Transmission dynamics of SARS-CoV-2 within-host diversity in two major hospital outbreaks in South Africa

Genomic epidemiology reveals the variation and transmission properties of SARS-CoV-2 in a single-source community outbreak

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused the coronavirus disease 2019 (COVID-19) pandemic, which is still a global public health concern. During March 2022, a rapid and confined single-source outbreak of SARS-CoV-2 was identified in a community in Nanjing municipal city. Overall, 95 individuals had laboratory-confirmed SARS-CoV-2 infection. The whole genomes of 61 viral samples were obtained, which were all members of the BA.2.2 lineage and clearly demonstrated the presence of one large clade, and all the infections could be traced back to the original index case. The most distant sequence from the index case presented a difference of 4 SNPs, and 118 intrahost single-nucleotide variants (iSNVs) at 74 genomic sites were identified. Some minor iSNVs can be transmitted and subsequently rapidly fixed in the viral population. The minor iSNVs transmission resulted in at least two nucleotide substitutions among all seven SNPs identified in the outbreak, generating genetically diverse populations. We estimated the overall transmission bottleneck size to be 3 using 11 convincing donor-recipient transmission pairs. Our study provides new insights into genomic epidemiology and viral transmission, revealing how iSNVs become fixed in local clusters, followed by viral transmission across the community, which contributes to population diversity.

The burden and dynamics of hospital-acquired SARS-CoV-2 in England

Hospital-based transmission had a dominant role in Middle East respiratory syndrome coronavirus (MERS-CoV) and severe acute respiratory syndrome coronavirus (SARS-CoV) epidemics1,2, but large-scale studies of its role in the SARS-CoV-2 pandemic are lacking. Such transmission risks spreading the virus to the most vulnerable individuals and can have wider-scale impacts through hospital-community interactions. Using data from acute hospitals in England, we quantify within-hospital transmission, evaluate likely pathways of spread and factors associated with heightened transmission risk, and explore the wider dynamical consequences. We estimate that between June 2020 and March 2021 between 95,000 and 167,000 inpatients acquired SARS-CoV-2 in hospitals (1% to 2% of all hospital admissions in this period). Analysis of time series data provided evidence that patients who themselves acquired SARS-CoV-2 infection in hospital were the main sources of transmission to other patients. Increased transmission to inpatients was associated with hospitals having fewer single rooms and lower heated volume per bed. Moreover, we show that reducing hospital transmission could substantially enhance the efficiency of punctuated lockdown measures in suppressing community transmission. These findings reveal the previously unrecognized scale of hospital transmission, have direct implications for targeting of hospital control measures and highlight the need to design hospitals better equipped to limit the transmission of future high-consequence pathogens.

Inferring Viral Transmission Pathways from Within-Host Variation

Genome sequencing can offer critical insight into pathogen spread in viral outbreaks, but existing transmission inference methods use simplistic evolutionary models and only incorporate a portion of available genetic data. Here, we develop a robust evolutionary model for transmission reconstruction that tracks the genetic composition of within-host viral populations over time and the lineages transmitted between hosts. We confirm that our model reliably describes within-host variant frequencies in a dataset of 134,682 SARS-CoV-2 deep-sequenced genomes from Massachusetts, USA. We then demonstrate that our reconstruction approach infers transmissions more accurately than two leading methods on synthetic data, as well as in a controlled outbreak of bovine respiratory syncytial virus and an epidemiologically-investigated SARS-CoV-2 outbreak in South Africa. Finally, we apply our transmission reconstruction tool to 5,692 outbreaks among the 134,682 Massachusetts genomes. Our methods and results demonstrate the utility of within-host variation for transmission inference of SARS-CoV-2 and other pathogens, and provide an adaptable mathematical framework for tracking within-host evolution.

Whole-genome sequencing to investigate transmission of SARS-CoV-2 in the acute healthcare setting: a systematic review

BACKGROUND

Whole-genome sequencing (WGS) has been used widely to elucidate transmission of SARS-CoV-2 in acute healthcare settings, and to guide infection, prevention, and control (IPC) responses.

