Dynamics of competing SARS-CoV-2 variants during the Omicron epidemic in England

Within-Host Fitness and Antigenicity Shift Are Key Factors Influencing the Prevalence of Within-Host Variations in the SARS-CoV-2 S Gene

Within-host evolution plays a critical role in shaping the diversity of SARS-CoV-2. However, understanding the primary factors contributing to the prevalence of intra-host single nucleotide variants (iSNVs) in the viral population remains elusive. Here, we conducted a comprehensive analysis of over 556,000 SARS-CoV-2 sequencing data and prevalence data of different SARS-CoV-2 S protein amino acid mutations to elucidate key factors influencing the prevalence of iSNVs in the SARS-CoV-2 S gene. Within-host diversity analysis revealed the presence of mutational hotspots within the S gene, mainly located in NTD, RBD, TM, and CT domains. Additionally, we generated a single amino acid resolution selection status map of the S protein. We observed a significant variance in within-host fitness among iSNVs in the S protein. The majority of iSNVs exhibited low to no within-host fitness and displayed low alternate allele frequency (AAF), suggesting that they will be eliminated due to the narrow transmission bottleneck of SARS-CoV-2. Notably, iSNVs with moderate AAFs (0.06-0.12) were found to be more prevalent than those with high AAFs. Furthermore, iSNVs with the potential to alter antigenicity were more prevalent. These findings underscore the significance of within-host fitness and antigenicity shift as two key factors influencing the prevalence of iSNVs in the SARS-CoV-2 S gene.

From Emergence to Evolution: Dynamics of the SARS-CoV-2 Omicron Variant in Florida

The continual evolution of SARS-CoV-2 has significantly influenced the global response to the COVID-19 pandemic, with the emergence of highly transmissible and immune-evasive variants posing persistent challenges. The Omicron variant, first identified in November 2021, rapidly replaced the Delta variant, becoming the predominant strain worldwide. In Florida, Omicron was first detected in December 2021, leading to an unprecedented surge in cases that surpassed all prior waves, despite extensive vaccination efforts. This study investigates the molecular evolution and transmission dynamics of the Omicron lineages during Florida's Omicron waves, supported by a robust dataset of over 1000 sequenced genomes. Through phylogenetic and phylodynamic analyses, we capture the rapid diversification of the Omicron lineages, identifying significant importation events, predominantly from California, Texas, and New York, and exportation to North America, Europe, and South America. Variants such as BA.1, BA.2, BA.4, and BA.5 exhibited distinct transmission patterns, with BA.2 showing the ability to reinfect individuals previously infected with BA.1. Despite the high transmissibility and immune evasion of the Omicron sub-lineages, the plateauing of cases by late 2022 suggests increasing population immunity from prior infection and vaccination. Our findings underscore the importance of continuous genomic surveillance in identifying variant introductions, mapping transmission pathways, and guiding public health interventions to mitigate current and future pandemic risks.

Acute hepatitis of unknown aetiology in children: evidence for and against causal relationships with SARS-CoV-2, HAdv and AAV2

BACKGROUND

The cause of acute paediatric hepatitis of unknown aetiology (2022) has not been established despite extensive investigation.

OBJECTIVE

To summarise the evidence for and against a causal role for human adenovirus (HAdv), adeno-associated virus 2 (AAV-2) and SARS-CoV-2 in outbreaks of paediatric hepatitis in 2022.

METHODS

We appraised and summarised relevant evidence for each of the Bradford Hill criteria for causality using quantitative (statistical modelling) and qualitative (narrative coherence) approaches. Each team member scored the evidence base for each criterion separately for HAdv, AAV-2 and SARS-CoV-2; differences were resolved by discussion. We additionally examined criteria of strength and temporality by examining the lagged association between SARS-CoV-2 positivity, respiratory HAdv positivity, positive faecal HAdv specimens and excess A&E attendances in 1-4 years for liver conditions in England.

