Genomic epidemiology of superspreading events in Austria reveals mutational dynamics and transmission properties of SARS-CoV-2

Genomic and spatial epidemiology: lessons learned from SARS-CoV-2 pandemic

PURPOSE OF REVIEW

The SARS-CoV-2 pandemic presented unprecedented challenges, particularly in understanding its complex spatial transmission patterns. The high transmissibility of the virus led to frequent super-spreading events. These events demonstrated clear spatial clustering patterns, often tied to specific events that facilitated transmission. The uneven geographic distribution of medical resources and varying access to care amplified the impact of SARS-CoV-2. Asymptomatic cases further complicated the situation, as infected individuals could silently spread the virus before being identified.Thus, this review examines how genomic and spatial epidemiology approaches can be integrated to answer some of the above-mentioned challenges. We first describe the methodological foundations of genomics and spatial epidemiology, detailing opportunities of their applications during the SARS-CoV-2 pandemic. We then present a novel interdisciplinary framework that combines these approaches to better guide public health interventions.

RECENT FINDINGS

During the pandemic, the genomic and spatial approaches were used to address key questions, including "how does the pathogen evolve and diversify?" and "how does the pathogen spread geographically?". Genomic epidemiology allows researchers to identify viral lineages and new variants. Conversely, spatial epidemiology focused on geographic distribution of infections, analyzing how the virus spread. However, despite their complementary nature, these approaches were largely applied independently during the pandemic. This separation limited our collective ability to fully understand the complex relationships between viral evolution and geographic spread.

SUMMARY

While phylogeography has traditionally combined phylogenetic and geographic data to understand long-term evolutionary patterns across large areas, events such as the recent SARS-CoV-2 pandemic demand frameworks that can inform public health interventions through joint analysis of genomic and local-scale spatial data.

An Expanding Universe of Mutational Signatures and Its Rapid Evolution in Single-Stranded RNA Viruses

The study of mutational processes in somatic genomes has gained recent momentum, uncovering a wide array of endogenous and exogenous factors associated with somatic changes. However, the overall landscape of mutational processes in germline mutations across the tree of life and associated evolutionary driving forces are rather unclear. In this study, we analyzed mutational processes in single-stranded RNA (ssRNA) viruses which are known to jump between different hosts with divergent exogenous environments. We found that mutational spectra in different ssRNA viruses differ significantly and are mainly associated with their genetic divergence. Surprisingly, host environments contribute much less significantly to the mutational spectrum, challenging the prevailing view that the exogenous cellular environment is a major determinant of the mutational spectrum in viruses. To dissect the evolutionary forces shaping viral spectra, we selected two important scenarios, namely the inter-host evolution between different viral strains as well as the intra-host evolution. In both scenarios, we found mutational spectra change significantly through space and time, strongly correlating with levels of natural selection. Combining the mutations across all ssRNA viruses, we identified a suite of mutational signatures with varying degrees of similarity to somatic signatures in humans, indicating universal and divergent mutational processes across the tree of life. Taken together, we unraveled an unprecedented dynamic landscape of mutational processes in ssRNA viruses, pinpointing important evolutionary forces shaping fast evolution of mutational spectra in different species.

Intra-host variability of SARS-CoV-2: Patterns, causes and impact on COVID-19

Intra-host viral variability is related to pathogenicity, persistence, drug resistance, and the emergence of new clades. This work reviews the large amount of data on SARS-CoV-2 intra-host variability accumulated to date, addressing known and potential implications in COVID-19 and the emergence of VOCs and lineage-defining mutations. Topics covered include the distribution of intra-host polymorphisms across the genome, the corresponding mutational signatures, their patterns of emergence and extinction throughout infection, and the processes governing their abundance, frequency, and type (synonymous, nonsynonymous, indels, nonsense). Besides, evidence is reviewed that the virus can replicate and mutate in isolation at different anatomical compartments, which may imply that what we have learned from respiratory samples could be part of a broader picture.

Early unrecognised SARS-CoV-2 introductions shaped the first pandemic wave, Sweden, 2020

BackgroundDespite the unprecedented measures implemented globally in early 2020 to prevent the spread of SARS-CoV-2, Sweden, as many other countries, experienced a severe first wave during the COVID-19 pandemic.AimWe investigated the introduction and spread of SARS-CoV-2 into Sweden.MethodsWe analysed stored respiratory specimens (n = 1,979), sampled 7 February-2 April 2020, by PCR for SARS-CoV-2 and sequenced PCR-positive specimens. Sequences generated from newly detected cases and stored positive specimens February-June 2020 (n = 954) were combined with sequences (Sweden: n = 730; other countries: n = 129,913) retrieved from other sources for Nextstrain clade assignment and phylogenetic analyses.ResultsTwelve previously unrecognised SARS-CoV-2 cases were identified: the earliest was sampled on 3 March, 1 week before recognised community transmission. We showed an early influx of clades 20A and 20B from Italy (201/328, 61% of cases exposed abroad) and clades 19A and 20C from Austria (61/328, 19%). Clade 20C dominated the first wave (20C: 908/1,684, 54%; 20B: 438/1,684, 26%; 20A: 263/1,684, 16%), and 800 of 1,684 (48%) Swedish sequences formed a country-specific 20C cluster defined by a spike mutation (G24368T). At the regional level, the proportion of clade 20C sequences correlated with an earlier weighted mean date of COVID-19 deaths.ConclusionCommunity transmission in Sweden started when mitigation efforts still focused on preventing influx. This created a transmission advantage for clade 20C, likely introduced from ongoing cryptic spread in Austria. Therefore, pandemic preparedness should have a comprehensive approach, including capacity for large-scale diagnostics to allow early detection of travel-related cases and community transmission.

Refining SARS-CoV-2 intra-host variation by leveraging large-scale sequencing data

Understanding viral genome evolution during host infection is crucial for grasping viral diversity and evolution. Analyzing intra-host single nucleotide variants (iSNVs) offers insights into new lineage emergence, which is important for predicting and mitigating future viral threats. Despite next-generation sequencing's potential, challenges persist, notably sequencing artifacts leading to false iSNVs. We developed a workflow to enhance iSNV detection in large NGS libraries, using over 130 000 SARS-CoV-2 libraries to distinguish mutations from errors. Our approach integrates bioinformatics protocols, stringent quality control, and dimensionality reduction to tackle batch effects and improve mutation detection reliability. Additionally, we pioneer the application of the PHATE visualization approach to genomic data and introduce a methodology that quantifies how related groups of data points are represented within a two-dimensional space, enhancing clustering structure explanation based on genetic similarities. This workflow advances accurate intra-host mutation detection, facilitating a deeper understanding of viral diversity and evolution.

Intrahost evolution leading to distinct lineages in the upper and lower respiratory tracts during SARS-CoV-2 prolonged infection

Accumulating evidence points to persistent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in immunocompromised individuals as a source of novel lineages. While intrahost evolution of the virus in chronically infected patients has previously been reported, existing knowledge is primarily based on samples from the nasopharynx. In this study, we investigate the intrahost evolution and genetic diversity that accumulated during a prolonged SARS-CoV-2 infection with the Omicron BF.7 sublineage, which is estimated to have persisted for >1 year in an immunosuppressed patient. Based on the sequencing of eight samples collected at six time points, we identified 87 intrahost single-nucleotide variants, 2 indels, and a 362-bp deletion. Our analysis revealed distinct viral genotypes in the nasopharyngeal (NP), endotracheal aspirate, and bronchoalveolar lavage samples. This suggests that NP samples may not offer a comprehensive representation of the overall intrahost viral diversity. Our findings not only demonstrate that the Omicron BF.7 sublineage can further diverge from its already exceptionally mutated state but also highlight that patients chronically infected with SARS-CoV-2 can develop genetically specific viral populations across distinct anatomic compartments. This provides novel insights into the intricate nature of viral diversity and evolution dynamics in persistent infections.

