors of severe outcomes.

Immune evasion of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2); molecular approaches

In December 2019, a new betacoronavirus, known as severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), caused an outbreak at the Wuhan seafood market in China. The disease was further named coronavirus disease 2019 (COVID-19). In March 2020, the World Health Organization (WHO) announced the disease to be a pandemic, as more cases were reported globally. SARS-CoV-2, like many other viruses, employs diverse strategies to elude the host immune response and/or counter immune responses. The infection outcome mainly depends on interactions between the virus and the host immune system. Inhibiting IFN production, blocking IFN signaling, enhancing IFN resistance, and hijacking the host's translation machinery to expedite the production of viral proteins are among the main immune evasion mechanisms of SARS-CoV-2. SARS-CoV-2 also downregulates the expression of MHC-I on infected cells, which is an additional immune-evasion mechanism of this virus. Moreover, antigenic modifications to the spike (S) protein, such as deletions, insertions, and also substitutions are essential for resistance to SARS-CoV-2 neutralizing antibodies. This review assesses the interaction between SARS-CoV-2 and host immune response and cellular and molecular approaches used by SARS-CoV-2 for immune evasion. Understanding the mechanisms of SARS-CoV-2 immune evasion is essential since it can improve the development of novel antiviral treatment options as well as vaccination methods.

Protective Effect of Inactivated COVID-19 Vaccines against Omicron BA.2 Infection in Guangzhou: A Test-Negative Case-Control Real-World Study

This study aims to explore the relationship between the doses of inactivated COVID-19 vaccines received and SARS-CoV-2 Omicron infection in the real-world setting, so as to preliminarily evaluate the protective effect induced by COVID-19 vaccination. We conducted a test-negative case-control study and recruited the test-positive cases and test-negative controls in the outbreak caused by Omicron BA.2 in April 2022 in Guangzhou, China. All the participants were 3 years and older. The vaccination status between the case group and the control group was compared in the vaccinated and all participants, respectively, to estimate the immune protection of inactivated COVID-19 vaccines. After adjusting for sex and age, compared with a mere single dose, full vaccination of inactivated COVID-19 vaccines (OR = 0.191, 95% CI: 0.050 to 0.727) and booster vaccination (OR = 0.091, 95% CI: 0.011 to 0.727) had a more superior protective effect. Compared with one dose, the second dose was more effective in males (OR = 0.090), as well as two doses (OR = 0.089) and three doses (OR = 0.090) among individuals aged 18–59. Whereas, when compared with the unvaccinated, one dose (OR = 7.715, 95% CI: 1.904 to 31.254) and three doses (OR = 2.055, 95% CI: 1.162 to 3.635) could contribute to the increased risk of Omicron infection after adjusting for sex and age. Meanwhile, by contrast with unvaccinated individuals, the result of increased risk was also manifested in the first dose in males (OR = 12.400) and one dose (OR = 21.500), two doses (OR = 1.890), and a booster dose (OR = 1.945) in people aged 18–59. In conclusion, the protective effect of full and booster vaccination with inactivated COVID-19 vaccines exceeded the incomplete vaccination, of which three doses were more effective. Nevertheless, vaccination may increase the risk of Omicron infection compared with unvaccinated people. This may result from the transmission traits of BA.2, the particularity and stronger protection awareness of the unvaccinated population, as well as the ADE effect induced by the decrease of antibody titers after a long time of vaccination. It is crucial to explore this issue in depth for the formulation of future COVID-19 vaccination strategies.

Positivization time of a COVID-19 rapid antigen self-test predicts SARS-CoV-2 viral load: a proof of concept

OBJECTIVES

This proof of concept study was aimed to validate the hypothesis that the time of positivization of SARS-CoV-2 self-performed rapid diagnostic tests (RDTs) may reflect the actual viral load in the specimen.