RESULTS

Assessing criteria using the published literature and our modelling: for HAdv three Bradford Hill criteria (strength, consistency and temporality) were partially met; and five criteria (consistency, coherence, experimental manipulation, analogy and temporality) were minimally met. For AAV-2, the strength of association criterion was fully met, five criteria (consistency, temporality, specificity, biological gradient and plausibility) were partially met and three (coherence, analogy and experimental manipulation) were minimally met. For SARS-CoV-2, five criteria (strength of association, plausibility, temporality, coherence and analogy) were fully met; one (consistency) was partially met and three (specificity, biological gradient and experimental manipulation) were minimally met.

CONCLUSION

Based on the Bradford Hill criteria and modelling, HAdv alone is unlikely to be the cause of the recent increase in hepatitis in children. The causal link between SARS-CoV-2, and to a lesser degree AAV-2, appears substantially stronger but remains unproven. Hepatitis is a known complication of multisystem inflammatory syndrome in children following COVID-19, and SARS-CoV-2 has been linked to increased susceptibility to infection post-COVID-19, which may suggest complex causal pathways including a possible interaction with AAV-2 infection/reactivation in hosts that are genetically susceptible or sensitised to infection.

Forecasting SARS-CoV-2 epidemic dynamic in Poland with the pDyn agent-based model

We employ pDyn (derived from "pandemics dynamics"), an agent-based epidemiological model, to forecast the fourth wave of the SARS-CoV-2 epidemic, primarily driven by the Delta variant, in Polish society. The model captures spatiotemporal dynamics of the epidemic spread, predicting disease-related states based on pathogen properties and behavioral factors. We assess pDyn's validity, encompassing pathogen variant succession, immunization level, and the proportion of vaccinated among confirmed cases. We evaluate its predictive capacity for pandemic dynamics, including wave peak timing, magnitude, and duration for confirmed cases, hospitalizations, ICU admissions, and deaths, nationally and regionally in Poland. Validation involves comparing pDyn's estimates with real-world data (excluding data used for calibration) to evaluate whether pDyn accurately reproduced the epidemic dynamics up to the simulation time. To assess the accuracy of pDyn's predictions, we compared simulation results with real-world data acquired after the simulation date. The findings affirm pDyn's accuracy in forecasting and enhancing our understanding of epidemic mechanisms.

SARS-CoV-2 anti-N antibodies among healthcare personnel without previous known COVID-19

Objective

To measure SARS-CoV-2 anti-nucleocapsid (anti-N) antibody seropositivity among healthcare personnel (HCP) without a history of COVID-19 and to identify HCP characteristics associated with seropositivity.

Design

Prospective cohort study from September 22, 2020, to March 3, 2022.

Setting

A tertiary care academic medical center.

Participants

727 HCP without prior positive SARS-CoV-2 PCR testing were enrolled; 559 HCP successfully completed follow-up.

Methods

At enrollment and follow-up 1-6 months later, HCP underwent SARS-CoV-2 anti-N testing and were surveyed on demographics, employment information, vaccination status, and COVID-19 symptoms and exposures.

Results

Of 727 HCP enrolled, 27 (3.7%) had a positive SARS-CoV-2 anti-N test at enrollment. Seropositive HCPs were more likely to have a household exposure to COVID-19 in the past 30 days (OR 7.92, 95% CI 2.44-25.73), to have had an illness thought to be COVID-19 (4.31, 1.94-9.57), or to work with COVID-19 patients more than half the time (2.09, 0.94-4.77). Among 559 HCP who followed-up, 52 (9.3%) had a positive SARS-CoV-2 anti-N antibody test result. Seropositivity at follow-up was associated with community/household exposures to COVID-19 within the past 30 days (9.50, 5.02-17.96; 2.90, 1.31-6.44), having an illness thought to be COVID-19 (8.24, 4.44-15.29), and working with COVID-19 patients more than half the time (1.50, 0.80-2.78).

Conclusions

Among HCP without prior positive SARS-CoV-2 testing, SARS-CoV-2 anti-N seropositivity was comparable to that of the general population and was associated with COVID-19 symptomatology and both occupational and non-occupational exposures to COVID-19.

