The rapid replacement of the Delta variant by Omicron (B.1.1.529) in England

Diverse BCR usage and T cell activation induced by different COVID-19 sequential vaccinations

Limited knowledge is available on the differences in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) specific antibody breadth and T cell differentiation among different COVID-19 sequential vaccination strategies. In this study, we compared the immunogenicity of the third different dose of COVID-19 vaccines, such as mRNA (I-I-M), adenoviral vector (I-I-A), and recombinant protein (I-I-R) vaccines, in terms of the magnitude and breadth of antibody response and differentiation of SARS-CoV-2-specific T and B cells. These studies were performed in the same clinical trial, and the samples were assessed in the same laboratory. IGHV1-69, IGHV3-9, and IGHV4-34 were the dominant B cell receptor (BCR) usages of the I-I-M, I-I-A, and I-I-R groups, respectively; the RBD+ B cell activation capacities were comparable. Additionally, the I-I-R group was characterized by higher numbers of regulatory T cells, circulating T follicular helper cells (cTFH) - cTFH1 (CXRC3+CCR6-), cTFH1-17 (CXRC3+CCR6+), cTFH17 (CXRC3-CCR6+), and cTFH-CM (CD45RA-CCR7+), and lower SMNE+ T cell proliferative capacity than the other two groups, whereas I-I-A showed a higher proportion and number of virus-specific CD4+ T cells than I-I-R, as determined in ex vivo experiments. Our data confirmed different SARS-CoV-2-specific antibody profiles among the three different vaccination strategies and also provided insights regarding BCR usage and T/B cell activation and differentiation, which will guide a better selection of vaccination strategies in the future.

IMPORTANCE

Using the same laboratory test to avoid unnecessary interference due to cohort ethnicity, and experimental and statistical errors, we have compared the T/B cell immune response in the same cohort sequential vaccinated by different types of COVID-19 vaccine. We found that different sequential vaccinations can induce different dominant BCR usage with no significant neutralizing titers and RBD+ B-cell phenotype. Recombinant protein vaccine can induce higher numbers of regulatory T cells, circulating TFH (CTFH)1, CTFH17, and CTFH-CM, and lower SMNE+ T-cell proliferative capacity than the other two groups, whereas I-I-A showed higher proportion and number of virus-specific CD4+ T cells than I-I-R. Overall, our study provides a deep insight about the source of differences in immune protection of different types of COVID-19 vaccines, which further improves our understanding of the mechanisms underlying the immune response to SARS-CoV-2.

Competitive networked bi-virus spread: Existence of coexistence equilibria

The paper studies multi-competitive continuous-time epidemic processes. We consider the setting where two viruses are simultaneously prevalent, and the spread occurs due to individual-to-individual interaction. In such a setting, an individual is either not affected by any of the viruses, or infected by one and exactly one of the two viruses. One of the equilibrium points is the coexistence equilibrium, i.e., multiple viruses simultaneously infect separate fractions of the population. We provide a sufficient condition for the existence of a coexistence equilibrium. We identify a condition such that for certain pairs of spread matrices either every coexistence equilibrium lies on a line that is locally exponentially attractive, or there is no coexistence equilibrium. We then provide a condition that, for certain pairs of spread matrices, rules out the possibility of the existence of a coexistence equilibrium, and, as a consequence, establishes global asymptotic convergence to the endemic equilibrium of the dominant virus. Finally, we provide a mitigation strategy that employs one virus to ensure that the other virus is eradicated. The theoretical results are illustrated using simulations.

High-resolution epidemiological landscape from ~290,000 SARS-CoV-2 genomes from Denmark

Vast amounts of pathogen genomic, demographic and spatial data are transforming our understanding of SARS-CoV-2 emergence and spread. We examined the drivers of molecular evolution and spread of 291,791 SARS-CoV-2 genomes from Denmark in 2021. With a sequencing rate consistently exceeding 60%, and up to 80% of PCR-positive samples between March and November, the viral genome set is broadly whole-epidemic representative. We identify a consistent rise in viral diversity over time, with notable spikes upon the importation of novel variants (e.g., Delta and Omicron). By linking genomic data with rich individual-level demographic data from national registers, we find that individuals aged  < 15 and  > 75 years had a lower contribution to molecular change (i.e., branch lengths) compared to other age groups, but similar molecular evolutionary rates, suggesting a lower likelihood of introducing novel variants. Similarly, we find greater molecular change among vaccinated individuals, suggestive of immune evasion. We also observe evidence of transmission in rural areas to follow predictable diffusion processes. Conversely, urban areas are expectedly more complex due to their high mobility, emphasising the role of population structure in driving virus spread. Our analyses highlight the added value of integrating genomic data with detailed demographic and spatial information, particularly in the absence of structured infection surveys.

Emergence of SARS-CoV-2 variants KP.2 and KP.3 sparks concerns: What should we do?

SARS-CoV-2 continues to evolve and circulate globally. In recent weeks, variants such as KP.2 and KP.3 have been rapidly increasing in many countries. Prevention strategies such as receiving updated COVID-19 vaccines, wearing masks when recommended, washing hands frequently, getting tested if symptoms appear, and staying home when sick can help protect individuals and others from COVID-19.

Vaccine-induced strain replacement: theory and real-life implications

The value of preventive medicine is superior to treatment with vaccinations occupying high priority. Nevertheless, heavy pressure has started to form in regard to strains not included in vaccines contributing to the changing epidemiology of pathogen subtypes leading to 'vaccine-induced strain replacement'. Among other mechanisms, increasing fitness of nonvaccine strains and metabolic shifts in the subtypes have been described. Classical examples include pneumococcal infections and viral diseases, such as the human papilloma virus. Recently, it has been described in SARS-CoV-2, leading to the emergence of new subtypes, such as Omicron and Delta variants. The phenomenon has also been reported in Mycobacterium tuberculosis, Neisseria meningitidis and rotavirus. This study addresses the concepts, examples and implications of this phenomenon.

The real-time infection hospitalisation and fatality risk across the COVID-19 pandemic in England

The COVID-19 pandemic led to 231,841 deaths and 940,243 hospitalisations in England, by the end of March 2023. This paper calculates the real-time infection hospitalisation risk (IHR) and infection fatality risk (IFR) using the Office for National Statistics Coronavirus Infection Survey (ONS CIS) and the Real-time Assessment of Community Transmission Survey between November 2020 to March 2023. The IHR and the IFR in England peaked in January 2021 at 3.39% (95% Credible Intervals (CrI): 2.79, 3.97) and 0.97% (95% CrI: 0.62, 1.36), respectively. After this time, there was a rapid decline in the severity from infection, with the lowest estimated IHR of 0.32% (95% CrI: 0.27, 0.39) in December 2022 and IFR of 0.06% (95% CrI: 0.04, 0.08) in April 2022. We found infection severity to vary more markedly between regions early in the pandemic however, the absolute heterogeneity has since reduced. The risk from infection of SARS-CoV-2 has changed substantially throughout the COVID-19 pandemic with a decline of 86.03% (80.86, 89.35) and 89.67% (80.18, 93.93) in the IHR and IFR, respectively, since early 2021. From April 2022 until March 2023, the end of the ONS CIS study, we found fluctuating patterns in the severity of infection with the resumption of more normative mixing, resurgent epidemic waves, patterns of waning immunity, and emerging variants that have shown signs of convergent evolution.

