Real-time Genomic Surveillance Research Articles

Bioinformatic identification of monkeypox virus phylogenetic gene trees that are representative of its whole-genome phylogenetic tree.

Phylogenetic analysis based on whole-genome sequences is the gold standard for monkeypox virus (MPXV) phylogeny. However, genomic epidemiology capability and capacity are lacking or limited in resource poor countries of sub-Saharan Africa. Therefore, these make real-time genome surveillance of MPXV virtually impossible. We hypothesized that phylogenetic analysis based on single, conserved genes will produce phylogenetic tree topology consistent with MPXV whole-genome phylogeny, thus serving as a reliable proxy to phylogenomic analysis. In this study, we analyzed 62 conserved MPXV genes and showed that Bayesian phylogenetic analysis based on five genes (OPG 066/E4L, OPG068/E6R, OPG079/I3L, OPG145/A18R, and OPG150/A23R) generated phylogenetic trees with 72.2-96.3% topology similarity index to the reference phylogenomic tree topology. Our results showed that phylogenetic analysis of the identified five genes singly or in combination can serve as surrogate for whole-genome phylogenetic analysis, and thus obviates the need for whole-genome sequencing and phylogenomic analysis in regions where genomic epidemiology competence and capacity are lacking or unavailable. This study is relevant to evolution and genome surveillance of MPXV in resource limited countries.

Genomic Surveillance for Enhanced Healthcare Outbreak Detection and Control.

Current methods are insufficient alone for outbreak detection in hospitals. Real-time genomic surveillance using offers the potential to detect otherwise unidentified outbreaks. We initiated and evaluated the Enhanced Detection System for Healthcare-associated Transmission (EDS-HAT), a real-time genomic surveillance program for outbreak detection and mitigation. This study was conducted at UPMC Presbyterian Hospital from November 2021 to October 2023. Whole genome sequencing (WGS) was performed weekly on healthcare-associated clinical bacterial isolates to identify otherwise undetected outbreaks. Interventions were implemented in real-time based on identified transmission. A clinical and economic impact analysis was conducted to estimate infections averted and net cost savings. There were 3,921 bacterial isolates from patient healthcare-associated infections that underwent WGS, of which 476 (12.1%) clustered into 172 outbreaks (size range 2-16 patients). Of the outbreak isolates, 292 (61.3%) had an identified epidemiological link. Among the outbreaks with interventions, 95.6% showed no further transmission on the intervened transmission route. The impact analysis estimated that, over the two-year period, 62 infections were averted, with gross cost savings of $1,011,146, and net savings of $695,706, which translates to a 3.2-fold return on investment. Probabilistic sensitivity analysis showed EDS-HAT was cost-saving and more effective in 98% of simulations. Real-time genomic surveillance enabled the rapid detection and control of outbreaks in our hospital and resulted in economic benefits and improvement in patient safety. This study demonstrates the feasibility and effectiveness of integrating genomic surveillance into routine infection prevention practice, offering a paradigm shift in healthcare outbreak detection and control.

Comparative Atlas of SARS-CoV-2 Substitution Mutations: A Focus on Iranian Strains Amidst Global Trends.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a new emerging coronavirus that caused coronavirus disease 2019 (COVID-19). Whole-genome tracking of SARS-CoV-2 enhanced our understanding of the mechanism of the disease, control, and prevention of COVID-19. we analyzed 3368 SARS-CoV-2 protein sequences from Iran and compared them with 15.6 million global sequences in the GISAID database, using the Wuhan-Hu-1 strain as a reference. Our investigation revealed that NSP12-P323L, ORF9c-G50N, NSP14-I42V, membrane-A63T, Q19E, and NSP3-G489S were found to be the most frequent mutations among Iranian SARS-CoV-2 sequences. Furthermore, it was observed that more than 94% of the SARS-CoV-2 genome, including NSP7, NSP8, NSP9, NSP10, NSP11, and ORF8, had no mutations when compared to the Wuhan-Hu-1 strain. Finally, our data indicated that the ORF3a-T24I, NSP3-G489S, NSP5-P132H, NSP14-I42V, envelope-T9I, nucleocapsid-D3L, membrane-Q19E, and membrane-A63T mutations might be responsible factors for the surge in the SARS-CoV-2 Omicron variant wave in Iran. real-time genomic surveillance is crucial for detecting new SARS-CoV-2 variants, updating diagnostic tools, designing vaccines, and understanding adaptation to new environments.