Structural and genomic evolutionary dynamics of Omicron variant of SARS-CoV-2 circulating in Madhya Pradesh, India

The SARS-CoV-2 Omicron (B.1.1.529) variant emerged in early November 2021 and its rapid spread created fear worldwide. This was attributed to its increased infectivity and escaping immune mechanisms. The spike protein of Omicron has more mutations (>30) than any other previous variants and was declared as the variant of concern (VOC) by the WHO. The concern among the scientific community was huge about this variant, and a piece of updated information on circulating viral strains is important in order to better understand the epidemiology, virus pathogenicity, transmission, therapeutic interventions, and vaccine development. A total of 710 samples were processed for sequencing and identification up to a resolution of sub-lineage. The sequence analysis revealed Omicron variant with distribution as follows: B.1.1, B.1.1.529, BA.1, BA.2, BA.2.10, BA.2.10.1, BA.2.23, BA.2.37, BA.2.38, BA.2.43, BA.2.74, BA.2.75, BA.2.76, and BA.4 sub-lineages. There is a shift noted in circulating lineage from BA.1 to BA.2 to BA.4 over a period from January to September 2022. Multiple signature mutations were identified in S protein T376A, D405N, and R408S mutations, which were new and common to all BA.2 variants. Additionally, R346T was seen in emerging BA.2.74 and BA.2.76 variants. The emerging BA.4 retained the common T376A, D405N, and R408S mutations of BA.2 along with a new mutation F486V. The samples sequenced were from different districts of Madhya Pradesh and showed a predominance of BA.2 and its variants circulating in this region. The current study identified circulation of BA.1 and BA.1.1 variants during initial phase. The predominant Delta strain of the second wave has been replaced by the Omicron variant in this region over a period of time. This study successfully deciphers the dynamics of the emergence and replacement of various sub-lineages of SARS-CoV-2 in central India on real real-time basis.

Challenges in the case-based surveillance of infectious diseases

To effectively inform infectious disease control strategies, accurate knowledge of the pathogen's transmission dynamics is required. Since the timings of infections are rarely known, estimates of the infection incidence, which is crucial for understanding the transmission dynamics, often rely on measurements of other quantities amenable to surveillance. Case-based surveillance, in which infected individuals are identified by a positive test, is the predominant form of surveillance for many pathogens, and was used extensively during the COVID-19 pandemic. However, there can be many biases present in case-based surveillance indicators due to, for example test sensitivity, changing testing behaviours and the co-circulation of pathogens with similar symptom profiles. Here, we develop a mathematical description of case-based surveillance of infectious diseases. By considering realistic epidemiological parameters and situations, we demonstrate many of the potential biases in common surveillance indicators based on case-based surveillance data. Crucially, we find that many of these common surveillance indicators (e.g. case numbers, test-positive proportion) are heavily biased by circulating pathogens with similar symptom profiles. Future surveillance strategies could be designed to minimize these sources of bias and uncertainty, providing more accurate estimates of a pathogen's transmission dynamics and, ultimately, more targeted application of public health measures.

Dynamic analysis of SARS-CoV-2 evolution based on different countries

Since late 2019, COVID-19 has significantly impacted the world. Understanding the evolution of SARS-CoV-2 is crucial for protecting against future infectious pathogens. In this study, we conducted a comprehensive chronological analysis of SARS-CoV-2 evolution by examining mutation prevalence from the source countries of VOCs: United Kingdom, India, Brazil, South Africa, plus two countries: United States, Russia, utilizing genomic sequences from GISAID. Our methodological approach involved large-scale genomic sequence alignment using MAFFT, Python-based data processing on a high-performance computing platform, and advanced statistical methods the Maximal Information Coefficient (MIC), and also Long Short-Term Memory (LSTM) models for correlation analysis. Our findings elucidate the dynamics of SARS-CoV-2 evolution, highlighting the virus's changing behaviour over various pandemic stages. Key results include the discovery of three temporal mutation patterns-lineage distinct, long-span, and competitive mutations-with varying levels of impact on the virus. Notably, we observed a convergence of advantageous mutations in the spike protein, especially in the later stages of the pandemic, indicating a substantial evolutionary pressure on the virus. One of the most significant revelations is the predominant role of natural immunity over vaccination-induced immunity in driving these evolutionary changes. This emphasizes the critical need for regular vaccine updates to maintain efficacy against evolving strains. In conclusion, our study not only sheds light on the evolutionary trajectory of SARS-CoV-2 but also underscores the urgency for robust, continuous global data collection and sharing. It highlights the necessity for rapid adaptations in medical countermeasures, including vaccine development, to stay ahead of pathogen evolution. This research provides valuable insights for future pandemic preparedness and response strategies.