AIM

To systematically appraise available literature, published between January 1st, 2020 and June 30th, 2022, describing the implementation of WGS in acute healthcare settings to characterize nosocomial SARS-CoV-2 transmission.

METHODS

Searches of the PubMed, Embase, Ovid MEDLINE, EBSCO MEDLINE, and Cochrane Library databases identified studies in English reporting the use of WGS to investigate SARS-CoV-2 transmission in acute healthcare environments. Publications involved data collected up to December 31st, 2021, and findings were reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement.

FINDINGS

In all, 3088 non-duplicate records were retrieved; 97 met inclusion criteria, involving 62 outbreak analyses and 35 genomic surveillance studies. No publications from low-income countries were identified. In 87/97 (90%), WGS supported hypotheses for nosocomial transmission, while in 46 out of 97 (47%) suspected transmission events were excluded. An IPC intervention was attributed to the use of WGS in 18 out of 97 (18%); however, only three (3%) studies reported turnaround times ≤7 days facilitating near real-time IPC action, and none reported an impact on the incidence of nosocomial COVID-19 attributable to WGS.

CONCLUSION

WGS can elucidate transmission of SARS-CoV-2 in acute healthcare settings to enhance epidemiological investigations. However, evidence was not identified to support sequencing as an intervention to reduce the incidence of SARS-CoV-2 in hospital or to alter the trajectory of active outbreaks.

SARS-CoV-2 Co-Infections and Recombinations Identified by Long-Read Single-Molecule Real-Time Sequencing

Co-infection with at least 2 strains of virus is the prerequisite for recombination, one of the means of genetic diversification. Little is known about the prevalence of these events in SARS-CoV-2, partly because it is difficult to detect them. We used long-read PacBio single-molecule real-time (SMRT) sequencing technology to sequence whole genomes and targeted regions for haplotyping. We identified 17 co-infections with SARS-CoV-2 strains belonging to different clades in 6829 samples sequenced between January and October, 2022 (prevalence 0.25%). There were 3 Delta/Omicron co-infections and 14 Omicron/Omicron co-infections (4 cases of 21K/21L, 1 case of 21L/22A, 2 cases of 21L/22B, 4 cases of 22A/22B, 2 cases of 22B/22C and 1 case of 22B/22E). Four of these patients (24%) also harbored recombinant minor haplotypes, including one with a recombinant virus that was selected in the viral quasispecies over the course of his chronic infection. While co-infections remain rare among SARS-CoV-2-infected individuals, long-read SMRT sequencing is a useful tool for detecting them as well as recombinant events, providing the basis for assessing their clinical impact, and a precise indicator of epidemic evolution. IMPORTANCE SARS-CoV-2 variants have been responsible for the successive waves of infection over the 3 years of pandemic. While co-infection followed by recombination is one driver of virus evolution, there have been few reports of co-infections, mainly between Delta and Omicron variants or between the first 2 Omicron variants 21K_BA.1 and 21L_BA.2. The 17 co-infections we detected during 2022 included cases with the recent clades of Omicron 22A, 22B, 22C, and 22E; 24% harbored recombinant variants. This study shows that long-read SMRT sequencing is well suited to SARS-CoV-2 genomic surveillance.

Traceability of SARS-CoV-2 transmission through quasispecies analysis

During COVID-19 pandemic, consensus genomic sequences were used for rapidly monitor the spread of the virus worldwide. However, less attention was paid to intrahost genetic diversity. In fact, in the infected host, SARS-CoV-2 consists in an ensemble of replicating and closely related viral variants so-called quasispecies. Here we show that intrahost single nucleotide variants (iSNVs) represent a target for contact tracing analysis. Our data indicate that in the acute phase of infection, in highly likely transmission links, the number of viral particles transmitted from one host to another (bottleneck size) is large enough to propagate iSNVs among individuals. Furthermore, we demonstrate that, during SARS-CoV-2 outbreaks when the consensus sequences are identical, it is possible to reconstruct the transmission chains by genomic investigations of iSNVs. Specifically, we found that it is possible to identify transmission chains by limiting the analysis of iSNVs to only three well-conserved genes, namely nsp2, ORF3, and ORF7.