Comprehensive contact tracing during an outbreak of alpha-variant SARS-CoV-2 in a rural community reveals less viral genomic diversity and higher household secondary attack rates than expected

Sequencing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes throughout the COVID-19 pandemic has generated a wealth of data on viral evolution across populations, but only a few studies have so far explored SARS-CoV-2 evolution across large connected transmission networks. Here, we couple data from SARS-CoV-2 sequencing with contact tracing data from an outbreak with a single origin in a rural Norwegian community where samples from all exposed persons were collected prospectively. A total of 134 nasopharyngeal samples were positive by PCR. Among the 121 retrievable genomes, 81 were identical to the genome of the introductor, thus demonstrating that genomics beyond clustering genotypically similar viral genomes to confirm relatedness offers limited additional value to manual contact tracing. In the cases where mutations were discovered, five small genetic clusters were identified. We observed a household secondary attack rate of 77%, with 92% of household members infected among households with secondary transmission, suggesting that SARS-CoV-2 introduction into large families is likely to affect all household members.

IMPORTANCE

In outbreak investigations, obtaining a full overview of infected individuals within a population is seldom achieved. We here present an example where a single introduction of B1.1.7 SARS-CoV-2 within a rural community allowed for tracing of the virus from an introductor via dissemination through larger gatherings into households. The outbreak occurred before widespread vaccination, allowing for a "natural" outbreak development with community lockdown. We show through sequencing that the virus can infect up to five consecutive persons without gaining mutations, thereby showing that contact tracing seems more important than sequencing for local outbreak investigations in settings with few alternative introductory transmission pathways. We also show how larger households where a child introduced transmission appeared more likely to promote further spread of the virus compared to households with an adult as the primary introductor.

CD4+ and CD8+ T cells are required to prevent SARS-CoV-2 persistence in the nasal compartment

SARS-CoV-2 infection induces the generation of virus-specific CD4+ and CD8+ effector and memory T cells. However, the contribution of T cells in controlling SARS-CoV-2 during infection is not well understood. Following infection of C57BL/6 mice, SARS-CoV-2-specific CD4+ and CD8+ T cells are recruited to the respiratory tract, and a vast proportion secrete the cytotoxic molecule granzyme B. Using depleting antibodies, we found that T cells within the lungs play a minimal role in viral control, and viral clearance occurs in the absence of both CD4+ and CD8+ T cells through 28 days postinfection. In the nasal compartment, depletion of both CD4+ and CD8+ T cells, but not individually, results in persistent, culturable virus replicating in the nasal epithelial layer through 28 days postinfection. Viral sequencing analysis revealed adapted mutations across the SARS-CoV-2 genome, including a large deletion in ORF6. Overall, our findings highlight the importance of T cells in controlling virus replication within the respiratory tract during SARS-CoV-2 infection.

Genomic surveillance of SARS-CoV-2 evolution by a centralised pipeline and weekly focused sequencing, Austria, January 2021 to March 2023

BackgroundThe COVID-19 pandemic was largely driven by genetic mutations of SARS-CoV-2, leading in some instances to enhanced infectiousness of the virus or its capacity to evade the host immune system. To closely monitor SARS-CoV-2 evolution and resulting variants at genomic-level, an innovative pipeline termed SARSeq was developed in Austria.AimWe discuss technical aspects of the SARSeq pipeline, describe its performance and present noteworthy results it enabled during the pandemic in Austria.MethodsThe SARSeq pipeline was set up as a collaboration between private and public clinical diagnostic laboratories, a public health agency, and an academic institution. Representative SARS-CoV-2 positive specimens from each of the nine Austrian provinces were obtained from SARS-CoV-2 testing laboratories and processed centrally in an academic setting for S-gene sequencing and analysis.ResultsSARS-CoV-2 sequences from up to 2,880 cases weekly resulted in 222,784 characterised case samples in January 2021-March 2023. Consequently, Austria delivered the fourth densest genomic surveillance worldwide in a very resource-efficient manner. While most SARS-CoV-2 variants during the study showed comparable kinetic behaviour in all of Austria, some, like Beta, had a more focused spread. This highlighted multifaceted aspects of local population-level acquired immunity. The nationwide surveillance system enabled reliable nowcasting. Measured early growth kinetics of variants were predictive of later incidence peaks.ConclusionWith low automation, labour, and cost requirements, SARSeq is adaptable to monitor other pathogens and advantageous even for resource-limited countries. This multiplexed genomic surveillance system has potential as a rapid response tool for future emerging threats.

How much should we sequence? An analysis of the Swiss SARS-CoV-2 surveillance effort

During the SARS-CoV-2 pandemic, many countries directed substantial resources toward genomic surveillance to detect and track viral variants. There is a debate over how much sequencing effort is necessary in national surveillance programs for SARS-CoV-2 and future pandemic threats. We aimed to investigate the effect of reduced sequencing on surveillance outcomes in a large genomic data set from Switzerland, comprising more than 143k sequences. We employed a uniform downsampling strategy using 100 iterations each to investigate the effects of fewer available sequences on the surveillance outcomes: (i) first detection of variants of concern (VOCs), (ii) speed of introduction of VOCs, (iii) diversity of lineages, (iv) first cluster detection of VOCs, (v) density of active clusters, and (vi) geographic spread of clusters. The impact of downsampling on VOC detection is disparate for the three VOC lineages, but many outcomes including introduction and cluster detection could be recapitulated even with only 35% of the original sequencing effort. The effect on the observed speed of introduction and first detection of clusters was more sensitive to reduced sequencing effort for some VOCs, in particular Omicron and Delta, respectively. A genomic surveillance program needs a balance between societal benefits and costs. While the overall national dynamics of the pandemic could be recapitulated by a reduced sequencing effort, the effect is strongly lineage-dependent-something that is unknown at the time of sequencing-and comes at the cost of accuracy, in particular for tracking the emergence of potential VOCs.IMPORTANCESwitzerland had one of the most comprehensive genomic surveillance systems during the COVID-19 pandemic. Such programs need to strike a balance between societal benefits and program costs. Our study aims to answer the question: How would surveillance outcomes have changed had we sequenced less? We find that some outcomes but also certain viral lineages are more affected than others by sequencing less. However, sequencing to around a third of the original effort still captured many important outcomes for the variants of concern such as their first detection but affected more strongly other measures like the detection of first transmission clusters for some lineages. Our work highlights the importance of setting predefined targets for a national genomic surveillance program based on which sequencing effort should be determined. Additionally, the use of a centralized surveillance platform facilitates aggregating data on a national level for rapid public health responses as well as post-analyses.