SARS-CoV-2 genomic surveillance and reliability of PCR single point mutation assay (SNPsig® SARS-CoV-2 EscapePLEX CE) for the rapid detection of variants of concern in Cameroon

Background

Surveillance of SARS-CoV-2 variants of concern (VOCs) and lineages is crucial for decision-making. Our objective was to study the SARS-CoV-2 clade dynamics across epidemiological waves and evaluate the reliability of SNPsig® SARS-CoV-2 EscapePLEX CE in detecting VOCs in Cameroon.

Material and methods

A laboratory-based study was conducted on SARS-CoV-2 positive nasopharyngeal specimens cycle threshold (Ct)≤30 at the Chantal BIYA International Reference Centre in Yaoundé-Cameroon, between April-2020 to August-2022. Samples were analyzed in parallel with Sanger sequencing and (SNPsig® SARS-CoV-2 EscapePLEX CE), and performance characteristics were evaluated by Cohen's coefficient and McNemar test.

Results

Of the 130 sequences generated, SARS-CoV-2 clades during wave-1 (April-November 2020) showed 97 % (30/31) wild-type lineages and 3 % (1/31) Gamma-variant; wave-2 (December-2020 to May-2021), 25 % (4/16) Alpha-variant, 25 % (4/16) Beta-variant, 44 % (7/16) wild-type and 6 % (1/16) mu; wave-3 (June-October 2021), 94 % (27/29) Delta-variant, 3 % (1/29) Alpha-variant, 3 % (1/29) wild-type; wave-4 (November-2021 to August-2022), 98 % (53/54) Omicron-variant and 2 % (1/54) Delta-variant. Omicron sub-variants were BA.1 (47 %), BA.5 (34 %), BA.2 (13 %) and BA.4 (6 %). Globally, the two genotyping methods accurately identified the SARS-CoV-2 VOCs (P = 0.17, McNemar test; Ka = 0.67).

Conclusion

Genomic surveillance reveals a rapid dynamic in SARS-CoV-2 strains between epidemiological waves in Cameroon. For wide-spread variant surveillance in resource-limited settings, SNPsig® SARS-CoV-2 EscapePLEX CEkit represents a suitable tool, pending upgrading for distinguishing Omicron sub-lineages.

Scalable neighbour search and alignment with uvaia

Despite millions of SARS-CoV-2 genomes being sequenced and shared globally, manipulating such data sets is still challenging, especially selecting sequences for focused phylogenetic analysis. We present a novel method, uvaia, which is based on partial and exact sequence similarity for quickly extracting database sequences similar to query sequences of interest. Many SARS-CoV-2 phylogenetic analyses rely on very low numbers of ambiguous sites as a measure of quality since ambiguous sites do not contribute to single nucleotide polymorphism (SNP) differences. Uvaia overcomes this limitation by using measures of sequence similarity which consider partially ambiguous sites, allowing for more ambiguous sequences to be included in the analysis if needed. Such fine-grained definition of similarity allows not only for better phylogenetic analyses, but could also lead to improved classification and biogeographical inferences. Uvaia works natively with compressed files, can use multiple cores and efficiently utilises memory, being able to analyse large data sets on a standard desktop.

Differences between the true reproduction number and the apparent reproduction number of an epidemic time series