SARS-CoV-2 spike protein diversity at an intra-host level, among SARS-CoV-2 infected individuals in South Africa, 2020 to 2022

Intra-host diversity studies are used to characterise the mutational heterogeneity of SARS-CoV-2 infections in order to understand the impact of virus-host adaptations. This study investigated the frequency and diversity of the spike (S) protein mutations within SARS-CoV-2 infected South African individuals. The study included SARS-CoV-2 respiratory samples, from individuals of all ages, received at the National Health Laboratory Service at Charlotte Maxeke Johannesburg Academic hospital, Gauteng, South Africa, from June 2020 to May 2022. Single nucleotide polymorphism (SNP) assays and whole genome sequencing were performed on a random selection of SARS-CoV-2 positive samples. The allele frequency (AF) was determined using TaqMan Genotyper software for SNP PCR analysis and galaxy.eu for analysis of FASTQ reads from sequencing. The SNP assays identified 5.3% (50/948) of Delta cases with heterogeneity at delY144 (4%; 2/50), E484Q (6%; 3/50), N501Y (2%; 1/50) and P681H (88%; 44/50), however only heterogeneity for E484Q and delY144 were confirmed by sequencing. From sequencing we identified 9% (210/2381) of cases with Beta, Delta, Omicron BA.1, BA.2.15, and BA.4 lineages that had heterogeneity in the S protein. Heterogeneity was primarily identified at positions 19 (1.4%) with T19IR (AF 0.2-0.7), 371 (92.3%) with S371FP (AF 0.1-1.0), and 484 (1.9%) with E484AK (0.2-0.7), E484AQ (AF 0.4-0.5) and E484KQ (AF 0.1-0.4). Mutations at heterozygous amino acid positions 19, 371 and 484 are known antibody escape mutations, however the impact of the combination of multiple substitutions identified at the same position is unknown. Therefore, we hypothesise that intra-host SARS-CoV-2 quasispecies with heterogeneity in the S protein facilitate competitive advantage of variants that can completely/partially evade host's natural and vaccine-induced immune responses.

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.

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.

Utility of SARS-CoV-2 Genomic Sequencing for Understanding Transmission and School Outbreaks

OBJECTIVE

An understanding of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) transmission in schools is important. It is often difficult, using epidemiological information alone, to determine whether cases associated with schools represent multiple introductions from the community or transmission within the school. We describe the use of whole genome sequencing (WGS) in multiple schools to investigate outbreaks of SARS-CoV-2 in the pre-Omicron period.

STUDY DESIGN

School outbreaks were identified for sequencing by local public health units based on multiple cases without known epidemiological links. Cases of SARS-CoV-2 from students and staff from 4 school outbreaks in Ontario underwent WGS and phylogenetic analysis. The epidemiological clinical cohort data and genomic cluster data are described to help further characterize these outbreaks.

RESULTS

A total of 132 positive SARS-CoV-2 cases among students and staff from 4 school outbreaks were identified with 65 (49%) of cases able to be sequenced with high-quality genomic data. The 4 school outbreaks consisted of 53, 37, 21 and 21 positive cases; within each outbreak there were between 8 and 28 different clinical cohorts identified. Among the sequenced cases, between 3 and 7 genetic clusters, defined as different strains, were identified in each outbreak. We found genetically different viruses within several clinical cohorts.

CONCLUSIONS

WGS, together with public health investigation, is a useful tool to investigate SARS-CoV-2 transmission within schools. Its early use has the potential to better understand when transmission may have occurred, can aid in evaluating how well mitigation interventions are working and has the potential to reduce unnecessary school closures when multiple genetic clusters are identified.

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.