Quantifying Exhaled Particles in Healthy Humans During Various Respiratory Activities Under Realistic Conditions

Background: Quantitatively collecting and characterizing exhaled aerosols is vital for infection risk assessment, but the entire droplet size spectrum has often been neglected. We analyzed particle number and size distribution of healthy participants in various respiratory activities, considering inter-individual variability, and deployed a simplified far-field model to inform on infection risks. Methods: Participants repeated the same respiratory activities on two visits. Particles were collected using an airtight extraction helmet supplied with High Efficiency Particulate Air (HEPA) filtered air. The sampling volume flow was transported to two particle counters covering the small and large particle spectrum. The applied simple mass balance model included respiratory activity, viral load, room size, and air exchange rates. Results: Thirty participants completed the study. The major fraction of the number-based size distribution was <5 μm in all respiratory activities. In contrast, the major fraction of the volume-based size distribution was 2-12 μm in tidal breathing, but >60 μm in all other activities. Aerosol volume flow was lowest in tidal breathing, 10-fold higher in quiet/normal speaking, deep breathing, coughing, and 100-fold higher in loud speaking/singing. Intra-individual reproducibility was high. Between participants, aerosol volume flow varied by two orders of magnitude in droplets <80 μm, and three orders of magnitude in droplets >80 μm. Simple model calculations not accounting for potential particle size-dependent differences in viral load and infection-related differences were used to model airborne pathogen concentrations. Conclusions: Quantitative analysis of exhaled aerosols for the entire droplet size spectrum as well as the variability in aerosol emission between individuals provides information that can support infection research. Clinical Trial Registration number: NCT04771585.

Evolutionary trajectory of diverse SARS-CoV-2 variants at the beginning of COVID-19 outbreak

Despite extensive scientific efforts directed toward the evolutionary trajectory of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in humans at the beginning of the COVID-19 epidemic, it remains unclear how the virus jumped into and evolved in humans so far. Herein, we recruited almost all adult coronavirus disease 2019 (COVID-19) cases appeared locally or imported from abroad during the first 8 months of the outbreak in Shanghai. From these patients, SARS-CoV-2 genomes occupying the important phylogenetic positions in the virus phylogeny were recovered. Phylogenetic and mutational landscape analyses of viral genomes recovered here and those collected in and outside of China revealed that all known SARS-CoV-2 variants exhibited the evolutionary continuity despite the co-circulation of multiple lineages during the early period of the epidemic. Various mutations have driven the rapid SARS-CoV-2 diversification, and some of them favor its better adaptation and circulation in humans, which may have determined the waxing and waning of various lineages.

The multi-dimensional challenges of controlling respiratory virus transmission in indoor spaces: Insights from the linkage of a microscopic pedestrian simulation and SARS-CoV-2 transmission model

SARS-CoV-2 transmission in indoor spaces, where most infection events occur, depends on the types and duration of human interactions, among others. Understanding how these human behaviours interface with virus characteristics to drive pathogen transmission and dictate the outcomes of non-pharmaceutical interventions is important for the informed and safe use of indoor spaces. To better understand these complex interactions, we developed the Pedestrian Dynamics-Virus Spread model (PeDViS), an individual-based model that combines pedestrian behaviour models with virus spread models incorporating direct and indirect transmission routes. We explored the relationships between virus exposure and the duration, distance, respiratory behaviour, and environment in which interactions between infected and uninfected individuals took place and compared this to benchmark 'at risk' interactions (1.5 metres for 15 minutes). When considering aerosol transmission, individuals adhering to distancing measures may be at risk due to the buildup of airborne virus in the environment when infected individuals spend prolonged time indoors. In our restaurant case, guests seated at tables near infected individuals were at limited risk of infection but could, particularly in poorly ventilated places, experience risks that surpass that of benchmark interactions. Combining interventions that target different transmission routes can aid in accumulating impact, for instance by combining ventilation with face masks. The impact of such combined interventions depends on the relative importance of transmission routes, which is hard to disentangle and highly context dependent. This uncertainty should be considered when assessing transmission risks upon different types of human interactions in indoor spaces. We illustrated the multi-dimensionality of indoor SARS-CoV-2 transmission that emerges from the interplay of human behaviour and the spread of respiratory viruses. A modelling strategy that incorporates this in risk assessments can help inform policy makers and citizens on the safe use of indoor spaces with varying inter-human interactions.

CD4+ and CD8+ T cells are required to prevent SARS-CoV-2 persistence in the nasal compartment

SARS-CoV-2 is the causative agent of COVID-19 and continues to pose a significant public health threat throughout the world. Following SARS-CoV-2 infection, virus-specific CD4+ and CD8+ T cells are rapidly generated to form effector and memory cells and persist in the blood for several months. However, the contribution of T cells in controlling SARS-CoV-2 infection within the respiratory tract are not well understood. Using C57BL/6 mice infected with a naturally occurring SARS-CoV-2 variant (B.1.351), we evaluated the role of T cells in the upper and lower respiratory tract. Following infection, SARS-CoV-2-specific CD4+ and CD8+ T cells are recruited to the respiratory tract and a vast proportion secrete the cytotoxic molecule Granzyme B. Using antibodies to deplete T cells prior to infection, we found that CD4+ and CD8+ T cells play distinct roles in the upper and lower respiratory tract. In the lungs, T cells play a minimal role in viral control with viral clearance occurring in the absence of both CD4+ and CD8+ T cells through 28 days post-infection. In the nasal compartment, depletion of both CD4+ and CD8+ T cells, but not individually, results in persistent and culturable virus replicating in the nasal compartment through 28 days post-infection. Using in situ hybridization, we found that SARS-CoV-2 infection persisted in the nasal epithelial layer of tandem CD4+ and CD8+ T cell-depleted mice. Sequence analysis of virus isolates from persistently infected mice revealed mutations spanning across the genome, including a deletion in ORF6. Overall, our findings highlight the importance of T cells in controlling virus replication within the respiratory tract during SARS-CoV-2 infection.

Transmission Bottleneck Size Estimation from De Novo Viral Genetic Variation

Sequencing of viral infections has become increasingly common over the last decade. Deep sequencing data in particular have proven useful in characterizing the roles that genetic drift and natural selection play in shaping within-host viral populations. They have also been used to estimate transmission bottleneck sizes from identified donor-recipient pairs. These bottleneck sizes quantify the number of viral particles that establish genetic lineages in the recipient host and are important to estimate due to their impact on viral evolution. Current approaches for estimating bottleneck sizes exclusively consider the subset of viral sites that are observed as polymorphic in the donor individual. However, these approaches have the potential to substantially underestimate true transmission bottleneck sizes. Here, we present a new statistical approach for instead estimating bottleneck sizes using patterns of viral genetic variation that arise de novo within a recipient individual. Specifically, our approach makes use of the number of clonal viral variants observed in a transmission pair, defined as the number of viral sites that are monomorphic in both the donor and the recipient but carry different alleles. We first test our approach on a simulated dataset and then apply it to both influenza A virus sequence data and SARS-CoV-2 sequence data from identified transmission pairs. Our results confirm the existence of extremely tight transmission bottlenecks for these 2 respiratory viruses.

Effect of Face Masking on Transmission of SARS-CoV-2

The efficacy of face masking for the public is not convincing to prevent the transmission of respiratory tract viruses such as SARS-CoV-2 when the criteria of evidence-based medicine are applied. This finding is mainly explained by the results from randomized-controlled trials (RCTs) when a high prevalence of the infection and a high compliance in mask wearing was assured. Throughout these studies no significant protective effect was observed. Observational studies with surgical masks describe a significant protective effect, but are prone to confounders such as physical distance. Respirators do not provide an additional health benefit compared to surgical or medical masks (RCTs). Community masks can even increase the risk of infection (RCTs). Based on the categories of evidence-based medicine, the efficacy results can best be categorized as conflicting evidence. Many relevant adverse events are described when masks are worn for hours such as dyspnea (12.2-52.8%), headache (3.9-73.4%), pruritus (0.0-60.0%), and skin reactions (0.0-85.0%). Their frequency is often higher with respirators. In future pandemics, masks should only be recommended or mandated for settings in which a clinically relevant health benefit can be expected, defined as the prevention of severe, critical or fatal disease, that clearly outweighs the expectable associated adverse reactions.