The time-varying reproduction number R(t) measures the number of new infections per infectious individual and is closely correlated with the time series of infection incidence by definition. The timings of actual infections are rarely known, and analysis of epidemics usually relies on time series data for other outcomes such as symptom onset. A common implicit assumption, when estimating R(t) from an epidemic time series, is that R(t) has the same relationship with these downstream outcomes as it does with the time series of incidence. However, this assumption is unlikely to be valid given that most epidemic time series are not perfect proxies of incidence. Rather they represent convolutions of incidence with uncertain delay distributions. Here we define the apparent time-varying reproduction number, RA(t), the reproduction number calculated from a downstream epidemic time series and demonstrate how differences between RA(t) and R(t) depend on the convolution function. The mean of the convolution function sets a time offset between the two signals, whilst the variance of the convolution function introduces a relative distortion between them. We present the convolution functions of epidemic time series that were available during the SARS-CoV-2 pandemic. Infection prevalence, measured by random sampling studies, presents fewer biases than other epidemic time series. Here we show that additionally the mean and variance of its convolution function were similar to that obtained from traditional surveillance based on mass-testing and could be reduced using more frequent testing, or by using stricter thresholds for positivity. Infection prevalence studies continue to be a versatile tool for tracking the temporal trends of R(t), and with additional refinements to their study protocol, will be of even greater utility during any future epidemics or pandemics.

Key Challenges for Respiratory Virus Surveillance while Transitioning out of Acute Phase of COVID-19 Pandemic

To support the ongoing management of viral respiratory diseases while transitioning out of the acute phase of the COVID-19 pandemic, many countries are moving toward an integrated model of surveillance for SARS-CoV-2, influenza virus, and other respiratory pathogens. Although many surveillance approaches catalyzed by the COVID-19 pandemic provide novel epidemiologic insight, continuing them as implemented during the pandemic is unlikely to be feasible for nonemergency surveillance, and many have already been scaled back. Furthermore, given anticipated cocirculation of SARS-CoV-2 and influenza virus, surveillance activities in place before the pandemic require review and adjustment to ensure their ongoing value for public health. In this report, we highlight key challenges for the development of integrated models of surveillance. We discuss the relative strengths and limitations of different surveillance practices and studies as well as their contribution to epidemiologic assessment, forecasting, and public health decision-making.

The relative prevalence of the Omicron variant within SARS-CoV-2 infected cohorts in different countries: A systematic review

The Omicron variant of SARS-CoV-2 was detected in October 2021 and exhibited high transmissibility, immune evasion, and reduced severity when compared to the earlier variants. The lesser vaccine effectiveness against Omicron and its reduced severity created vaccination hesitancy among the public. This review compiled data reporting the relative prevalence of Omicron as compared to the early variants to give an insight into the existing variants, which may shape the decisions regarding the targets of the newly developed vaccines. Complied data revealed more than 90% prevalence within the infected cohorts in some countries. The BA.1 subvariant predominated over the BA.2 during the early stages of the Omicron wave. Moreover, BA.4/BA.5 subvariants were detected in South Africa, USA and Italy between October 2021 and April 2022. It is therefore important to develop vaccines that protect against Omicron as well as the early variants, which are known to cause more severe complications.

Unraveling the Dynamics of Omicron (BA.1, BA.2, and BA.5) Waves and Emergence of the Deltacton Variant: Genomic Epidemiology of the SARS-CoV-2 Epidemic in Cyprus (Oct 2021-Oct 2022)