METHODS

A SARS-CoV-2 positive sample with high viral load was diluted and concomitantly assayed with molecular assay (Xpert Xpress SARS-CoV-2) and RDT (COVID-VIRO ALL IN RDT). The (mean cycle threshold; Ct) values and RDT positivization times of these dilutions were plotted and interpolated by calculating the best fit. The parameters of this equation were then used for converting the positivization times into RDT-estimated SARS-CoV-2 Ct values in routine patient samples.

RESULTS

The best fit between measured and RDT-estimated Ct values could be achieved with a 2-degree polynomial curve. The RDT-estimated Ct values exhibited high correlation (r=0.996) and excellent Deming fit (y=1.01 × x - 0.18) with measured Ct values. In 30 consecutive patients with positive RDT test, the correlation between RDT positivization time and measured Ct value was r=0.522 (p=0.003). The correlation of RDT-estimated and measured Ct values slightly improved to 0.577 (Deming fit: y=0.44 × x + 11.08), displaying a negligible bias (1.0; 95% CI, -0.2 to 2.2; p=0.105). Concordance of RDT-estimated and measured Ct values at the <20 cut-off was 80%, with 0.84 sensitivity and 0.73 specificity.

CONCLUSIONS

This proof of concept study demonstrates the potential feasibility of using RDTs for garnering information on viral load in patients with acute SARS-CoV-2 infection.

Omicron Variant of SARS-CoV-2: An Indian Perspective of Vaccination and Management

Omicron variants have highly influenced the entire globe. It has a high rate of transmissibility, which makes its management tedious. There are various subtypes of omicron, namely BA.1, BA.2, BA.3, BA.4, and BA.5. Currently, one omicron subvariant BF.7 is also immersed in some parts of India. Further studies are required for a better understanding of the new immersing SARS-CoV-2 subvariant of the omicron. They differ in the mutation of the spike proteins, which alters their attachment to the host receptor and hence modifies their virulence and adaptability. Delta variants have a great disastrous influence on the entire world, especially in India. While overcoming it, another mutant catches the pace. The Indian population is highly affected by omicron variants. It alters the entire management and diagnosis system against COVID-19. It demanded forcemeat in the health care system, both qualitatively and quantitively, to cope with the omicron wave. The alteration in spike protein, which is the major target of vaccines, leads to varied immunization against the subvariants. The efficacy of vaccines against the new variant was questioned. Every vaccine had a different shielding effect on the new variant. The hesitancy of vaccination was a prevalent factor in India that might have contributed to its outbreak. The prevalence of omicron, monkeypox, and tomato flu shared some similarities and distinct features when compared to their influence on the Indian population. This review emphasizes the changes omicron brings with it and how the Indian health care system outrage this dangerous variant.

Thymosin alpha1 use in adult COVID-19 patients: A systematic review and meta-analysis on clinical outcomes

OBJECTIVE

Thymosin alpha1 (Ta1) is widely used to treat patients with coronavirus disease 2019 (COVID-19), however, its effect remains unclear. This systematic review and meta-analysis aimed to evaluate the effect of Ta1 as a COVID-19 therapy.

METHODS

PubMed, EMBASE, the Cochrane library, Web of Science, and the reference lists of relevant articles were searched to identify eligible studies. Assessment of heterogeneity was done using the I-squared (I²) test and random/fixed effect analysis was done to determine the risk ratio (RR). We polled the data related to mortality mainly by using Review Manager 5.4. Predefined subgroup analyses and sensitivity analyses were also performed.

RESULTS

A total of 9 studies were included, on a total of 5352 (Ta1 = 1152, control = 4200) patient outcomes. Meta-analysis results indicated that Ta1 therapy had no statistically significant effect on mortality [RR 1.03 (0.60, 1.75), p = 0.92, I² = 90 %]. Subgroup analyses demonstrated that the beneficial effect in mortality was associated with mean age＞60 years in the Tα1 group [RR 0.68 (0.58, 0.78), p < 0.0000.1, I² = 0 %], the proportion of female ≤ 40 % in the Tα1 group [RR 0.67 (0.58, 0.77), p < 0.0000.1, I² = 0 %], and severe/critical COVID-19 patients [RR 0.66 (0.57, 0.76), p < 0.0000.1, I² = 0 %]. Sensitivity analysis further demonstrated the results to be robust.