Within-host genetic diversity of SARS-CoV-2 lineages in unvaccinated and vaccinated individuals

Viral and host factors can shape SARS-CoV-2 evolution. However, little is known about lineage-specific and vaccination-specific mutations that occur within individuals. Here, we analysed deep sequencing data from 2,820 SARS-CoV-2 respiratory samples with different viral lineages to describe the patterns of within-host diversity under different conditions, including vaccine-breakthrough infections. In unvaccinated individuals, variant of Concern (VOC) Alpha, Delta, and Omicron respiratory samples were found to have higher within-host diversity and were under neutral to purifying selection at the full genome level compared to non-VOC SARS-CoV-2. Breakthrough infections in 2-dose or 3-dose Comirnaty and CoronaVac vaccinated individuals did not increase levels of non-synonymous mutations and did not change the direction of selection pressure. Vaccine-induced antibody or T cell responses did not appear to have significant impact on within-host SARS-CoV-2 sequence diversification. Our findings suggest that vaccination does not increase exploration of SARS-CoV-2 protein sequence space and may not facilitate emergence of viral variants.

Challenges in Harnessing Shared Within-Host Severe Acute Respiratory Syndrome Coronavirus 2 Variation for Transmission Inference

Background

The limited variation observed among severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) consensus sequences makes it difficult to reconstruct transmission linkages in outbreak settings. Previous studies have recovered variation within individual SARS-CoV-2 infections but have not yet measured the informativeness of within-host variation for transmission inference.

Methods

We performed tiled amplicon sequencing on 307 SARS-CoV-2 samples, including 130 samples from 32 individuals in 14 households and 47 longitudinally sampled individuals, from 4 prospective studies with household membership data, a proxy for transmission linkage.

Results

Consensus sequences from households had limited diversity (mean pairwise distance, 3.06 single-nucleotide polymorphisms [SNPs]; range, 0-40). Most (83.1%, 255 of 307) samples harbored at least 1 intrahost single-nucleotide variant ([iSNV] median, 117; interquartile range [IQR], 17-208), above a minor allele frequency threshold of 0.2%. Pairs in the same household shared significantly more iSNVs (mean, 1.20 iSNVs; 95% confidence interval [CI], 1.02-1.39) than did pairs in different households infected with the same viral clade (mean, 0.31 iSNVs; 95% CI, .28-.34), a signal that decreases with increasingly stringent minor allele frequency thresholds. The number of shared iSNVs was significantly associated with an increased odds of household membership (adjusted odds ratio, 1.35; 95% CI, 1.23-1.49). However, the poor concordance of iSNVs detected across sequencing replicates (24.8% and 35.0% above a 0.2% and 1% threshold) confirms technical concerns that current sequencing and bioinformatic workflows do not consistently recover low-frequency within-host variants.

Conclusions

Shared within-host variation may augment the information in consensus sequences for predicting transmission linkages. Improving sensitivity and specificity of within-host variant identification will improve the informativeness of within-host variation.

Lessons learned: use of WGS in real-time investigation of suspected intrahospital SARS-CoV-2 outbreaks

BACKGROUND

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has been a continuing source of hospital-acquired infection and outbreaks. At Akershus University Hospital in Norway, traditional contact tracing has been combined with whole-genome sequencing (WGS) surveillance in real-time to investigate potential hospital outbreaks.

AIM

To describe the advantages and challenges encountered when using WGS as a real-time tool in hospital outbreak investigation and surveillance during the SARS-CoV-2 pandemic.

METHODS

Routine contact tracing in the hospital was performed for all healthcare workers (HCWs) who tested positive for SARS-CoV-2. Viral RNA from all positive patient and HCW samples was sequenced in real-time using nanopore sequencing and the ARTIC Network protocol. Suspected outbreaks involving five or more individuals with viral sequences were described.

FINDINGS

Nine outbreaks were suspected based on contact tracing, and one outbreak was suspected based on WGS results. Five outbreaks were confirmed; of these, two outbreaks were supported but could not be confirmed by WGS with high confidence, one outbreak was found to consist of two different lineages, and two outbreaks were refuted.

CONCLUSIONS

WGS is a valuable tool in hospital outbreak investigations when combined with traditional contact tracing. Inclusion of WGS data improved outbreak demarcation, identified unknown transmission chains, and highlighted weaknesses in existing infection control measures.