Commencing in December 2019 with the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), three years of the coronavirus disease 2019 (COVID-19) pandemic have transpired. The virus has consistently demonstrated a tendency for evolutionary adaptation, resulting in mutations that impact both immune evasion and transmissibility. This ongoing process has led to successive waves of infections. This study offers a comprehensive assessment spanning genetic, phylogenetic, phylodynamic, and phylogeographic dimensions, focused on the trajectory of the SARS-CoV-2 epidemic in Cyprus. Based on a dataset comprising 4700 viral genomic sequences obtained from affected individuals between October 2021 and October 2022, our analysis is presented. Over this timeframe, a total of 167 distinct lineages and sublineages emerged, including variants such as Delta and Omicron (1, 2, and 5). Notably, during the fifth wave of infections, Omicron subvariants 1 and 2 gained prominence, followed by the ascendancy of Omicron 5 in the subsequent sixth wave. Additionally, during the fifth wave (December 2021-January 2022), a unique set of Delta sequences with genetic mutations associated with Omicron variant 1, dubbed "Deltacron", was identified. The emergence of this phenomenon initially evoked skepticism, characterized by concerns primarily centered around contamination or coinfection as plausible etiological contributors. These hypotheses were predominantly disseminated through unsubstantiated assertions within the realms of social and mass media, lacking concurrent scientific evidence to validate their claims. Nevertheless, the exhaustive molecular analyses presented in this study have demonstrated that such occurrences would likely lead to a frameshift mutation-a genetic aberration conspicuously absent in our provided sequences. This substantiates the accuracy of our initial assertion while refuting contamination or coinfection as potential etiologies. Comparable observations on a global scale dispelled doubt, eventually leading to the recognition of Delta-Omicron variants by the scientific community and their subsequent monitoring by the World Health Organization (WHO). As our investigation delved deeper into the intricate dynamics of the SARS-CoV-2 epidemic in Cyprus, a discernible pattern emerged, highlighting the major role of international connections in shaping the virus's local trajectory. Notably, the United States and the United Kingdom were the central conduits governing the entry and exit of the virus to and from Cyprus. Moreover, notable migratory routes included nations such as Greece, South Korea, France, Germany, Brazil, Spain, Australia, Denmark, Sweden, and Italy. These empirical findings underscore that the spread of SARS-CoV-2 within Cyprus was markedly influenced by the influx of new, highly transmissible variants, triggering successive waves of infection. This investigation elucidates the emergence of new waves of infection subsequent to the advent of highly contagious and transmissible viral variants, notably characterized by an abundance of mutations localized within the spike protein. Notably, this discovery decisively contradicts the hitherto hypothesis of seasonal fluctuations in the virus's epidemiological dynamics. This study emphasizes the importance of meticulously examining molecular genetics alongside virus migration patterns within a specific region. Past experiences also emphasize the substantial evolutionary potential of viruses such as SARS-CoV-2, underscoring the need for sustained vigilance. However, as the pandemic's dynamics continue to evolve, a balanced approach between caution and resilience becomes paramount. This ethos encourages an approach founded on informed prudence and self-preservation, guided by public health authorities, rather than enduring apprehension. Such an approach empowers societies to adapt and progress, fostering a poised confidence rooted in well-founded adaptation.

Enhancing global preparedness during an ongoing pandemic from partial and noisy data

As the coronavirus disease 2019 spread globally, emerging variants such as B.1.1.529 quickly became dominant worldwide. Sustained community transmission favors the proliferation of mutated sub-lineages with pandemic potential, due to cross-national mobility flows, which are responsible for consecutive cases surge worldwide. We show that, in the early stages of an emerging variant, integrating data from national genomic surveillance and global human mobility with large-scale epidemic modeling allows to quantify its pandemic potential, providing quantifiable indicators for pro-active policy interventions. We validate our framework on worldwide spreading variants and gain insights about the pandemic potential of BA.5, BA.2.75, and other sub- and lineages. We combine the different sources of information in a simple estimate of the pandemic delay and show that only in combination, the pandemic potentials of the lineages are correctly assessed relative to each other. Compared to a country-level epidemic intelligence, our scalable integrated approach, that is pandemic intelligence, permits to enhance global preparedness to contrast the pandemic of respiratory pathogens such as SARS-CoV-2.

Dynamics of SARS-CoV-2 infection hospitalisation and infection fatality ratios over 23 months in England

