Genomic reconstruction of the SARS-CoV-2 epidemic in England

A protein language model for exploring viral fitness landscapes

Successively emerging SARS-CoV-2 variants lead to repeated epidemic surges through escalated fitness (i.e., relative effective reproduction number between variants). Modeling the genotype-fitness relationship enables us to pinpoint the mutations boosting viral fitness and flag high-risk variants immediately after their detection. Here, we present CoVFit, a protein language model adapted from ESM-2, designed to predict variant fitness based solely on spike protein sequences. CoVFit was trained on genotype-fitness data derived from viral genome surveillance and functional mutation assays related to immune evasion. CoVFit successively ranked the fitness of unknown future variants harboring nearly 15 mutations with informative accuracy. CoVFit identified 959 fitness elevation events throughout SARS-CoV-2 evolution until late 2023. Furthermore, we show that CoVFit is applicable for predicting viral evolution through single amino acid mutations. Our study gives insight into the SARS-CoV-2 fitness landscape and provides a tool for efficiently identifying SARS-CoV-2 variants with higher epidemic risk.

Restoring flowcell type and basecaller configuration from FASTQ files of nanopore sequencing data

As nanopore sequencing has been widely adopted, data accumulation has surged, resulting in over 700,000 public datasets. While these data hold immense potential for advancing genomic research, their utility is compromised by the absence of flowcell type and basecaller configuration in about 85% of the data and associated publications. These parameters are essential for many analysis algorithms, and their misapplication can lead to significant drops in performance. To address this issue, we present LongBow, designed to infer flowcell type and basecaller configuration directly from the base quality value patterns of FASTQ files. LongBow has been tested on 66 in-house basecalled FAST5/POD5 datasets and 1989 public FASTQ datasets, achieving accuracies of 95.33% and 91.45%, respectively. We demonstrate its utility by reanalyzing nanopore sequencing data from the COVID-19 Genomics UK (COG-UK) project. The results show that LongBow is essential for reproducing reported genomic variants and, through a LongBow-based analysis pipeline, we discovered substantially more functionally important variants while improving accuracy in lineage assignment. Overall, LongBow is poised to play a critical role in maximizing the utility of public nanopore sequencing data, while significantly enhancing the reproducibility of related research.

Breaking barriers: we need a multidisciplinary approach to tackle cancer drug resistance

Most cancer-related deaths result from drug-resistant disease(1,2). However, cancer drug resistance is not a primary focus in drug development. Effectively mitigating and treating drug-resistant cancer will require advancements in multiple fields, including early detection, drug discovery, and our fundamental understanding of cancer biology. Therefore, successfully tackling drug resistance requires an increasingly multidisciplinary approach. A recent workshop on cancer drug resistance, jointly organised by Cancer Research UK, the Rosetrees Trust, and the UKRI-funded Physics of Life Network, brought together experts in cell biology, physical sciences, computational biology, drug discovery, and clinicians to focus on these key challenges and devise interdisciplinary approaches to address them. In this perspective, we review the outcomes of the workshop and highlight unanswered research questions. We outline the emerging hallmarks of drug resistance and discuss lessons from the COVID-19 pandemic and antimicrobial resistance that could help accelerate information sharing and timely adoption of research discoveries into the clinic. We envisage that initiatives that drive greater interdisciplinarity will yield rich dividends in developing new ways to better detect, monitor, and treat drug resistance, thereby improving treatment outcomes for cancer patients.

Using minor variant genomes and machine learning to study the genome biology of SARS-CoV-2 over time

In infected individuals, viruses are present as a population consisting of dominant and minor variant genomes. Most databases contain information on the dominant genome sequence. Since the emergence of SARS-CoV-2 in late 2019, variants have been selected that are more transmissible and capable of partial immune escape. Currently, models for projecting the evolution of SARS-CoV-2 are based on using dominant genome sequences to forecast whether a known mutation will be prevalent in the future. However, novel variants of SARS-CoV-2 (and other viruses) are driven by evolutionary pressure acting on minor variant genomes, which then become dominant and form a potential next wave of infection. In this study, sequencing data from 96 209 patients, sampled over a 3-year period, were used to analyse patterns of minor variant genomes. These data were used to develop unsupervised machine learning clusters to identify amino acids that had a greater potential for mutation than others in the Spike protein. Being able to identify amino acids that may be present in future variants would better inform the design of longer-lived medical countermeasures and allow a risk-based evaluation of viral properties, including assessment of transmissibility and immune escape, thus providing candidates with early warning signals for when a new variant of SARS-CoV-2 emerges.

A retrospective genomic characterisation of the 2022 mpox outbreak in Belgium, and in vitro assessment of three antiviral compounds

BACKGROUND

Since the beginning of May 2022, cases of mpox have been reported in several European and American countries where the disease is nonendemic. We performed a retrospective genomic characterisation of the 2022 mpox outbreak in Belgium, and assessed the in vitro sensitivity of three antiviral compounds to a monkeypox virus (MPXV) strain from the 2022 outbreak.

METHODS

We sequenced the complete genomes of MPXV isolated from skin-, throat-, anorectal- and genital swab samples using the Oxford Nanopore Technologies (ONT) GridION. We subsequently analysed high-quality complete MPXV genomes and conducted a genomic analysis of MPXV complete genomes from this study with all other complete MPXV genomes available on GISAID up to October 28th, 2022. The in vitro activity of tecovirimat, brincidofovir, and cidofovir was also tested in human and monkey cell lines.

FINDINGS

We produced 248 complete MPXV genomes. Phylogenetic analysis of the complete MPXV genomes revealed that they all belong to MPXV Clade IIb B.1. Surprisingly, through phylogeographic analysis we identified a minimum number of 79 introduction events into Belgium, along with sustained local transmission. We also demonstrated the superior in vitro efficacy and selectivity of tecovirimat to the 2022 MPXV clinical strain.

INTERPRETATION

The number of sequences provides sufficient information about the MPXV lineages that were circulating in Belgium. The 2022 mpox outbreak, in Belgium, was mainly characterised by many introduction events that were promptly contained and resulted in limited human-to-human transmission of MPXV. The in vitro efficacy of antivirals against a 2022 MPXV Belgian strain highlights the potent activity and specificity of tecovirimat and its ability to prevent the formation of the extracellular enveloped viruses.

FUNDING

None.

Routes of importation and spatial dynamics of SARS-CoV-2 variants during localized interventions in Chile

Human mobility is strongly associated with the spread of SARS-CoV-2 via air travel on an international scale and with population mixing and the number of people moving between locations on a local scale. However, these conclusions are drawn mostly from observations in the context of the global north where international and domestic connectivity is heavily influenced by the air travel network; scenarios where land-based mobility can also dominate viral spread remain understudied. Furthermore, research on the effects of nonpharmaceutical interventions (NPIs) has mostly focused on national- or regional-scale implementations, leaving gaps in our understanding of the potential benefits of implementing NPIs at higher granularity. Here, we use Chile as a model to explore the role of human mobility on disease spread within the global south; the country implemented a systematic genomic surveillance program and NPIs at a very high spatial granularity. We combine viral genomic data, anonymized human mobility data from mobile phones and official records of international travelers entering the country to characterize the routes of importation of different variants, the relative contributions of airport and land border importations, and the real-time impact of the country's mobility network on the diffusion of SARS-CoV-2. The introduction of variants which are dominant in neighboring countries (and not detected through airport genomic surveillance) is predicted by land border crossings and not by air travelers, and the strength of connectivity between comunas (Chile's lowest administrative divisions) predicts the time of arrival of imported lineages to new locations. A higher stringency of local NPIs was also associated with fewer domestic viral importations. Our analysis sheds light on the drivers of emerging respiratory infectious disease spread outside of air travel and on the consequences of disrupting regular movement patterns at lower spatial scales.