A Simulation Framework for Modeling the Within-Patient Evolutionary Dynamics of SARS-CoV-2

The global impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to considerable interest in detecting novel beneficial mutations and other genomic changes that may signal the development of variants of concern (VOCs). The ability to accurately detect these changes within individual patient samples is important in enabling early detection of VOCs. Such genomic scans for rarely acting positive selection are best performed via comparison of empirical data with simulated data wherein commonly acting evolutionary factors, including mutation and recombination, reproductive and infection dynamics, and purifying and background selection, can be carefully accounted for and parameterized. Although there has been work to quantify these factors in SARS-CoV-2, they have yet to be integrated into a baseline model describing intrahost evolutionary dynamics. To construct such a baseline model, we develop a simulation framework that enables one to establish expectations for underlying levels and patterns of patient-level variation. By varying eight key parameters, we evaluated 12,096 different model-parameter combinations and compared them with existing empirical data. Of these, 592 models (∼5%) were plausible based on the resulting mean expected number of segregating variants. These plausible models shared several commonalities shedding light on intrahost SARS-CoV-2 evolutionary dynamics: severe infection bottlenecks, low levels of reproductive skew, and a distribution of fitness effects skewed toward strongly deleterious mutations. We also describe important areas of model uncertainty and highlight additional sequence data that may help to further refine a baseline model. This study lays the groundwork for the improved analysis of existing and future SARS-CoV-2 within-patient data.

Evolution of the viral genomes of SARS-CoV-2 in association with the changes in local condition: a genomic epidemiological study of a suburban city of Japan

Understanding the factors driving the spread and evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) at the local, regional, national, and international levels is important in protecting against future pandemics. By exploring their viral genomes, we attempted to analyse the spread of SARS-CoV-2 and its evolutionary convergence in Kashiwa City, as an example of a representative commuter town in Japan. From September 2020 to January 2023, a total of 47,134 nasopharyngeal swab and saliva specimens were collected from patients in 47 local clinics and hospitals, covering the vast majority of healthcare facilities. All SARS-CoV-2-positive samples were subjected to whole genome sequencing. Based on the analysis of 5,536 identified genomes, all major strains were represented. Unique regional mutations were occasionally identified in each strain. Inspection of these mutations revealed that the overall base substitution rate increased with progressive waves of the pandemic, at an overall rate of 2.56 bases/year. Interestingly, the spread and evolutionary patterns appeared to be distinct between regions and between individual clinics. Further analysis of the synonymous base substitution rate showed that the speed of viral evolution accelerated coincident with the beginning of public vaccination. Comprehensive genomic epidemiological studies, as presented here, should be useful in precisely understanding the pandemic and preparing for possible future pandemics.

Within-host diversity improves phylogenetic and transmission reconstruction of SARS-CoV-2 outbreaks

Accurate inference of who infected whom in an infectious disease outbreak is critical for the delivery of effective infection prevention and control. The increased resolution of pathogen whole-genome sequencing has significantly improved our ability to infer transmission events. Despite this, transmission inference often remains limited by the lack of genomic variation between the source case and infected contacts. Although within-host genetic diversity is common among a wide variety of pathogens, conventional whole-genome sequencing phylogenetic approaches exclusively use consensus sequences, which consider only the most prevalent nucleotide at each position and therefore fail to capture low-frequency variation within samples. We hypothesized that including within-sample variation in a phylogenetic model would help to identify who infected whom in instances in which this was previously impossible. Using whole-genome sequences from SARS-CoV-2 multi-institutional outbreaks as an example, we show how within-sample diversity is partially maintained among repeated serial samples from the same host, it can transmitted between those cases with known epidemiological links, and how this improves phylogenetic inference and our understanding of who infected whom. Our technique is applicable to other infectious diseases and has immediate clinical utility in infection prevention and control.

Lessons from COVID-19 for rescalable data collection

Novel data and analyses have had an important role in informing the public health response to the COVID-19 pandemic. Existing surveillance systems were scaled up, and in some instances new systems were developed to meet the challenges posed by the magnitude of the pandemic. We describe the routine and novel data that were used to address urgent public health questions during the pandemic, underscore the challenges in sustainability and equity in data generation, and highlight key lessons learnt for designing scalable data collection systems to support decision making during a public health crisis. As countries emerge from the acute phase of the pandemic, COVID-19 surveillance systems are being scaled down. However, SARS-CoV-2 resurgence remains a threat to global health security; therefore, a minimal cost-effective system needs to remain active that can be rapidly scaled up if necessary. We propose that a retrospective evaluation to identify the cost-benefit profile of the various data streams collected during the pandemic should be on the scientific research agenda.

Intra- vs. Interhost Evolution of SARS-CoV-2 Driven by Uncorrelated Selection-The Evolution Thwarted

In viral evolution, a new mutation has to proliferate within the host (Stage I) in order to be transmitted and then compete in the host population (Stage II). We now analyze the intrahost single nucleotide variants (iSNVs) in a set of 79 SARS-CoV-2 infected patients with most transmissions tracked. Here, every mutation has two measures: 1) iSNV frequency within each individual host in Stage I; 2) occurrence among individuals ranging from 1 (private), 2-78 (public), to 79 (global) occurrences in Stage II. In Stage I, a small fraction of nonsynonymous iSNVs are sufficiently advantageous to rise to a high frequency, often 100%. However, such iSNVs usually fail to become public mutations. Thus, the selective forces in the two stages of evolution are uncorrelated and, possibly, antagonistic. For that reason, successful mutants, including many variants of concern, have to avoid being eliminated in Stage I when they first emerge. As a result, they may not have the transmission advantage to outcompete the dominant strains and, hence, are rare in the host population. Few of them could manage to slowly accumulate advantageous mutations to compete in Stage II. When they do, they would appear suddenly as in each of the six successive waves of SARS-CoV-2 strains. In conclusion, Stage I evolution, the gate-keeper, may contravene the long-term viral evolution and should be heeded in viral studies.

Transmission bottleneck size estimation from de novo viral genetic variation

Sequencing of viral infections has become increasingly common over the last decade. Deep sequencing data in particular have proven useful in characterizing the roles that genetic drift and natural selection play in shaping within-host viral populations. They have also been used to estimate transmission bottleneck sizes from identified donor-recipient pairs. These bottleneck sizes quantify the number of viral particles that establish genetic lineages in the recipient host and are important to estimate due to their impact on viral evolution. Current approaches for estimating bottleneck sizes exclusively consider the subset of viral sites that are observed as polymorphic in the donor individual. However, allele frequencies can change dramatically over the course of an individual's infection, such that sites that are polymorphic in the donor at the time of transmission may not be polymorphic in the donor at the time of sampling and allele frequencies at donor-polymorphic sites may change dramatically over the course of a recipient's infection. Because of this, transmission bottleneck sizes estimated using allele frequencies observed at a donor's polymorphic sites may be considerable underestimates of true bottleneck sizes. Here, we present a new statistical approach for instead estimating bottleneck sizes using patterns of viral genetic variation that arose de novo within a recipient individual. Specifically, our approach makes use of the number of clonal viral variants observed in a transmission pair, defined as the number of viral sites that are monomorphic in both the donor and the recipient but carry different alleles. We first test our approach on a simulated dataset and then apply it to both influenza A virus sequence data and SARS-CoV-2 sequence data from identified transmission pairs. Our results confirm the existence of extremely tight transmission bottlenecks for these two respiratory viruses, using an approach that does not tend to underestimate transmission bottleneck sizes.