Introduction of New Dengue Virus Lineages of Multiple Serotypes after COVID-19 Pandemic, Nicaragua, 2022.

Major dengue epidemics throughout Nicaragua's history have been dominated by 1 of 4 dengue virus serotypes (DENV-1-4). To examine serotypes during the dengue epidemic in Nicaragua in 2022, we performed real-time genomic surveillance in-country and documented cocirculation of all 4 serotypes. We observed a shift toward co-dominance of DENV-1 and DENV-4 over previously dominant DENV-2. By analyzing 135 new full-length DENV sequences, we found that introductions underlay the resurgence: DENV-1 clustered with viruses from Ecuador in 2014 rather than those previously seen in Nicaragua; DENV-3, which last circulated locally in 2014, grouped instead with Southeast Asia strains expanding into Florida and Cuba in 2022; and new DENV-4 strains clustered within a South America lineage spreading to Florida in 2022. In contrast, DENV-2 persisted from the formerly dominant Nicaragua clade. We posit that the resurgence emerged from travel after the COVID-19 pandemic and that the resultant intensifying hyperendemicity could affect future dengue immunity and severity.

Real-time genomic surveillance for enhanced control of infectious diseases and antimicrobial resistance

This article advocates for mobilizing pathogen genomic surveillance to contain and mitigate health threats from infectious diseases and antimicrobial resistance (AMR), building upon successes achieved by large-scale genome sequencing analysis of SARS-CoV-2 variants in guiding COVID-19 monitoring and public health responses and adopting a One Health approach. Capabilities of laboratory-based surveillance and epidemic alert systems should be enhanced by fostering (i) universal access to real-time whole genome sequence (WGS) data of pathogens to inform clinical practice, infection control, public health policies, and vaccine and antimicrobial drug research and development; (ii) integration of diagnostic microbiology data, data from testing asymptomatic individuals, pathogen sequence data, clinical data, and epidemiological data into surveillance programs; (iii) stronger cross-sectorial collaborations between healthcare, public health, animal health, and environmental surveillance and research using One Health approaches, toward understanding the ecology and transmission pathways of pathogens and AMR across ecosystems; (iv) international collaboration and interconnection of surveillance networks, harmonization of laboratory methods, and standardization of surveillance methods for global reporting, including on pathogen genomic variant or strain nomenclature; (v) responsible data sharing between surveillance networks, databases, and platforms according to FAIR (findability, accessibility, interoperability, and reusability) principles; and (vi) research on genomic surveillance system implementation and its cost-effectiveness for different pathogens and AMR threats across different settings. Regional and global One Health policies and governance initiatives should foster the concerted development and efficient utilization of pathogen genomic surveillance to protect the health of humans, animals, and the environment.

Genomic and eco-epidemiological investigations in Uruguay reveal local Chikungunya virus transmission dynamics during its expansion across the Americas in 2023.

Uruguay experienced its first Chikungunya virus outbreak in 2023, resulting in a significant burden to its healthcare system. We conducted analysis based on real-time genomic surveillance (30 novel whole genomes) to offer timely insights into recent local transmission dynamics and eco-epidemiological factors behind its emergence and spread in the country.