Advancing CRISPR-Based Solutions for COVID-19 Diagnosis and Therapeutics

Since the onset of the COVID-19 pandemic, a variety of diagnostic approaches, including RT-qPCR, RAPID, and LFA, have been adopted, with RT-qPCR emerging as the gold standard. However, a significant challenge in COVID-19 diagnostics is the wide range of symptoms presented by patients, necessitating early and accurate diagnosis for effective management. Although RT-qPCR is a precise molecular technique, it is not immune to false-negative results. In contrast, CRISPR-based detection methods for SARS-CoV-2 offer several advantages: they are cost-effective, time-efficient, highly sensitive, and specific, and they do not require sophisticated instruments. These methods also show promise for scalability, enabling diagnostic tests. CRISPR technology can be customized to target any genomic region of interest, making it a versatile tool with applications beyond diagnostics, including therapeutic development. The CRISPR/Cas systems provide precise gene targeting with immense potential for creating next-generation diagnostics and therapeutics. One of the key advantages of CRISPR/Cas-based therapeutics is the ability to perform multiplexing, where different sgRNAs or crRNAs can target multiple sites within the same gene, reducing the likelihood of viral escape mutants. Among the various CRISPR systems, CRISPR/Cas13 and CARVER (Cas13-assisted restriction of viral expression and readout) are particularly promising. These systems can target a broad range of single-stranded RNA viruses, making them suitable for the diagnosis and treatment of various viral diseases, including SARS-CoV-2. However, the efficacy and safety of CRISPR-based therapeutics must be thoroughly evaluated in pre-clinical and clinical settings. While CRISPR biotechnologies have not yet been fully harnessed to control the current COVID-19 pandemic, there is an optimism that the limitations of the CRISPR/Cas system can be overcome soon. This review discusses how CRISPR-based strategies can revolutionize disease diagnosis and therapeutic development, better preparing us for future viral threats.

Molecular and structural insights into SARS-CoV-2 evolution: from BA.2 to XBB subvariants

Due to the incessant emergence of various SARS-CoV-2 variants with enhanced fitness in the human population, controlling the COVID-19 pandemic has been challenging. Understanding how the virus enhances its fitness during a pandemic could offer valuable insights for more effective control of viral epidemics. In this manuscript, we review the evolution of SARS-CoV-2 from early 2022 to the end of 2023-from Omicron BA.2 to XBB descendants. Focusing on viral evolution during this period, we provide concrete examples that SARS-CoV-2 has increased its fitness by enhancing several functions of the spike (S) protein, including its binding affinity to the ACE2 receptor and its ability to evade humoral immunity. Furthermore, we explore how specific mutations modify these functions of the S protein through structural alterations. This review provides evolutionary, molecular, and structural insights into how SARS-CoV-2 has increased its fitness and repeatedly caused epidemic surges during the pandemic.

A tale of two cities: London and New York City during Covid-19

Using publicly available data, this paper investigates the diffusion of COVID-19 across neighborhoods in two major cities, London and New York. We link neighborhood demographics to incidence, and we investigate patterns of change over time in conjunction with changing policy responses to the pandemic. By comparing and contrasting these two cities, we are able to exploit surveillance and policy differences, demonstrating how each contributes information to the other. We conclude that better coordination can be translated into improved health policy.

The Emergence and Evolution of SARS-CoV-2

The origin of SARS-CoV-2 has evoked heated debate and strong accusations, yet seemingly little resolution. I review the scientific evidence on the origin of SARS-CoV-2 and its subsequent spread through the human population. The available data clearly point to a natural zoonotic emergence within, or closely linked to, the Huanan Seafood Wholesale Market in Wuhan. There is no direct evidence linking the emergence of SARS-CoV-2 to laboratory work conducted at the Wuhan Institute of Virology. The subsequent global spread of SARS-CoV-2 was characterized by a gradual adaptation to humans, with dual increases in transmissibility and virulence until the emergence of the Omicron variant. Of note has been the frequent transmission of SARS-CoV-2 from humans to other animals, marking it as a strongly host generalist virus. Unless lessons from the origin of SARS-CoV-2 are learned, it is inevitable that more zoonotic events leading to more epidemics and pandemics will plague human populations.

Real-time identification of epistatic interactions in SARS-CoV-2 from large genome collections

BACKGROUND

The emergence of the SARS-CoV-2 virus has highlighted the importance of genomic epidemiology in understanding the evolution of pathogens and guiding public health interventions. The Omicron variant in particular has underscored the role of epistasis in the evolution of lineages with both higher infectivity and immune escape, and therefore the necessity to update surveillance pipelines to detect them early on.

RESULTS

In this study, we apply a method based on mutual information between positions in a multiple sequence alignment, which is capable of scaling up to millions of samples. We show how it can reliably predict known experimentally validated epistatic interactions, even when using as little as 10,000 sequences, which opens the possibility of making it a near real-time prediction system. We test this possibility by modifying the method to account for the sample collection date and apply it retrospectively to multiple sequence alignments for each month between March 2020 and March 2023. We detected a cornerstone epistatic interaction in the Spike protein between codons 498 and 501 as soon as seven samples with a double mutation were present in the dataset, thus demonstrating the method's sensitivity. We test the ability of the method to make inferences about emerging interactions by testing candidates predicted after March 2023, which we validate experimentally.

CONCLUSIONS

We show how known epistatic interaction in SARS-CoV-2 can be detected with high sensitivity, and how emerging ones can be quickly prioritized for experimental validation, an approach that could be implemented downstream of pandemic genome sequencing efforts.

CMAPLE: Efficient Phylogenetic Inference in the Pandemic Era

We have recently introduced MAPLE (MAximum Parsimonious Likelihood Estimation), a new pandemic-scale phylogenetic inference method exclusively designed for genomic epidemiology. In response to the need for enhancing MAPLE's performance and scalability, here we present two key components: (i) CMAPLE software, a highly optimized C++ reimplementation of MAPLE with many new features and advancements, and (ii) CMAPLE library, a suite of application programming interfaces to facilitate the integration of the CMAPLE algorithm into existing phylogenetic inference packages. Notably, we have successfully integrated CMAPLE into the widely used IQ-TREE 2 software, enabling its rapid adoption in the scientific community. These advancements serve as a vital step toward better preparedness for future pandemics, offering researchers powerful tools for large-scale pathogen genomic analysis.