Quantitative Microbial Risk Assessment of Contracting COVID-19 Derived from Measured and Simulated Aerosol Particle Transmission in Aircraft Cabins

BACKGROUND

SARS-CoV-2 can be effectively transmitted between individuals located in close proximity to each other for extended durations. Aircraft provide such conditions. Although high attack rates during flights were reported, little was known about the risk levels of aerosol transmission of SARS-CoV-2 in aircraft cabins.

OBJECTIVES

The major objective was to estimate the risk of contracting COVID-19 from transmission of aerosol particles in aircraft cabins.

METHODS

In two single-aisle and one twin-aisle aircraft, dispersion of generated aerosol particles over a seven-row economy class cabin section was measured under cruise and taxi conditions and simulated with a computational fluid dynamic model under cruise conditions. Using the aerosol particle dispersion data, a quantitative microbial risk assessment was conducted for scenarios with an asymptomatic infectious person expelling aerosol particles by breathing and speaking. Effects of flight conditions were evaluated using generalized additive mixed models.

RESULTS

Aerosol particle concentration decreased with increasing distance from the infectious person, and this decrease varied with direction. On a typical flight with an average shedder, estimated mean risk of contracting COVID-19 ranged from 1.3 × 10 - 3 to 9.0 × 10 - 2 . Risk increased to 7.7 × 10 - 2 with a super shedder (< 3 % of cases) on a long flight. Risks increased with increasing flight duration: 2-23 cruise flights of typical duration and 2-10 flights of longer duration resulted in at least 1 case of COVID-19 due to onboard aerosol transmission by one average shedder, and in the case of one super shedder, at least 1 case in 1-3 flights of typical duration cruise and 1 flight of longer duration.

DISCUSSION

Our findings indicate that the risk of contracting COVID-19 by aerosol transmission in an aircraft cabin is low, but it will not be zero. Testing before boarding may help reduce the chance of a (super)shedder boarding an aircraft and mask use further reduces aerosol transmission in the aircraft cabin. https://doi.org/10.1289/EHP11495.

Characterization of superspreaders movement in a bidirectional corridor using a social force model

During infectious disease outbreaks, some infected individuals may spread the disease widely and amplify risks in the community. People whose daily activities bring them in close proximity to many others can unknowingly become superspreaders. The use of contact tracking based on social networks, GPS, or mobile tracking data can help to identify superspreaders and break the chain of transmission. We propose a model that aims at providing insight into risk factors of superspreading events. Here, we use a social force model to estimate the superspreading potential of individuals walking in a bidirectional corridor. First, we applied the model to identify parameters that favor exposure to an infectious person in scattered crowds. We find that low walking speed and high body mass both increase the expected number of close exposures. Panic events exacerbate the risks while social distancing reduces both the number and duration of close encounters. Further, in dense crowds, pedestrians interact more and cannot easily maintain the social distance between them. The number of exposures increases with the density of person in the corridor. The study of movements reveals that individuals walking toward the center of the corridor tend to rotate and zigzag more than those walking along the edges, and thus have higher risks of superspreading. The corridor model can be applied to designing risk reduction measures for specific high volume venues, including transit stations, stadiums, and schools.

COVID-19 annual update: a narrative review

Three and a half years after the pandemic outbreak, now that WHO has formally declared that the emergency is over, COVID-19 is still a significant global issue. Here, we focus on recent developments in genetic and genomic research on COVID-19, and we give an outlook on state-of-the-art therapeutical approaches, as the pandemic is gradually transitioning to an endemic situation. The sequencing and characterization of rare alleles in different populations has made it possible to identify numerous genes that affect either susceptibility to COVID-19 or the severity of the disease. These findings provide a beginning to new avenues and pan-ethnic therapeutic approaches, as well as to potential genetic screening protocols. The causative virus, SARS-CoV-2, is still in the spotlight, but novel threatening virus could appear anywhere at any time. Therefore, continued vigilance and further research is warranted. We also note emphatically that to prevent future pandemics and other world-wide health crises, it is imperative to capitalize on what we have learnt from COVID-19: specifically, regarding its origins, the world's response, and insufficient preparedness. This requires unprecedented international collaboration and timely data sharing for the coordination of effective response and the rapid implementation of containment measures.

SARS-CoV-2 entry into and evolution within a skilled nursing facility

SARS-CoV-2 belongs to the family Coronaviridae which includes multiple human pathogens that have an outsized impact on aging populations. As a novel human pathogen, SARS-CoV-2 is undergoing continuous adaptation to this new host species and there is evidence of this throughout the scientific and public literature. However, most investigations of SARS-CoV-2 evolution have focused on large-scale collections of data across diverse populations and/or living environments. Here we investigate SARS-CoV-2 evolution in epidemiologically linked individuals within a single outbreak at a skilled nursing facility beginning with initial introduction of the pathogen. The data demonstrate that SARS-CoV-2 was introduced to the facility multiple times without establishing an interfacility transmission chain, followed by a single introduction that infected many individuals within a week. This large-scale introduction by a single genotype then persisted in the facility. SARS-CoV-2 sequences were investigated at both the consensus and intra-host variation levels. Understanding the variability in SARS-CoV-2 during transmission chains will assist in understanding the spread of this disease and can ultimately inform best practices for mitigation strategies.

A simulation framework for modeling the within-patient evolutionary dynamics of SARS-CoV-2

The global impact of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has led to considerable interest in detecting novel beneficial mutations and other genomic changes that may signal the development of variants of concern (VOCs). The ability to accurately detect these changes within individual patient samples is important in enabling early detection of VOCs. Such genomic scans for positive selection are best performed via comparison of empirical data to simulated data wherein evolutionary factors, including mutation and recombination rates, reproductive and infection dynamics, and purifying and background selection, can be carefully accounted for and parameterized. While there has been work to quantify these factors in SARS-CoV-2, they have yet to be integrated into a baseline model describing intra-host evolutionary dynamics. To construct such a baseline model, we develop a simulation framework that enables one to establish expectations for underlying levels and patterns of patient-level variation. By varying eight key parameters, we evaluated 12,096 different model-parameter combinations and compared them to existing empirical data. Of these, 592 models (~5%) were plausible based on the resulting mean expected number of segregating variants. These plausible models shared several commonalities shedding light on intra-host SARS-CoV-2 evolutionary dynamics: severe infection bottlenecks, low levels of reproductive skew, and a distribution of fitness effects skewed towards strongly deleterious mutations. We also describe important areas of model uncertainty and highlight additional sequence data that may help to further refine a baseline model. This study lays the groundwork for the improved analysis of existing and future SARS-CoV-2 within-patient data.

The SARS-CoV-2 mutation landscape is shaped before replication starts

Mutation landscapes and signatures have been thoroughly studied in SARS-CoV-2. Here, we analyse those patterns and link their changes to the viral replication tissue in the respiratory tract. Surprisingly, a substantial difference in those patterns is observed in samples from vaccinated patients. Hence, we propose a model to explain where those mutations could originate during the replication cycle.

