Increased transmissibility and global spread of SARS-CoV-2 variants of concern as at June 2021

A systematic mutation analysis of 13 major SARS-CoV-2 variants

SARS-CoV-2 evolves constantly with various novel mutations. Due to their enhanced infectivity, transmissibility and immune evasion, a comprehensive understanding of the association between these mutations and the respective functional changes is crucial. However, previous mutation studies of major SARS-CoV-2 variants remain limited. Here, we performed systematic analyses of full-length amino acids mutation, phylogenetic features, protein physicochemical properties, molecular dynamics and immune escape as well as pseudotype virus infection assays among thirteen major SARS-CoV-2 variants. We found that Omicron exhibited the most abundant and complex mutation sites, higher indices of hydrophobicity and flexibility than other variants. The results of molecular dynamics simulation suggest that Omicron has the highest number of hydrogen bonds and strongest binding free energy between the S protein and ACE2 receptor. Furthermore, we revealed 10 immune escape sites in 13 major variants, some of them were reported previously, but four of which (i.e. 339/373/477/496) are first reported to be specific to Omicron, whereas 462 is specific to Epslion. The infectivity of these variants was confirmed by the pseudotype virus infection assays. Our findings may help us understand the functional consequences of the mutations within various variants and the underlying mechanisms of the immune escapes conferred by the S proteins.

Spatiotemporal transmission of SARS-CoV-2 lineages during 2020-2021 in Pernambuco-Brazil

SARS-CoV-2 virus emerged as a new threat to humans and spread around the world, leaving a large death toll. As of January 2023, Brazil is among the countries with the highest number of registered deaths. Nonpharmacological and pharmacological interventions have been heterogeneously implemented in the country, which, associated with large socioeconomic differences between the country regions, has led to distinct virus spread dynamics. Here, we investigate the spatiotemporal dispersion of SARS-CoV-2 lineages in the Pernambuco state (Northeast Brazil) throughout the distinct epidemiological scenarios that unfolded in the first 2 years of the pandemic. We generated a total of 1,389 new SARS-CoV-2 genomes from June 2020 to August 2021. This sampling captured the arrival, communitary transmission, and the circulation of the B1.1, B.1.1.28, and B.1.1.33 lineages; the emergence of the former variant of interest P.2; and the emergence and fast replacement of all previous variants by the more transmissible variant of concern P.1 (Gamma). Based on the incidence and lineage spread pattern, we observed an East-to-West to inner state pattern of transmission, which is in agreement with the transmission of more populous metropolitan areas to medium- and small-size country-side cities in the state. Such transmission patterns may be partially explained by the main routes of traffic across municipalities in the state. Our results highlight that the fine-grained intrastate analysis of lineages and incidence spread can provide actionable insights for planning future nonpharmacological intervention for air-borne transmissible human pathogens.IMPORTANCEDuring the COVID-19 pandemic, Brazil was one of the most affected countries, mainly due its continental-size, socioeconomic differences among regions, and heterogeneous implementation of intervention methods. In order to investigate SARS-CoV-2 dynamics in the state of Pernambuco, we conducted a spatiotemporal dispersion study, covering the period from June 2020 to August 2021, to comprehend the dynamics of viral transmission during the first 2 years of the pandemic. Throughout this study, we were able to track three significant epidemiological waves of transmission caused by B1.1, B.1.1.28, B.1.1.33, P.2, and P.1 lineages. These analyses provided valuable insights into the evolution of the epidemiological landscape, contributing to a deeper understanding of the dynamics of virus transmission during the early years of the pandemic in the state of Pernambuco.

SARS-CoV-2 Seroprevalence Trends in the Netherlands in the Variant of Concern Era: Input for Future Response

BACKGROUND

To inform future response planning we aimed to assess SARS-CoV-2 trends in infection- and/or vaccine-induced immunity, including breakthrough infections, among (sub)groups, professions and regions in the Dutch population during the Variant of Concern (VOC)-era.

METHODS

In this prospective population-based cohort, randomly selected participants (n = 9985) aged 1-92 years (recruited early-2020) donated home-collected fingerstick-blood samples at six timepoints in 2021/2022, covering waves dominated by Alpha, Delta, and multiple Omicron (sub-)variants. IgG antibody assessment against Spike-S1 and Nucleoprotein was combined with vaccination- and testing data to estimate infection-induced (inf) and total (infection- and vaccination-induced) seroprevalence.

RESULTS

Nationwide inf-seroprevalence rose modestly from 12% (95% CI 11-13) since Alpha to 26% (95% CI 24-28) amidst Delta, while total seroprevalence increased rapidly to 87% (95% CI 85-88), particularly in elderly and those with comorbidities (i.e., vulnerable groups). Interestingly, highest infection rates were noticeable among low/middle educated elderly, non-Western, those in contact professions, adolescents and young adults, and in low-vaccination coverage regions. Following Omicron emergence, inf-seroprevalence elevated sharply to 62% (95% CI 59-65) and further to 86% (95% CI 83-90) in late-2022, with frequent breakthrough infections and decreasing seroprevalence dissimilarities between most groups. Whereas > 90% of < 60-year-olds had been infected at least once, 30% of vaccinated vulnerable individuals had still not acquired hybrid immunity.

CONCLUSIONS

Groups identified to have been infected disproportionally during the acute phase of the pandemic require specific attention in evaluation of control measures and future response planning worldwide. Furthermore, ongoing tailored vaccination efforts and (sero-)monitoring of vulnerable groups may remain important.

Fitness models provide accurate short-term forecasts of SARS-CoV-2 variant frequency

Genomic surveillance of pathogen evolution is essential for public health response, treatment strategies, and vaccine development. In the context of SARS-COV-2, multiple models have been developed including Multinomial Logistic Regression (MLR) describing variant frequency growth as well as Fixed Growth Advantage (FGA), Growth Advantage Random Walk (GARW) and Piantham parameterizations describing variant R t . These models provide estimates of variant fitness and can be used to forecast changes in variant frequency. We introduce a framework for evaluating real-time forecasts of variant frequencies, and apply this framework to the evolution of SARS-CoV-2 during 2022 in which multiple new viral variants emerged and rapidly spread through the population. We compare models across representative countries with different intensities of genomic surveillance. Retrospective assessment of model accuracy highlights that most models of variant frequency perform well and are able to produce reasonable forecasts. We find that the simple MLR model provides ~0.6% median absolute error and ~6% mean absolute error when forecasting 30 days out for countries with robust genomic surveillance. We investigate impacts of sequence quantity and quality across countries on forecast accuracy and conduct systematic downsampling to identify that 1000 sequences per week is fully sufficient for accurate short-term forecasts. We conclude that fitness models represent a useful prognostic tool for short-term evolutionary forecasting.

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

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

Cost-effectiveness of mask mandates on subways to prevent SARS-CoV-2 transmission in the United States

BACKGROUND

Community-based mask wearing has been shown to reduce the transmission of SARS-CoV-2. However, few studies have conducted an economic evaluation of mask mandates, specifically in public transportation settings. This study evaluated the cost-effectiveness of implementing mask mandates for subway passengers in the United States by evaluating its potential to reduce COVID-19 transmission during subway travel.

MATERIALS AND METHODS

We assessed the health impacts and costs of subway mask mandates compared to mask recommendations based on the number of infections that would occur during subway travel in the U.S. Using a combined box and Wells-Riley infection model, we estimated monthly infections, hospitalizations, and deaths averted under a mask mandate scenario as compared to a mask recommendation scenario. The analysis included costs of implementing mask mandates and COVID-19 treatment from a limited societal perspective. The cost-effectiveness (net cost per averted death) of mandates was estimated for three different periods based on dominant SARS-CoV-2 variants: Alpha, Beta, and Gamma (November 2020 to February 2021); Delta (July to October 2021); and early Omicron (January to March 2022).

RESULTS

Compared with mask recommendations only, mask mandates were cost-effective across all periods, with costs per averted death less than a threshold of $11.4 million (ranging from cost-saving to $3 million per averted death). Additionally, mask mandates were more cost-effective during the early Omicron period than the other two periods and were cost saving in January 2022. Our findings showed that mandates remained cost-effective when accounting for uncertainties in input parameters (e.g., even if mandates only resulted in small increases in mask usage by subway ridership).

CONCLUSIONS

The findings highlight the economic value of mask mandates on subways, particularly during high virus transmissibility periods, during the COVID-19 pandemic. This study may inform stakeholders on mask mandate decisions during future outbreaks of novel viral respiratory diseases.

Mathematical modeling of SARS-CoV-2 variant substitutions in European countries: transmission dynamics and epidemiological insights

Background

Countries across Europe have faced similar evolutions of SARS-CoV-2 variants of concern, including the Alpha, Delta, and Omicron variants.

Materials and methods

We used data from GISAID and applied a robust, automated mathematical substitution model to study the dynamics of COVID-19 variants in Europe over a period of more than 2 years, from late 2020 to early 2023. This model identifies variant substitution patterns and distinguishes between residual and dominant behavior. We used weekly sequencing data from 19 European countries to estimate the increase in transmissibility  ( Δ β )   between consecutive SARS-CoV-2 variants. In addition, we focused on large countries with separate regional outbreaks and complex scenarios of multiple competing variants.

Results

Our model accurately reproduced the observed substitution patterns between the Alpha, Delta, and Omicron major variants. We estimated the daily variant prevalence and calculated Δ β between variants, revealing that: ( i ) Δ β increased progressively from the Alpha to the Omicron variant; ( i i ) Δ β showed a high degree of variability within Omicron variants; ( i i i ) a higher Δ β was associated with a later emergence of the variant within a country; ( i v ) a higher degree of immunization of the population against previous variants was associated with a higher Δ β for the Delta variant; ( v ) larger countries exhibited smaller Δ β ,  suggesting regionally diverse outbreaks within the same country; and finally ( v i ) the model reliably captures the dynamics of competing variants, even in complex scenarios.