Importations of SARS-CoV-2 lineages decline after nonpharmaceutical interventions in phylogeographic analyses

During the early stages of the SARS-CoV-2 pandemic, before vaccines were available, nonpharmaceutical interventions (NPIs) such as reducing contacts or antigenic testing were used to control viral spread. Quantifying their success is therefore key for future pandemic preparedness. Using 1.8 million SARS-CoV-2 genomes from systematic surveillance, we study viral lineage importations into Germany for the third pandemic wave from late 2020 to early 2021, using large-scale Bayesian phylogenetic and phylogeographic analysis with a longitudinal assessment of lineage importation dynamics over multiple sampling strategies. All major nationwide NPIs were followed by fewer importations, with the strongest decreases seen for free rapid tests, the strengthening of regulations on mask-wearing in public transport and stores, as well as on internal movements and gatherings. Most SARS-CoV-2 lineages first appeared in the three most populous states with most cases, and spread from there within the country. Importations rose before and peaked shortly after the Christmas holidays. The substantial effects of free rapid tests and obligatory medical/surgical mask-wearing suggests these as key for pandemic preparedness, given their relatively few negative socioeconomic effects. The approach relates environmental factors at the host population level to viral lineage dissemination, facilitating similar analyses of rapidly evolving pathogens in the future.

Nanopore sequencing of influenza A and B in Oxfordshire and the United Kingdom, 2022-23

OBJECTIVES

We evaluated Nanopore sequencing for influenza surveillance.

METHODS

Influenza A and B PCR-positive samples from hospital patients in Oxfordshire, UK, and a UK-wide population survey from winter 2022-23 underwent Nanopore sequencing following targeted rt-PCR amplification.

RESULTS

From 941 infections, successful sequencing was achieved in 292/388 (75 %) available Oxfordshire samples: 231 (79 %) A/H3N2, 53 (18 %) A/H1N1, and 8 (3 %) B/Victoria and in 53/113 (47 %) UK-wide samples. Sequencing was more successful at lower Ct values. Most same-sample replicate sequences had identical haemagglutinin segments (124/141, 88 %); 36/39 (92 %) Illumina vs. Nanopore comparisons were identical, and 3 (8 %) differed by 1 variant. Comparison of Oxfordshire and UK-wide sequences showed frequent inter-regional transmission. Infections were closely-related to 2022-23 vaccine strains. Only one sample had a neuraminidase inhibitor resistance mutation. 849/941 (90 %) Oxfordshire infections were community-acquired. 63/88 (72 %) potentially healthcare-associated cases shared a hospital ward with ≥ 1 known infectious case. 33 epidemiologically-plausible transmission links had sequencing data for both source and recipient: 8 were within ≤ 5 SNPs, of these, 5 (63 %) involved potential sources that were also hospital-acquired.

CONCLUSIONS

Nanopore influenza sequencing was reproducible and antiviral resistance rare. Inter-regional transmission was common; most infections were genomically similar. Hospital-acquired infections are likely an important source of nosocomial transmission and should be prioritised for infection prevention and control.

Inferring community transmission of SARS-CoV-2 in the United Kingdom using the ONS COVID-19 Infection Survey

Key epidemiological parameters, including the effective reproduction number, R ( t ) , and the instantaneous growth rate, r ( t ) , generated from an ensemble of models, have been informing public health policy throughout the COVID-19 pandemic in the four nations of the United Kingdom of Great Britain and Northern Ireland (UK). However, estimation of these quantities became challenging with the scaling down of surveillance systems as part of the transition from the "emergency" to "endemic" phase of the pandemic. The Office for National Statistics (ONS) COVID-19 Infection Survey (CIS) provided an opportunity to continue estimating these parameters in the absence of other data streams. We used a penalised spline model fitted to the publicly-available ONS CIS test positivity estimates to produce a smoothed estimate of the prevalence of SARS-CoV-2 positivity over time. The resulting fitted curve was used to estimate the "ONS-based" R ( t ) and r ( t ) across the four nations of the UK. Estimates produced under this model are compared to government-published estimates with particular consideration given to the contribution that this single data stream can offer in the estimation of these parameters. Depending on the nation and parameter, we found that up to 77% of the variance in the government-published estimates can be explained by the ONS-based estimates, demonstrating the value of this singular data stream to track the epidemic in each of the four nations. We additionally find that the ONS-based estimates uncover epidemic trends earlier than the corresponding government-published estimates. Our work shows that the ONS CIS can be used to generate key COVID-19 epidemiological parameters across the four UK nations, further underlining the enormous value of such population-level studies of infection. This is not intended as an alternative to ensemble modelling, rather it is intended as a potential solution to the aforementioned challenge faced by public health officials in the UK in early 2022.

Emerging Variants of Canine Enteric Coronavirus Associated with Outbreaks of Gastroenteric Disease

A 2022 canine gastroenteritis outbreak in the United Kingdom was associated with circulation of a new canine enteric coronavirus closely related to a 2020 variant with an additional spike gene recombination. The variants are unrelated to canine enteric coronavirus-like viruses associated with human disease but represent a model for coronavirus population adaptation.

Impact of COVID-19 vaccination: a global perspective

Introduction

The COVID-19 pandemic has caused widespread morbidity, mortality, and socio-economic disruptions worldwide. Vaccination has proven to be a crucial strategy in controlling the spread of the virus and mitigating its impact.

Objective

The study focuses on assessing the effectiveness of COVID-19 vaccination in reducing the incidence of positive cases, hospitalizations, and ICU admissions. The presented study is focused on the COVID-19 fully vaccinated population by considering the data from the first positive case reported until 20 September 2021.

Methods

Using data from multiple countries, time series analysis is deployed to investigate the variations in the COVID-19 positivity rates, hospitalization rates, and ICU requirements after successful vaccination campaigns at the country scale.

Results

Analysis of the COVID-19 positivity rates revealed a substantial decline in countries with high pre-vaccination rates. Within 1-3 months of vaccination campaigns, these rates decreased by 20-44%. However, certain countries experienced an increase in positivity rates with the emergence of the new Delta variant, emphasizing the importance of ongoing monitoring and adaptable vaccination strategies. Similarly, the analysis of hospitalization rates demonstrated a steady decline as vaccination drive rates rose in various countries. Within 90 days of vaccination, several countries achieved hospitalization rates below 200 per million. However, a slight increase in hospitalizations was observed in some countries after 180 days of vaccination, underscoring the need for continued vigilance. Furthermore, the ICU patient rates decreased as vaccination rates increased across most countries. Within 120 days, several countries achieved an ICU patient rate of 20 per million, highlighting the effectiveness of vaccination in preventing severe cases requiring intensive care.

Conclusion

COVID-19 vaccination has proven to be very much effective in reducing the incidence of cases, hospitalizations, and ICU admissions. However, ongoing surveillance, variant monitoring, and adaptive vaccination strategies are crucial for maximizing the benefits of vaccination and effectively controlling the spread of the virus.

Serum HCoV-spike specific antibodies do not protect against subsequent SARS-CoV-2 infection in children and adolescents

SARS-CoV-2 infections in children are generally asymptomatic or mild and rarely progress to severe disease and hospitalization. Why this is so remains unclear. Here we explore the potential for protection due to pre-existing cross-reactive seasonal coronavirus antibodies and compare the rate of antibody decline for nucleocapsid and spike protein in serum and oral fluid against SARS-CoV-2 within the pediatric population. No differences in seasonal coronaviruses antibody concentrations were found at baseline between cases and controls, suggesting no protective effect from pre-existing immunity against seasonal coronaviruses. Antibodies against seasonal betacoronaviruses were boosted in response to SARS-CoV-2 infection. In serum, anti-nucleocapsid antibodies fell below the threshold of positivity more quickly than anti-spike protein antibodies. These findings add to our understanding of protection against infection with SARS-CoV-2 within the pediatric population, which is important when considering pediatric SARS-CoV-2 immunization policies.