CONCLUSIONS

The results of this meta-analysis do not support the use of Ta1 in hospitalized adult COVID-19 patients.

Association between immunity and viral shedding duration in non-severe SARS-CoV-2 Omicron variant-infected patients

Background

Coronavirus disease 2019 (COVID-19) is a respiratory-related disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). More than 200 countries worldwide are affected by this disease. The Omicron variant of SARS-CoV-2 is the major epidemic variant worldwide and is characterized by higher infectivity. However, the immunity and risk factors for prolonged viral elimination in patients with non-severe SARS-CoV-2 Omicron variant infections are unclear. Therefore, this study aimed to examine the relationship between immunity and duration of viral elimination in non-severe SARS-CoV-2 Omicron variant-infected patients in Shanghai.

Methods

In total, 108 non-severe SARS-CoV-2 Omicron variant-infected patients from Shanghai New International Expo Center Fangcang Shelter Hospital were recruited in this study. They were further allocated to the early elimination (EE) and prolonged elimination (PE) groups according to SARS-CoV-2 nucleic acid positivity duration.

Results

Compared to patients with EE, those with PE had increased serum concentrations of interleukin (IL)-5, IL-6, and IL-8; higher neutrophil count and neutrophil-to-lymphocyte ratio (NLR); lower lymphocyte, eosinophil, and red blood cell counts; and lower concentrations of hemoglobin and albumin (ALB). In lymphocyte subpopulation analysis, lower numbers of CD3⁺ T cells, CD4⁺ T cells, CD8⁺ T cells, and NK cells and a higher CD4/CD8 ratio were observed in patients with PE. In addition, correlation analysis results revealed that cycle threshold values of SARS-CoV-2 Omicron variant ORF1ab and N were negatively correlated with IL-6 and IL-8 levels and positively correlated with eosinophil count in patients with COVID-19. Finally, multivariate regression analysis showed that ALB, CD4/CD8 ratio, NLR, and eosinophil count were predictors of the SARS-CoV-2 Omicron variant elimination.

Conclusion

In this study, we identified that the ALB, CD4/CD8 ratio, NLR, and eosinophil count were risk factors for prolonged viral elimination in non-severe SARS-CoV-2 Omicron variant-infected patients. These factors might be efficient indicators in the diagnosis, evaluation, and prognosis monitoring of the disease.

The emergence of SARS-CoV-2 Omicron subvariants: current situation and future trends

The SARS-CoV-2 Omicron variant (B.1.1.529) has been the most recent variant of concern (VOC) established by the World Health Organization (WHO). Because of its greater infectivity and immune evasion, this variant quickly became the dominant type of circulating SARS-CoV-2 worldwide. Our literature review thoroughly explains the current state of Omicron emergence, particularly by comparing different omicron subvariants, including BA.2, BA.1, and BA.3. Such elaboration would be based on structural variations, mutations, clinical manifestation, transmissibility, pathogenicity, and vaccination effectiveness. The most notable difference between the three subvariants is the insufficiency of deletion (Δ69-70) in the spike protein, which results in a lower detection rate of the spike (S) gene target known as (S) gene target failure (SGTF). Furthermore, BA.2 had a stronger affinity to the human Angiotensin-converting Enzyme (hACE2) receptor than other Omicron sub-lineages. Regarding the number of mutations, BA.1.1 has the most (40), followed by BA.1, BA.3, and BA.3 with 39, 34, and 31 mutations, respectively. In addition, BA.2 and BA.3 have greater transmissibility than other sub-lineages (BA.1 and BA.1.1). These characteristics are primarily responsible for Omicron's vast geographical spread and high contagiousness rates, particularly BA.2 sub-lineages.

Older age and depressive state are risk factors for re-positivity with SARS-CoV-2 Omicron variant

Background

The reinfection rate of SARS-CoV-2 Omicron variant is high; thus, exploring the risk factors for reinfection is important for the effective control of the epidemic. This study aimed to explore the effects of psychological and sleep factors on re-positivity with Omicron.