Conclusion

The use of mathematical models allows for precise and reliable estimation of daily cases of each variant. By quantifying Δ β ,  we have tracked the spread of the different variants across Europe, highlighting a robust increase in transmissibility trend from Alpha to Omicron. Additionally, we have shown that the geographical characteristics of a country, as well as the timing of new variant entrances, can explain some of the observed differences in variant substitution dynamics across countries.

Social contacts in Switzerland during the COVID-19 pandemic: Insights from the CoMix study

To mitigate the spread of SARS-CoV-2, the Swiss government enacted restrictions on social contacts from 2020 to 2022. In addition, individuals changed their social contact behavior to limit the risk of COVID-19. In this study, we aimed to investigate the changes in social contact patterns of the Swiss population. As part of the CoMix study, we conducted a survey consisting of 24 survey waves from January 2021 to May 2022. We collected data on social contacts and constructed contact matrices for the age groups 0-4, 5-14, 15-29, 30-64, and 65 years and older. We estimated the change in contact numbers during the COVID-19 pandemic to a synthetic pre-pandemic contact matrix. We also investigated the association of the largest eigenvalue of the social contact and transmission matrices with the stringency of pandemic measures, the effective reproduction number (Re), and vaccination uptake. During the pandemic period, 7084 responders reported an average number of 4.5 contacts (95% confidence interval, CI: 4.5-4.6) per day overall, which varied by age and survey wave. Children aged 5-14 years had the highest number of contacts with 8.5 (95% CI: 8.1-8.9) contacts on average per day and participants that were 65 years and older reported the fewest (3.4, 95% CI: 3.2-3.5) per day. Compared with the pre-pandemic baseline, we found that the 15-29 and 30-64 year olds had the largest reduction in contacts. We did not find statistically significant associations between the largest eigenvalue of the social contact and transmission matrices and the stringency of measures, Re, or vaccination uptake. The number of social contacts in Switzerland fell during the COVID-19 pandemic and remained below pre-pandemic levels after contact restrictions were lifted. The collected social contact data will be critical in informing modeling studies on the transmission of respiratory infections in Switzerland and to guide pandemic preparedness efforts.

Comparative Analysis of Vaccine-Induced Neutralizing Antibodies against the Alpha, Beta, Delta, and Omicron Variants of SARS-CoV-2

The SARS-CoV-2 virus has infected more than 660 million people and caused nearly seven million deaths worldwide. During the pandemic, a number of SARS-CoV-2 vaccines were rapidly developed, and several are currently licensed for use in Europe. However, the optimization of vaccination regimens is still ongoing, particularly with regard to booster vaccinations. At the same time, the emergence of new virus variants poses an ongoing challenge to vaccine efficacy. In this study, we focused on a comparative analysis of the neutralization capacity of vaccine-induced antibodies against four different variants of concern (i.e., Alpha, Beta, Delta, and Omicron) after two and three doses of COVID-19 vaccine. We were able to show that both two (prime/boost) and three (prime/boost/boost) vaccinations elicit highly variable levels of neutralizing antibodies. In addition, we did not observe a significant difference in antibody levels after two and three vaccinations. We also observed a significant decrease in the neutralization susceptibility of all but one SARS-CoV-2 variants to vaccine-induced antibodies. In contrast, a SARS-CoV-2 breakthrough infection between the second and third vaccination results in overall higher levels of neutralizing antibodies with a concomitant improved neutralization of all virus variants. Titer levels remained highly variable across the cohort but a common trend was observed. This may be due to the fact that at the time of this study, all licensed vaccines were still based exclusively on wild-type SARS-CoV-2, whereas infections were caused by virus variants. Overall, our data demonstrate the importance of (booster) vaccinations, but at the same time emphasize the need for the continued adaptation of vaccines to induce a protective immune response against virus variants in order to be prepared for future (seasonal) SARS-CoV-2 outbreaks.

Using a population-based Kalman estimator to model the COVID-19 epidemic in France: estimating associations between disease transmission and non-pharmaceutical interventions

In response to the COVID-19 pandemic caused by SARS-CoV-2, governments have adopted a wide range of non-pharmaceutical interventions (NPI). These include stringent measures such as strict lockdowns, closing schools, bars and restaurants, curfews, and barrier gestures such as mask-wearing and social distancing. Deciphering the effectiveness of each NPI is critical to responding to future waves and outbreaks. To this end, we first develop a dynamic model of the French COVID-19 epidemics over a one-year period. We rely on a global extended Susceptible-Infectious-Recovered (SIR) mechanistic model of infection that includes a dynamic transmission rate over time. Multilevel data across French regions are integrated using random effects on the parameters of the mechanistic model, boosting statistical power by multiplying integrated observation series. We estimate the parameters using a new population-based statistical approach based on a Kalman filter, used for the first time in analysing real-world data. We then fit the estimated time-varying transmission rate using a regression model that depends on the NPIs while accounting for vaccination coverage, the occurrence of variants of concern (VoC), and seasonal weather conditions. We show that all NPIs considered have an independent significant association with transmission rates. In addition, we show a strong association between weather conditions that reduces transmission in summer, and we also estimate increased transmissibility of VoC.

SARS-CoV-2 Test-to-Stay in Daycare

BACKGROUND AND OBJECTIVES

Test-to-stay concepts apply serial testing of children in daycare after exposure to SARS-CoV-2 without use of quarantine. This study aims to assess the safety of a test-to-stay screening in daycare facilities.

METHODS

714 daycare facilities and approximately 50 000 children ≤6 years in Cologne, Germany participated in a SARS-CoV-2 Pool-polymerase chain reaction (PCR) screening from March 2021 to April 2022. The screening initially comprised post-exposure quarantine and was adapted to a test-to-stay approach during its course. To assess safety of the test-to-stay approach, we explored potential changes in frequencies of infections among children after the adaptation to the test-to-stay approach by applying regression discontinuity in time (RDiT) analyses. To this end, PCR-test data were linked with routinely collected data on reported infections in children and analyzed using ordinary least squares regressions.

RESULTS

219 885 Pool-PCRs and 352 305 Single-PCRs were performed. 6440 (2.93%) Pool-PCRs tested positive, and 17 208 infections in children were reported. We estimated that during a period of 30 weeks, the test-to-stay concept avoided between 7 and 20 days of quarantine per eligible daycare child. RDiT revealed a 26% reduction (Exp. Coef: 0.74, confidence interval 0.52-1.06) in infection frequency among children and indicated no significant increase attributable to the test-to-stay approach. This result was not sensitive to adjustments for 7-day incidence, season, SARS-CoV-2 variant, and socioeconomic status.

CONCLUSIONS

Our analyses provide evidence that suggest safety of the test-to-stay approach compared with quarantine measures. This approach offers a promising option to avoid use of quarantine after exposure to respiratory pathogens in daycare settings.

From Detection to Protection: Antibodies and Their Crucial Role in Diagnosing and Combatting SARS-CoV-2

Understanding the antibody response to SARS-CoV-2, the virus responsible for COVID-19, is crucial to comprehending disease progression and the significance of vaccine and therapeutic development. The emergence of highly contagious variants poses a significant challenge to humoral immunity, underscoring the necessity of grasping the intricacies of specific antibodies. This review emphasizes the pivotal role of antibodies in shaping immune responses and their implications for diagnosing, preventing, and treating SARS-CoV-2 infection. It delves into the kinetics and characteristics of the antibody response to SARS-CoV-2 and explores current antibody-based diagnostics, discussing their strengths, clinical utility, and limitations. Furthermore, we underscore the therapeutic potential of SARS-CoV-2-specific antibodies, discussing various antibody-based therapies such as monoclonal antibodies, polyclonal antibodies, anti-cytokines, convalescent plasma, and hyperimmunoglobulin-based therapies. Moreover, we offer insights into antibody responses to SARS-CoV-2 vaccines, emphasizing the significance of neutralizing antibodies in order to confer immunity to SARS-CoV-2, along with emerging variants of concern (VOCs) and circulating Omicron subvariants. We also highlight challenges in the field, such as the risks of antibody-dependent enhancement (ADE) for SARS-CoV-2 antibodies, and shed light on the challenges associated with the original antigenic sin (OAS) effect and long COVID. Overall, this review intends to provide valuable insights, which are crucial to advancing sensitive diagnostic tools, identifying efficient antibody-based therapeutics, and developing effective vaccines to combat the evolving threat of SARS-CoV-2 variants on a global scale.