A study on the transmission dynamics of COVID-19 considering the impact of asymptomatic infection

The COVID-19 epidemic has been spreading around the world for nearly three years, and asymptomatic infections have exacerbated the spread of the epidemic. To analyse and evaluate the role of asymptomatic infections in the spread of the epidemic, we establish an improved COVID-19 infectious disease dynamics model. We fit the epidemic data in the four time periods corresponding to the selected 614G, Alpha, Delta and Omicron variants and obtain the proportion of asymptomatic persons among the infected persons gradually increased and with the increase of the detection ratio, the cumulative number of cases has dropped significantly, but the decline in the proportion of asymptomatic infections is not obvious. Therefore, in view of the hidden transmission of asymptomatic infections, the cooperation between various epidemic prevention and control policies is required to effectively curb the spread of the epidemic.

Genomic epidemiology reveals early transmission of SARS-CoV-2 and mutational dynamics in Nanning, China

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants are a fatal pathogen resulting in substantial morbidity and mortality, and posing a great threat to human health with epidemics and pandemics.

METHODS

Next-generation sequencing (NGS) was performed to investigate the SARS-CoV-2 genomic characterization. Phylogenetic analysis of SARS-CoV-2 genomes was used to probe the evolutionary. Homology protein structure modelling was done to explore potential effect of the mutations.

RESULTS

The eighty genome sequences of SARS-CoV-2 obtained from the thirty-nine patients with COVID-19. A novel variant with mutation H625R concomitant with S50L in spike glycoprotein had been identified. Phylogenetic analysis revealed that SARS-CoV-2 variants belong to several distinct lineages. Homology modelling indicated that variant with mutation H625R and S50L increases flexibility of S1 subunit.

CONCLUSIONS

SARS-CoV-2 genomes are constantly evolving by accumulation of point mutations. The amino acid H625R in combination with S50L may have a significant impact on the interaction between spike glycoprotein and ACE2.

Lineage replacement and evolution captured by 3 years of the United Kingdom Coronavirus (COVID-19) Infection Survey

The Office for National Statistics Coronavirus (COVID-19) Infection Survey (ONS-CIS) is the largest surveillance study of SARS-CoV-2 positivity in the community, and collected data on the United Kingdom (UK) epidemic from April 2020 until March 2023 before being paused. Here, we report on the epidemiological and evolutionary dynamics of SARS-CoV-2 determined by analysing the sequenced samples collected by the ONS-CIS during this period. We observed a series of sweeps or partial sweeps, with each sweeping lineage having a distinct growth advantage compared to their predecessors, although this was also accompanied by a gradual fall in average viral burdens from June 2021 to March 2023. The sweeps also generated an alternating pattern in which most samples had either S-gene target failure (SGTF) or non-SGTF over time. Evolution was characterized by steadily increasing divergence and diversity within lineages, but with step increases in divergence associated with each sweeping major lineage. This led to a faster overall rate of evolution when measured at the between-lineage level compared to within lineages, and fluctuating levels of diversity. These observations highlight the value of viral sequencing integrated into community surveillance studies to monitor the viral epidemiology and evolution of SARS-CoV-2, and potentially other pathogens.

Comparing SARS-CoV-2 variants among children and adolescents in Germany: relative risk of COVID-19-related hospitalization, ICU admission and mortality

PURPOSE

SARS-CoV-2 infections cause COVID-19 and have a wide spectrum of morbidity. Severe disease courses among children are rare. To date, data on the variability of morbidity in relation to variant of concern (VOC) in children has been sparse and inconclusive. We compare the clinical severity of SARS-CoV-2 infection among children and adolescents in Germany during the Wildtype and Alpha combined, Delta and Omicron phases of the COVID-19 pandemic.

METHODS

Comparing risk of COVID-19-related hospitalization, intensive care unit (ICU) admission and death due to COVID-19 in children and adolescents, we used: (1) a multi-center seroprevalence study (SARS-CoV-2-KIDS study); (2) a nationwide registry of pediatric patients hospitalized with SARS-CoV-2 infections; and (3) compulsory national reporting for RT-PCR-confirmed SARS-CoV-2 infections in Germany.

RESULTS

During the Delta predominant phase, risk of COVID-19-related hospitalization among all SARS-CoV-2 seropositive children was 3.35, ICU admission 1.19 and fatality 0.09 per 10,000; hence about halved for hospitalization and ICU admission and unchanged for deaths as compared to the Wildtype- and Alpha-dominant period. The relative risk for COVID-19-related hospitalization and ICU admission compared to the alpha period decreased during Delta [0.60 (95% CI 0.54; 0.67) and 0.51 (95% CI 0.42; 0.61)] and Omicron [0.27 (95% CI 0.24; 0.30) and 0.06 (95% CI 0.05; 0.08)] period except for the < 5-year-olds. The rate of case fatalities decreased slightly during Delta, and substantially during Omicron phase.

CONCLUSION

Morbidity caused by SARS-CoV-2 infections among children and adolescents in Germany decreased over the course of the COVID-19 pandemic, as different VOCs) emerged.

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.

Representativeness of whole-genome sequencing approaches in England: the importance for understanding inequalities associated with SARS-CoV-2 infection

Whole-genome sequencing (WGS) information has played a crucial role in the SARS-CoV-2 (COVID-19) pandemic by providing evidence about variants to inform public health policy. The purpose of this study was to assess the representativeness of sequenced cases compared with all COVID-19 cases in England, between March 2020 and August 2021, by demographic and socio-economic characteristics, to evaluate the representativeness and utility of these data in epidemiological analyses. To achieve this, polymerase chain reaction (PCR)-confirmed COVID-19 cases were extracted from the national laboratory system and linked with WGS data. During the study period, over 10% of COVID-19 cases in England had WGS data available for epidemiological analysis. With sequencing capacity increasing throughout the period, sequencing representativeness compared to all reported COVID-19 cases increased over time, allowing for valuable epidemiological analyses using demographic and socio-economic characteristics, particularly during periods with emerging novel SARS-CoV-2 variants. This study demonstrates the comprehensiveness of England's sequencing throughout the COVID-19 pandemic, rapidly detecting variants of concern, and enabling representative epidemiological analyses to inform policy.