Nanomaterials to combat SARS-CoV-2: Strategies to prevent, diagnose and treat COVID-19

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and the associated coronavirus disease 2019 (COVID-19), which severely affect the respiratory system and several organs and tissues, and may lead to death, have shown how science can respond when challenged by a global emergency, offering as a response a myriad of rapid technological developments. Development of vaccines at lightning speed is one of them. SARS-CoV-2 outbreaks have stressed healthcare systems, questioning patients care by using standard non-adapted therapies and diagnostic tools. In this scenario, nanotechnology has offered new tools, techniques and opportunities for prevention, for rapid, accurate and sensitive diagnosis and treatment of COVID-19. In this review, we focus on the nanotechnological applications and nano-based materials (i.e., personal protective equipment) to combat SARS-CoV-2 transmission, infection, organ damage and for the development of new tools for virosurveillance, diagnose and immune protection by mRNA and other nano-based vaccines. All the nano-based developed tools have allowed a historical, unprecedented, real time epidemiological surveillance and diagnosis of SARS-CoV-2 infection, at community and international levels. The nano-based technology has help to predict and detect how this Sarbecovirus is mutating and the severity of the associated COVID-19 disease, thereby assisting the administration and public health services to make decisions and measures for preparedness against the emerging variants of SARS-CoV-2 and severe or lethal COVID-19.

Understanding Early Pandemic Severe Acute Respiratory Syndrome Coronavirus 2 Transmission in a Medical Center by Incorporating Public Sequencing Databases to Mitigate Bias

BACKGROUND

Throughout the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, healthcare workers (HCWs) have faced risk of infection from within the workplace via patients and staff as well as from the outside community, complicating our ability to resolve transmission chains in order to inform hospital infection control policy. Here we show how the incorporation of sequences from public genomic databases aided genomic surveillance early in the pandemic when circulating viral diversity was limited.

METHODS

We sequenced a subset of discarded, diagnostic SARS-CoV-2 isolates between March and May 2020 from Boston Medical Center HCWs and combined this data set with publicly available sequences from the surrounding community deposited in GISAID with the goal of inferring specific transmission routes.

RESULTS

Contextualizing our data with publicly available sequences reveals that 73% (95% confidence interval, 63%-84%) of coronavirus disease 2019 cases in HCWs are likely novel introductions rather than nosocomial spread.

CONCLUSIONS

We argue that introductions of SARS-CoV-2 into the hospital environment are frequent and that expanding public genomic surveillance can better aid infection control when determining routes of transmission.

Within-host diversity of SARS-CoV-2 lineages and effect of vaccination

Viral and host factors can shape SARS-CoV-2 within-host viral diversity and virus evolution. However, little is known about lineage-specific and vaccination-specific mutations that occur within individuals. Here we analysed deep sequencing data from 2,146 SARS-CoV-2 samples with different viral lineages to describe the patterns of within-host diversity in different conditions, including vaccine-breakthrough infections. Variant of Concern (VOC) Alpha, Delta, and Omicron samples were found to have higher within-host nucleotide diversity while being under weaker purifying selection at full genome level compared to non-VOC SARS-CoV-2 viruses. Breakthrough Delta and Omicron infections in Comirnaty and CoronaVac vaccinated individuals appeared to have higher within-host purifying selection at the full-genome and/or Spike gene levels. Vaccine-induced antibody or T cell responses did not appear to have significant impact on within-host SARS-CoV-2 evolution. Our findings suggest that vaccination does not increase SARS-CoV-2 protein sequence space and may not facilitate emergence of more viral variants.

Narrow transmission bottlenecks and limited within-host viral diversity during a SARS-CoV-2 outbreak on a fishing boat

The long-term evolution of viruses is ultimately due to viral mutants that arise within infected individuals and transmit to other individuals. Here, we use deep sequencing to investigate the transmission of viral genetic variation among individuals during a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak that infected the vast majority of crew members on a fishing boat. We deep-sequenced nasal swabs to characterize the within-host viral population of infected crew members, using experimental duplicates and strict computational filters to ensure accurate variant calling. We find that within-host viral diversity is low in infected crew members. The mutations that did fix in some crew members during the outbreak are not observed at detectable frequencies in any of the sampled crew members in which they are not fixed, suggesting that viral evolution involves occasional fixation of low-frequency mutations during transmission rather than persistent maintenance of within-host viral diversity. Overall, our results show that strong transmission bottlenecks dominate viral evolution even during a superspreading event with a very high attack rate.