Computational analysis of affinity dynamics between the variants of SARS-CoV-2 spike protein (RBD) and human ACE-2 receptor

The novel coronavirus SARS-CoV-2 resulted in a significant worldwide health emergency known as the COVID-19 pandemic. This crisis has been marked by the widespread of various variants, with certain ones causing notable apprehension. In this study, we harnessed computational techniques to scrutinize these Variants of Concern (VOCs), including various Omicron subvariants. Our approach involved the use of protein structure prediction algorithms and molecular docking techniques, we have investigated the effects of mutations within the Receptor Binding Domain (RBD) of SARS-CoV-2 and how these mutations influence its interactions with the human angiotensin-converting enzyme 2 (hACE-2) receptor. Further we have predicted the structural alterations in the RBD of naturally occurring SARS-CoV-2 variants using the tr-Rosetta algorithm. Subsequent docking and binding analysis employing HADDOCK and PRODIGY illuminated crucial interactions occurring at the Receptor-Binding Motif (RBM). Our findings revealed a hierarchy of increased binding affinity between the human ACE2 receptor and the various RBDs, in the order of wild type (Wuhan-strain) < Beta < Alpha < Gamma < Omicron-B.1.1.529 < Delta < Omicron-BA.2.12.1 < Omicron-BA.5.2.1 < Omicron-BA.1.1. Notably, Omicron-BA.1.1 demonstrated the highest binding affinity of -17.4 kcal mol-1 to the hACE2 receptor when compared to all the mutant complexes. Additionally, our examination indicated that mutations occurring in active residues of the Receptor Binding Domain (RBD) consistently improved the binding affinity and intermolecular interactions in all mutant complexes. Analysis of the differences among variants has laid a foundation for the structure-based drug design targeting the RBD region of SARS-CoV-2.

Longitudinal dynamics of the nasopharyngal microbiome in response to SARS-CoV-2 Omicron variant and HIV infection in Kenyan women and their infants

The nasopharynx and its microbiota are implicated in respiratory health and disease. The interplay between viral infection and the nasopharyngeal microbiome is an area of increased interest and of clinical relevance. The impact of SARS-CoV-2, the etiological agent of the Coronavirus Disease 2019 (COVID-19) pandemic, on the nasopharyngeal microbiome, particularly among individuals living with HIV, is not fully characterized. Here we describe the nasopharyngeal microbiome before, during and after SARS-CoV-2 infection in a longitudinal cohort of Kenyan women (21 living with HIV and 14 HIV-uninfected) and their infants (18 HIV-exposed, uninfected and 18 HIV-unexposed, uninfected), followed between September 2021 through March 2022. We show using genomic epidemiology that mother and infant dyads were infected with the same strain of the SARS-CoV-2 Omicron variant that spread rapidly across Kenya. Additionally, we used metagenomic sequencing to characterize the nasopharyngeal microbiome of 20 women and infants infected with SARS-CoV-2, 6 infants negative for SARS-CoV-2 but experiencing respiratory symptoms, and 34 timepoint matched SARS-CoV-2 negative mothers and infants. Since individuals were sampled longitudinally before and after SARS-CoV-2 infection, we could characterize the short- and long-term impact of SARS-CoV-2 infection on the nasopharyngeal microbiome. We found that mothers and infants had significantly different microbiome composition and bacterial load (p-values <.0001). However, in both mothers and infants, the nasopharyngeal microbiome did not differ before and after SARS-CoV-2 infection, regardless of HIV-exposure status. Our results indicate that the nasopharyngeal microbiome is resilient to SARS-CoV-2 infection and was not significantly modified by HIV.

Clinical features of patients with rheumatic and musculoskeletal diseases during the coronavirus disease 2019 pandemic and the association of its relapse with infection: Across-sectional study

AIM

The aim of this study was to investigate the clinical features of patients with rheumatic and musculoskeletal diseases (RMDs) infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the relationship between RMDs relapse and SARS-CoV-2 infection.

METHODS

We carried out a cross-sectional observational study among 585 patients with RMDs and 619 individuals without RMDs. Data on demographics, the clinical features of coronavirus disease 2019 (COVID-19), antirheumatic therapy, and RMD relapse were collected. Differences between RMDs and control groups, infected and uninfected groups, relapse and non-relapse RMDs groups were examined. The influence of COVID-19 infection on medications and relapse of RMDs was also assessed.

RESULTS

Among 1204 participants finally recruited for analysis, 1030 (85.5%) were infected with COVID-19. Seven hundred and ninety-five (77.2%) of infected individuals were female, and the median age was 40 years (IQR 33, 50). Patients in the RMD group had a relatively lower risk of COVID-19 symptoms whereas were significantly more likely to require hospitalization (6.7% vs. 2.2%). In the RMDs group, younger patients who were under the age of 65 were more likely to report more symptoms. More patients with RMD relapse (27, 34.6%) adjusted their medications during the period of COVID-19 infection than those without relapse (59, 13.2%).

CONCLUSION

Patients with RMDs were at lower risk of symptoms of COVID-19. Rheumatic and musculoskeletal disease patients experience a higher risk of relapse especially when they adjust medications during COVID-19 infection. The long-term prognosis of infected RMDs patients need further investigation.

Lineage frequency time series reveal elevated levels of genetic drift in SARS-CoV-2 transmission in England

Genetic drift in infectious disease transmission results from randomness of transmission and host recovery or death. The strength of genetic drift for SARS-CoV-2 transmission is expected to be high due to high levels of superspreading, and this is expected to substantially impact disease epidemiology and evolution. However, we don't yet have an understanding of how genetic drift changes over time or across locations. Furthermore, noise that results from data collection can potentially confound estimates of genetic drift. To address this challenge, we develop and validate a method to jointly infer genetic drift and measurement noise from time-series lineage frequency data. Our method is highly scalable to increasingly large genomic datasets, which overcomes a limitation in commonly used phylogenetic methods. We apply this method to over 490,000 SARS-CoV-2 genomic sequences from England collected between March 2020 and December 2021 by the COVID-19 Genomics UK (COG-UK) consortium and separately infer the strength of genetic drift for pre-B.1.177, B.1.177, Alpha, and Delta. We find that even after correcting for measurement noise, the strength of genetic drift is consistently, throughout time, higher than that expected from the observed number of COVID-19 positive individuals in England by 1 to 3 orders of magnitude, which cannot be explained by literature values of superspreading. Our estimates of genetic drift suggest low and time-varying establishment probabilities for new mutations, inform the parametrization of SARS-CoV-2 evolutionary models, and motivate future studies of the potential mechanisms for increased stochasticity in this system.

Wastewater-based surveillance as a tool for public health action: SARS-CoV-2 and beyond

Wastewater-based surveillance (WBS) has undergone dramatic advancement in the context of the coronavirus disease 2019 (COVID-19) pandemic. The power and potential of this platform technology were rapidly realized when it became evident that not only did WBS-measured SARS-CoV-2 RNA correlate strongly with COVID-19 clinical disease within monitored populations but also, in fact, it functioned as a leading indicator. Teams from across the globe rapidly innovated novel approaches by which wastewater could be collected from diverse sewersheds ranging from wastewater treatment plants (enabling community-level surveillance) to more granular locations including individual neighborhoods and high-risk buildings such as long-term care facilities (LTCF). Efficient processes enabled SARS-CoV-2 RNA extraction and concentration from the highly dilute wastewater matrix. Molecular and genomic tools to identify, quantify, and characterize SARS-CoV-2 and its various variants were adapted from clinical programs and applied to these mixed environmental systems. Novel data-sharing tools allowed this information to be mobilized and made immediately available to public health and government decision-makers and even the public, enabling evidence-informed decision-making based on local disease dynamics. WBS has since been recognized as a tool of transformative potential, providing near-real-time cost-effective, objective, comprehensive, and inclusive data on the changing prevalence of measured analytes across space and time in populations. However, as a consequence of rapid innovation from hundreds of teams simultaneously, tremendous heterogeneity currently exists in the SARS-CoV-2 WBS literature. This manuscript provides a state-of-the-art review of WBS as established with SARS-CoV-2 and details the current work underway expanding its scope to other infectious disease targets.

Impact of vaccination on the association of COVID-19 with cardiovascular diseases: An OpenSAFELY cohort study

Infection with SARS-CoV-2 is associated with an increased risk of arterial and venous thrombotic events, but the implications of vaccination for this increased risk are uncertain. With the approval of NHS England, we quantified associations between COVID-19 diagnosis and cardiovascular diseases in different vaccination and variant eras using linked electronic health records for ~40% of the English population. We defined a 'pre-vaccination' cohort (18,210,937 people) in the wild-type/Alpha variant eras (January 2020-June 2021), and 'vaccinated' and 'unvaccinated' cohorts (13,572,399 and 3,161,485 people respectively) in the Delta variant era (June-December 2021). We showed that the incidence of each arterial thrombotic, venous thrombotic and other cardiovascular outcomes was substantially elevated during weeks 1-4 after COVID-19, compared with before or without COVID-19, but less markedly elevated in time periods beyond week 4. Hazard ratios were higher after hospitalised than non-hospitalised COVID-19 and higher in the pre-vaccination and unvaccinated cohorts than the vaccinated cohort. COVID-19 vaccination reduces the risk of cardiovascular events after COVID-19 infection. People who had COVID-19 before or without being vaccinated are at higher risk of cardiovascular events for at least two years.