Development of an accurate and rapid method for whole genome characterization of canine parvovirus

Canine parvovirus is a highly contagious pathogen affecting domestic dogs and other carnivores globally. Monitoring CPV through continuous genomic surveillance is crucial for mapping variability and developing effective control measures. Here, we developed a method using multiplex-PCR-next-generation sequencing to obtain full-length CPV genomes directly from clinical samples. This approach utilizes tiling and tailed amplicons to amplify overlapping fragments of roughly 250 base pairs. This enables the creation of Illumina libraries by conducting two PCR reaction runs. We tested the assay in 10 fecal samples from dogs diagnosed with CPV and one CPV-2 vaccine strain. Furthermore, we applied it to a feline sample previously diagnosed with the feline panleukopenia virus. The assay provided 100 % genome coverage and high sequencing depth across all 12 samples. It successfully provided the sequence of the coding regions and the left and right non-translated regions, including tandem and terminal repeats. The assay effectively amplified viral variants from divergent evolutionary groups, including the antigenic variants (2a, 2b, and 2c) and the ancestral CPV-2 strain included in vaccine formulations. Moreover, it successfully amplified the entire genome of the feline panleukopenia virus found in cat feces. This method is cost-effective, time-efficient, and does not require lab expertise in Illumina library preparation. The multiplex-PCR-next-generation methodology facilitates large-scale genomic sequencing, expanding the limited number of complete genomes currently available in databases and enabling real-time genomic surveillance. Furthermore, the method helps identify and track emerging CPV viral variants, facilitating molecular epidemiology and control. Adopting this approach can enhance our understanding of the evolution and genetic diversity of Protoparvovirus carnivoran1.

Frequent Emergence of Resistance Mutations Following Complex Intra-Host Genomic Dynamics in SARS-CoV-2 Patients Receiving Sotrovimab.

The emergence of the Omicron variant of SARS-CoV-2 represented a challenge to the treatment of COVID-19 using monoclonal antibodies. Only Sotrovimab maintained partial activity, allowing it to be used in high-risk patients infected with the Omicron variant. However, reports of resistance mutations to Sotrovimab demand efforts to better understand the intra-patient emergence of Sotrovimab resistance. A retrospective genomic analysis was conducted on respiratory samples from immunocompromised patients infected with SARS-CoV-2 who received Sotrovimab at our hospital between December 2021 and August 2022. The study involved 95 sequential specimens from 22 patients (1 to 12 samples/patient; 3 to 107 days post-infusion; threshold cycle [CT] ≤ 32). Resistance mutations (in P337, E340, K356, and R346) were detected in 68% of cases; the shortest time to detection of a resistance mutation was 5 days after Sotrovimab infusion. The dynamics of resistance acquisition were highly complex, with up to 11 distinct amino acid changes in specimens from the same patient. In two patients, the mutation distribution was compartmentalized in respiratory samples from different sources. This is the first study to examine the acquisition of Sotrovimab resistance in the BA.5 lineage, enabling us to determine the lack of genomic or clinical differences between Sotrovimab resistance in BA.5 relative to that in BA.1/2. Across all Omicron lineages, the acquisition of resistance delayed SARS-CoV-2 clearance (40.67 versus 19.5 days). Close, real-time genomic surveillance of patients receiving Sotrovimab should be mandatory to facilitate early therapeutic interventions.

Clinical and Genomic Characterization of Carbapenem-Resistant Klebsiella pneumoniae with Concurrent Production of NDM and OXA-48-like Carbapenemases in Southern California, 2016-2022.