Investigating the cause of a 2021 winter wave of COVID-19 in a border region in eastern Germany: a mixed-methods study, August to November 2021

It is so far unclear how the COVID-19 winter waves started and what should be done to prevent possible future waves. In this study, we deciphered the dynamic course of a winter wave in 2021 in Saxony, a state in Eastern Germany neighbouring the Czech Republic and Poland. The study was carried out through the integration of multiple virus genomic epidemiology approaches to track transmission chains, identify emerging variants and investigate dynamic changes in transmission clusters. For identified local variants of interest, functional evaluations were performed. Multiple long-lasting community transmission clusters have been identified acting as driving force for the winter wave 2021. Analysis of the dynamic courses of two representative clusters indicated a similar transmission pattern. However, the transmission cluster caused by a locally occurring new Delta variant AY.36.1 showed a distinct transmission pattern, and functional analyses revealed a replication advantage of it. This study indicated that long-lasting community transmission clusters starting since early autumn caused by imported or locally occurring variants all contributed to the development of the 2021 winter wave. The information we achieved might help future pandemic prevention.

Changes in hospital mortality in patients with cancer during the COVID-19 pandemic (ISARIC-CCP-UK): a prospective, multicentre cohort study

BACKGROUND

Patients with cancer are at greater risk of dying from COVID-19 than many other patient groups. However, how this risk evolved during the pandemic remains unclear. We aimed to determine, on the basis of the UK national pandemic protocol, how factors influencing hospital mortality from COVID-19 could differentially affect patients undergoing cancer treatment. We also examined changes in hospital mortality and escalation of care in patients on cancer treatment during the first 2 years of the COVID-19 pandemic in the UK.

METHODS

We conducted a prospective cohort study of patients aged older than 19 years and admitted to 306 health-care facilities in the UK with confirmed SARS-CoV-2 infection, who were enrolled in the International Severe Acute Respiratory and emerging Infections Consortium (ISARIC) WHO Clinical Characterisation Protocol (CCP) across the UK from April 23, 2020, to Feb 28, 2022; this analysis included all patients in the complete dataset when the study closed. The primary outcome was 30-day in-hospital mortality, comparing patients on cancer treatment and those without cancer. The study was approved by the South Central-Oxford C Research Ethics Committee in England (Ref: 13/SC/0149) and the Scotland A Research Ethics Committee (Ref 20/SS/0028), and is registered on the ISRCTN Registry (ISRCTN66726260).

FINDINGS

177 871 eligible adult patients either with no history of cancer (n=171 303) or on cancer treatment (n=6568) were enrolled; 93 205 (52·4%) were male, 84 418 (47·5%) were female, and in 248 (13·9%) sex or gender details were not specified or data were missing. Patients were followed up for a median of 13 (IQR 6-21) days. Of the 6568 patients receiving cancer treatment, 2080 (31·7%) died at 30 days, compared with 30 901 (18·0%) of 171 303 patients without cancer. Patients aged younger than 50 years on cancer treatment had the highest age-adjusted relative risk (hazard ratio [HR] 5·2 [95% CI 4·0-6·6], p<0·0001; vs 50-69 years 2·4 [2·2-2·6], p<0·0001; 70-79 years 1·8 [1·6-2·0], p<0·0001; and >80 years 1·5 [1·3-1·6], p<0·0001) but a lower absolute risk (51 [6·7%] of 763 patients <50 years died compared with 459 [30·2%] of 1522 patients aged >80 years). In-hospital mortality decreased for all patients during the pandemic but was higher for patients on cancer treatment than for those without cancer throughout the study period.

INTERPRETATION

People with cancer have a higher risk of mortality from COVID-19 than those without cancer. Patients younger than 50 years with cancer treatment have the highest relative risk of death. Continued action is needed to mitigate the poor outcomes in patients with cancer, such as through optimising vaccination, long-acting passive immunisation, and early access to therapeutics. These findings underscore the importance of the ISARIC-WHO pandemic preparedness initiative.

FUNDING

National Institute for Health Research and the Medical Research Council.

Investigating the rise of Omicron variant through genomic surveillance of SARS-CoV-2 infections in a highly vaccinated university population

Novel variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continue to emerge as the coronavirus disease 2019 (COVID-19) pandemic extends into its fourth year. Understanding SARS-CoV-2 circulation in university populations is vital for effective interventions in higher education settings and will inform public health policy during pandemics. In this study, we generated 793 whole-genome sequences collected over an entire academic year in a university population in Indiana, USA. We clearly captured the rapidity with which Delta variant was wholly replaced by Omicron variant across the West Lafayette campus over the length of two academic semesters in a community with high vaccination rates. This mirrored the emergence of Omicron throughout the state of Indiana and the USA. Further, phylogenetic analyses demonstrated that there was a more diverse set of potential geographic origins for Omicron viruses introduction into campus when compared to Delta. Lastly, statistics indicated that there was a more significant role for international and out-of-state migration in the establishment of Omicron variants at Purdue. This surveillance workflow, coupled with viral genomic sequencing and phylogeographic analyses, provided critical insights into SARS-CoV-2 transmission dynamics and variant arrival.

Risk factors of Omicron variant associated acute encephalitis/encephalopathy in children

BACKGROUND

Outbreak of Omicron BA.2 in Taiwan led to an increased number of acute encephalitis/encephalopathy cases in children and several fatal cases drew public attention. In pre-Omicron period, pediatric cases of COVID-19-associated acute encephalitis have been reported and during Omicron epidemic, febrile convulsions, encephalitis were mentioned more frequently. The outcome of patients with neurological complications was worse. However, few studies investigated the risk factors, pathophysiology and prognosis of COVID-19-associated encephalitis/encephalopathy. Here, we describe the presentation of pediatric cases of COVID-19-associated acute encephalitis/encephalopathy and explore the associated risk factors.

METHODS

Pediatric patients with confirmed SARS-CoV-2 infections were prospectively enrolled at admission at Chang Gung Memorial Hospital between April and August 2022. Patients were categorized into groups of acute encephalitis/encephalopathy, febrile convulsions or mild disease. Demographic descriptions, clinical manifestations and laboratory data were collected.