Methods

Through a prospective cohort study, 933 adult patients diagnosed with Omicron BA.2.2 infection and testing negative after treatment were included for screening and follow-up. We collected data on patients' demographic characteristics, SARS-CoV-2 Omicron vaccination status, anxiety, depression, and sleep status. Patients underwent nucleic acid testing for SARS-CoV-2 Omicron for 30 days. Regression and Kaplan-Meier analyses were used to determine the risk factors for re-positivity of Omicron.

Results

Ultimately, 683 patients were included in the analysis. Logistic regression analysis showed that older age (P = 0.006) and depressive status (P = 0.006) were two independent risk factors for Omicron re-positivity. The odds ratios of re-positivity in patients aged ≥60 years and with a Patient Health Questionnaire-9 (PHQ-9) score ≥5 was 1.82 (95% confidence interval:1.18-2.78) and 2.22 (1.27-3.85), respectively. In addition, the time from infection to recovery was significantly longer in patients aged ≥60 years (17.2 ± 4.5 vs. 16.0 ± 4.4, P = 0.003) and in patients with PHQ-9≥5 (17.5 ± 4.2vs. 16.2 ± 4.5, P = 0.026). Kaplan-Meier analysis showed that there was a significantly higher primary re-positivity rate in patients aged ≥60 years (P = 0.004) and PHQ-9 ≥ 5 (P = 0.007).

Conclusion

This study demonstrated that age of ≥60 years and depressive status were two independent risk factors for re-positivity with Omicron and that these factors could prolong the time from infection to recovery. Thus, it is necessary to pay particular attention to older adults and patients in a depressive state.

Could the New BA.2.75 Sub-Variant Cause the Emergence of a Global Epidemic of COVID-19? A Scoping Review

With over 58 million cases and 6 million deaths by August 2022, the Coronavirus disease 2019 (COVID-19), causing severe acute respiratory syndrome coronavirus 2 (SARs-CoV-2), has had an insurmountable impact on the world’s population. This is one of the worst health crises since 1918’s influenza pandemic. There are four subvariants of Omicron; BA.1, BA.1.1, BA.2 and BA.3. As a result of new mutations in its spike protein, most of which occur in its receptor binding site, the Omicron variant appears to be more transmissible and less resistant to vaccination and antibody response. Understanding Omicron’s virology and mutations is essential to developing diagnostic and therapeutic methods. A thorough assessment of control measures, as well as timely adjustment of control measures, requires addressing such issues as re-infection risk, vaccine response, booster vaccine doses, and the increased rate of Omicron infections. This review article aims to look at the current information about the different types of SARs-CoV-2, focusing on the new subtype BA.2.75.

Occurrence of SARS-CoV-2 reinfections at regular intervals in Ecuador

SARS-CoV-2 reinfection is defined as a new infection with a different virus variant in an individual who has already recovered from a previous episode of COVID-19. The first case of reinfection in the world was described in August 2020, since then, reinfections have increased over time and their incidence has fluctuated with specific SARS-CoV-2 variant waves. Initially, reinfections were estimated to represent less than 1% of total COVID-19 infections. With the advent of the Omicron variant, reinfections became more frequent, representing up to 10% of cases (based on data from developed countries). The frequency of reinfections in Latin America has been scarcely reported. The current study shows that in Ecuador, the frequency of reinfections has increased 10-fold following the introduction of Omicron, after 22 months of surveillance in a single center of COVID-19 diagnostics. Suspected reinfections were identified retrospectively from a database of RT-qPCR-positive patients. Cases were confirmed by sequencing viral genomes from the first and second infections using the ONT MinION platform. Monthly surveillance showed that the main incidence peaks of reinfections were reached within four to five months, coinciding with the increase of COVID-19 cases in the country, suggesting that the emergence of reinfections is related to higher exposure to the virus during outbreaks. This study performed the longest monitoring of SARS-CoV-2 reinfections, showing an occurrence at regular intervals of 4-5 months and confirming a greater propensity of Omicron to cause reinfections.