CoVigator-A Knowledge Base for Navigating SARS-CoV-2 Genomic Variants

BACKGROUND

The outbreak of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) resulted in the global COVID-19 pandemic. The urgency for an effective SARS-CoV-2 vaccine has led to the development of the first series of vaccines at unprecedented speed. The discovery of SARS-CoV-2 spike-glycoprotein mutants, however, and consequentially the potential to escape vaccine-induced protection and increased infectivity, demonstrates the persisting importance of monitoring SARS-CoV-2 mutations to enable early detection and tracking of genomic variants of concern.

RESULTS

We developed the CoVigator tool with three components: (1) a knowledge base that collects new SARS-CoV-2 genomic data, processes it and stores its results; (2) a comprehensive variant calling pipeline; (3) an interactive dashboard highlighting the most relevant findings. The knowledge base routinely downloads and processes virus genome assemblies or raw sequencing data from the COVID-19 Data Portal (C19DP) and the European Nucleotide Archive (ENA), respectively. The results of variant calling are visualized through the dashboard in the form of tables and customizable graphs, making it a versatile tool for tracking SARS-CoV-2 variants. We put a special emphasis on the identification of intrahost mutations and make available to the community what is, to the best of our knowledge, the largest dataset on SARS-CoV-2 intrahost mutations. In the spirit of open data, all CoVigator results are available for download. The CoVigator dashboard is accessible via covigator.tron-mainz.de.

CONCLUSIONS

With increasing demand worldwide in genome surveillance for tracking the spread of SARS-CoV-2, CoVigator will be a valuable resource of an up-to-date list of mutations, which can be incorporated into global efforts.

Early warning of emerging infectious diseases based on multimodal data

The coronavirus disease 2019 (COVID-19) pandemic has dramatically increased the awareness of emerging infectious diseases. The advancement of multiomics analysis technology has resulted in the development of several databases containing virus information. Several scientists have integrated existing data on viruses to construct phylogenetic trees and predict virus mutation and transmission in different ways, providing prospective technical support for epidemic prevention and control. This review summarized the databases of known emerging infectious viruses and techniques focusing on virus variant forecasting and early warning. It focuses on the multi-dimensional information integration and database construction of emerging infectious viruses, virus mutation spectrum construction and variant forecast model, analysis of the affinity between mutation antigen and the receptor, propagation model of virus dynamic evolution, and monitoring and early warning for variants. As people have suffered from COVID-19 and repeated flu outbreaks, we focused on the research results of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza viruses. This review comprehensively viewed the latest virus research and provided a reference for future virus prevention and control research.

Epidemiological inference for emerging viruses using segregating sites

Epidemiological models are commonly fit to case and pathogen sequence data to estimate parameters and to infer unobserved disease dynamics. Here, we present an inference approach based on sequence data that is well suited for model fitting early on during the expansion of a viral lineage. Our approach relies on a trajectory of segregating sites to infer epidemiological parameters within a Sequential Monte Carlo framework. Using simulated data, we first show that our approach accurately recovers key epidemiological quantities under a single-introduction scenario. We then apply our approach to SARS-CoV-2 sequence data from France, estimating a basic reproduction number of approximately 2.3-2.7 under an epidemiological model that allows for multiple introductions. Our approach presented here indicates that inference approaches that rely on simple population genetic summary statistics can be informative of epidemiological parameters and can be used for reconstructing infectious disease dynamics during the early expansion of a viral lineage.

Modeling identifies variability in SARS-CoV-2 uptake and eclipse phase by infected cells as principal drivers of extreme variability in nasal viral load in the 48 h post infection

The SARS-CoV-2 coronavirus continues to evolve with scores of mutations of the spike, membrane, envelope, and nucleocapsid structural proteins that impact pathogenesis. Infection data from nasal swabs, nasal PCR assays, upper respiratory samples, ex vivo cell cultures and nasal epithelial organoids reveal extreme variabilities in SARS-CoV-2 RNA titers within and between the variants. Some variabilities are naturally prone to clinical testing protocols and experimental controls. Here we focus on nasal viral load sensitivity arising from the timing of sample collection relative to onset of infection and from heterogeneity in the kinetics of cellular infection, uptake, replication, and shedding of viral RNA copies. The sources of between-variant variability are likely due to SARS-CoV-2 structural protein mutations, whereas within-variant population variability is likely due to heterogeneity in cellular response to that particular variant. With the physiologically faithful, agent-based mechanistic model of inhaled exposure and infection from (Chen et al., 2022), we perform statistical sensitivity analyses of the progression of nasal viral titers in the first 0-48 h post infection, focusing on three kinetic mechanisms. Model simulations reveal shorter latency times of infected cells (including cellular uptake, viral RNA replication, until the onset of viral RNA shedding) exponentially accelerate nasal viral load. Further, the rate of infectious RNA copies shed per day has a proportional influence on nasal viral load. Finally, there is a very weak, negative correlation of viral load with the probability of infection per virus-cell encounter, the model proxy for spike-receptor binding affinity.

Web Resources for SARS-CoV-2 Genomic Database, Annotation, Analysis and Variant Tracking

The SARS-CoV-2 genomic data continue to grow, providing valuable information for researchers and public health officials. Genomic analysis of these data sheds light on the transmission and evolution of the virus. To aid in SARS-CoV-2 genomic analysis, many web resources have been developed to store, collate, analyze, and visualize the genomic data. This review summarizes web resources used for the SARS-CoV-2 genomic epidemiology, covering data management and sharing, genomic annotation, analysis, and variant tracking. The challenges and further expectations for these web resources are also discussed. Finally, we highlight the importance and need for continued development and improvement of related web resources to effectively track the spread and understand the evolution of the virus.

Maximum likelihood pandemic-scale phylogenetics

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

Antiviral Activity of Active Materials: Standard and Finger-Pad-Based Innovative Experimental Approaches

Environmental surfaces, including high-touch surfaces (HITS), bear a high risk of becoming fomites and can participate in viral dissemination through contact and transmission to other persons, due to the capacity of viruses to persist on such contaminated surface before being transferred to hands or other supports at sufficient concentration to initiate infection through direct contact. Interest in the development of self-decontaminating materials as additional safety measures towards preventing viral infectious disease transmission has been growing. Active materials are expected to reduce the viral charge on surfaces over time and consequently limit viral transmission capacity through direct contact. In this study, we compared antiviral activities obtained using three different experimental procedures by assessing the survival of an enveloped virus (influenza virus) and non-enveloped virus (feline calicivirus) over time on a reference surface and three active materials. Our data show that experimental test conditions can have a substantial impact of over 1 log₁₀ on the antiviral activity of active material for the same contact period, depending on the nature of the virus. We then developed an innovative and reproducible approach based on finger-pad transfer to evaluate the antiviral activity of HITS against a murine norovirus inoculum under conditions closely reflecting real-life surface exposure.

Developing an appropriate evolutionary baseline model for the study of SARS-CoV-2 patient samples

Over the past 3 years, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has spread through human populations in several waves, resulting in a global health crisis. In response, genomic surveillance efforts have proliferated in the hopes of tracking and anticipating the evolution of this virus, resulting in millions of patient isolates now being available in public databases. Yet, while there is a tremendous focus on identifying newly emerging adaptive viral variants, this quantification is far from trivial. Specifically, multiple co-occurring and interacting evolutionary processes are constantly in operation and must be jointly considered and modeled in order to perform accurate inference. We here outline critical individual components of such an evolutionary baseline model-mutation rates, recombination rates, the distribution of fitness effects, infection dynamics, and compartmentalization-and describe the current state of knowledge pertaining to the related parameters of each in SARS-CoV-2. We close with a series of recommendations for future clinical sampling, model construction, and statistical analysis.

