Transmission cluster characteristics of global, regional, and lineage-specific SARS-CoV-2 phylogenies.

The SARS-CoV-2 pandemic has been presenting in periodic waves and multiple variants, of which some dominated over time with increased transmissibility. SARS-CoV-2 is still adapting in the human population, thus it is crucial to understand its evolutionary patterns and dynamics ahead of time. In this work, we analyzed transmission clusters and topology of SARS-CoV-2 phylogenies at the global, regional (North America) and clade-specific (Delta and Omicron) epidemic scales. We used the Nextstrain's nCov open global all-time phylogeny (September 2022, 2,698 strains, 2,243 for North America, 499 for Delta21A, and 543 for Omicron20M), with Nextstrain's clade annotation and Pango lineages. Transmission clusters were identified using Phylopart, DYNAMITE, and several tree imbalance measures were calculated, including staircase-ness, Sackin and Colless index. We found that the phylogenetic clustering profiles of the global epidemic have highest diversification at a distance threshold of 3% (divergence of 10, where the tree sampled median is 49). Phylopart and DYNAMITE clusters moderately-to-highly agree with the Pango nomenclature and the Nextstrain's clade. At the regional and clade-specific scale, transmission clustering profiles tend to flatten and similar clusters are found at distance thresholds between 0.05% and 25%. All the considered phylogenies exhibit high tree imbalance with respect to what expected in random phylogenies, suggesting short infection times and antigenic drift, perhaps due to progressive transition from innate to adaptive immunity in the population.

Predicting emerging SARS-CoV-2 variants of concern through a One Class dynamic anomaly detection algorithm.

OBJECTIVES: The objective of this study is the implementation of an automatic procedure to weekly detect new SARS-CoV-2 variants and non-neutral variants (variants of concern (VOC) and variants of interest (VOI)). METHODS: We downloaded spike protein primary sequences from the public resource GISAID and we represented each sequence as k-mer counts. For each week since 1 July 2020, we evaluate if each sequence represents an anomaly based on a One Class support vector machine (SVM) classification algorithm trained on neutral protein sequences collected from February to June 2020. RESULTS: We assess the ability of the One Class classifier to detect known VOC and VOI, such as Alpha, Delta or Omicron, ahead of their official classification by health authorities. In median, the classifier predicts a non-neutral variant as outlier 10 weeks before the official date of designation as VOC/VOI. DISCUSSION: The identification of non-neutral variants during a pandemic usually relies on indicators available during time, such as changing population size of a variant. Automatic variant surveillance systems based on protein sequences can enhance the fast identification of variants of potential concern. CONCLUSION: Machine learning, and in particular One Class SVM classification, can support the detection of potentially VOC/VOI variants during an evolving pandemics.

Severe Acute Respiratory Syndrome Coronavirus 2 Delta Vaccine Breakthrough Transmissibility in Alachua County, Florida.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Delta variant has caused a dramatic resurgence in infections in the United Sates, raising questions regarding potential transmissibility among vaccinated individuals. METHODS: Between October 2020 and July 2021, we sequenced 4439 SARS-CoV-2 full genomes, 23% of all known infections in Alachua County, Florida, including 109 vaccine breakthrough cases. Univariate and multivariate regression analyses were conducted to evaluate associations between viral RNA burden and patient characteristics. Contact tracing and phylogenetic analysis were used to investigate direct transmissions involving vaccinated individuals. RESULTS: The majority of breakthrough sequences with lineage assignment were classified as Delta variants (74.6%) and occurred, on average, about 3 months (104 ±â€…57.5 days) after full vaccination, at the same time (June-July 2021) of Delta variant exponential spread within the county. Six Delta variant transmission pairs between fully vaccinated individuals were identified through contact tracing, 3 of which were confirmed by phylogenetic analysis. Delta breakthroughs exhibited broad viral RNA copy number values during acute infection (interquartile range, 1.2-8.64 Log copies/mL), on average 38% lower than matched unvaccinated patients (3.29-10.81 Log copies/mL, P < .00001). Nevertheless, 49% to 50% of all breakthroughs, and 56% to 60% of Delta-infected breakthroughs exhibited viral RNA levels above the transmissibility threshold (4 Log copies/mL) irrespective of time after vaccination. CONCLUSIONS: Delta infection transmissibility and general viral RNA quantification patterns in vaccinated individuals suggest limited levels of sterilizing immunity that need to be considered by public health policies. In particular, ongoing evaluation of vaccine boosters should specifically address whether extra vaccine doses curb breakthrough contribution to epidemic spread.

Dynamic Prediction of Non-Neutral SARS-Cov-2 Variants Using Incremental Machine Learning.

In this work we show that Incremental Machine Learning can be used to predict the classification of emerging SARS-CoV-2 lineages, dynamically distinguishing between neutral variants and non-neutral ones, i.e. variants of interest or variants of concerns. Starting from the Spike protein primary sequences collected in the GISAID db, we have derived a set of k-mers features, i.e., aminoacid subsequences with fixed length k. We have then implemented a Logistic Regression Incremental Learner that was monthly tested on the variants collected since February 2020 until October 2021. The average value of balanced accuracy of the classifier is 0.72 ± 0.2, which increased to 0.78 ± 0.16 in the last 12 months. The alpha, beta, gamma, eta, kappa and delta variants were recognized as non-neutral variants with mean recall ∼90%. In summary, incremental learning proved to be a useful instrument for pandemic surveillance, given its capability to update the model on new data over time.