Statistical Challenges in Tracking the Evolution of SARS-CoV-2

Genomic surveillance of SARS-CoV-2 has been instrumental in tracking the spread and evolution of the virus during the pandemic. The availability of SARS-CoV-2 molecular sequences isolated from infected individuals, coupled with phylodynamic methods, have provided insights into the origin of the virus, its evolutionary rate, the timing of introductions, the patterns of transmission, and the rise of novel variants that have spread through populations. Despite enormous global efforts of governments, laboratories, and researchers to collect and sequence molecular data, many challenges remain in analyzing and interpreting the data collected. Here, we describe the models and methods currently used to monitor the spread of SARS-CoV-2, discuss long-standing and new statistical challenges, and propose a method for tracking the rise of novel variants during the epidemic.

Narrow transmission bottlenecks and limited within-host viral diversity during a SARS-CoV-2 outbreak on a fishing boat.. [PMID: 35169803 PMCID: PMC8845427 DOI: 10.1101/2022.02.09.479546]

The long-term evolution of viruses is ultimately due to viral mutants that arise within infected individuals and transmit to other individuals. Here we use deep sequencing to investigate the transmission of viral genetic variation among individuals during a SARS-CoV-2 outbreak that infected the vast majority of crew members on a fishing boat. We deep-sequenced nasal swabs to characterize the within-host viral population of infected crew members, using experimental duplicates and strict computational filters to ensure accurate variant calling. We find that within-host viral diversity is low in infected crew members. The mutations that did fix in some crew members during the outbreak are not observed at detectable frequencies in any of the sampled crew members in which they are not fixed, suggesting viral evolution involves occasional fixation of low-frequency mutations during transmission rather than persistent maintenance of within-host viral diversity. Overall, our results show that strong transmission bottlenecks dominate viral evolution even during a superspreading event with a very high attack rate.

OUP accepted manuscript

A detailed understanding of how and when severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission occurs is crucial for designing effective prevention measures. Other than contact tracing, genome sequencing provides information to help infer who infected whom. However, the effectiveness of the genomic approach in this context depends on both (high enough) mutation and (low enough) transmission rates. Today, the level of resolution that we can obtain when describing SARS-CoV-2 outbreaks using just genomic information alone remains unclear. In order to answer this question, we sequenced forty-nine SARS-CoV-2 patient samples from ten local clusters in NW Spain for which partial epidemiological information was available and inferred transmission history using genomic variants. Importantly, we obtained high-quality genomic data, sequencing each sample twice and using unique barcodes to exclude cross-sample contamination. Phylogenetic and cluster analyses showed that consensus genomes were generally sufficient to discriminate among independent transmission clusters. However, levels of intrahost variation were low, which prevented in most cases the unambiguous identification of direct transmission events. After filtering out recurrent variants across clusters, the genomic data were generally compatible with the epidemiological information but did not support specific transmission events over possible alternatives. We estimated the effective transmission bottleneck size to be one to two viral particles for sample pairs whose donor–recipient relationship was likely. Our analyses suggest that intrahost genomic variation in SARS-CoV-2 might be generally limited and that homoplasy and recurrent errors complicate identifying shared intrahost variants. Reliable reconstruction of direct SARS-CoV-2 transmission based solely on genomic data seems hindered by a slow mutation rate, potential convergent events, and technical artifacts. Detailed contact tracing seems essential in most cases to study SARS-CoV-2 transmission at high resolution.