Difference in mortality risk predicted by leukocyte and lymphocyte levels in COVID-19 patients infected with the Wild-type, Delta, and Omicron strains

This study aimed to investigate the changing trends, level differences, and prognostic performance of the leukocyte and lymphocyte levels of patients infected with the Wild strains, Delta strains and Omicron strains to provide a reference for prognostic assessment. In the current study, we conducted a retrospective cross-sectional study to evaluate the changing trends, level differences, and prognostic performance of leukocyte and lymphocyte of different strains at admission and discharge may already exist in patients with coronavirus disease-2019 (COVID-19) infected with the Wild type, Delta, and Omicron strains. A retrospective cross-sectional study was conducted. We recruited and screened the 243 cases infected with the Wild-type strains in Wuhan, the 629 cases infected with the Delta and 116 cases infected strains with the Omicron strains in Xi'an. The leukocyte and lymphocyte levels were compared the cohort of Wild-type infection with the cohort of Delta and the Omicron. The changes in the levels of leukocytes and lymphocytes exhibit a completely opposite trend in patients with COVID-19 infected with the different strains. The lymphocyte level at admission and discharge in patients with COVID-19 infected with Omicron strains (area under curve [AUC] receiver operating characteristic curve [ROC] 72.8-90.2%, 82.8-97.2%) presented better performance compared patients with COVID-19 infected with Wild type strains (AUC ROC 60.9-80.7%, 82.3-97.2%) and Delta strains (AUC ROC 56.1-84.7%, 40.3-93.3%). Kaplan-Meier curves showed that the leukocyte levels above newly established cutoff values and the lymphocyte levels below newly established cutoff values had a significantly higher risk of in-hospital mortality in COVID-19 patients with Wild-type and Omicron strains (P < .01). The levels of leukocyte and lymphocyte at admission and discharge in patients with COVID-19 infected with the Wild type, Delta, and Omicron strains may be differences among strains, which indicates different death risks. Our research may help clinicians identify patients with a poor prognosis for severe acute respiratory syndrome coronavirus 2 infection.

Evaluating the performance of Plasmodium falciparum genetic metrics for inferring National Malaria Control Programme reported incidence in Senegal

BACKGROUND

Genetic surveillance of the Plasmodium falciparum parasite shows great promise for helping National Malaria Control Programmes (NMCPs) assess parasite transmission. Genetic metrics such as the frequency of polygenomic (multiple strain) infections, genetic clones, and the complexity of infection (COI, number of strains per infection) are correlated with transmission intensity. However, despite these correlations, it is unclear whether genetic metrics alone are sufficient to estimate clinical incidence.

METHODS

This study examined parasites from 3147 clinical infections sampled between the years 2012-2020 through passive case detection (PCD) across 16 clinic sites spread throughout Senegal. Samples were genotyped with a 24 single nucleotide polymorphism (SNP) molecular barcode that detects parasite strains, distinguishes polygenomic (multiple strain) from monogenomic (single strain) infections, and identifies clonal infections. To determine whether genetic signals can predict incidence, a series of Poisson generalized linear mixed-effects models were constructed to predict the incidence level at each clinical site from a set of genetic metrics designed to measure parasite clonality, superinfection, and co-transmission rates.

RESULTS

Model-predicted incidence was compared with the reported standard incidence data determined by the NMCP for each clinic and found that parasite genetic metrics generally correlated with reported incidence, with departures from expected values at very low annual incidence (< 10/1000/annual [‰]).

CONCLUSIONS

When transmission is greater than 10 cases per 1000 annual parasite incidence (annual incidence > 10‰), parasite genetics can be used to accurately infer incidence and is consistent with superinfection-based hypotheses of malaria transmission. When transmission was < 10‰, many of the correlations between parasite genetics and incidence were reversed, which may reflect the disproportionate impact of importation and focal transmission on parasite genetics when local transmission levels are low.

Dispersion patterns of SARS-CoV-2 variants Gamma, Lambda and Mu in Latin America and the Caribbean

Latin America and Caribbean (LAC) regions were an important epicenter of the COVID-19 pandemic and SARS-CoV-2 evolution. Through the COVID-19 Genomic Surveillance Regional Network (COVIGEN), LAC countries produced an important number of genomic sequencing data that made possible an enhanced SARS-CoV-2 genomic surveillance capacity in the Americas, paving the way for characterization of emerging variants and helping to guide the public health response. In this study we analyzed approximately 300,000 SARS-CoV-2 sequences generated between February 2020 and March 2022 by multiple genomic surveillance efforts in LAC and reconstructed the diffusion patterns of the main variants of concern (VOCs) and of interest (VOIs) possibly originated in the Region. Our phylogenetic analysis revealed that the spread of variants Gamma, Lambda and Mu reflects human mobility patterns due to variations of international air passenger transportation and gradual lifting of social distance measures previously implemented in countries. Our results highlight the potential of genetic data to reconstruct viral spread and unveil preferential routes of viral migrations that are shaped by human mobility patterns.

Impacts of Vaccination and Severe Acute Respiratory Syndrome Coronavirus 2 Variants Alpha and Delta on Coronavirus Disease 2019 Transmission Dynamics in Four Metropolitan Areas of the United States

To characterize Coronavirus Disease 2019 (COVID-19) transmission dynamics in each of the metropolitan statistical areas (MSAs) surrounding Dallas, Houston, New York City, and Phoenix in 2020 and 2021, we extended a previously reported compartmental model accounting for effects of multiple distinct periods of non-pharmaceutical interventions by adding consideration of vaccination and Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) variants Alpha (lineage B.1.1.7) and Delta (lineage B.1.617.2). For each MSA, we found region-specific parameterizations of the model using daily reports of new COVID-19 cases available from January 21, 2020 to October 31, 2021. In the process, we obtained estimates of the relative infectiousness of Alpha and Delta as well as their takeoff times in each MSA (the times at which sustained transmission began). The estimated infectiousness of Alpha ranged from 1.1x to 1.4x that of viral strains circulating in 2020 and early 2021. The estimated relative infectiousness of Delta was higher in all cases, ranging from 1.6x  to 2.1x. The estimated Alpha takeoff times ranged from February 1 to February 28, 2021. The estimated Delta takeoff times ranged from June 2 to June 26, 2021. Estimated takeoff times are consistent with genomic surveillance data.

Online public concern about allergic rhinitis and its association with COVID-19 and air quality in China: an informative epidemiological study using Baidu index

BACKGROUND

Allergic rhinitis is a common health concern that affects quality of life. This study aims to examine the online search trends of allergic rhinitis in China before and after the COVID-19 epidemic and to explore the association between the daily air quality and online search volumes of allergic rhinitis in Beijing.

METHODS

We extracted the online search data of allergic rhinitis-related keywords from the Baidu index database from January 23, 2017 to June 23, 2022. We analyzed and compared the temporal distribution of online search behaviors across different themes of allergic rhinitis before and after the COVID-19 pandemic in mainland China, using the Baidu search index (BSI). We also obtained the air quality index (AQI) data in Beijing and assessed its correlation with daily BSIs of allergic rhinitis.

RESULTS

The online search for allergic rhinitis in China showed significant seasonal variations, with two peaks each year in spring from March to May and autumn from August and October. The BSI of total allergic rhinitis-related searches increased gradually from 2017 to 2019, reaching a peak in April 2019, and declined after the COVID-19 pandemic, especially in the first half of 2020. The BSI for all allergic rhinitis themes was significantly lower after the COVID-19 pandemic than before (all p values < 0.05). The results also revealed that, in Beijing, there was a significant negative association between daily BSI and AQI for each allergic rhinitis theme during the original variant strain epidemic period and a significant positive correlation during the Omicron variant period.

CONCLUSION

Both air quality and the interventions used for COVID-19 pandemic, including national and local quarantines and mask wearing behaviors, may have affected the incidence and public concern about allergic rhinitis in China. The online search trends can serve as a valuable tool for tracking real-time public concerns about allergic rhinitis. By complementing traditional disease monitoring systems of health departments, these search trends can also offer insights into the patterns of disease outbreaks. Additionally, they can provide references and suggestions regarding the public's knowledge demands related to allergic rhinitis, which can further be instrumental in developing targeted strategies to enhance population-based disease education on allergic diseases.

To be remembered: B cell memory response against SARS-CoV-2 and its variants in vaccinated and unvaccinated individuals

COVID-19 disease has plagued the world economy and affected the overall well-being and life of most of the people. Natural infection as well as vaccination leads to the development of an immune response against the pathogen. This involves the production of antibodies, which can neutralize the virus during future challenges. In addition, the development of cellular immune memory with memory B and T cells provides long-lasting protection. The longevity of the immune response has been a subject of intensive research in this field. The extent of immunity conferred by different forms of vaccination or natural infections remained debatable for long. Hence, understanding the effectiveness of these responses among different groups of people can assist government organizations in making informed policy decisions. In this article, based on the publicly available data, we have reviewed the memory response generated by some of the vaccines against SARS-CoV-2 and its variants, particularly B cell memory in different groups of individuals.

Model uncertainty, the COVID-19 pandemic, and the science-policy interface

The COVID-19 pandemic illustrated many of the challenges with using science to guide planning and policymaking. One such challenge has to do with how to manage, represent and communicate uncertainties in epidemiological models. This is considerably complicated, we argue, by the fact that the models themselves are often instrumental in structuring the involved uncertainties. In this paper we explore how models 'domesticate' uncertainties and what this implies for science-for-policy. We analyse three examples of uncertainty domestication in models of COVID-19 and argue that we need to pay more attention to how uncertainties are domesticated in models used for policy support, and the many ways in which uncertainties are domesticated within particular models can fail to fit with the needs and demands of policymakers and planners.

A mouse xenograft long-term replication yields a SARS-CoV-2 Delta mutant with increased lethality

We recently established a long-term SARS-CoV-2 infection model using lung-cancer xenograft mice and identified mutations that arose in the SARS-CoV-2 genome during long-term propagation. Here, we applied our model to the SARS-CoV-2 Delta variant, which has increased transmissibility and immune escape compared with ancestral SARS-CoV-2. We observed limited mutations in SARS-CoV-2 Delta during long-term propagation, including two predominant mutations: R682W in the spike protein and L330W in the nucleocapsid protein. We analyzed two representative isolates, Delta-10 and Delta-12, with both predominant mutations and some additional mutations. Delta-10 and Delta-12 showed lower replication capacity compared with SARS-CoV-2 Delta in cultured cells; however, Delta-12 was more lethal in K18-hACE2 mice compared with SARS-CoV-2 Delta and Delta-10. Mice infected with Delta-12 had higher viral titers, more severe histopathology in the lungs, higher chemokine expression, increased astrocyte and microglia activation, and extensive neutrophil infiltration in the brain. Brain tissue hemorrhage and mild vacuolation were also observed, suggesting that the high lethality of Delta-12 was associated with lung and brain pathology. Our long-term infection model can provide mutant viruses derived from SARS-CoV-2 Delta and knowledge about the possible contributions of emergent mutations to the properties of new variants.