RESULTS

Of 288 acute COVID-19 patients, there were 38 (13.2%) acute encephalitis/encephalopathy, 40 (13.9%) febrile convulsions, and 210 (72.9%) mild disease. Among acute encephalitis/encephalopathy group, the mean age was 68.3 ± 45.0 months. The common neurological symptoms were lethargy (65.8%), seizures (52.6%), and impaired consciousness (34.2%). Over 3 years old (adjusted odds ratio [aOR]: 7.57, p < 0.001), absolute neutrophil count ≥3150/μL (aOR: 5.46, p = 0.008), and procalcitonin ≥0.5 ng/mL (aOR: 4.32, p = 0.021) were independent factors for acute encephalitis/encephalopathy.

CONCLUSIONS

Most cases of COVID-19-associated acute encephalitis/encephalopathy showed no evidence of direct viral invasion but associations with older age, increased peripheral neutrophil, and serum procalcitonin. These findings may imply the neutrophil-mediated systemic inflammatory response plays an important role on central nerve system, leading to cerebral dysfunction.

SARS-CoV-2 genomics and impact on clinical care for COVID-19

The emergence and worldwide spread of SARS-CoV-2 during the COVID-19 pandemic necessitated the adaptation and rapid deployment of viral WGS and analysis techniques that had been previously applied on a more limited basis to other viral pathogens, such as HIV and influenza viruses. The need for WGS was driven in part by the low mutation rate of SARS-CoV-2, which necessitated measuring variation along the entire genome sequence to effectively differentiate lineages and characterize viral evolution. Several WGS approaches designed to maximize throughput and accuracy were quickly adopted by surveillance labs around the world. These broad-based SARS-CoV-2 genomic sequencing efforts revealed ongoing evolution of the virus, highlighted by the successive emergence of new viral variants throughout the course of the pandemic. These genomic insights were instrumental in characterizing the effects of viral mutations on transmissibility, immune escape and viral tropism, which in turn helped guide public health policy, the use of monoclonal antibody therapeutics and vaccine development strategies. As the use of direct-acting antivirals for the treatment of COVID-19 became more widespread, the potential for emergence of antiviral resistance has driven ongoing efforts to delineate resistance mutations and to monitor global sequence databases for their emergence. Given the critical role of viral genomics in the international effort to combat the COVID-19 pandemic, coordinated efforts should be made to expand global genomic surveillance capacity and infrastructure towards the anticipation and prevention of future pandemics.

Azvudine and mortality in patients with coronavirus disease 2019: A retrospective cohort study

OBJECTIVES

Several studies have found that azvudine (FNC) can inhibit severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) replication both in vivo and in vitro. However, the effect of FNC on the risk of death in patients with coronavirus disease 2019 (COVID-19) is unclear. This study aims to investigate the effect of FNC on the risk of death in patients with coronavirus disease 2019 (COVID-19).

METHODS

Charts of consecutive patients hospitalized at five hospitals in Chongqing with confirmed COVID-19. The primary outcome of the study was 28-day mortality. Secondary outcomes were: ICU admission rates, length of hospital and ICU stay, and also the range of mechanical ventilation days when admission. We compared primary outcome in patients who received FNC with those in patients who did not, using a multivariable model with inverse probability weighting according to the propensity score.

RESULTS

We included 1,110 patients in our study cohort. Of the 236 patients treated with FNC, 30 died within 28 days (12.7%), and of the 874 patients not treated with FNC, 206 died within 28 days (23.6%). In the crude, unadjusted analysis, a significant beneficial effect of FNC in terms of the 28-day mortality (OR 0.472, 95% CI 0.312-0.714; p < 0.001) in the overall population was detected. The adjusted odds ratio by multivariate analysis was (OR 0.498, 95% CI 0.287-0.864; p = 0.013). In the multivariate analysis with inverse probability weighting according to the propensity score, a significantly beneficial effect of FNC in terms of the 28-day mortality was further confirmed (OR 0.754, 95% CI 0.614-0.925; p = 0.007). Moreover, multivariable propensity-score analyses with matching also yielded similar results (OR 0.438, 95% CI 0.246-0.778; p = 0.005).

CONCLUSION

Our results reveal that in patients with COVID-19, FNC administration was associated with a significantly reduced 28-day mortality.

Bayesian spatial modelling of localised SARS-CoV-2 transmission through mobility networks across England

In the early phases of growth, resurgent epidemic waves of SARS-CoV-2 incidence have been characterised by localised outbreaks. Therefore, understanding the geographic dispersion of emerging variants at the start of an outbreak is key for situational public health awareness. Using telecoms data, we derived mobility networks describing the movement patterns between local authorities in England, which we have used to inform the spatial structure of a Bayesian BYM2 model. Surge testing interventions can result in spatio-temporal sampling bias, and we account for this by extending the BYM2 model to include a random effect for each timepoint in a given area. Simulated-scenario modelling and real-world analyses of each variant that became dominant in England were conducted using our BYM2 model at local authority level in England. Simulated datasets were created using a stochastic metapopulation model, with the transmission rates between different areas parameterised using telecoms mobility data. Different scenarios were constructed to reproduce real-world spatial dispersion patterns that could prove challenging to inference, and we used these scenarios to understand the performance characteristics of the BYM2 model. The model performed better than unadjusted test positivity in all the simulation-scenarios, and in particular when sample sizes were small, or data was missing for geographical areas. Through the analyses of emerging variant transmission across England, we found a reduction in the early growth phase geographic clustering of later dominant variants as England became more interconnected from early 2022 and public health interventions were reduced. We have also shown the recent increased geographic spread and dominance of variants with similar mutations in the receptor binding domain, which may be indicative of convergent evolution of SARS-CoV-2 variants.

COVID-19 vaccine effectiveness against hospitalisation and death of people in clinical risk groups during the Delta variant period: English primary care network cohort study

BACKGROUND

COVID-19 vaccines have been shown to be highly effective against hospitalisation and death following COVID-19 infection. COVID-19 vaccine effectiveness estimates against severe endpoints among individuals with clinical conditions that place them at increased risk of critical disease are limited.

METHODS

We used English primary care medical record data from the Oxford-Royal College of General Practitioners Research and Surveillance Centre sentinel network (N > 18 million). Data were linked to the National Immunisation Management Service database, Second Generation Surveillance System for virology test data, Hospital Episode Statistics, and death registry data. We estimated adjusted vaccine effectiveness (aVE) against COVID-19 infection followed by hospitalisation and death among individuals in specific clinical risk groups using a cohort design during the delta-dominant period. We also report mortality statistics and results from our antibody surveillance in this population.