Comprehensive Contact Tracing, Testing and Sequencing Show Limited Transmission of SARS-CoV-2 between Children in Schools in Norway, August 2020 to May 2021

The role of children in the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in schools has been a topic of controversy. In this study among school contacts of SARS-CoV-2 positive children in 43 contact-investigations, we investigated SARS-CoV-2 transmission in Norway, August 2020-May 2021. All participants were tested twice within seven to ten days, using SARS-CoV-2 PCR on home-sampled saliva. Positive samples were whole genome sequenced. Among the 559 child contacts, eight tested positive (1.4%, 95% CI 0.62-2.80), with no significant difference between primary (1.0%, 95% CI 0.27-2.53) and secondary schools (2.6%, 95% CI 0.70-6.39), p = 0.229, nor by viral strain, non-Alpha (1.4%, 95% CI 0.50-2.94) and Alpha variant (B.1.1.7) (1.7%, 95% CI 0.21-5.99), p = 0.665. One adult contact (1/100) tested positive. In 34 index cases, we detected 13 different SARS-CoV-2 Pango lineage variants, with B.1.1.7 being most frequent. In the eight contact-investigations with SARS-CoV-2 positive contacts, four had the same sequence identity as the index, one had no relation, and three were inconclusive. With mitigation measures in place, the spread of SARS-CoV-2 from children in schools is limited. By excluding contact-investigations with adult cases known at the time of enrolment, our data provide a valid estimate on the role of children in the transmission of SARS-CoV-2 in schools.

Atypical Prolonged Viral Shedding With Intra-Host SARS-CoV-2 Evolution in a Mildly Affected Symptomatic Patient

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is caused by a respiratory virus with a wide range of manifestations, varying from asymptomatic to fatal cases, with a generally short outcome. However, some individuals present long-term viral shedding. We monitored 38 individuals who were mildly affected by the SARS-CoV-2 infection. Out of the total studied population, three (7.9%) showed atypical events regarding the duration of positivity for viral RNA detection. In one of these atypical cases, a previously HIV-positive male patient presented a SARS-CoV-2 RNA shedding and subgenomic RNA (sgRNA) detected from the upper respiratory tract, respectively, for 232 and 224 days after the onset of the symptoms. The SARS-CoV-2 B.1.1.28 lineage, one of the most prevalent in Brazil in 2020, was identified in this patient in three serial samples. Interestingly, the genomic analyses performed throughout the infectious process showed an increase in the genetic diversity of the B.1.1.28 lineage within the host itself, with viral clearance occurring naturally, without any intervention measures to control the infection. Contrasting widely spread current knowledge, our results indicate that potentially infectious SARS-CoV-2 virus might be shed by much longer periods by some infected patients. This data call attention to better adapted non-pharmacological measures and clinical discharge of patients aiming at preventing the spread of SARS-CoV-2 to the population.

A Global Mutational Profile of SARS-CoV-2: A Systematic Review and Meta-Analysis of 368,316 COVID-19 Patients

Since its first detection in December 2019, more than 232 million cases of COVID-19, including 4.7 million deaths, have been reported by the WHO. The SARS-CoV-2 viral genomes have evolved rapidly worldwide, causing the emergence of new variants. This systematic review and meta-analysis was conducted to provide a global mutational profile of SARS-CoV-2 from December 2019 to October 2020. The review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA), and a study protocol was lodged with PROSPERO. Data from 62 eligible studies involving 368,316 SARS-CoV-2 genomes were analyzed. The mutational data analyzed showed most studies detected mutations in the Spike protein (n = 50), Nucleocapsid phosphoprotein (n = 34), ORF1ab gene (n = 29), 5′-UTR (n = 28) and ORF3a (n = 25). Under the random-effects model, pooled prevalence of SARS-CoV-2 variants was estimated at 95.1% (95% CI; 93.3–96.4%; I² = 98.952%; p = 0.000) while subgroup meta-analysis by country showed majority of the studies were conducted ‘Worldwide’ (n = 10), followed by ‘Multiple countries’ (n = 6) and the USA (n = 5). The estimated prevalence indicated a need to continuously monitor the prevalence of new mutations due to their potential influence on disease severity, transmissibility and vaccine effectiveness.