Real-Time Analysis of SARS-CoV-2-Induced Cytolysis Reveals Distinct Variant-Specific Replication Profiles

The ability of each new SARS-CoV-2 variant to evade host humoral immunity is the focus of intense research. Each variant may also harbor unique replication capabilities relevant for disease and transmission. Here, we demonstrate a new approach to assessing viral replication kinetics using real-time cell analysis (RTCA). Virus-induced cell death is measured in real time as changes in electrical impedance through cell monolayers while images are acquired at defined intervals via an onboard microscope and camera. Using this system, we quantified replication kinetics of five clinically important viral variants: WA1/2020 (ancestral), Delta, and Omicron subvariants BA.1, BA.4, and BA.5. Multiple measures proved useful in variant replication comparisons, including the elapsed time to, and the slope at, the maximum rate of cell death. Important findings include significantly weaker replication kinetics of BA.1 by all measures, while BA.5 harbored replication kinetics at or near ancestral levels, suggesting evolution to regain replicative capacity, and both an altered profile of cell killing and enhanced fusogenicity of the Delta variant. Together, these data show that RTCA is a robust method to assess replicative capacity of any given SARS-CoV-2 variant rapidly and quantitatively, which may be useful in assessment of newly emerging variants.

Association of vaccination, international travel, public health and social measures with lineage dynamics of SARS-CoV-2

Continually emerging SARS-CoV-2 variants of concern that can evade immune defenses are driving recurrent epidemic waves of COVID-19 globally. However, the impact of measures to contain the virus and their effect on lineage diversity dynamics are poorly understood. Here, we jointly analyzed international travel, public health and social measures (PHSM), COVID-19 vaccine rollout, SARS-CoV-2 lineage diversity, and the case growth rate (GR) from March 2020 to September 2022 across 63 countries. We showed that despite worldwide vaccine rollout, PHSM are effective in mitigating epidemic waves and lineage diversity. An increase of 10,000 monthly travelers in a single country-to-country route between endemic countries corresponds to a 5.5% (95% CI: 2.9 to 8.2%) rise in local lineage diversity. After accounting for PHSM, natural immunity from previous infections, and waning immunity, we discovered a negative association between the GR of cases and adjusted vaccine coverage (AVC). We also observed a complex relationship between lineage diversity and vaccine rollout. Specifically, we found a significant negative association between lineage diversity and AVC at both low and high levels but not significant at the medium level. Our study deepens the understanding of population immunity and lineage dynamics for future pandemic preparedness and responsiveness.

Comparing the evolutionary dynamics of predominant SARS-CoV-2 virus lineages co-circulating in Mexico

Over 200 different SARS-CoV-2 lineages have been observed in Mexico by November 2021. To investigate lineage replacement dynamics, we applied a phylodynamic approach and explored the evolutionary trajectories of five dominant lineages that circulated during the first year of local transmission. For most lineages, peaks in sampling frequencies coincided with different epidemiological waves of infection in Mexico. Lineages B.1.1.222 and B.1.1.519 exhibited similar dynamics, constituting clades that likely originated in Mexico and persisted for >12 months. Lineages B.1.1.7, P.1 and B.1.617.2 also displayed similar dynamics, characterized by multiple introduction events leading to a few successful extended local transmission chains that persisted for several months. For the largest B.1.617.2 clades, we further explored viral lineage movements across Mexico. Many clades were located within the south region of the country, suggesting that this area played a key role in the spread of SARS-CoV-2 in Mexico.

Maximum likelihood pandemic-scale phylogenetics

Phylogenetics has a crucial role in genomic epidemiology. Enabled by unparalleled volumes of genome sequence data generated to study and help contain the COVID-19 pandemic, phylogenetic analyses of SARS-CoV-2 genomes have shed light on the virus's origins, spread, and the emergence and reproductive success of new variants. However, most phylogenetic approaches, including maximum likelihood and Bayesian methods, cannot scale to the size of the datasets from the current pandemic. We present 'MAximum Parsimonious Likelihood Estimation' (MAPLE), an approach for likelihood-based phylogenetic analysis of epidemiological genomic datasets at unprecedented scales. MAPLE infers SARS-CoV-2 phylogenies more accurately than existing maximum likelihood approaches while running up to thousands of times faster, and requiring at least 100 times less memory on large datasets. This extends the reach of genomic epidemiology, allowing the continued use of accurate phylogenetic, phylogeographic and phylodynamic analyses on datasets of millions of genomes.

Zooanthroponotic transmission of SARS-CoV-2 and host-specific viral mutations revealed by genome-wide phylogenetic analysis

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a generalist virus, infecting and evolving in numerous mammals, including captive and companion animals, free-ranging wildlife, and humans. Transmission among non-human species poses a risk for the establishment of SARS-CoV-2 reservoirs, makes eradication difficult, and provides the virus with opportunities for new evolutionary trajectories, including the selection of adaptive mutations and the emergence of new variant lineages. Here, we use publicly available viral genome sequences and phylogenetic analysis to systematically investigate the transmission of SARS-CoV-2 between human and non-human species and to identify mutations associated with each species. We found the highest frequency of animal-to-human transmission from mink, compared with lower transmission from other sampled species (cat, dog, and deer). Although inferred transmission events could be limited by sampling biases, our results provide a useful baseline for further studies. Using genome-wide association studies, no single nucleotide variants (SNVs) were significantly associated with cats and dogs, potentially due to small sample sizes. However, we identified three SNVs statistically associated with mink and 26 with deer. Of these SNVs, ~⅔ were plausibly introduced into these animal species from local human populations, while the remaining ~⅓ were more likely derived in animal populations and are thus top candidates for experimental studies of species-specific adaptation. Together, our results highlight the importance of studying animal-associated SARS-CoV-2 mutations to assess their potential impact on human and animal health.

High-throughput sequencing approaches applied to SARS-CoV-2

High-throughput sequencing is crucial for surveillance and control of viral outbreaks. During the ongoing coronavirus disease 2019 (COVID-19) pandemic, advances in the high-throughput sequencing technology resources have enhanced diagnosis, surveillance, and vaccine discovery. From the onset of the pandemic in December 2019, several genome-sequencing approaches have been developed and supported across the major sequencing platforms such as Illumina, Oxford Nanopore, PacBio, MGI DNBSEQTM and Ion Torrent. Here, we share insights from the sequencing approaches developed for sequencing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) between December 2019 and October 2022.

Seasonal effects decouple SARS-CoV-2 haplotypes worldwide

Background: Variants of concern (VOCs) have been replacing each other during the still rampant COVID-19 pandemic. As a result, SARS-CoV-2 populations have evolved increasingly intricate constellations of mutations that often enhance transmissibility, disease severity, and other epidemiological characteristics. The origin and evolution of these constellations remain puzzling. Methods: Here we study the evolution of VOCs at the proteome level by analyzing about 12 million genomic sequences retrieved from GISAID on July 23, 2022. A total 183,276 mutations were identified and filtered with a relevancy heuristic. The prevalence of haplotypes and free-standing mutations was then tracked monthly in various latitude corridors of the world. Results: A chronology of 22 haplotypes defined three phases driven by protein flexibility-rigidity, environmental sensing, and immune escape. A network of haplotypes illustrated the recruitment and coalescence of mutations into major VOC constellations and seasonal effects of decoupling and loss. Protein interaction networks mediated by haplotypes predicted communications impacting the structure and function of proteins, showing the increasingly central role of molecular interactions involving the spike (S), nucleocapsid (N), and membrane (M) proteins. Haplotype markers either affected fusogenic regions while spreading along the sequence of the S-protein or clustered around binding domains. Modeling of protein structure with AlphaFold2 showed that VOC Omicron and one of its haplotypes were major contributors to the distortion of the M-protein endodomain, which behaves as a receptor of other structural proteins during virion assembly. Remarkably, VOC constellations acted cooperatively to balance the more extreme effects of individual haplotypes. Conclusions: Our study uncovers seasonal patterns of emergence and diversification occurring amid a highly dynamic evolutionary landscape of bursts and waves. The mapping of genetically-linked mutations to structures that sense environmental change with powerful ab initio modeling tools demonstrates the potential of deep-learning for COVID-19 predictive intelligence and therapeutic intervention.