FINDINGS

aVE against severe endpoints was high, 14-69d following a third dose aVE was 96.4% (95.1%-97.4%) and 97.9% (97.2%-98.4%) for clinically vulnerable people given a Vaxzevria and Comirnaty primary course respectively. Lower aVE was observed in the immunosuppressed group: 88.6% (79.1%-93.8%) and 91.9% (85.9%-95.4%) for Vaxzevria and Comirnaty respectively. Antibody levels were significantly lower among the immunosuppressed group than those not in this risk group across all vaccination types and doses. The standardised case fatality rate within 28 days of a positive test was 3.9/1000 in people not in risk groups, compared to 12.8/1000 in clinical risk groups. Waning aVE with time since 2nd dose was also demonstrated, for example, Comirnaty aVE against hospitalisation reduced from 96.0% (95.1-96.7%) 14-69days post-dose 2-82.9% (81.4-84.2%) 182days+ post-dose 2.

INTERPRETATION

In all clinical risk groups high levels of vaccine effectiveness against severe endpoints were seen. Reduced vaccine effectiveness was noted among the immunosuppressed group.

Fitness, growth and transmissibility of SARS-CoV-2 genetic variants

The massive scale of the global SARS-CoV-2 sequencing effort created new opportunities and challenges for understanding SARS-CoV-2 evolution. Rapid detection and assessment of new variants has become one of the principal objectives of genomic surveillance of SARS-CoV-2. Because of the pace and scale of sequencing, new strategies have been developed for characterizing fitness and transmissibility of emerging variants. In this Review, I discuss a wide range of approaches that have been rapidly developed in response to the public health threat posed by emerging variants, ranging from new applications of classic population genetics models to contemporary synthesis of epidemiological models and phylodynamic analysis. Many of these approaches can be adapted to other pathogens and will have increasing relevance as large-scale pathogen sequencing becomes a regular feature of many public health systems.

A long-term passive sampling approach for wastewater-based monitoring of SARS-CoV-2 in Leipzig, Germany

Wastewater-based monitoring of SARS-CoV-2 has become a promising and useful tool in tracking the potential spread or dynamics of the virus. Its recording can be used to predict how the potential number of infections in a population will develop. Recent studies have shown that the use of passive samplers is also suitable for the detection of SARS-CoV-2 genome copies (GC) in wastewater. They can be used at any site, provide timely data and may collect SARS-CoV-2 GC missed by traditional sampling methods. Therefore, the aim of this study was to evaluate the suitability of passive samplers for the detection of SARS-CoV-2 GC in wastewater in the long-term at two different scales. Polyethylene-based plastic passive samplers were deployed at the city-scale level of Leipzig at 13 different locations, with samples being taken from March 2021 to August 2022. At the smaller city district level, three types of passive samplers (cotton-cloth, unravelled polypropylene plastic rope and polyethylene-based plastic strips) were used and sampled on a weekly basis from March to August 2022. The results are discussed in relation to wastewater samples taken at the individual passive sampling point. Our results show that passive samplers can indicate at a city-scale level an accurate level of positive infections in the population (positive-rate: 86 %). On a small-scale level, the use of passive samplers was also feasible and effective to detect SARS-CoV-2 GC easily and cost-effectively, mirroring a similar trend to that at a city-scale level. Thus, this study demonstrated that passive samplers provide reproducible SARS-CoV-2 GC signals from wastewater and a time-integrated measurement of the sampled matrix with greater sensitivity compared to wastewater. We thus recommend the use of passive samplers as an alternative method for wastewater-based epidemiology. Passive samplers can in particular be considered for a better estimation of infections compared to incidence levels.

Efficacy of novel SARS-CoV-2 rapid antigen tests in the era of omicron outbreak

Following the outbreak of Omicron and its subvariants, many of the currently available rapid Ag tests (RATs) showed a decrease in clinical performance. In this study, we evaluated the clinical sensitivity of the SARS-CoV-2 Rapid Antigen Test 2.0 for nasopharyngeal swabs and SARS-CoV-2 Rapid Antigen Test 2.0 Nasal for nasal swabs in 56 symptomatic individuals by comparing the results between RATs, RT-PCR, Omicron RT-PCR, and whole-genome sequencing (WGS). Furthermore, sequences of the Omicron subvariants' spike proteins were subjected to phylogenetic analysis. Both novel RATs demonstrated a high sensitivity of up to 92.86%, (95% CI 82.71%- 98.02%), 94.23%, (95% CI 83.07%- 98.49%), and 97.95% (95% CI 87.76%- 99.89%) compared to the RT-PCR, Omicron RT-PCR, and WGS, respectively. The clinical sensitivity of RATs was at its highest when the Ct value was restricted to 15≤Ct<25, with a sensitivity of 97.05% for RdRp genes. The Omicron RT-PCR analysis revealed subvariants BA.4 or BA.5 (76.8%) and BA.2.75 (16.1%). Subsequently, the WGS analysis identified BA.5 (65.5%) as the dominant subvariant. Phylogenetic analysis of the spike protein of Omicron's subvariants showed a close relationship between BA.4, BA.5, and BA.2.75. These results demonstrated that SARS-CoV-2 Rapid Antigen Test 2.0 and SARS-CoV-2 Rapid Antigen Test 2.0 Nasal are considered useful and efficient RATs for the detection of SARS-CoV-2, particularly during the current Omicron subvariants wave.

An ARMS-Multiplex PCR Targeting SARS-CoV-2 Omicron Sub-Variants

As of November 2021, the SARS-CoV-2 Omicron variant had made its appearance, gradually replacing the predominant Delta variant. Since its emergence, the Omicron variant has been continuously evolving through more than 500 strains, most of which belong to five sub-variants known as BA.1, BA.2, BA.3, BA.4, and BA.5. The aim of this study was to develop a multiplex polymerase chain reaction (PCR) that will be able to distinguish the basic sub-variants of Omicron in a rapid and specific way. Full genome sequences of Omicron strains with high frequency and wide geographical distribution were retrieved by the NCBI Virus and ENA databases. These sequences were compared to each other in order to locate single nucleotide polymorphisms common to all strains of the same sub-variant. These polymorphisms should also be capable of distinguishing Omicron sub-variants not only from each other but from previously circulating variants of SARS-CoV-2 as well. Thus, specific primers targeting characteristic polymorphisms of the four Omicron main branches BA.1, BA.2, BA.4, and BA.5 were designed according to the principles of the amplification refractory mutation system (ARMS) and with the ability to react under multiplex PCR conditions. According to our results, the ARMS-multiplex PCR could successfully distinguish all Omicron sub-variants that carry the corresponding mutations.

Rebound in asthma exacerbations following relaxation of COVID-19 restrictions: a longitudinal population-based study (COVIDENCE UK)

BACKGROUND

The imposition of restrictions on social mixing early in the COVID-19 pandemic was followed by a reduction in asthma exacerbations in multiple settings internationally. Temporal trends in social mixing, incident acute respiratory infections (ARI) and asthma exacerbations following relaxation of COVID-19 restrictions have not yet been described.

METHODS

We conducted a population-based longitudinal study in 2312 UK adults with asthma between November 2020 and April 2022. Details of face covering use, social mixing, incident ARI and severe asthma exacerbations were collected via monthly online questionnaires. Temporal changes in these parameters were visualised using Poisson generalised additive models. Multilevel logistic regression was used to test for associations between incident ARI and risk of asthma exacerbations, adjusting for potential confounders.