Dynamic clade transitions and the influence of vaccine rollout on the spatiotemporal circulation of SARS-CoV-2 variants in São Paulo, Brazil

Since 2021, the emergence of variants of concern (VOC) has led Brazil to experience record numbers of in COVID-19 cases and deaths. The expanded spread of the SARS-CoV-2 combined with a low vaccination rate has contributed to the emergence of new mutations that may enhance viral fitness, leading to the persistence of the disease. Due to limitations in the real-time genomic monitoring of new variants in some Brazilian states, we aimed to investigate whether genomic surveillance, coupled with epidemiological data and SARS-CoV-2 variants spatiotemporal spread in a smaller region, can reflect the pandemic progression at a national level. Our findings revealed three SARS-CoV-2 variant replacements from 2021 to early 2022, corresponding to the introduction and increase in the frequency of Gamma, Delta, and Omicron variants, as indicated by peaks of the Effective Reproductive Number (Reff). These distinct clade replacements triggered two waves of COVID-19 cases, influenced by the increasing vaccine uptake over time. Our results indicated that the effectiveness of vaccination in preventing new cases during the Delta and Omicron circulations was six and eleven times higher, respectively, than during the period when Gamma was predominant, and it was highly efficient in reducing the number of deaths. Furthermore, we demonstrated that genomic monitoring at a local level can reflect the national trends in the spread and evolution of SARS-CoV-2.

Tobacco Use and Uptake of COVID-19 Vaccinations in Finland: A Population-Based Study

INTRODUCTION

People who smoke are at higher risk of Coronavirus Disease-2019 (COVID-19) hospitalizations and deaths and might benefit greatly from high COVID-19 vaccination coverage. Studies on tobacco use and COVID-19 vaccine uptake in the general population are lacking.

AIMS AND METHODS

We conducted a cohort study utilizing linked data from 42 935 participants from two national surveys in Finland (FinSote 2018 and 2020). Exposures were smoking and smokeless tobacco (snus) use. The primary outcome was the uptake of two COVID-19 vaccine doses. Secondary outcomes were the uptake of one COVID-19 vaccine dose; three COVID-19 vaccine doses; time between the first and second dose; and time between the second and third dose. We examined the association between tobacco use and COVID-19 vaccine uptake and between-dose spacing in Finland.

RESULTS

People who smoke had a 7% lower risk of receiving two COVID-19 vaccine doses (95% confidence interval [CI] = 0.91; 0.96) and a 14% lower risk of receiving three doses (95% CI = 0.78; 0.94) compared to never smokers. People who smoked occasionally had a lower risk of receiving three vaccine doses. People who currently used snus had a 28% lower uptake of three doses (95% CI = 0.56; 0.93) compared to never users but we did not find evidence of an association for one or two doses. We did not find evidence of an association between tobacco use and spacing between COVID-19 vaccine doses.

CONCLUSIONS

People who smoke tobacco products daily, occasionally, and use snus had a lower uptake of COVID-19 vaccines. Our findings support a growing body of literature on lower vaccination uptake among people who use tobacco products.

IMPLICATIONS

People who smoke or use snus might be a crucial target group of public health efforts to increase COVID-19 vaccinations and plan future vaccination campaigns.

CLINICAL TRIALS REGISTRATION NUMBER

NCT05479383.

A regional genomic surveillance program is implemented to monitor the occurrence and emergence of SARS-CoV-2 variants in Yubei District, China

BACKGROUND

In December 2022, Chongqing experienced a significant surge in coronavirus disease 2019 (COVID-19) epidemic after adjusting control measures in China. Given the widespread immunization of the population with the BA.5 variant, it is crucial to actively monitor severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant evolution in Chongqing's Yubei district.

METHODS

In this retrospective study based on whole genome sequencing, we collected oropharyngeal and nasal swab of native COVID-19 cases from Yubei district between January to May 2023, along with imported cases from January 2022 to January 2023. Through second-generation sequencing, we generated a total of 578 genomes.

RESULTS

Phylogenetic analyses revealed these genomes belong to 47 SARS-CoV-2 Pango lineages. BA.5.2.48 was dominant from January to April 2023, rapidly replaced by XBB* variants from April to May 2023. Bayesian Skyline Plot reconstructions indicated a higher evolutionary rate (6.973 × 10-4 subs/site/year) for the XBB.1.5* lineage compared to others. The mean time to the most recent common ancestor (tMRCA) of BA.5.2.48* closely matched BA.2.75* (May 27, 2022). Using multinomial logistic regression, we estimated growth advantages, with XBB.1.9.1 showing the highest growth advantage (1.2, 95% HPI:1.1-1.2), followed by lineage FR.1 (1.1, 95% HPI:1.1-1.2).

CONCLUSIONS

Our monitoring reveals the rapid replacement of the previously prevalent BA.5.2.48 variant by XBB and its sub-variants, underscoring the ineffectiveness of herd immunity and breakthrough BA.5 infections against XBB variants. Given the ongoing evolutionary pressure, sustaining a SARS-CoV-2 genomic surveillance program is imperative.

The role of nutritional support with probiotics in outpatients with symptomatic acute respiratory tract infections: a multicenter, randomized, double-blind, placebo-controlled dietary study

BACKGROUND

A number of laboratory data and clinical studies have shown that probiotic bacteria may be beneficial in respiratory viral diseases. We investigated the role of probiotics in coronavirus disease-19 (COVID -19), post-disease symptoms, and humoral immune responses to viral antigens.

METHODS

This was a randomized, double-blind, placebo-controlled, prospective, multicenter study. We included symptomatic patients aged 18-65 years without risk of severe disease, and positive antigen/PCR test for SARS-CoV-2. Patients received (Bifidobacterium (B.) lactis BI040, B. longum BL020, Lactobacillus (L) rhamnosus LR110, L. casei LC130, L. acidophilus LA120, 5 billion CFU total) or placebo 1 capsule a day for 28 days and recorded symptoms. Three months later patients completed Post-COVID-19 Questionnaire (PCQ-19). On days 0-5 and 28-35, blood was sampled for IgG to nucleocapsid protein (NCP) and receptor binding domain (RBD)/spike 1 (S1) protein. The primary outcome measure was a patient global symptom score on day 10 of observation. The difference between groups was assessed using the Mann-Whitney U test.

RESULTS

Seventy-three patients were assessed for clinical endpoints and 44 patients were evaluated for antibody production. At day 10, the median global symptom score (interquartile range) was lower in the probiotic group (0.0 (0.0-2.0) vs. 2.0 (1.0-5.0), P < 0.05). The probiotic group had a shorter duration of fatigue and anxiety after COVID -19 (P < 0.05) and a greater change in IgG concentration on RBD/S1 (225.9 vs. 105.6 binding antibody units/mL, P < 0.05).

CONCLUSIONS

Use of probiotics alleviates acute and post-disease symptoms, and improves humoral immune response to viral antigens.

TRIAL REGISTRATION

Registered at clinicaltrials.gov as NCT04907877, June 1, 2021.

Molecular biology of SARS-CoV-2 and techniques of diagnosis and surveillance

The World Health Organization (WHO) declared coronavirus disease 2019 (COVID-19), a disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a global pandemic in March 2020. Reverse transcription-polymerase chain reaction (RT-PCR) is the reference technique for molecular diagnosis of SARS-CoV-2 infection. The SARS-CoV-2 virus is constantly mutating, and more transmissible variants have emerged, making genomic surveillance a crucial tool for investigating virus transmission dynamics, detecting novel genetic variants, and assessing mutation impact. The S gene, which encodes the spike protein, is frequently mutated, and it plays an important role in transmissibility. Spike protein mutations affect infectivity and vaccine effectiveness. SARS-CoV-2 variants are tracked using whole genome sequencing (WGS) and S-gene analysis. WGS, Sanger sequencing, and many S-gene-targeted RT-PCR methods have been developed. WGS and Sanger sequencing are standard methods for detecting mutations and can be used to identify known and unknown mutations. Melting curve analysis, endpoint genotyping assay, and S-gene target failure are used in the RT-PCR-based method for the rapid detection of specific mutations in SARS-CoV-2 variants. Therefore, these assays are suitable for high-throughput screening. The combinatorial use of RT-PCR-based assays, Sanger sequencing, and WGS enables rapid and accurate tracking of SARS-CoV-2 variants. In this review, we described RT-PCR-based detection and surveillance techniques for SARS-CoV-2.