Risk assessment of banknotes as a fomite of SARS-CoV-2 in cash payment transactions

The COVID 19 pandemic has triggered concerns and assumptions globally about transmission of the SARS-CoV-2 virus via cash transactions. This paper assesses the risk of contracting COVID-19 through exposure to SARS-CoV-2 via cash acting as a fomite in payment transactions. A quantitative microbial risk assessment was conducted for a scenario assuming an infectious person at the onset of symptoms, when virion concentrations in coughed droplets are at their highest. This person then contaminates a banknote by coughing on it and immediately hands it over to another person, who might then be infected by transferring the virions with a finger from the contaminated banknote to a facial mucous membrane. The scenario considered transfer efficiency of virions on the banknote to fingertips when droplets were still wet and after having dried up and subsequently being touched by finger printing or rubbing the object. Accounting for the likelihood of the scenario to occur by considering (1) a local prevalence of 100 COVID-19 cases/100,000 persons, (2) a maximum of about one-fifth of infected persons transmit high virus loads, and (3) the numbers of cash transactions/person/day, the risk of contracting COVID-19 via person-to-person cash transactions was estimated to be much lower than once per 39,000 days (107 years) for a single person. In the general populace, there will be a maximum of 2.6 expected cases/100,000 persons/day. The risk for a cashier at an average point of sale was estimated to be much less than once per 430 working days (21 months). The depicted scenario is a rare event, therefore, for a single person, the risk of contracting COVID-19 via person-to-person cash transactions is very low. At a point of sale, the risk to the cashier proportionally increases but it is still low.

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

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

Cross-disciplinary information for understanding macroevolution

Many different macroevolutionary models can produce the same observations. Despite efforts in building more complex and realistic models, it may still be difficult to distinguish the processes that have generated the biodiversity we observe. In this opinion we argue that we can make new progress by reaching out across disciplines, relying on independent data and theory to constrain macroevolutionary inference. Using mainly paleontological insights and data, we illustrate how we can eliminate less plausible or implausible models, and/or parts of parameter space, while applying comparative phylogenetic approaches. We emphasize that such cross-disciplinary insights and data can be drawn between many other disciplines relevant to macroevolution. We urge cross-disciplinary training, and collaboration using common-use databases as a platform for increasing our understanding.

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

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

Accelerated SARS-CoV-2 intrahost evolution leading to distinct genotypes during chronic infection

The chronic infection hypothesis for novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant emergence is increasingly gaining credence following the appearance of Omicron. Here, we investigate intrahost evolution and genetic diversity of lineage B.1.517 during a SARS-CoV-2 chronic infection lasting for 471 days (and still ongoing) with consistently recovered infectious virus and high viral genome copies. During the infection, we find an accelerated virus evolutionary rate translating to 35 nucleotide substitutions per year, approximately 2-fold higher than the global SARS-CoV-2 evolutionary rate. This intrahost evolution results in the emergence and persistence of at least three genetically distinct genotypes, suggesting the establishment of spatially structured viral populations continually reseeding different genotypes into the nasopharynx. Finally, we track the temporal dynamics of genetic diversity to identify advantageous mutations and highlight hallmark changes for chronic infection. Our findings demonstrate that untreated chronic infections accelerate SARS-CoV-2 evolution, providing an opportunity for the emergence of genetically divergent variants.

Comprehensive Comparison of Seven SARS-CoV-2-Specific Surrogate Virus Neutralization and Anti-Spike IgG Antibody Assays Using a Live-Virus Neutralization Assay as a Reference

Neutralizing antibodies (nAbs) are considered a valuable marker for measuring humoral immunity against SARS-CoV-2. However, live-virus neutralization tests (NTs) require high-biosafety-level laboratories and are time-consuming. Therefore, surrogate virus neutralization tests (sVNTs) have been widely applied, but unlike most anti-spike (S) antibody assays, NTs and sVNTs are not harmonized, requiring further evaluation and comparative analyses. This study compared seven commercial sVNTs and anti-S-antibody assays with a live-virus NT as a reference, using a panel of 720 single and longitudinal serum samples from 666 convalescent patients after SARS-CoV-2 infection. The sensitivity of these assays for detecting antibodies ranged from 48 to 94% after PCR-confirmed infection and from 56% to 100% relative to positivity in the in-house live-virus NT. Furthermore, we performed receiver operating characteristic (ROC) curve analyses to determine which immunoassays were most suitable for assessing nAb titers exceeding a specific cutoff (NT titer, ≥80) and found that the NeutraLISA and the cPass assays reached the highest area under the curve (AUC), exceeding 0.91. In addition, when the assays were compared for their correlation with nAb kinetics over time in a set of longitudinal samples, the extent of the measured decrease of nAbs after infection varied widely among the evaluated immunoassays. Finally, in vaccinated convalescent patients, high titers of nAbs exceeded the upper limit of the evaluated assays' quantification ranges. Based on data from this study, we conclude that commercial immunoassays are acceptable substitutes for live-virus NTs, particularly when additional adapted cutoffs are employed to detect nAbs beyond a specific threshold titer. IMPORTANCE While the measurement of neutralizing antibodies is considered a valuable tool in assessing protection against SARS-CoV-2, neutralization tests employ live-virus isolates and cell culture, requiring advanced laboratory biosafety levels. Including a large sample panel (over 700 samples), this study provides adapted cutoff values calculated for seven commercial immunoassays (including four surrogate neutralization assays and a protein-based microarray) that robustly correlate with specific titers of neutralizing antibodies.

Single-Center Experience in Detecting Influenza Virus, RSV and SARS-CoV-2 at the Emergency Department

Reverse transcription polymerase chain reaction (RT-PCR) on respiratory tract swabs has become the gold standard for sensitive and specific detection of influenza virus, respiratory syncytial virus (RSV) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this retrospective analysis, we report on the successive implementation and routine use of multiplex RT-PCR testing for patients admitted to the Internal Medicine Emergency Department (ED) at a tertiary care center in Western Austria, one of the hotspots in the early coronavirus disease 2019 (COVID-19) pandemic in Europe. Our description focuses on the use of the Cepheid® Xpert® Xpress closed RT-PCR system in point-of-care testing (POCT). Our indications for RT-PCR testing changed during the observation period: From the cold season 2016/2017 until the cold season 2019/2020, we used RT-PCR to diagnose influenza or RSV infection in patients with fever and/or respiratory symptoms. Starting in March 2020, we used the RT-PCR for SARS-CoV-2 and a multiplex version for the combined detection of all these three respiratory viruses to also screen subjects who did not present with symptoms of infection but needed in-hospital medical treatment for other reasons. Expectedly, the switch to a more liberal RT-PCR test strategy resulted in a substantial increase in the number of tests. Nevertheless, we observed an immediate decline in influenza virus and RSV detections in early 2020 that coincided with public SARS-CoV-2 containment measures. In contrast, the extensive use of the combined RT-PCR test enabled us to monitor the re-emergence of influenza and RSV detections, including asymptomatic cases, at the end of 2022 when COVID-19 containment measures were no longer in place. Our analysis of PCR results for respiratory viruses from a real-life setting at an ED provides valuable information on the epidemiology of those infections over several years, their contribution to morbidity and need for hospital admission, the risk for nosocomial introduction of such infection into hospitals from asymptomatic carriers, and guidance as to how general precautions and prophylactic strategies affect the dynamics of those infections.