RESULTS

Relaxation of COVID-19 restrictions from April 2021 coincided with reduced face covering use (p<0.001), increased frequency of indoor visits to public places and other households (p<0.001) and rising incidence of COVID-19 (p<0.001), non-COVID-19 ARI (p<0.001) and severe asthma exacerbations (p=0.007). Incident non-COVID-19 ARI associated independently with increased risk of asthma exacerbation (adjusted OR 5.75, 95% CI 4.75 to 6.97) as did incident COVID-19, both prior to emergence of the omicron variant of SARS-CoV-2 (5.89, 3.45 to 10.04) and subsequently (5.69, 3.89 to 8.31).

CONCLUSIONS

Relaxation of COVID-19 restrictions coincided with decreased face covering use, increased social mixing and a rebound in ARI and asthma exacerbations. Associations between incident ARI and risk of severe asthma exacerbation were similar for non-COVID-19 ARI and COVID-19, both before and after emergence of the SARS-CoV-2 omicron variant.

STUDY REGISTRATION NUMBER

NCT04330599.

One year of SARS-CoV-2 circulation in the Nouvelle-Aquitaine region, February 2021-2022, France

Background

Since 2021, 3 variants of concern (VOC) have spread to France, causing successive epidemic waves.

Objectives

To describe the features of Alpha, Delta and Omicron VOC circulation in the Nouvelle-Aquitaine region, France, between February 2021 and February 2022.

Study design

Data from the three university hospitals (UH) of Nouvelle-Aquitaine were used to describe regional SARS-CoV-2 circulation (RT-PCR positive rates and identified VOC) as well as its consequences (total number of hospitalizations and admissions in intensive care unit). They were analyzed according to the predominant variant and compared with national data.

Results

A total of 611,106 SARS-CoV-2 RT-PCR tests were performed in the 3 Nouvelle-Aquitaine UH during the study period. The 37,750 positive samples were analyzed by variant-specific RT-PCR or whole-genome sequencing. In 2021, Alpha VOC was detected from week 5 until week 35. Delta became the most prevalent variant (77.3%) in week 26, reaching 100% in week 35. It was replaced by Omicron, which was initially detected week 48, represented 77% of positive samples in week 52 and was still predominant in February 2022. The RT-PCR positive rates were 4.3, 4.2, and 21.9% during the Alpha, Delta and Omicron waves, respectively. The ratio between intensive care unit admissions and total hospitalizations was lower during the Omicron wave than during the two previous waves due to the Alpha and Delta variants.

Conclusion

This study highlighted the need for strong regional cooperation to achieve effective SARS-CoV-2 epidemiological surveillance, in close association with the public health authorities.

Genomic Insights Into the Evolution and Demographic History of the SARS-CoV-2 Omicron Variant: Population Genomics Approach

Background

A thorough understanding of the patterns of genetic subdivision in a pathogen can provide crucial information that is necessary to prevent disease spread. For SARS-CoV-2, the availability of millions of genomes makes this task analytically challenging, and traditional methods for understanding genetic subdivision often fail.

Objective

The aim of our study was to use population genomics methods to identify the subtle subdivisions and demographic history of the Omicron variant, in addition to those captured by the Pango lineage.

Methods

We used a combination of an evolutionary network approach and multivariate statistical protocols to understand the subdivision and spread of the Omicron variant. We identified subdivisions within the BA.1 and BA.2 lineages and further identified the mutations associated with each cluster. We further characterized the overall genomic diversity of the Omicron variant and assessed the selection pressure for each of the genetic clusters identified.

Results

We observed concordant results, using two different methods to understand genetic subdivision. The overall pattern of subdivision in the Omicron variant was in broad agreement with the Pango lineage definition. Further, 1 cluster of the BA.1 lineage and 3 clusters of the BA.2 lineage revealed statistically significant signatures of selection or demographic expansion (Tajima's D<-2), suggesting the role of microevolutionary processes in the spread of the virus.

Conclusions

We provide an easy framework for assessing the genetic structure and demographic history of SARS-CoV-2, which can be particularly useful for understanding the local history of the virus. We identified important mutations that are advantageous to some lineages of Omicron and aid in the transmission of the virus. This is crucial information for policy makers, as preventive measures can be designed to mitigate further spread based on a holistic understanding of the variability of the virus and the evolutionary processes aiding its spread.

SARS-CoV-2 before and after Omicron: two different viruses and two different diseases?

For the first time in the history of medicine, it has been possible to describe-after a spillover-the evolution of a new human virus spreading in a non-immune population. This allowed not only to observe the subsequent emersion of variants endowed with features providing the virus with an evolutionary advantage, but also the shift of the pathways of virus replication and the acquisition of immunoevasive features. These characteristics had a remarkable influence on the diffusion of the SARS-CoV-2 and on the clinical presentation and prognosis of COVID-19, aspects that are described and commented in this review.

SARS-CoV-2 variant biology: immune escape, transmission and fitness

In late 2020, after circulating for almost a year in the human population, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exhibited a major step change in its adaptation to humans. These highly mutated forms of SARS-CoV-2 had enhanced rates of transmission relative to previous variants and were termed 'variants of concern' (VOCs). Designated Alpha, Beta, Gamma, Delta and Omicron, the VOCs emerged independently from one another, and in turn each rapidly became dominant, regionally or globally, outcompeting previous variants. The success of each VOC relative to the previously dominant variant was enabled by altered intrinsic functional properties of the virus and, to various degrees, changes to virus antigenicity conferring the ability to evade a primed immune response. The increased virus fitness associated with VOCs is the result of a complex interplay of virus biology in the context of changing human immunity due to both vaccination and prior infection. In this Review, we summarize the literature on the relative transmissibility and antigenicity of SARS-CoV-2 variants, the role of mutations at the furin spike cleavage site and of non-spike proteins, the potential importance of recombination to virus success, and SARS-CoV-2 evolution in the context of T cells, innate immunity and population immunity. SARS-CoV-2 shows a complicated relationship among virus antigenicity, transmission and virulence, which has unpredictable implications for the future trajectory and disease burden of COVID-19.