Persistence of circulating CD169+monocytes and HLA-DR downregulation underline the immune response impairment in PASC individuals: the potential contribution of different COVID-19 pandemic waves

The use of CD169 as a marker of viral infection has been widely discussed in the context of COVID-19, and in particular, its crucial role in the early detection of SARS-CoV-2 infection and its association with the severity and clinical outcome of COVID-19 were demonstrated. COVID-19 patients show relevant systemic alteration and immunological dysfunction that persists in individuals with post-acute sequelae of SARS-CoV-2 infection (PASC). It is critical to implement the characterization of the disease, focusing also on the possible impact of the different COVID-19 waves and the consequent effects found after infection. On this basis, we evaluated by flow cytometry the expression of CD169 and HLA-DR on monocytes from COVID-19 patients and PASC individuals to better elucidate their involvement in immunological dysfunction, also evaluating the possible impact of different pandemic waves. The results confirm CD169 RMFI is a good marker of viral infection. Moreover, COVID-19 patients and PASC individuals showed high percentage of CD169+ monocytes, but low percentage of HLA-DR+ monocytes and the alteration of systemic inflammatory indices. We have also observed alterations of CD169 and HLA-DR expression and indices of inflammation upon different COVID-19 waves. The persistence of specific myeloid subpopulations suggests a role of CD169+ monocytes and HLA-DR in COVID-19 disease and chronic post-infection inflammation, opening new opportunities to evaluate the impact of specific pandemic waves on the immune response impairment and systemic alterations with the perspective to provide new tools to monitoring new variants and diseases associated to emerging respiratory viruses.

Structural plasticity of omicron BA.5 and BA.2.75 for enhanced ACE-dependent entry into cells

The current study investigated the binding variations among the wilt type, Omicron sub-variants BA.2.75 and BA.5, using protein-protein docking, protein structural graphs (P SG), and molecular simulation methods. HADDOCK predicted docking scores and dissociation constant (KD) revealed tighter binding of these sub-variants in contrast to the WT. Further investigation revealed variations in the hub residues, protein sub-networks, and GlobalMetapath in these variants as compared to the WT. A very unusual dynamic for BA.2.75 and BA.5 was observed, and secondary structure transition can also be witnessed in the loops (44-505). The results show that the flexibility of these three loops is increased by the mutations as an allosteric effect and thus enhances the chances of bonding with the nearby residues to connect and form a stable connection. Furthermore, the additional hydrogen bonding contacts steer the robust binding of these variants in contrast to the wild type. The total binding free energy for the wild type was calculated to be -61.38 kcal/mol, while for BA.2.75 and BA.5 variants the T BE was calculated to be -70.42 kcal/mol and 69.78 kcal/mol, respectively. We observed that the binding of BA.2.75 is steered by the electrostatic interactions while the BA.5 additional contacts are due to the vdW (Van der Waal) energy. From these findings, it can be observed the Spike (S) protein is undergoing structural adjustments to bind efficiently to the hACE2 (human angiotensin-converting enzyme 2) receptor and, in turn, increase entry to the host cells. The current study will aid the development of structure-based drugs against these variants.Communicated by Ramaswamy H. Sarma.

Epidemiological and clinical features of COVID-19 inpatients in Changsha, China: A retrospective study from 2020 to 2022

Objectives

The spread of SARS-Cov-2 remains a global concern along with the emergence of variants. This study aims to characterize the epidemiological and clinical features of hospitalized patients who were dragonized with five different variants of SARS-CoV-2 during the past 3 years.

Methods

This retrospective study recruited 432 COVID-19 patients who were hospitalized in the First Hospital of Changsha from January 2020 to August 2022. Clinical records on clinical symptoms, laboratory profiles, and chest CT images was collected. The epidemiological and clinical features were compared between COVID-19 patients infected with either the wild-type, Omicron variant or pre- Omicron variants (e.g., Alpha, Beta, Delta).

Results

A total of 432 laboratory-confirmed COVID-19 inpatients were dialogized during three waves, including 247 cases during the wild-type transmission period, 65 cases during the transmission period of pre-Omicron variants, and 119 cases during the transmission period of Omicron variants. The proportion of moderately or severely ill inpatients showed a gradual decline from the wild-type transmission period to the Omicron transmission period. The common symptoms of inpatients infected with SARS-CoV-2 wildtype strains included fever (67.61 %), cough (57.89 %), fatigue (33.60 %), and shortness of breath (12.15 %). In contrast, patients infected with other variants mostly showed upper respiratory symptoms. Based on chest CT images, a lower degree of acute pulmonary infection was observed among inpatients infected with the Omicron variants than those infected with the wild-type strain (31.09 % vs 93.12 %, p-value<0.01).

Conclusions

Compared with the wild-type strain, SARS-CoV-2 variants of concern, especially the Omicron variant, mostly caused a lower degree of acute pulmonary infection, indicating the reduced disease severity and mortality among hospitalized COVID-19 patients.

Characterization of Pharmacokinetics, Biotransformation and Elimination of Pomotrelvir Orally Administered in Healthy Male Adults Using Two [14C]-Labeled Microtracers with Separate Labeling Positions

Pomotrelvir is an orally bioavailable, target antiviral inhibitor of the main protease (Mpro) of coronaviruses, including severe acute respiratory syndrome coronavirus 2, the etiological agent of Coronavirus Disease 2019. The pharmacokinetics, metabolism and elimination of two [14C]-labeled microtracers of 5 µCi/700 mg pomotrelvir with separate labeling positions (isotopomers), [lactam carbonyl-14C-pomotelvir] and [benzene ring-U-14C-pomotrelvir], following a single oral dose in healthy adult males was evaluated in two separate cohorts. Pomotrelvir was rapidly absorbed and eliminated primarily through metabolism and subsequently excreted via urine and feces. There were no differences in pomotrelvir pharmacokinetics between the two cohorts. The mean total radioactive dose recovered was 93.8% (n = 8) in the lactam cohort (58% in urine and 36% in feces) and 94.2% (n = 8) in the benzene cohort (75% in urine and 19% in feces), with ≥80% of [14C] recovered within 96 hours after dosing. About 5% and 3% of the intact pomotrelvir was recovered in feces and urine, respectively. Eleven major metabolites were detected and characterized using liquid chromatography-accelerator mass spectrometry and liquid chromatography tandem mass spectrometry methods, with three and six different metabolites elucidated in the samples collected from lactam and benzene cohorts, respectively, and two metabolites observed in both cohorts. The major metabolism pathway of pomotrelvir is through hydrolysis of its peptide bonds followed by phase II conjugations. These results support that the application of two radiolabeled isotopomers provided a comprehensive metabolite profiling analysis and was a successful approach in identifying the major disposition pathways of pomotrelvir that has complex routes of metabolism. SIGNIFICANCE STATEMENT: An unconventional approach using two differentially labeled [14C] microtracers, [lactam carbonyl-14C-pomotrelvir] and [benzene ring-U-14C-pomotrelvir] evaluated the mass balance of orally administered pomotrelvir in healthy adult males in two separate cohorts. The radioactive dose recovered in excreta was about 94% for both cohorts. While the two isotopomers of the radiolabeled-pomotrelvir showed no major differences in pharmacokinetics overall, they allowed for differential detection of their radiolabeled metabolites and appropriate characterization of their plasma exposure and excretion in urine and feces.

Vaccination reduces viral load and accelerates viral clearance in SARS-CoV-2 Delta variant-infected patients

OBJECTIVE

The purpose of this study was to investigate vaccine effectiveness in relieving symptoms in patients with the SARS-CoV-2 delta (B.1.617.2) variant.

METHODS

In this retrospective study, 31 patients did not receive any vaccine (non-vaccination, NV), 21 patients received 1-dose of inactivated vaccine (one-dose vaccination, OV), and 60 patients received at least 2-dose inactivated vaccine (two-dose vaccination, TV). The baseline data, clinical outcomes and vaccination information were collected and analyzed.

RESULTS

Patients in the OV group were younger than those in the other two groups (p = 0.001), but there was no significant difference in any of the other baseline data among the three groups. The TV group showed higher IgG antibody levels and cycle threshold values of SARS-CoV-2 than the NV and OV groups (p < 0.01), and time to peak viral load was shorter in the TV group (3.5 ± 2.3 d) than in the NV (4.8 ± 2.8 d) and OV groups (4.8 ± 2.9 d, p = 0.03). The patients in the TV group (18%) showed a higher recovery rate without drug therapy (p < 0.001). Viral clearance time and hospital stay were significantly shorter in the TV group than in the NV and OV groups (p < 0.01), and there were no significant differences in these parameters between the OV and NV groups, but IgG values were higher in the OV group (p = 0.025). No severe complications occurred in this study.

CONCLUSIONS

Our results suggest that 2-dose vaccination can reduce viral load and accelerate viral clearance in patients with the delta variant and enhance the protection afforded by IgG antibodies in vivo.Key MessagesIn this study, our results shows that two-dose vaccination can reduce viral loads and accelerate viral clearance, and two-dose vaccination enhance the protection of IgG antibodies in vivo; however, one-dose vaccination did not confer protective effectiveness.

Coupled models of genomic surveillance and evolving pandemics with applications for timely public health interventions

Disease surveillance systems provide early warnings of disease outbreaks before they become public health emergencies. However, pandemics containment would be challenging due to the complex immunity landscape created by multiple variants. Genomic surveillance is critical for detecting novel variants with diverse characteristics and importation/emergence times. Yet, a systematic study incorporating genomic monitoring, situation assessment, and intervention strategies is lacking in the literature. We formulate an integrated computational modeling framework to study a realistic course of action based on sequencing, analysis, and response. We study the effects of the second variant's importation time, its infectiousness advantage and, its cross-infection on the novel variant's detection time, and the resulting intervention scenarios to contain epidemics driven by two-variants dynamics. Our results illustrate the limitation in the intervention's effectiveness due to the variants' competing dynamics and provide the following insights: i) There is a set of importation times that yields the worst detection time for the second variant, which depends on the first variant's basic reproductive number; ii) When the second variant is imported relatively early with respect to the first variant, the cross-infection level does not impact the detection time of the second variant. We found that depending on the target metric, the best outcomes are attained under different interventions' regimes. Our results emphasize the importance of sustained enforcement of Non-Pharmaceutical Interventions on preventing epidemic resurgence due to importation/emergence of novel variants. We also discuss how our methods can be used to study when a novel variant emerges within a population.