The race to understand immunopathology in COVID-19: Perspectives on the impact of quantitative approaches to understand within-host interactions

The COVID-19 pandemic has revealed the need for the increased integration of modelling and data analysis to public health, experimental, and clinical studies. Throughout the first two years of the pandemic, there has been a concerted effort to improve our understanding of the within-host immune response to the SARS-CoV-2 virus to provide better predictions of COVID-19 severity, treatment and vaccine development questions, and insights into viral evolution and the impacts of variants on immunopathology. Here we provide perspectives on what has been accomplished using quantitative methods, including predictive modelling, population genetics, machine learning, and dimensionality reduction techniques, in the first 26 months of the COVID-19 pandemic approaches, and where we go from here to improve our responses to this and future pandemics.

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.

The 2022 RSV surge was driven by multiple viral lineages

The US experienced an early and severe respiratory syncytial virus (RSV) surge in autumn 2022. Despite the pressure this has put on hospitals and care centers, the factors promoting the surge in cases are unknown. To investigate whether viral characteristics contributed to the extent or severity of the surge, we sequenced 105 RSV-positive specimens from symptomatic patients diagnosed with RSV who presented to the Massachusetts General Hospital (MGH) and its outpatient practices in the Greater Boston Area. Genomic analysis of the resulting 77 genomes (54 with >80% coverage, and 23 with >5% coverage) demonstrated that the surge was driven by multiple lineages of RSV-A (91%; 70/77) and RSV-B (9%; 7/77). Phylogenetic analysis of all US RSV-A revealed 12 clades, 4 of which contained Massachusetts and Washington genomes. These clades individually had times to most recent common ancestor (tMRCA) between 2014 and 2017, and together had a tMRCA of 2009, suggesting that they emerged well before the COVID-19 pandemic. Similarly, the RSV-B genomes had a tMRCA between 2016 and 2019. We found that the RSV-A and RSV-B genomes in our sample did not differ statistically from the estimated clock rate of the larger phylogenetic tree (10.6 and 12.4 substitutions per year, respectively). In summary, the polyphyletic nature of viral genomes sequenced in the US during the autumn 2022 surge is inconsistent with the emergence of a single, highly transmissible causal RSV lineage.

The origins of COVID-19 pandemic: A brief overview

The novel coronavirus disease (COVID-19) outbreak that emerged at the end of 2019 has now swept the world for more than 2 years, causing immeasurable damage to the lives and economies of the world. It has drawn so much attention to discovering how the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) originated and entered the human body. The current argument revolves around two contradictory theories: a scenario of laboratory spillover events and human contact with zoonotic diseases. Here, we reviewed the transmission, pathogenesis, possible hosts, as well as the genome and protein structure of SARS-CoV-2, which play key roles in the COVID-19 pandemic. We believe the coronavirus was originally transmitted to human by animals rather than by a laboratory leak. However, there still needs more investigations to determine the source of the pandemic. Understanding how COVID-19 emerged is vital to developing global strategies for mitigating future outbreaks.

Mandrake: visualizing microbial population structure by embedding millions of genomes into a low-dimensional representation

In less than a decade, population genomics of microbes has progressed from the effort of sequencing dozens of strains to thousands, or even tens of thousands of strains in a single study. There are now hundreds of thousands of genomes available even for a single bacterial species, and the number of genomes is expected to continue to increase at an accelerated pace given the advances in sequencing technology and widespread genomic surveillance initiatives. This explosion of data calls for innovative methods to enable rapid exploration of the structure of a population based on different data modalities, such as multiple sequence alignments, assemblies and estimates of gene content across different genomes. Here, we present Mandrake, an efficient implementation of a dimensional reduction method tailored for the needs of large-scale population genomics. Mandrake is capable of visualizing population structure from millions of whole genomes, and we illustrate its usefulness with several datasets representing major pathogens. Our method is freely available both as an analysis pipeline (https://github.com/johnlees/mandrake) and as a browser-based interactive application (https://gtonkinhill.github.io/mandrake-web/).

This article is part of a discussion meeting issue ‘Genomic population structures of microbial pathogens’.

Estimating SARS-CoV-2 variant fitness and the impact of interventions in England using statistical and geo-spatial agent-based models

The SARS-CoV-2 epidemic has been extended by the evolution of more transmissible viral variants. In autumn 2020, the B.1.177 lineage became the dominant variant in England, before being replaced by the B.1.1.7 (Alpha) lineage in late 2020, with the sweep occurring at different times in each region. This period coincided with a large number of non-pharmaceutical interventions (e.g. lockdowns) to control the epidemic, making it difficult to estimate the relative transmissibility of variants. In this paper, we model the spatial spread of these variants in England using a meta-population agent-based model which correctly characterizes the regional variation in cases and distribution of variants. As a test of robustness, we additionally estimated the relative transmissibility of multiple variants using a statistical model based on the renewal equation, which simultaneously estimates the effective reproduction number R. Relative to earlier variants, the transmissibility of B.1.177 is estimated to have increased by 1.14 (1.12-1.16) and that of Alpha by 1.71 (1.65-1.77). The vaccination programme starting in December 2020 is also modelled. Counterfactual simulations demonstrate that the vaccination programme was essential for reopening in March 2021, and that if the January lockdown had started one month earlier, up to 30 k (24 k-38 k) deaths could have been prevented. This article is part of the theme issue 'Technical challenges of modelling real-life epidemics and examples of overcoming these'.

Estimating SARS-CoV-2 variant fitness and the impact of interventions in England using statistical and geo-spatial agent-based models

The SARS-CoV-2 epidemic has been extended by the evolution of more transmissible viral variants. In autumn 2020, the B.1.177 lineage became the dominant variant in England, before being replaced by the B.1.1.7 (Alpha) lineage in late 2020, with the sweep occurring at different times in each region. This period coincided with a large number of non-pharmaceutical interventions (e.g. lockdowns) to control the epidemic, making it difficult to estimate the relative transmissibility of variants. In this paper, we model the spatial spread of these variants in England using a meta-population agent-based model which correctly characterizes the regional variation in cases and distribution of variants. As a test of robustness, we additionally estimated the relative transmissibility of multiple variants using a statistical model based on the renewal equation, which simultaneously estimates the effective reproduction number R. Relative to earlier variants, the transmissibility of B.1.177 is estimated to have increased by 1.14 (1.12-1.16) and that of Alpha by 1.71 (1.65-1.77). The vaccination programme starting in December 2020 is also modelled. Counterfactual simulations demonstrate that the vaccination programme was essential for reopening in March 2021, and that if the January lockdown had started one month earlier, up to 30 k (24 k-38 k) deaths could have been prevented. This article is part of the theme issue 'Technical challenges of modelling real-life epidemics and examples of overcoming these'.