Monitoring and immunogenicity of SARS-CoV-2 vaccination of laboratory rhesus monkeys (Macaca mulatta)

The availability of effective vaccines and a high vaccination rate allowed the recent mitigation, or even withdrawal, of many protective measures for containing the SARS CoV-2 pandemic. At the same time, new and highly mutated variants of the virus are found to have significantly higher transmissibility and reduced vaccine efficacy, thus causing high infection rates during the third year of the pandemic. The combination of reduced measures and increased infectivity poses a particular risk for unvaccinated individuals, including animals susceptible to the virus. Among the latter, non-human primates (NHPs) are particularly vulnerable. They serve as important models in various fields of biomedical research and because of their cognitive capabilities, they receive particular attention in animal welfare regulations around the world. Yet, although they played an extraordinarily important role for developing and testing vaccines against SARS-CoV-2, the protection of captive rhesus monkeys against Covid-19 has rarely been discussed. We here report upon twofold mRNA vaccination of a cohort of 19 elderly rhesus monkeys (Macaca mulatta) against infection by SARS-CoV-2. All animals were closely monitored on possible side effects of vaccination, and were tested for neutralising antibodies against the virus. The data show that vaccination of rhesus monkeys is a safe and reliable measure to protect these animals against SARS-CoV-2.

Analyzing the Trends of COVID-19 and Human Activity Intensity in Malaysia

COVID-19 has struck the world with multiple waves. Each wave was caused by a variant and presented different peaks and baselines. This made the identification of waves with the time series of the cases a difficult task. Human activity intensities may affect the occurrence of an outbreak. We demonstrated a metric of time series, namely log-moving-average-ratio (LMAR), to identify the waves and directions of the changes in the disease cases and check-ins (MySejahtera). Based on the detected waves and changes, we explore the relationship between the two. Using the stimulus-organism-response model with our results, we presented a four-stage model: (1) government-imposed movement restrictions, (2) revenge travel, (3) self-imposed movement reduction, and (4) the new normal. The inverse patterns between check-ins and pandemic waves suggested that the self-imposed movement reduction would naturally happen and would be sufficient for a smaller epidemic wave. People may spontaneously be aware of the severity of epidemic situations and take appropriate disease prevention measures to reduce the risks of exposure and infection. In summary, LMAR is more sensitive to the waves and could be adopted to characterize the association between travel willingness and confirmed disease cases.

Replacement dynamics and the pathogenesis of the Alpha, Delta and Omicron variants of SARS-CoV-2

New SARS-CoV-2 variants causing COVID-19 are a major risk to public health worldwide due to the potential for phenotypic change and increases in pathogenicity, transmissibility and/or vaccine escape. Recognising signatures of new variants in terms of replacing growth and severity are key to informing the public health response. To assess this, we aimed to investigate key time periods in the course of infection, hospitalisation and death, by variant. We linked datasets on contact tracing (Contact Tracing Advisory Service), testing (the Second-Generation Surveillance System) and hospitalisation (the Admitted Patient Care dataset) for the entire length of contact tracing in the England - from March 2020 to March 2022. We modelled, for England, time delay distributions using a Bayesian doubly interval censored modelling approach for the SARS-CoV-2 variants Alpha, Delta, Delta Plus (AY.4.2), Omicron BA.1 and Omicron BA.2. This was conducted for the incubation period, the time from infection to hospitalisation and hospitalisation to death. We further modelled the growth of novel variant replacement using a generalised additive model with a negative binomial error structure and the relationship between incubation period length and the risk of a fatality using a Bernoulli generalised linear model with a logit link. The mean incubation periods for each variant were: Alpha 4.19 (95% credible interval (CrI) 4.13-4.26) days; Delta 3.87 (95% CrI 3.82-3.93) days; Delta Plus 3.92 (95% CrI 3.87-3.98) days; Omicron BA.1 3.67 (95% CrI 3.61-3.72) days and Omicron BA.2 3.48 (95% CrI 3.43-3.53) days. The mean time from infection to hospitalisation was for Alpha 11.31 (95% CrI 11.20-11.41) days, Delta 10.36 (95% CrI 10.26-10.45) days and Omicron BA.1 11.54 (95% CrI 11.38-11.70) days. The mean time from hospitalisation to death was, for Alpha 14.31 (95% CrI 14.00-14.62) days; Delta 12.81 (95% CrI 12.62-13.00) days and Omicron BA.2 16.02 (95% CrI 15.46-16.60) days. The 95th percentile of the incubation periods were: Alpha 11.19 (95% CrI 10.92-11.48) days; Delta 9.97 (95% CrI 9.73-10.21) days; Delta Plus 9.99 (95% CrI 9.78-10.24) days; Omicron BA.1 9.45 (95% CrI 9.23-9.67) days and Omicron BA.2 8.83 (95% CrI 8.62-9.05) days. Shorter incubation periods were associated with greater fatality risk when adjusted for age, sex, variant, vaccination status, vaccination manufacturer and time since last dose with an odds ratio of 0.83 (95% confidence interval 0.82-0.83) (P value < 0.05). Variants of SARS-CoV-2 that have replaced previously dominant variants have had shorter incubation periods. Conversely co-existing variants have had very similar and non-distinct incubation period distributions. Shorter incubation periods reflect generation time advantage, with a reduction in the time to the peak infectious period, and may be a significant factor in novel variant replacing growth. Shorter times for admission to hospital and death were associated with variant severity - the most severe variant, Delta, led to significantly earlier hospitalisation, and death. These measures are likely important for future risk assessment of new variants, and their potential impact on population health.

Strain-stream model of epidemic spread in application to COVID-19

ABSTRACT

The recently developed model of the epidemic spread of two virus strains in a closed population is generalized to the situation typical for the couple of strains delta and omicron, when there is a high probability of omicron infection soon enough after recovering from delta infection. This model can be considered as a kind of combination of SIR and SIS models for the case of competition of two strains of the same virus with different contagiousness in a population. The obtained equations and results can be directly implemented for practical calculations of the replacement of strains of the SARS-CoV-2 virus. A comparison between the estimated replacement time and the corresponding statistics shows reasonable agreement.

Global Distribution, Dispersal Patterns, and Trend of Several Omicron Subvariants of SARS-CoV-2 across the Globe

Our study aims to describe the global distribution and dispersal patterns of the SARS-CoV-2 Omicron subvariants. Genomic surveillance data were extracted from the CoV-Spectrum platform, searching for BA.1*, BA.2*, BA.3*, BA.4*, and BA.5* variants by geographic region. BA.1* increased in November 2021 in South Africa, with a similar increase across all continents in early December 2021. BA.1* did not reach 100% dominance in all continents. The spread of BA.2*, first described in South Africa, differed greatly by geographic region, in contrast to BA.1*, which followed a similar global expansion, firstly occurring in Asia and subsequently in Africa, Europe, Oceania, and North and South America. BA.4* and BA.5* followed a different pattern, where BA.4* reached high proportions (maximum 60%) only in Africa. BA.5* is currently, by Mid-August 2022, the dominant strain, reaching almost 100% across Europe, which is the first continent aside from Africa to show increasing proportions, and Asia, the Americas, and Oceania are following. The emergence of new variants depends mostly on their selective advantage, translated as enhanced transmissibility and ability to invade people with existing immunity. Describing these patterns is useful for a better understanding of the epidemiology of the VOCs' transmission and for generating hypotheses about the future of emerging variants.