Genomic surveillance of SARS-CoV-2 in Weihai, China, march 2022 to march 2023

COVID-19 is an acute respiratory infectious disease caused by SARS-CoV-2. It was first reported in Wuhan, China in December 2019 and rapidly spread globally in early 2020, triggering a global pandemic. In December 2022, China adjusted the dynamic COVID-zero strategy that lasted for three years. The number of positive cases in China increased rapidly in the short term. Weihai was also affected during this period. We conducted genomic surveillance of SARS-CoV-2 variants in Weihai during this period, hoping to understand the changes in the genomic characteristics of SARS-CoV-2 before and after the adjustment of the epidemic policy. In this study,we collected SARS-CoV-2 positive samples from March 2022 to March 2023 in Weihai and performed SARS-CoV-2 whole genome sequencing on these samples using next-generation sequencing technology. we obtained a total of 704 SARS-CoV-2 whole genome sequences, and selected 581 high-quality sequences for further analysis. The analysis results showed that from March 2022 to November 2022, before the adjustment of epidemic policy, the COVID-19 cases in Weihai were mainly from four local clusters,which were caused by four variants, including BA.2,BA.1.1,P.1.15 and BA.5.2.1. Phylogenetic analysis showed that: In the same cluster,the sequences between each other were highly homologous, and the whole genome sequence were almost identical. After December 2022, the epidemic policy was adjusted, BF.7 and BA.5.2 became the dominant variants in Weihai, consistent with the main domestic strains in China during the same period. Phylodynamic analysis showed that BF.7 and BA.5.2 had a large amount of genetic diversities in December, and the effective population size of BF.7 and BA.5.2 also showed explosive growth in December. In conclusion, we reported the composition and dynamic trend of SARS-CoV-2 variants in Weihai from March 2022 to March 2023. We found that there have been significant changes in the variants and expansion patterns of SARS-CoV-2 before and after the adjustment of epidemic policies. But the dominant variants in Weihai were the same as the SARS-CoV-2 variants circulating globally at the same time and we found no persistently dominant variants or new lineages during this period.

Seasonality of endemic COVID-19

Successive waves of infection by SARS-CoV-2 have left little doubt that this virus will transition to an endemic disease. Foreknowledge of when to expect seasonal surges is crucial for healthcare and public health decision-making. However, the future seasonality of COVID-19 remains uncertain. Evaluating its seasonality is complicated due to the limited years of SARS-CoV-2 circulation, pandemic dynamics, and varied interventions. In this study, we project the expected endemic seasonality by employing a phylogenetic ancestral and descendant state approach that leverages long-term data on the incidence of circulating HCoV coronaviruses. Our projections indicate asynchronous surges of SARS-CoV-2 across different locations in the northern hemisphere, occurring between October and January in New York and between January and March in Yamagata, Japan. This knowledge of spatiotemporal surges leads to medical preparedness and enables the implementation of targeted public health interventions to mitigate COVID-19 transmission.IMPORTANCEThe seasonality of COVID-19 is important for effective healthcare and public health decision-making. Previous waves of SARS-CoV-2 infections have indicated that the virus will likely persist as an endemic pathogen with distinct surges. However, the timing and patterns of potentially seasonal surges remain uncertain, rendering effective public health policies uninformed and in danger of poorly anticipating opportunities for intervention, such as well-timed booster vaccination drives. Applying an evolutionary approach to long-term data on closely related circulating coronaviruses, our research provides projections of seasonal surges that should be expected at major temperate population centers. These projections enable local public health efforts that are tailored to expected surges at specific locales or regions. This knowledge is crucial for enhancing medical preparedness and facilitating the implementation of targeted public health interventions.

Seroprevalence of anti-SARS-CoV-2 antibodies before and after implementation of anti-COVID-19 vaccination among hospital staff in Bangui, Central African Republic

Healthcare workers (HCWs) are at high to very high risk for SARS-CoV-2 infection. The persistence of this pandemic worldwide has instigated the need for an investigation of the level of prevention through immunization and vaccination against SARS-CoV-2 among HCWs. The objective of our study was to evaluate any changes in anti-COVID-19 serological status before and after the vaccination campaign of health personnel in the Central African Republic. We carried out a repeated cross-sectional serological study on HCWs at the university hospital centers of Bangui. Blood samples were collected and tested for anti-SARS-CoV-2 IgM and IgG using the ELISA technique on blood samples. A total of 179 and 141 HCWs were included in the first and second surveys, respectively. Of these staff, 31.8% of HCWs were positive for anti-SARS-CoV-2 IgG in the first survey, whereas 95.7% were positive for anti-SARS-CoV-2 IgG in the second survey. However, the proportion of HCWs positive for SARS-CoV-2 IgM antibodies was low (9.7% in the first survey and 3.6% in the second survey). These findings showed a sharp increase in seroprevalence over a one-year period. This increase is primarily due to the synergistic effect of the infection and the implementation of vaccines against COVID-19. Further studies to assess the persistence of anti-SARS-CoV-2 antibodies are needed.

Surveillance for variants of SARS-CoV-2 to inform risk assessments

Since the beginning of the coronavirus disease 2019 (COVID-19) pandemic, numerous severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants have emerged, some leading to large increases in infections, hospitalizations and deaths globally. The virus's impact on public health depends on many factors, including the emergence of new viral variants and their global spread. Consequently, the early detection and surveillance of variants and characterization of their clinical effects are vital for assessing their health risk. The unprecedented capacity for viral genomic sequencing and data sharing built globally during the pandemic has enabled new variants to be rapidly detected and assessed. This article describes the main variants circulating globally between January 2020 and June 2023, the genetic features driving variant evolution, and the epidemiological impact of these variants across countries and regions. Second, we report how integrating genetic variant surveillance with epidemiological data and event-based surveillance, through a network of World Health Organization partners, supported risk assessment and helped provide guidance on pandemic responses. In addition, given the evolutionary characteristics of circulating variants and the immune status of populations, we propose future directions for the sustainable genomic surveillance of SARS-CoV-2 variants, both nationally and internationally: (i) optimizing variant surveillance by including environmental monitoring; (ii) coordinating laboratory assessment of variant evolution and phenotype; (iii) linking data on circulating variants with clinical data; and (iv) expanding genomic surveillance to additional pathogens. Experience during the COVID-19 pandemic has shown that genomic surveillance of pathogens can provide essential, timely and evidence-based information for public health decision-making.

Chronicling the 3-year evolution of the COVID-19 pandemic: analysis of disease management, characteristics of major variants, and impacts on pathogenicity

Announced on December 31, 2019, the novel coronavirus arising in Wuhan City, Hubei Province resulted in millions of cases and lives lost. Following intense tracking, coronavirus disease 2019 (COVID-19) was declared a pandemic by the World Health Organization (WHO) in 2020. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was identified as the cause of COVID-19 and the continuous evolution of the virus has given rise to several variants. In this review, a comprehensive analysis of the response to the pandemic over the first three-year period is provided, focusing on disease management, development of vaccines and therapeutics, and identification of variants. The transmissibility and pathogenicity of SARS-CoV-2 variants including Alpha, Beta, Gamma, Delta, and Omicron are compared. The binding characteristics of the SARS-CoV-2 spike protein to the angiotensin-converting enzyme 2 (ACE2) receptor and reproduction numbers are evaluated. The effects of major variants on disease severity, hospitalisation, and case-fatality rates are outlined. In addition to the spike protein, open reading frames mutations are investigated. We also compare the pathogenicity of SARS-CoV-2 with SARS-CoV and Middle East respiratory syndrome coronavirus (MERS-CoV). Overall, this study highlights the strengths and weaknesses of the global response to the pandemic, as well as the importance of prevention and preparedness. Monitoring the evolution of SARS-CoV-2 is critical in identifying and potentially predicting the health outcomes of concerning variants as they emerge. The ultimate goal would be a position in which existing vaccines and therapeutics could be adapted to suit new variants in as close to real-time as possible.

Evaluating the performance of Plasmodium falciparum genetics for inferring National Malaria Control Program reported incidence in Senegal

Genetic surveillance of the Plasmodium falciparum parasite shows great promise for helping National Malaria Control Programs (NMCPs) assess parasite transmission. Genetic metrics such as the frequency of polygenomic (multiple strain) infections, genetic clones, and the complexity of infection (COI, number of strains per infection) are correlated with transmission intensity. However, despite these correlations, it is unclear whether genetic metrics alone are sufficient to estimate clinical incidence. Here, we examined parasites from 3,147 clinical infections sampled between the years 2012-2020 through passive case detection (PCD) across 16 clinic sites spread throughout Senegal. Samples were genotyped with a 24 single nucleotide polymorphism (SNP) molecular barcode that detects parasite strains, distinguishes polygenomic (multiple strain) from monogenomic (single strain) infections, and identifies clonal infections. To determine whether genetic signals can predict incidence, we constructed a series of Poisson generalized linear mixed-effects models to predict the incidence level at each clinical site from a set of genetic metrics designed to measure parasite clonality, superinfection, and co-transmission rates. We compared the model-predicted incidence with the reported standard incidence data determined by the NMCP for each clinic and found that parasite genetic metrics generally correlated with reported incidence, with departures from expected values at very low annual incidence (<10/1000/annual [‰]). When transmission is greater than 10 cases per 1000 annual parasite incidence (annual incidence >10 ‰), parasite genetics can be used to accurately infer incidence and is consistent with superinfection-based hypotheses of malaria transmission. When transmission was <10 ‰, we found that many of the correlations between parasite genetics and incidence were reversed, which we hypothesize reflects the disproportionate impact of importation and focal transmission on parasite genetics when local transmission levels are low.