The global emergence of carbapenem-resistant Klebsiella pneumoniae (CRKP) has become a critical public healthcare concern due to treatment challenges and high mortality. In recent years, there has been an increase in cases of CRKP co-producing New Delhi metallo-β-lactamases (NDM) and oxacillinase 48 (OXA-48)-like carbapenemases in the US. The aim of this study was to correlate the clinical and genomic characteristics of CRKP co-producing NDM and OXA-48-like carbapenemases isolated from patients in Southern California since 2016. Whole-genome sequencing was performed on clinical isolates obtained from various sources, including blood, abdominal fluid, wounds, and urine. Genetic diversity was observed in these CRKP, including ST-14, ST-16, ST-167, ST-437, ST-2096, and ST-2497 lineages. Phylogenetic analysis revealed two closely related clusters (ST-14 and ST-2497), with single nucleotide polymorphism (SNP) differences ranging from 0 to 36, suggesting a possible local spread of these CRKP. Significant antimicrobial resistance (AMR) genes were identified in these CRKP, including blaNDM-1, blaNDM-5, blaOXA-232, blaOXA-181, blaCTX-M-15, armA, tet(A), and tet(D). Moreover, pColKP3-type and Inc-type plasmids known to harbor AMR genes were also detected in these isolates. Most of the patients infected with this rare type of CRKP died, although their severe comorbidities also played important roles in their demise. Our study highlighted the extremely limited treatment options and poor clinical outcomes associated with these dual-carbapenemase-producing CRKP. Real-time genomic surveillance of these unusual and deadly CRKP can provide critical information for infection prevention and treatment guidance.

Using Genomics To Investigate an Outbreak of Vancomycin-Resistant Enterococcus faecium ST78 at a Large Tertiary Hospital in Queensland.

To investigate an outbreak of vancomycin-resistant Enterococcus faecium (VREfm) sequence type 78 (ST78) in a large tertiary Australian hospital. A collection of 63 VREfm ST78 isolates, identified during a routine genomic surveillance program, were subjected to genomic epidemiological analysis based on whole-genome sequencing (WGS) data. The population structure was reconstructed using phylogenetic analysis, and a collection of publicly available VREfm ST78 genomes were used to provide global context. Core genome single nucleotide polymorphism (SNP) distances and available clinical metadata were used to characterize outbreak clusters and reconstruct transmission events. In silico genotyping confirmed that all study isolates were vanB-type VREfm carrying virulence characteristics of the hospital-associated E. faecium. Phylogenetic analysis identified two distinct phylogenetic clades, only one of which was responsible for a hospital outbreak. Four outbreak subtypes could be defined with examples of recent transmissions. Inference on transmission trees suggested complex transmission routes with unknown environmental reservoirs mediating the outbreak. WGS-based cluster analysis with publicly available genomes identified closely related Australian ST78 and ST203 isolates, highlighting the capacity for WGS to resolve complex clonal relationships between the VREfm lineages. Whole genome-based analysis has provided a high-resolution description of an outbreak of vanB-type VREfm ST78 in a Queensland hospital. Combined routine genomic surveillance and epidemiological analysis have facilitated better understanding of the local epidemiology of this endemic strain, providing valuable insight for better targeted control of VREfm. IMPORTANCE Vancomycin-resistant Enterococcus faecium (VREfm) is a leading cause of health care-associated infections (HAIs) globally. In Australia, the spread of hospital-adapted VREfm is largely driven by a single clonal group (clonal complex [CC]), CC17, to which the lineage ST78 belongs. While implementing a genomic surveillance program in Queensland, we observed increased incidence of ST78 colonizations and infections among patients. Here, we demonstrate the use of real-time genomic surveillance as a tool to support and enhance infection control (IC) practices. Our results show that real-time whole-genome sequencing (WGS) can efficiently disrupt outbreaks by identifying transmission routes that in turn can be targeted using resource-limited interventions. Additionally, we demonstrate that by placing local outbreaks in a global context, high-risk clones can be identified and targeted prior to them becoming established within clinical environments. Finally, the persistence of these organism within the hospital highlights the need for routine genomic surveillance as a management tool to control VRE transmission.

A Multiplexed, Tiled PCR Method for Rapid Whole-Genome Sequencing of Infectious Spleen and Kidney Necrosis Virus (ISKNV) in Tilapia.