Context-specific emergence and growth of the SARS-CoV-2 Delta variant

The SARS-CoV-2 Delta (Pango lineage B.1.617.2) variant of concern spread globally, causing resurgences of COVID-19 worldwide1,2. The emergence of the Delta variant in the UK occurred on the background of a heterogeneous landscape of immunity and relaxation of non-pharmaceutical interventions. Here we analyse 52,992 SARS-CoV-2 genomes from England together with 93,649 genomes from the rest of the world to reconstruct the emergence of Delta and quantify its introduction to and regional dissemination across England in the context of changing travel and social restrictions. Using analysis of human movement, contact tracing and virus genomic data, we find that the geographic focus of the expansion of Delta shifted from India to a more global pattern in early May 2021. In England, Delta lineages were introduced more than 1,000 times and spread nationally as non-pharmaceutical interventions were relaxed. We find that hotel quarantine for travellers reduced onward transmission from importations; however, the transmission chains that later dominated the Delta wave in England were seeded before travel restrictions were introduced. Increasing inter-regional travel within England drove the nationwide dissemination of Delta, with some cities receiving more than 2,000 observable lineage introductions from elsewhere. Subsequently, increased levels of local population mixing-and not the number of importations-were associated with the faster relative spread of Delta. The invasion dynamics of Delta depended on spatial heterogeneity in contact patterns, and our findings will inform optimal spatial interventions to reduce the transmission of current and future variants of concern, such as Omicron (Pango lineage B.1.1.529).

The emergence, spread and vanishing of a French SARS-CoV-2 variant exemplifies the fate of RNA virus epidemics and obeys the Mistigri rule

The nature and dynamics of mutations associated with the emergence, spread, and vanishing of SARS-CoV-2 variants causing successive waves are complex. We determined the kinetics of the most common French variant ("Marseille-4") for 10 months since its onset in July 2020. Here, we analyzed and classified into subvariants and lineages 7453 genomes obtained by next-generation sequencing. We identified two subvariants, Marseille-4A, which contains 22 different lineages of at least 50 genomes, and Marseille-4B. Their average lifetime was 4.1 ± 1.4 months, during which 4.1 ± 2.6 mutations accumulated. Growth rate was 0.079 ± 0.045, varying from 0.010 to 0.173. Most of the lineages exhibited a bell-shaped distribution. Several beneficial mutations at unpredicted sites initiated a new outbreak, while the accumulation of other mutations resulted in more viral heterogenicity, increased diversity and vanishing of the lineages. Marseille-4B emerged when the other Marseille-4 lineages vanished. Its ORF8 gene was knocked out by a stop codon, as reported in SARS-CoV-2 of mink and in the Alpha variant. This subvariant was associated with increased hospitalization and death rates, suggesting that ORF8 is a nonvirulence gene. We speculate that the observed heterogenicity of a lineage may predict the end of the outbreak.

SARS-CoV-2 and COVID-19: A Narrative Review

The World Health Organisation has reported that the viral disease known as COVID-19, caused by SARS-CoV-2, is the leading cause of death by a single infectious agent. This narrative review examines certain components of the pandemic: its origins, early clinical data, global and UK-focussed epidemiology, vaccination, variants, and long COVID.

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

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

Immunogenicity and protective efficacy of SARS-CoV-2 recombinant S-protein vaccine S-268019-b in cynomolgus monkeys

The vaccine S-268019-b is a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike (S)-protein vaccine consisting of full-length recombinant SARS-CoV-2 S-protein (S-910823) as antigen, mixed with the squalene-based adjuvant A-910823. The current study evaluated the immunogenicity of S-268019-b using various doses of S-910823 and its vaccine efficacy against SARS-CoV-2 challenge in cynomolgus monkeys. The different doses of S-910823 combined with A-910823 were intramuscularly administered twice at a 3-week interval. Two weeks after the second dosing, dose-dependent humoral immune responses were observed with neutralizing antibody titers being comparable to that of human convalescent plasma. Pseudoviruses harboring S proteins from Beta and Gamma SARS-CoV-2 variants displayed approximately 3- to 4-fold reduced sensitivity to neutralizing antibodies induced after two vaccine doses compared with that against ancestral viruses, whereas neutralizing antibody titers were reduced >14-fold against the Omicron variant. Cellular immunity was also induced with a relative Th1 polarized response. No adverse clinical signs or weight loss associated with the vaccine were observed, suggesting safety of the vaccine in cynomolgus monkeys. Immunization with 10 µg of S-910823 with A-910823 demonstrated protective efficacy against SARS-CoV-2 challenge according to genomic and subgenomic viral RNA transcript levels in nasopharyngeal, throat, and rectal swab specimens. Pathological analysis revealed no detectable vaccine-dependent enhancement of disease in the lungs of challenged vaccinated monkeys. The current findings provide fundamental information regarding vaccine doses for human trials and support the development of S-268019-b as a safe and effective vaccine for controlling the current pandemic, as well as general protection against SARS-CoV-2 moving forward.

Burden of SARS-CoV-2 infection in healthcare workers during second wave in England and impact of vaccines: prospective multicentre cohort study (SIREN) and mathematical model

OBJECTIVE

To describe the incidence of, risk factors for, and impact of vaccines on primary SARS-CoV-2 infection during the second wave of the covid-19 pandemic in susceptible hospital healthcare workers in England.

DESIGN

Multicentre prospective cohort study.

SETTING

National Health Service secondary care health organisations (trusts) in England between 1 September 2020 and 30 April 2021.

PARTICIPANTS

Clinical, support, and administrative staff enrolled in the SARS-CoV-2 Immunity and Reinfection Evaluation (SIREN) study with no evidence of previous infection. Vaccination status was obtained from national covid-19 vaccination registries and self-reported.

MAIN OUTCOME MEASURE

SARS-CoV-2 infection confirmed by polymerase chain reaction. Mixed effects logistic regression was conducted to determine demographic and occupational risk factors for infection, and an individual based mathematical model was used to predict how large the burden could have been if vaccines had not been available from 8 December 2020 .

RESULTS

During England's second wave, 12.9% (2353/18 284) of susceptible SIREN participants became infected with SARS-CoV-2. Infections peaked in late December 2020 and decreased from January 2021, concurrent with the cohort's rapid vaccination coverage and a national lockdown. In multivariable analysis, factors increasing the likelihood of infection in the second wave were being under 25 years old (20.3% (132/651); adjusted odds ratio 1.35, 95% confidence interval 1.07 to 1.69), living in a large household (15.8% (282/1781); 1.54, 1.23 to 1.94, for participants from households of five or more people), having frequent exposure to patients with covid-19 (19.2% (723/3762); 1.79, 1.56 to 2.06, for participants with exposure every shift), working in an emergency department or inpatient ward setting (20.8% (386/1855); 1.76, 1.45 to 2.14), and being a healthcare assistant (18.1% (267/1479); 1.43, 1.16 to 1.77). Time to first vaccination emerged as being strongly associated with infection (P<0.001), with each additional day multiplying a participant's adjusted odds ratio by 1.02. Mathematical model simulations indicated that an additional 9.9% of all patient facing hospital healthcare workers would have been infected were it not for the rapid vaccination coverage.