Evolution of the coronavirus spike protein in the full-length genome and defective viral genome under diverse selection pressures

How coronaviruses evolve by altering the structures of their full-length genome and defective viral genome (DVG) under dynamic selection pressures has not been studied. In this study, we aimed to experimentally identify the dynamic evolutionary patterns of the S protein sequence in the full-length genome and DVG under diverse selection pressures, including persistence, innate immunity and antiviral drugs. The evolutionary features of the S protein sequence in the full-length genome and in the DVG under diverse selection pressures are as follows: (i) the number of nucleotide (nt) mutations does not necessarily increase with the number of selection pressures; (ii) certain types of selection pressure(s) can lead to specific nt mutations; (iii) the mutated nt sequence can be reverted to the wild-type nt sequence under the certain type of selection pressure(s); (iv) the DVG can also undergo mutations and evolve independently of the full-length genome; and (v) DVG species are regulated during evolution under diverse selection pressures. The various evolutionary patterns of the S protein sequence in the full-length genome and DVG identified in this study may contribute to coronaviral fitness under diverse selection pressures.

Measuring unequal distribution of pandemic severity across census years, variants of concern and interventions

BACKGROUND

The COVID-19 pandemic stressed public health systems worldwide due to emergence of several highly transmissible variants of concern. Diverse and complex intervention policies deployed over the last years have shown varied effectiveness in controlling the pandemic. However, a systematic analysis and modelling of the combined effects of different viral lineages and complex intervention policies remains a challenge due to the lack of suitable measures of pandemic inequality and nonlinear effects.

METHODS

Using large-scale agent-based modelling and a high-resolution computational simulation matching census-based demographics of Australia, we carried out a systematic comparative analysis of several COVID-19 pandemic scenarios. The scenarios covered two most recent Australian census years (2016 and 2021), three variants of concern (ancestral, Delta and Omicron), and five representative intervention policies. We introduced pandemic Lorenz curves measuring an unequal distribution of the pandemic severity across local areas. We also quantified pandemic biomodality, distinguishing between urban and regional waves, and measured bifurcations in the effectiveness of interventions.

RESULTS

We quantified nonlinear effects of population heterogeneity on the pandemic severity, highlighting that (i) the population growth amplifies pandemic peaks, (ii) the changes in population size amplify the peak incidence more than the changes in density, and (iii) the pandemic severity is distributed unequally across local areas. We also examined and delineated the effects of urbanisation on the incidence bimodality, distinguishing between urban and regional pandemic waves. Finally, we quantified and examined the impact of school closures, complemented by partial interventions, and identified the conditions when inclusion of school closures may decisively control the transmission.

CONCLUSIONS

Public health response to long-lasting pandemics must be frequently reviewed and adapted to demographic changes. To control recurrent waves, mass-vaccination rollouts need to be complemented by partial NPIs. Healthcare and vaccination resources need to be prioritised towards the localities and regions with high population growth and/or high density.

Evaluating the COVID-19 vaccination program in Japan, 2021 using the counterfactual reproduction number

Japan implemented its nationwide vaccination program against COVID-19 in 2021, immunizing more than one million people (approximately 1%) a day. However, the direct and indirect impacts of the program at the population level have yet to be fully evaluated. To assess the vaccine effectiveness during the Delta variant (B.1.617.2) epidemic in 2021, we used a renewal process model. A transmission model was fitted to the confirmed cases from 17 February to 30 November 2021. In the absence of vaccination, the cumulative numbers of infections and deaths during the study period were estimated to be 63.3 million (95% confidence interval [CI] 63.2-63.6) and 364,000 (95% CI 363-366), respectively; the actual numbers of infections and deaths were 4.7 million and 10,000, respectively. Were the vaccination implemented 14 days earlier, there could have been 54% and 48% fewer cases and deaths, respectively, than the actual numbers. We demonstrated the very high effectiveness of COVID-19 vaccination in Japan during 2021, which reduced mortality by more than 97% compared with the counterfactual scenario. The timing of expanding vaccination and vaccine recipients could be key to mitigating the disease burden of COVID-19. Rapid and proper decision making based on firm epidemiological input is vital.

Index cases first identified by nasal-swab rapid COVID-19 tests had more transmission to household contacts than cases identified by other test types

At-home rapid COVID-19 tests in the U.S. utilize nasal-swab specimens and require high viral loads to reliably give positive results. Longitudinal studies from the onset of infection have found infectious virus can present in oral specimens days before nasal. Detection and initiation of infection-control practices may therefore be delayed when nasal-swab rapid tests are used, resulting in greater transmission to contacts. We assessed whether index cases first identified by rapid nasal-swab COVID-19 tests had more transmission to household contacts than index cases who used other test types (tests with higher analytical sensitivity and/or non-nasal specimen types). In this observational cohort study, 370 individuals from 85 households with a recent COVID-19 case were screened at least daily by RT-qPCR on one or more self-collected upper-respiratory specimen types. A two-level random intercept model was used to assess the association between the infection outcome of household contacts and each covariable (household size, race/ethnicity, age, vaccination status, viral variant, infection-control practices, and whether a rapid nasal-swab test was used to initially identify the household index case). Transmission was quantified by adjusted secondary attack rates (aSAR) and adjusted odds ratios (aOR). An aSAR of 53.6% (95% CI 38.8-68.3%) was observed among households where the index case first tested positive by a rapid nasal-swab COVID-19 test, which was significantly higher than the aSAR for households where the index case utilized another test type (27.2% 95% CI 19.5-35.0%, P = 0.003 pairwise comparisons of predictive margins). We observed an aOR of 4.90 (95% CI 1.65-14.56) for transmission to household contacts when a nasal-swab rapid test was used to identify the index case, compared to other test types. Use of nasal-swab rapid COVID-19 tests for initial detection of infection and initiation of infection control may be less effective at limiting transmission to household contacts than other test types.

Emergence of SARS-CoV-2 Delta Variant and Effect of Nonpharmaceutical Interventions, British Columbia, Canada

In British Columbia, Canada, initial growth of the SARS-CoV-2 Delta variant was slower than that reported in other jurisdictions. Delta became the dominant variant (>50% prevalence) within ≈7-13 weeks of first detection in regions within the United Kingdom and United States. In British Columbia, it remained at <10% of weekly incident COVID-19 cases for 13 weeks after first detection on March 21, 2021, eventually reaching dominance after 17 weeks. We describe the growth of Delta variant cases in British Columbia during March 1-June 30, 2021, and apply retrospective counterfactual modeling to examine factors for the initially low COVID-19 case rate after Delta introduction, such as vaccination coverage and nonpharmaceutical interventions. Growth of COVID-19 cases in the first 3 months after Delta emergence was likely limited in British Columbia because additional nonpharmaceutical interventions were implemented to reduce levels of contact at the end of March 2021, soon after variant emergence.

International Pediatric COVID-19 Severity Over the Course of the Pandemic

Importance

Multiple SARS-CoV-2 variants have emerged over the COVID-19 pandemic. The implications for COVID-19 severity in children worldwide are unclear.

Objective

To determine whether the dominant circulating SARS-CoV-2 variants of concern (VOCs) were associated with differences in COVID-19 severity among hospitalized children.

Design, Setting, and Participants

Clinical data from hospitalized children and adolescents (younger than 18 years) who were SARS-CoV-2 positive were obtained from 9 countries (Australia, Brazil, Italy, Portugal, South Africa, Switzerland, Thailand, UK, and the US) during 3 different time frames. Time frames 1 (T1), 2 (T2), and 3 (T3) were defined to represent periods of dominance by the ancestral virus, pre-Omicron VOCs, and Omicron, respectively. Age groups for analysis were younger than 6 months, 6 months to younger than 5 years, and 5 to younger than 18 years. Children with an incidental positive test result for SARS-CoV-2 were excluded.

Exposures

SARS-CoV-2 hospitalization during the stipulated time frame.

Main Outcomes and Measures

The severity of disease was assessed by admission to intensive care unit (ICU), the need for ventilatory support, or oxygen therapy.

Results

Among 31 785 hospitalized children and adolescents, the median age was 4 (IQR 1-12) years and 16 639 were male (52.3%). In children younger than 5 years, across successive SARS-CoV-2 waves, there was a reduction in ICU admission (T3 vs T1: risk ratio [RR], 0.56; 95% CI, 0.42-0.75 [younger than 6 months]; RR, 0.61, 95% CI; 0.47-0.79 [6 months to younger than 5 years]), but not ventilatory support or oxygen therapy. In contrast, ICU admission (T3 vs T1: RR, 0.39, 95% CI, 0.32-0.48), ventilatory support (T3 vs T1: RR, 0.37; 95% CI, 0.27-0.51), and oxygen therapy (T3 vs T1: RR, 0.47; 95% CI, 0.32-0.70) decreased across SARS-CoV-2 waves in children 5 years to younger than 18 years old. The results were consistent when data were restricted to unvaccinated children.

Conclusions and Relevance

This study provides valuable insights into the impact of SARS-CoV-2 VOCs on the severity of COVID-19 in hospitalized children across different age groups and countries, suggesting that while ICU admissions decreased across the pandemic in all age groups, ventilatory and oxygen support generally did not decrease over time in children aged younger than 5 years. These findings highlight the importance of considering different pediatric age groups when assessing disease severity in COVID-19.

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.