Relationships between building attributes and COVID-19 infection in London

In the UK, all domestic COVID-19 restrictions have been removed since they were introduced in March 2020. After illustrating the spatial-temporal variations in COVID-19 infection rates across London, this study then particularly aimed to examine the relationships of COVID-19 infection rates with building attributes, including building density, type, age, and use, since previous studies have shown that the built environment plays an important role in public health. Multisource data from national health services and the London Geomni map were processed with GIS techniques and statistically analysed. From March 2020 to April 2022, the infection rate of COVID-19 in London was 3,159.28 cases per 10,000 people. The spatial distribution across London was uneven, with a range from 1,837.88 to 4,391.79 per 10,000 people. During this period, it was revealed that building attributes played a significant role in COVID-19 infection. It was noted that higher building density areas had lower COVID-19 infection rates in London. Moreover, a higher percentage of historic or flat buildings tended to lead to a decrease in infection rates. In terms of building use, the rate of COVID-19 infection tended to be lower in public buildings and higher in residential buildings. Variations in the infection rate were more sensitive to building type; in particular, the percentage of residents living in flats contributed the most to variations in COVID-19 infection rates, with a value of 2.3%. This study is expected to provide support for policy and practice towards pandemic-resilient architectural design.

SARS-CoV-2 Seroprevalence among Canadian Blood Donors: The Advance of Omicron

With the emergence of the SARS-CoV-2 Omicron variant in late 2021, Canadian public health case/contact testing was scaled back due to high infection rates with milder symptoms in a highly vaccinated population. We monitored the seroprevalence of SARS-CoV-2 nucleocapsid (anti-N) and spike protein (anti-S) antibodies in blood donors across Canada from September 2021 to June 2022 in 202,123 randomly selected samples. Multivariable logistic regression of anti-N positivity with month, age, sex, racialization, region, material and social deprivation (based on postal code) identified as independent predictors. Piece-wise logistic regression analysed the association between anti-S concentration and month, and anti-N/anti-S positivity. Infection-related seroprevalence (anti-N positive) was 4.38% (95% CI: 3.96, 4.81) in September reaching 50.70% (50.15, 52.16) in June; nearly 100% were anti-S positive throughout. Anti-N positivity was associated with younger age, male sex, the Alberta and Prairies regions, greater material deprivation and less social deprivation (p < 0.001). Anti-S concentration was high initially (3306 U/mL, IQR 4280 U/mL), increased to (13,659 U/mL, IQR 28,224 U/mL) by June (p < 0.001), following the pattern of deployment of the third and fourth vaccine doses and was higher in those that were anti-N positive (p < 0.001). Despite already high vaccination-related seroprevalence, infection-related seroprevalence increased dramatically with the emergence of the Omicron SARS-CoV-2 variant.

Clinical predictors and RT-PCR profile of prolonged viral shedding in patients with SARS-CoV-2 Omicron variant in Shanghai: A retrospective observational study

Objective

To evaluate determinants of prolonged viral RNA shedding in hospitalized patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant infection.

Materials and methods

Hospitalized patients tested SARS-CoV-2 positive by nasopharyngeal real-time reverse transcriptase-polymerase chain reaction (RT-PCR) were included in the single-center, retrospective study. Patients were divided into 2 groups according to the timing of viral clearance (≤ 8 days, "early clearance" and ≥15 days, "late clearance").

Results

4,084 patients were included in the study (1,023 late clearance, 3,061 early clearance), with median age of 50 years and a higher proportion (61.4%) of male. Univariate analyses showed that comorbidities (including hypertension, diabetes, and coronary heart disease), receiving vaccine, the number of vaccinations, cycle threshold (Ct) open reading frame 1ab (ORF 1ab), and nucleocapsid protein (N) gene values on admission were associated with late viral clearance. In the multivariable analysis, the number of vaccinations (P = 0.010) and Ct ORF 1ab gene (P < 0.001) values on admission were significantly associated with late viral clearance. Generalized Estimating Equations (GEE) analysis showed that the Ct value of ORF 1ab gene and N gene remained unchanged within 3 days, and showed progressively higher values with increasing days during late viral RNA clearance.

Conclusion

The number of vaccinations and Ct values of ORF 1ab gene were independently associated with a prolonged SARS-CoV-2 RNA shedding.

Global estimates of the fitness advantage of SARS-CoV-2 variant Omicron

New variants of SARS-CoV-2 show remarkable heterogeneity in their relative fitness over both time and space. In this paper we extend the tools available for estimating the selection strength for new SARS-CoV-2 variants to a hierarchical, mixed-effects, renewal equation model. This formulation allows us to estimate selection effects at the global level while incorporating both measured and unmeasured heterogeneity among countries. Applying this model to the spread of Omicron in forty countries, we find evidence for very strong but very heterogeneous selection effects. To test whether this heterogeneity is explained by differences in the immune landscape, we considered several measures of vaccination rates and recent population-level infection as covariates, finding moderately strong, statistically significant effects. We also found a significant positive correlation between the selection advantage of Delta and Omicron at the country level, suggesting that other region-specific explanatory variables of fitness differences do exist. Our method is implemented in the Stan programming language, can be run on standard consumer-grade computing resources, and will be straightforward to apply to future variants.

Development of multiplex S-gene-targeted RT-PCR for rapid identification of SARS-CoV-2 variants by extended S-gene target failure

Background

Tracking SARS-CoV-2 variants of concern (VOC) by genomic sequencing is time-consuming. The rapid screening of VOCs is necessary for clinical laboratories. In this study, we developed a rapid screening method based on multiplex RT-PCR by extended S-gene target failure (eSGTF), a false negative result caused by S-gene mutations.

Methods

Three S-gene target (SGT) regions (SGT1, codons 65–72; SGT2, codons 152–159; and SGT3, codons 370–377) and an N-gene region (for internal control) were detected in single-tube. Four types of VOC (Alpha, Delta, Omicron BA.1, and Omicron BA.2) are classified by positive/negative patterns of 3 S-gene regions (eSGTF pattern).

Results

The eSGTF patterns of VOCs were as follows (SGT1, SGT2, SGT3; P, positive; N, negative): Alpha, NPP; Delta, PNP; Omicron BA.1, NPN pattern; and Omicron BA.2, PPN. As compared with the S-gene sequencing, eSGTF patterns were identical to the specific VOCs (concordance rate = 96.7%, N = 206/213). Seven samples with discordant results had a minor mutation in the probe binding region. The epidemics of VOCs estimated by eSGTF patterns were similar to those in Japan.

Conclusions

Multiplex RT-PCR and eSGTF patterns enable high-throughput screening of VOCs. It will be useful for the rapid determination of VOCs in clinical laboratories.

Pathogen evolution during vaccination campaigns

Following the initiation of the unprecedented global vaccination campaign against Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), attention has now turned to the potential impact of this large-scale intervention on the evolution of the virus. In this Essay, we summarize what is currently known about pathogen evolution in the context of immune priming (including vaccination) from research on other pathogen species, with an eye towards the future evolution of SARS-CoV-2.