Early Emergence Phase of SARS-CoV-2 Delta Variant in Florida, US.

SARS-CoV-2, the causative agent of COVID-19, emerged in late 2019. The highly contagious B.1.617.2 (Delta) variant of concern (VOC) was first identified in October 2020 in India and subsequently disseminated worldwide, later becoming the dominant lineage in the US. Understanding the local transmission dynamics of early SARS-CoV-2 introductions may inform actionable mitigation efforts during subsequent pandemic waves. Yet, despite considerable genomic analysis of SARS-CoV-2 in the US, several gaps remain. Here, we explore the early emergence of the Delta variant in Florida, US using phylogenetic analysis of representative Florida and globally sampled genomes. We find multiple independent introductions into Florida primarily from North America and Europe, with a minority originating from Asia. These introductions led to three distinct clades that demonstrated varying relative rates of transmission and possessed five distinct substitutions that were 3-21 times more prevalent in the Florida sample as compared to the global sample. Our results underscore the benefits of routine viral genomic surveillance to monitor epidemic spread and support the need for more comprehensive genomic epidemiology studies of emerging variants. In addition, we provide a model of epidemic spread of newly emerging VOCs that can inform future public health responses.

Low-frequency variants in mildly symptomatic vaccine breakthrough infections presents a doubled-edged sword.

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOC) has raised questions regarding vaccine protection against SARS-CoV-2 infection, transmission, and ongoing virus evolution. Twenty-three mildly symptomatic "vaccination breakthrough" infections were identified as early as January 2021 in Alachua County, Florida, among individuals fully vaccinated with either the BNT162b2 (Pfizer) or the Ad26 (Janssen/J&J) vaccines. SARS-CoV-2 genomes were successfully generated for 11 of the vaccine breakthroughs, and 878 individuals in the surrounding area and were included for reference-based phylogenetic investigation. These 11 individuals were characterized by infection with VOCs, but also low-frequency variants present within the surrounding population. Low-frequency mutations were observed, which have been more recently identified as mutations of interest owing to their location within targeted immune epitopes (P812L) and association with increased replicative capacity (L18F). We present these results to posit the nature of the efficacy of vaccines in reducing symptoms as both a blessing and a curse-as vaccination becomes more widespread and self-motivated testing reduced owing to the absence of severe symptoms, we face the challenge of early recognition of novel mutations of potential concern. This case study highlights the critical need for continued testing and monitoring of infection and transmission among individuals regardless of vaccination status.

Earliest detection to date of SARS-CoV-2 in Florida: Identification together with influenza virus on the main entry door of a university building, February 2020.

In February and March, 2020, environmental surface swab samples were collected from the handle of the main entry door of a major university building in Florida, as part of a pilot surveillance project screening for influenza. Samples were taken at the end of regular classroom hours, between the dates of February 1-5 and February 19-March 4, 2020. Influenza A(H1N1)pdm09 virus was isolated from the door handle on four of the 19 days sampled. Both SARS-CoV-2 and A(H1N1)pdm09 virus were detected in a sample collected on February 21, 2020. Based on sequence analysis, the Florida SARS-CoV-2 strain (designated UF-11) was identical to strains being identified in Washington state during the same time period, while the earliest similar sequences were sampled in China/Hubei between Dec 30th 2019 and Jan 5th 2020. The first human case of COVID-19 was not officially reported in Florida until March 1st. In an analysis of sequences from COVID-19 patients in this region of Florida, there was only limited evidence of subsequent dissemination of the UF-11 strain. Identical or highly similar strains, possibly related through a common transmission chain, were detected with increasing frequency in Washington state between end of February and beginning of March. Our data provide further documentation of the rapid early spread of SARS-CoV-2 and underscore the likelihood that closely related strains were cryptically circulating in multiple U.S. communities before the first "official" cases were recognized.

Correction: A Snapshot of SARS-CoV-2 Genome Availability up to April 2020 and its Implications: Data Analysis.

[This corrects the article DOI: 10.2196/19170.].

A snapshot of SARS-CoV-2 genome availability up to April 2020 and its implications

BACKGROUND: : The SARS-CoV-2 pandemic has been growing exponentially, affecting over four million people and causing enormous distress to economies and societies worldwide. A plethora of analyses based on viral sequences has already been published in scientific journals, as well as through non-peer reviewed channels, to investigate SARS-CoV-2 genetic heterogeneity and spatiotemporal dissemination. Yet, a systematic investigation of phylogenetic information and sampling bias in the available data is missing. OBJECTIVE: The objective of this study was to determine the quality of the current SARS-CoV-2 full genome data, in terms of sampling bias as well as phylogenetic and temporal signal, to inform and guide the scientific community. METHODS: We used maximum likelihood based methods to assess the presence of sufficient information for robust phylogenetic and phylogeographic studies in several SARS-CoV-2 sequence alignments, assembled from GISAID data released between March and April 2020. RESULTS: Although number of high quality full-genomes is growing daily, and recent sequence data released in April contains sufficient phylogenetic information that would allow reliable inference of phylogenetic relationships, country-specific SARS-CoV-2 data sets still present severe limitations. CONCLUSIONS: At the present time, studies assessing within country spread or transmission clusters should be considered preliminary at best, or hypothesis generating. Hence, the need for interpreting current reports with caution, and continuing concerted efforts to increase number and quality of sequences required for robust tracing of the epidemic. CLINICALTRIAL: INTERNATIONAL REGISTERED REPORT: RR2-https://doi.org/10.1101/2020.04.01.020594.