Rapid transmission and tight bottlenecks constrain the evolution of highly transmissible SARS-CoV-2 variants

Transmission bottlenecks limit the spread of novel mutations and reduce the efficiency of selection along a transmission chain. While increased force of infection, receptor binding, or immune evasion may influence bottleneck size, the relationship between transmissibility and the transmission bottleneck is unclear. Here we compare the transmission bottleneck of non-VOC SARS-CoV-2 lineages to those of Alpha, Delta, and Omicron. We sequenced viruses from 168 individuals in 65 households. Most virus populations had 0-1 single nucleotide variants (iSNV). From 64 transmission pairs with detectable iSNV, we identify a per clade bottleneck of 1 (95% CI 1-1) for Alpha, Delta, and Omicron and 2 (95% CI 2-2) for non-VOC. These tight bottlenecks reflect the low diversity at the time of transmission, which may be more pronounced in rapidly transmissible variants. Tight bottlenecks will limit the development of highly mutated VOC in transmission chains, adding to the evidence that selection over prolonged infections may drive their evolution.

Characterization of SARS-CoV-2 Aerosols Dispersed During Noninvasive Respiratory Support of Patients With COVID-19

BACKGROUND

In the midst of the COVID-19 pandemic, noninvasive respiratory support (NRS) therapies such as high-flow nasal cannula (HFNC) and noninvasive ventilation (NIV) were central to respiratory care. The extent to which these treatments increase the generation and dispersion of infectious respiratory aerosols is not fully understood. The objective of this study was to characterize SARS-CoV-2 aerosol dispersion from subjects with COVID-19 undergoing NRS therapy.

METHODS

Several different aerosol sampling devices were used to collect air samples in the vicinity of 31 subjects with COVID-19, most of whom were receiving NRS therapy, primarily HFNC. Aerosols were collected onto filters and analyzed for the presence of SARS-CoV-2 RNA. Additional measurements were collected in an aerosol chamber with healthy adult subjects using respiratory therapy devices under controlled and reproducible conditions.

RESULTS

Fifty aerosol samples were collected from subjects receiving HFNC or NIV therapy, whereas 6 samples were collected from subjects not receiving NRS. Only 4 of the 56 aerosol samples were positive for SARS-CoV-2 RNA, and all positive samples were collected using a high air flow scavenger mask collection device placed in close proximity to the subject. The chamber measurements with healthy subjects did not show any significant increase in aerosol dispersion caused by the respiratory therapy devices compared to baseline.

CONCLUSIONS

Our findings demonstrate very limited detection of SARS-CoV-2-containing aerosols in the vicinity of subjects with COVID-19 receiving NRS therapies in the clinical setting. These results, combined with controlled chamber measurements showing that HFNC and NIV device usage was not associated with increased aerosol dispersion, suggest that NRS therapies do not result in increased dispersal of aerosols in the clinical setting.

Risk assessment of SARS-CoV-2 transmission in hospitality employees in a highly frequented tourist area

Right from the start of the COVID pandemic in January 2020, the entire tourism sector was put under immense pressure because of its assumed role in SARS-CoV-2 transmission and infection dynamics. Based on reports of single superspreading events in the early days of the pandemic, the hotel industry appeared in a bad light that impaired a strategic risk-assessment of existing transmission risks between tourists and employees. We prospectively analysed samples of 679 employees of 21 hotels and restaurants from July 2020 to December 2020, a time during which more than 1.5 million tourists visited the Lübeck/Ostholstein Baltic Sea vacation area in Northern Germany. Employees were tested up to three times for an acute SARS-CoV-2 infection (PCR from nasopharyngeal swabs) and the presence of SARS-CoV-2 specific antibodies, and were asked to complete a short questionnaire. Despite the massive increase in tourist influx, no significant increase in SARS-CoV-2 cases was observed amongst employees of the tourism sector from July to September 2020. In a cluster-outbreak analysis of 104 study participants of one single hotel in the Lübeck/Ostholstein region in October 2020 being employed in the low-wage sector "housekeeping" could be determined as major risk factor for becoming infected. In conclusion, in a low incidence setting, touristic activities are safe under COVID-related hygiene measures for both the local population and employees of the tourism sector. Whereas, the field of work is a potential risk factor for increased infection dynamics.

Viral variant-resolved wastewater surveillance of SARS-CoV-2 at national scale

SARS-CoV-2 surveillance by wastewater-based epidemiology is poised to provide a complementary approach to sequencing individual cases. However, robust quantification of variants and de novo detection of emerging variants remains challenging for existing strategies. We deep sequenced 3,413 wastewater samples representing 94 municipal catchments, covering >59% of the population of Austria, from December 2020 to February 2022. Our system of variant quantification in sewage pipeline designed for robustness (termed VaQuERo) enabled us to deduce the spatiotemporal abundance of predefined variants from complex wastewater samples. These results were validated against epidemiological records of >311,000 individual cases. Furthermore, we describe elevated viral genetic diversity during the Delta variant period, provide a framework to predict emerging variants and measure the reproductive advantage of variants of concern by calculating variant-specific reproduction numbers from wastewater. Together, this study demonstrates the power of national-scale WBE to support public health and promises particular value for countries without extensive individual monitoring.

Persistence and occurrence of SARS-CoV-2 in water and wastewater environments: a review of the current literature

As the world continues to cope with the COVID-19 pandemic, emerging evidence indicates that respiratory transmission may not the only pathway in which the virus can be spread. This review paper aims to summarize current knowledge surrounding possible fecal-oral transmission of SARS-CoV-2. It covers recent evidence of proliferation of SARS-CoV-2 in the gastrointestinal tract, as well as presence and persistence of SARS-CoV-2 in water, and suggested future directions. Research indicates that SARS-CoV-2 can actively replicate in the human gastrointestinal system and can subsequently be shed via feces. Several countries have reported SARS-CoV-2 RNA fractions in wastewater systems, and various factors such as temperature and presence of solids have been shown to affect the survival of the virus in water. The detection of RNA does not guarantee infectivity, as current methods such as RT-qPCR are not yet able to distinguish between infectious and non-infectious particles. More research is needed to determine survival time and potential infectivity, as well as to develop more accurate methods for detection and surveillance.

SARS-CoV-2 intra-host single-nucleotide variants associated with disease severity

Variants of severe acute respiratory syndrome coronavirus 2 frequently arise within infected individuals. Here, we explored the level and pattern of intra-host viral diversity in association with disease severity. Then, we analyzed information underlying these nucleotide changes to infer the impetus including mutational signatures and immune selection from neutralizing antibody or T-cell recognition. From 23 January to 31 March 2020, a set of cross-sectional samples were collected from individuals with homogeneous founder virus regardless of disease severity. Intra-host single-nucleotide variants (iSNVs) were enumerated using deep sequencing. Human leukocyte antigen (HLA) alleles were genotyped by Sanger sequencing. Medical records were collected and reviewed by attending physicians. A total of 836 iSNVs (3-106 per sample) were identified and distributed in a highly individualized pattern. The number of iSNVs paced with infection duration peaked within days and declined thereafter. These iSNVs did not stochastically arise due to a strong bias toward C > U/G > A and U > C/A > G substitutions in reciprocal proportion with escalating disease severity. Eight nonsynonymous iSNVs in the receptor-binding domain could escape from neutralization, and eighteen iSNVs were significantly associated with specific HLA alleles. The level and pattern of iSNVs reflect the in vivo viral-host interaction and the disease pathogenesis.