Real-world effectiveness of Yindan Jiedu granules-based treatment on patients infected with the SARS-CoV-2 Omicron variants BA.2 combined with high-risk factors: A cohort study

Background: Our previous studies have shown that Yindan Jiedu granules (YDJDG) can effectively treat coronavirus disease 2019 (COVID-19); however, the high infectivity and the immune escape potential of the Omicron variant BA.2 make it more difficult to control, and patients with high-risk factors prone to progress rapidly.

Purpose: To evaluate YDJDG’s efficacy in treating patients with the Omicron variant BA.2 with high-risk factors and compared it with that of Paxlovid.

Methods: A total of 257 patients who fulfilled the inclusion criteria were allocated to the YDJDG (115 cases), Paxlovid (115 cases), and control (27 cases) groups. A Cox regression model was used to analyze the independent factors affecting the shedding time of nucleic acid in 14 days. Propensity score matching (PSM) was used to match the characteristics of individuals in the three groups, while the Kaplan-Meier method was used to compare the shedding proportion of nucleic acids.

Results: Cox analysis showed that the vaccine booster (p = 0.006), YDJDG treatment (p = 0.020), and Paxlovid treatment (p < 0.0001) were independent predictors of nucleic acid shedding at 14 days. The median recovery time was 11.49 days in the YDJDG group, 10.21 days in the Paxlovid group, and 13.93 days in the control group. After PSM (3:1), the results showed that the nucleic acid shedding time of the YDJDG group (n = 53) was 2.47 days shorter than that of the control group (n = 21) (p = 0.0076), while the Paxlovid group (n = 44) had a 4.34 days shorter than that of the control group (n = 17) (p < 0.0001). After PSM (1:1), YDJDG and Paxlovid (76 pairs) were also analyzed. In the YDJDG group, nucleic acid shedding time was 1.43 days longer than that observed in the Paxlovid group (p = 0.020). At 10 and 14 days, the Paxlovid group showed a significant difference in the nucleic acid shedding proportion compared with the control group (p = 0.036, p = 0.0015). A significant difference was also observed between the YDJDG and control groups (p = 0.040) at 14 days.

Conclusion: As a safe and convenient oral drug, YDJDG can be used as an alternative to antiviral therapy for such patients.

Origin, virological features, immune evasion and intervention of SARS-CoV-2 Omicron sublineages

Recently, a large number of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants continuously emerged and posed a major threat to global public health. Among them, particularly, Omicron variant (B.1.1.529), first identified in November 2021, carried numerous mutations in its spike protein (S), and then quickly spread around the world. Currently, Omicron variant has expanded into more than one hundred sublineages, such as BA.1, BA.2, BA.2.12.1, BA.4 and BA.5, which have already become the globally dominant variants. Different from other variants of concern (VOCs) of SARS-CoV-2, the Omicron variant and its sublineages exhibit increased transmissibility and immune escape from neutralizing antibodies generated through previous infection or vaccination, and have caused numerous re-infections and breakthrough infections. In this prospective, we have focused on the origin, virological features, immune evasion and intervention of Omicron sublineages, which will benefit the development of next-generation vaccines and therapeutics, including pan-sarbecovirus and universal anti-CoV therapeutics, to combat currently circulating and future emerging Omicron sublineages as well as other SARS-CoV-2 variants.

Assessment of SARS-CoV-2 Infected Patients and Their Clinical Outcomes During the Third Wave in India: A Single-Center Observational Study

Background

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) that emerged from the Chinese mainland has spread throughout the world affecting the normal lives of the people. Both developed and developing nations have been equally affected and coronavirus disease-19 (COVID-19) resulted in the death of millions of people worldwide. The virus is undergoing mutations and is evolving into variants that are responsible for wave after wave. This study was carried out to assess the clinical outcomes of people infected with the novel virus during the third wave of the COVID-19 pandemic in India.

Methods

The study was carried out between November 2021 and January 2022 and included 100 consecutive patients attending the hospital attached to the BLDE (Deemed to be University) Shri B.M. Patil Medical College, Bijapur, Karnataka, South India. All patients included in the study returned a positive report in a real-time polymerase chain reaction (RT-PCR). The patient details collected included age, sex, cycle threshold (Ct) values for envelope (E)/nucleocapsid (N), and Orf1b (open reading frame 1b) genes, hospitalization status, vaccine status, C-reactive protein (CRP), D-dimer, interleukin-6 (IL-6), and final clinical outcome. The data were entered into Microsoft Office Excel sheets, and statistical inferences were drawn using SPSS 24 (IBM Corp., Armonk, NY).

Results

Of the 100 patients included in the study, only 14 (14%) patients were vaccinated. The patient's mean age was 34.22±17.50. Among the vaccinated patients, the majority had taken COVISHIELD™ (85.71%) compared to COVAXIN^® (14.29%). Only 14% of patients were symptomatic, and the mean Ct values among all the patients were 29.92±3.74 (E gene/N gene) and 27.6±4.78 (Orf1B gene). Eight (8%) patients were hospitalized, and all the patients recovered from the infection. Among the hospitalized patients, six (75%) were vaccinated. The mean age of the hospitalized patients was 43.8±14.25 years. The mean CRP, D-dimer, and IL-6 concentrations among the hospitalized patients were noted to be 22.375±16.58 mg/L, 654.325±577.24 ng/mL, and 5.075±2.15 ng/mL, respectively.

Conclusion

The study results demonstrate that despite unvaccinated status, most patients in the third wave had only suffered from asymptomatic infection. Moreover, people who developed a clinical infection and those who required hospitalization had an uneventful recovery irrespective of their vaccination status.

Global estimates of the fitness advantage of SARS-CoV-2 variant Omicron

New variants of SARS-CoV-2 show remarkable heterogeneity in their relative fitness both over time and space. In this paper we extend a previously published model for estimating the selection strength for new SARS-CoV-2 variants to a hierarchical, mixed-effects, renewal equation model. This formulation allows us to globally estimate selection effects at different spatial levels while controlling for complex patterns of transmission and jointly inferring the effects of unit-level covariates in the spatial heterogeneity of SARS-CoV-2 selection effects. Applying this model to the spread of Omicron in 40 counties finding evidence for very strong (64%) but very heterogeneous selection effects at the country level. We further considered different measures of vaccination levels and measures of recent population-level infection as possible explanations. However, none of those variables were found to explain a significant proportion of the heterogeneity in country-level selection effects. We did find a significant positive correlation between the selection advantage of Delta and Omicron at the country level, suggesting that region-specific explanatory variables of fitness differences do exist. Our method is implemented in the Stan programming language, can be run on standard commercial-grade computing resources, and should be straightforward to apply to future variants.