The relationship between prevalence of infection and severe outcomes such as hospitalisation and death changed over the course of the COVID-19 pandemic. Reliable estimates of the infection fatality ratio (IFR) and infection hospitalisation ratio (IHR) along with the time-delay between infection and hospitalisation/death can inform forecasts of the numbers/timing of severe outcomes and allow healthcare services to better prepare for periods of increased demand. The REal-time Assessment of Community Transmission-1 (REACT-1) study estimated swab positivity for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection in England approximately monthly from May 2020 to March 2022. Here, we analyse the changing relationship between prevalence of swab positivity and the IFR and IHR over this period in England, using publicly available data for the daily number of deaths and hospitalisations, REACT-1 swab positivity data, time-delay models, and Bayesian P-spline models. We analyse data for all age groups together, as well as in 2 subgroups: those aged 65 and over and those aged 64 and under. Additionally, we analysed the relationship between swab positivity and daily case numbers to estimate the case ascertainment rate of England's mass testing programme. During 2020, we estimated the IFR to be 0.67% and the IHR to be 2.6%. By late 2021/early 2022, the IFR and IHR had both decreased to 0.097% and 0.76%, respectively. The average case ascertainment rate over the entire duration of the study was estimated to be 36.1%, but there was some significant variation in continuous estimates of the case ascertainment rate. Continuous estimates of the IFR and IHR of the virus were observed to increase during the periods of Alpha and Delta's emergence. During periods of vaccination rollout, and the emergence of the Omicron variant, the IFR and IHR decreased. During 2020, we estimated a time-lag of 19 days between hospitalisation and swab positivity, and 26 days between deaths and swab positivity. By late 2021/early 2022, these time-lags had decreased to 7 days for hospitalisations and 18 days for deaths. Even though many populations have high levels of immunity to SARS-CoV-2 from vaccination and natural infection, waning of immunity and variant emergence will continue to be an upwards pressure on the IHR and IFR. As investments in community surveillance of SARS-CoV-2 infection are scaled back, alternative methods are required to accurately track the ever-changing relationship between infection, hospitalisation, and death and hence provide vital information for healthcare provision and utilisation.

Design and Implementation of a National SARS-CoV-2 Monitoring Program in England: REACT-1 Study

Data System. The REal-time Assessment of Community Transmission-1 (REACT-1) Study was funded by the Department of Health and Social Care in England to provide reliable and timely estimates of prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection over time, by person and place. Data Collection/Processing. The study team (researchers from Imperial College London and its logistics partner Ipsos) wrote to named individuals aged 5 years and older in random cross-sections of the population of England, using the National Health Service list of patients registered with a general practitioner (near-universal coverage) as a sampling frame. We collected data over 2 to 3 weeks approximately every month across 19 rounds of data collection from May 1, 2020, to March 31, 2022. Data Analysis/Dissemination. We have disseminated the data and study materials widely via the study Web site, preprints, publications in peer-reviewed journals, and the media. We make available data tabulations, suitably anonymized to protect participant confidentiality, on request to the study's data access committee. Public Health Implications. The study provided inter alia real-time data on SARS-CoV-2 prevalence over time, by area, and by sociodemographic variables; estimates of vaccine effectiveness; and symptom profiles, and detected emergence of new variants based on viral genome sequencing. (Am J Public Health. 2023;113(5):545-554. https://doi.org/10.2105/AJPH.2023.307230).

Comparative epidemic expansion of SARS-CoV-2 variants Delta and Omicron in the Brazilian State of Amazonas

The SARS-CoV-2 variants of concern (VOCs) Delta and Omicron spread globally during mid and late 2021, respectively. In this study, we compare the dissemination dynamics of these VOCs in the Amazonas state, one of Brazil's most heavily affected regions. We sequenced the virus genome from 4128 patients collected in Amazonas between July 1st, 2021, and January 31st, 2022, and investigated the viral dynamics using a phylodynamic approach. The VOCs Delta and Omicron BA.1 displayed similar patterns of phylogeographic spread but different epidemic dynamics. The replacement of Gamma by Delta was gradual and occurred without an upsurge of COVID-19 cases, while the rise of Omicron BA.1 was extremely fast and fueled a sharp increase in cases. Thus, the dissemination dynamics and population-level impact of new SARS-CoV-2 variants introduced in the Amazonian population after mid-2021, a setting with high levels of acquired immunity, greatly vary according to their viral phenotype.

The third vaccine dose significantly reduces susceptibility to the B.1.1.529 (Omicron) SARS-CoV-2 variant