Rapid incidence estimation from SARS-CoV-2 genomes reveals decreased case detection in Europe during summer 2020

By October 2021, 230 million SARS-CoV-2 diagnoses have been reported. Yet, a considerable proportion of cases remains undetected. Here, we propose GInPipe, a method that rapidly reconstructs SARS-CoV-2 incidence profiles solely from publicly available, time-stamped viral genomes. We validate GInPipe against simulated outbreaks and elaborate phylodynamic analyses. Using available sequence data, we reconstruct incidence histories for Denmark, Scotland, Switzerland, and Victoria (Australia) and demonstrate, how to use the method to investigate the effects of changing testing policies on case ascertainment. Specifically, we find that under-reporting was highest during summer 2020 in Europe, coinciding with more liberal testing policies at times of low testing capacities. Due to the increased use of real-time sequencing, it is envisaged that GInPipe can complement established surveillance tools to monitor the SARS-CoV-2 pandemic. In post-pandemic times, when diagnostic efforts are decreasing, GInPipe may facilitate the detection of hidden infection dynamics.

Epidemiological data and genome sequencing reveals that nosocomial transmission of SARS-CoV-2 is underestimated and mostly mediated by a small number of highly infectious individuals

OBJECTIVES

Despite robust efforts, patients and staff acquire SARS-CoV-2 infection in hospitals. We investigated whether whole-genome sequencing enhanced the epidemiological investigation of healthcare-associated SARS-CoV-2 acquisition.

METHODS

From 17-November-2020 to 5-January-2021, 803 inpatients and 329 staff were diagnosed with SARS-CoV-2 infection at four Oxfordshire hospitals. We classified cases using epidemiological definitions, looked for a potential source for each nosocomial infection, and evaluated genomic evidence supporting transmission.

RESULTS

Using national epidemiological definitions, 109/803(14%) inpatient infections were classified as definite/probable nosocomial, 615(77%) as community-acquired and 79(10%) as indeterminate. There was strong epidemiological evidence to support definite/probable cases as nosocomial. Many indeterminate cases were likely infected in hospital: 53/79(67%) had a prior-negative PCR and 75(95%) contact with a potential source. 89/615(11% of all 803 patients) with apparent community-onset had a recent hospital exposure. Within 764 samples sequenced 607 genomic clusters were identified (>1 SNP distinct). Only 43/607(7%) clusters contained evidence of onward transmission (subsequent cases within ≤ 1 SNP). 20/21 epidemiologically-identified outbreaks contained multiple genomic introductions. Most (80%) nosocomial acquisition occurred in rapid super-spreading events in settings with a mix of COVID-19 and non-COVID-19 patients.

CONCLUSIONS

Current surveillance definitions underestimate nosocomial acquisition. Most nosocomial transmission occurs from a relatively limited number of highly infectious individuals.

HIV infection drives interferon signaling within intestinal SARS-CoV-2 target cells

SARS-CoV-2 infects epithelial cells of the human gastrointestinal (GI) tract and causes related symptoms. HIV infection impairs gut homeostasis and is associated with an increased risk of COVID-19 fatality. To investigate the potential link between these observations, we analyzed single-cell transcriptional profiles and SARS-CoV-2 entry receptor expression across lymphoid and mucosal human tissue from chronically HIV-infected individuals and uninfected controls. Absorptive gut enterocytes displayed the highest coexpression of SARS-CoV-2 receptors ACE2, TMPRSS2, and TMPRSS4, of which ACE2 expression was associated with canonical interferon response and antiviral genes. Chronic treated HIV infection was associated with a clear antiviral response in gut enterocytes and, unexpectedly, with a substantial reduction of ACE2 and TMPRSS2 target cells. Gut tissue from SARS-CoV-2–infected individuals, however, showed abundant SARS-CoV-2 nucleocapsid protein in both the large and small intestine, including an HIV-coinfected individual. Thus, upregulation of antiviral response genes and downregulation of ACE2 and TMPRSS2 in the GI tract of HIV-infected individuals does not prevent SARS-CoV-2 infection in this compartment. The impact of these HIV-associated intestinal mucosal changes on SARS-CoV-2 infection dynamics, disease severity, and vaccine responses remains unclear and requires further investigation.