CONCLUSIONS

The rapid covid-19 vaccine rollout from December 2020 averted infection in a large proportion of hospital healthcare workers in England: without vaccines, second wave infections could have been 69% higher. With booster vaccinations being needed for adequate protection from the omicron variant, and perhaps the need for further boosters for future variants, ensuring equitable delivery to healthcare workers is essential. The findings also highlight occupational risk factors that persisted in healthcare workers despite vaccine rollout; a greater understanding of the transmission dynamics responsible for these is needed to help to optimise the infection prevention and control policies that protect healthcare workers from infection and therefore to support staffing levels and maintain healthcare provision.

TRIAL REGISTRATION

ISRCTN registry ISRCTN11041050.

VOC-alarm: mutation-based prediction of SARS-CoV-2 variants of concern

SUMMARY

Mutation is the key for a variant of concern (VOC) to overcome selective pressures, but this process is still unclear. Understanding the association of the mutational process with VOCs is an unmet need. Motivation: Here, we developed VOC-alarm, a method to predict VOCs and their caused COVID surges, using mutations of about 5.7 million SARS-CoV-2 complete sequences. We found that VOCs rely on lineage-level entropy value of mutation numbers to compete with other variants, suggestive of the importance of population-level mutations in the virus evolution. Thus, we hypothesized that VOCs are a result of a mutational process across the globe. Results: Analyzing the mutations from January 2020 to December 2021, we simulated the mutational process by estimating the pace of evolution, and thus divided the time period, January 2020-March 2022, into eight stages. We predicted Alpha, Delta, Delta Plus (AY.4.2) and Omicron (B.1.1.529) by their mutational entropy values in the Stages I, III, V and VII with accelerated paces, respectively. In late November 2021, VOC-alarm alerted that Omicron strongly competed with Delta and Delta plus to become a highly transmissible variant. Using simulated data, VOC-alarm also predicted that Omicron could lead to another COVID surge from January 2022 to March 2022.

AVAILABILITY AND IMPLEMENTATION

Our software implementation is available at https://github.com/guangxujin/VOC-alarm.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

COVID-19 due to the B.1.617.2 (Delta) variant compared to B.1.1.7 (Alpha) variant of SARS-CoV-2: a prospective observational cohort study

The Delta (B.1.617.2) variant was the predominant UK circulating SARS-CoV-2 strain between May and December 2021. How Delta infection compares with previous variants is unknown. This prospective observational cohort study assessed symptomatic adults participating in the app-based COVID Symptom Study who tested positive for SARS-CoV-2 from May 26 to July 1, 2021 (Delta overwhelmingly the predominant circulating UK variant), compared (1:1, age- and sex-matched) with individuals presenting from December 28, 2020 to May 6, 2021 (Alpha (B.1.1.7) the predominant variant). We assessed illness (symptoms, duration, presentation to hospital) during Alpha- and Delta-predominant timeframes; and transmission, reinfection, and vaccine effectiveness during the Delta-predominant period. 3581 individuals (aged 18 to 100 years) from each timeframe were assessed. The seven most frequent symptoms were common to both variants. Within the first 28 days of illness, some symptoms were more common with Delta versus Alpha infection (including fever, sore throat, and headache) and some vice versa (dyspnoea). Symptom burden in the first week was higher with Delta versus Alpha infection; however, the odds of any given symptom lasting ≥ 7 days was either lower or unchanged. Illness duration ≥ 28 days was lower with Delta versus Alpha infection, though unchanged in unvaccinated individuals. Hospitalisation for COVID-19 was unchanged. The Delta variant appeared more (1.49) transmissible than Alpha. Re-infections were low in all UK regions. Vaccination markedly reduced the risk of Delta infection (by 69-84%). We conclude that COVID-19 from Delta or Alpha infections is similar. The Delta variant is more transmissible than Alpha; however, current vaccines showed good efficacy against disease. This research framework can be useful for future comparisons with new emerging variants.

Identifying SARS-CoV-2 regional introductions and transmission clusters in real time

The unprecedented severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) global sequencing effort has suffered from an analytical bottleneck. Many existing methods for phylogenetic analysis are designed for sparse, static datasets and are too computationally expensive to apply to densely sampled, rapidly expanding datasets when results are needed immediately to inform public health action. For example, public health is often concerned with identifying clusters of closely related samples, but the sheer scale of the data prevents manual inspection and the current computational models are often too expensive in time and resources. Even when results are available, intuitive data exploration tools are of critical importance to effective public health interpretation and action. To help address this need, we present a phylogenetic heuristic that quickly and efficiently identifies newly introduced strains in a region, resulting in clusters of infected individuals, and their putative geographic origins. We show that this approach performs well on simulated data and yields results largely congruent with more sophisticated Bayesian phylogeographic modeling approaches. We also introduce Cluster-Tracker (https://clustertracker.gi.ucsc.edu/), a novel interactive web-based tool to facilitate effective and intuitive SARS-CoV-2 geographic data exploration and visualization across the USA. Cluster-Tracker is updated daily and automatically identifies and highlights groups of closely related SARS-CoV-2 infections resulting from the transmission of the virus between two geographic areas by travelers, streamlining public health tracking of local viral diversity and emerging infection clusters. The site is open-source and designed to be easily configured to analyze any chosen region, making it a useful resource globally. The combination of these open-source tools will empower detailed investigations of the geographic origins and spread of SARS-CoV-2 and other densely sampled pathogens.

Virological characteristics of the SARS-CoV-2 Omicron BA.2 spike

Soon after the emergence and global spread of the SARS-CoV-2 Omicron lineage BA.1, another Omicron lineage, BA.2, began outcompeting BA.1. The results of statistical analysis showed that the effective reproduction number of BA.2 is 1.4-fold higher than that of BA.1. Neutralization experiments revealed that immunity induced by COVID vaccines widely administered to human populations is not effective against BA.2, similar to BA.1, and that the antigenicity of BA.2 is notably different from that of BA.1. Cell culture experiments showed that the BA.2 spike confers higher replication efficacy in human nasal epithelial cells and is more efficient in mediating syncytia formation than the BA.1 spike. Furthermore, infection experiments using hamsters indicated that the BA.2 spike-bearing virus is more pathogenic than the BA.1 spike-bearing virus. Altogether, the results of our multiscale investigations suggest that the risk of BA.2 to global health is potentially higher than that of BA.1.

Virological characteristics of the SARS-CoV-2 Omicron BA.2 spike

Soon after the emergence and global spread of the SARS-CoV-2 Omicron lineage BA.1, another Omicron lineage, BA.2, began outcompeting BA.1. The results of statistical analysis showed that the effective reproduction number of BA.2 is 1.4-fold higher than that of BA.1. Neutralization experiments revealed that immunity induced by COVID vaccines widely administered to human populations is not effective against BA.2, similar to BA.1, and that the antigenicity of BA.2 is notably different from that of BA.1. Cell culture experiments showed that the BA.2 spike confers higher replication efficacy in human nasal epithelial cells and is more efficient in mediating syncytia formation than the BA.1 spike. Furthermore, infection experiments using hamsters indicated that the BA.2 spike-bearing virus is more pathogenic than the BA.1 spike-bearing virus. Altogether, the results of our multiscale investigations suggest that the risk of BA.2 to global health is potentially higher than that of BA.1.