The main coronavirus disease 2019 (COVID-19) vaccine formulations used today are mainly based on the wild-type severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike glycoprotein as an antigen. However, new virus variants capable of escaping neutralization activity of serum antibodies elicited in vaccinated individuals have emerged. The Omicron (B.1.1.529) variant caused epidemics in regions of the world in which most of the population has been vaccinated. In this study, we aimed to understand what determines individual's susceptibility to Omicron in a scenario of extensive vaccination. For that purpose, we collected nasopharynx swab (n = 286) and blood samples (n = 239) from flu-like symptomatic patients, as well as their vaccination history against COVID-19. We computed the data regarding vaccine history, COVID-19 diagnosis, COVID-19 serology, and viral genome sequencing to evaluate their impact on the number of infections. As main results, we showed that vaccination in general did not reduce the number of individuals infected by Omicron, even with an increased immune response found among vaccinated, noninfected individuals. Nonetheless, we found that individuals who received the third vaccine dose showed significantly reduced susceptibility to Omicron infections. A relevant evidence that support this finding was the higher virus neutralization capacity of serum samples of most patients who received the third vaccine dose. In summary, this study shows that boosting immune responses after a third vaccine dose reduces susceptibility to COVID-19 caused by the Omicron variant. Results presented in this study are useful for future formulations of COVID-19 vaccination policies.

BA.1, BA.2 and BA.2.75 variants show comparable replication kinetics, reduced impact on epithelial barrier and elicit cross-neutralizing antibodies

The Omicron variant of SARS-CoV-2 is capable of infecting unvaccinated, vaccinated and previously-infected individuals due to its ability to evade neutralization by antibodies. With multiple sub-lineages of Omicron emerging in the last 12 months, there is inadequate information on the quantitative antibody response generated upon natural infection with Omicron variant and whether these antibodies offer cross-protection against other sub-lineages of Omicron variant. In this study, we characterized the growth kinetics of Kappa, Delta and Omicron variants of SARS-CoV-2 in Calu-3 cells. Relatively higher amounts infectious virus titers, cytopathic effect and disruption of epithelial barrier functions was observed with Delta variant whereas infection with Omicron sub-lineages led to a more robust induction of interferon pathway, lower level of virus replication and mild effect on epithelial barrier. The replication kinetics of BA.1, BA.2 and BA.2.75 sub-lineages of the Omicron variant were comparable in cell culture and natural infection in a subset of individuals led to a significant increase in binding and neutralizing antibodies to the Delta variant and all the three sub-lineages of Omicron but the level of neutralizing antibodies were lowest against the BA.2.75 variant. Finally, we show that Cu2+, Zn2+ and Fe2+ salts inhibited in vitro RdRp activity but only Cu2+ and Fe2+ inhibited both the Delta and Omicron variants in cell culture. Thus, our results suggest that high levels of interferons induced upon infection with Omicron variant may counter virus replication and spread. Waning neutralizing antibody titers rendered subjects susceptible to infection by Omicron variants and natural Omicron infection elicits neutralizing antibodies that can cross-react with other sub-lineages of Omicron and other variants of concern.

Fractal-fractional age-structure study of omicron SARS-CoV-2 variant transmission dynamics

This paper proposes a new fractal-fractional age-structure model for the omicron SARS-CoV-2 variant under the Caputo-Fabrizio fractional order derivative. Caputo-Fabrizio fractal-fractional order is particularly successful in modelling real-world phenomena due to its repeated memory effect and ability to capture the exponentially decreasing impact of disease transmission dynamics. We consider two age groups, the first of which has a population under 50 and the second of a population beyond 50. Our results show that at a population dynamics level, there is a high infection and recovery of omicron SARS-CoV-2 variant infection among the population under 50 (Group-1), while a high infection rate and low recovery of omicron SARS-CoV-2 variant infection among the population beyond 50 (Group-2) when the fractal-fractional order is varied.

Variant-specific symptoms of COVID-19 in a study of 1,542,510 adults in England

Infection with SARS-CoV-2 virus is associated with a wide range of symptoms. The REal-time Assessment of Community Transmission -1 (REACT-1) study monitored the spread and clinical manifestation of SARS-CoV-2 among random samples of the population in England from 1 May 2020 to 31 March 2022. We show changing symptom profiles associated with the different variants over that period, with lower reporting of loss of sense of smell or taste for Omicron compared to previous variants, and higher reporting of cold-like and influenza-like symptoms, controlling for vaccination status. Contrary to the perception that recent variants have become successively milder, Omicron BA.2 was associated with reporting more symptoms, with greater disruption to daily activities, than BA.1. With restrictions lifted and routine testing limited in many countries, monitoring the changing symptom profiles associated with SARS-CoV-2 infection and effects on daily activities will become increasingly important.