Tilapia farming is one of the most important sectors in aquaculture worldwide and of major importance to global food security. Infectious spleen and kidney necrosis virus (ISKNV) has been identified as an agent of high morbidity and mortality, threatening tilapia aquaculture. ISKNV was detected in Lake Volta, Ghana, in September 2018 and spread rapidly, with mortality rates between 60 and 90% and losses of more than 10 tonnes of fish per day. Understanding the spread and evolution of viral pathogens is important for control strategies. Here, we developed a tiled-PCR sequencing approach for the whole-genome sequencing of ISKNV, using long read sequencing to enable field-based, real-time genomic surveillance. This work represents the first use of tiled-PCR for whole genome recovery of viruses in aquaculture, with the longest genome target (>110 kb dsDNA) to date. Our protocol was applied to field samples collected from the ISKNV outbreaks from four intensive tilapia cage culture systems across Lake Volta, between October 2018 and May 2022. Despite the low mutation rate of dsDNA viruses, 20 single nucleotide polymorphisms accumulated during the sampling period. Droplet digital PCR identified a minimum requirement of template in a sample to recover 50% of an ISKNV genome at 275 femtograms (2410 viral templates per 5 µL sequencing reaction). Overall, tiled-PCR sequencing of ISKNV provides an informative tool to assist in disease control in aquaculture.

Future COVID19 surges prediction based on SARS-CoV-2 mutations surveillance.

COVID19 has aptly revealed that airborne viruses such as SARS-CoV-2 with the ability to rapidly mutate combined with high rates of transmission and fatality can cause a deadly worldwide pandemic in a matter of weeks (Plato et al., 2021). Apart from vaccines and post-infection treatment options, strategies for preparedness will be vital in responding to the current and future pandemics. Therefore, there is wide interest in approaches that allow predictions of increase in infections ('surges') before they occur. We describe here real-time genomic surveillance particularly based on mutation analysis, of viral proteins as a methodology for a priori determination of surge in number of infection cases. The full results are available for SARS-CoV-2 at http://pandemics.okstate.edu/covid19/, and are updated daily as new virus sequences become available. This approach is generic and will also be applicable to other pathogens.

Technology transfer during the COVID-19 pandemic: report on the first face-to-face practical training course in Brazil.

Technology transfer can take place at large events, as long as safety protocols are strictly enforced. It is important to disseminate, at these events, the concepts of the Responsible Research and Innovation (RRI). Implications for services: Face-to-face training course is fundamental for training public health professionals. Technology transfer between research institutions and health services results in updating and improving health system performance. Based on the success of the reported technology transfer, a new module will be incorporated into the next edition of VEME (Panama 2022), entitled Virus Evolution to Public Health Policy Makers. The objective of this report was to describe the first face-to-face course aimed at training public health professionals in performing real-time genomic surveillance during the pandemic period. Experience report on a theoretical-practical course focusing on genomic research and surveillance, including mobile sequencing technologies, bioinformatics, phylogenetics and epidemiological modeling. There were 162 participants in the event and it was the first major face-to-face training course conducted during the COVID-19 epidemic in Brazil. No cases of SARS-CoV-2 infection was detected among the participants at the end of the event, suggesting the safety and effectiveness of all safety measures adopted. The results of this experience suggest that it is possible to conduct professional training safely during pandemics, as long as all safety protocols are followed.

Genomic Surveillance of Listeria monocytogenes in Taiwan, 2014 to 2019.

Listeria monocytogenes is a life-threatening foodborne pathogen. Here, we report the genomic characterization of a nationwide dataset of 411 clinical and 82 food isolates collected in Taiwan between 2014 and 2019. The observed incidence of listeriosis increased from 0.83 to 7 cases per million population upon implementation of mandatory notification in 2018. Pregnancy-associated cases accounted for 2.8% of human listeriosis and all-cause 7-day mortality was of 11.9% in nonmaternal-neonatal listeriosis. L. monocytogenes was isolated from 90% of raw pork and 34% of chicken products collected in supermarkets. Sublineages SL87, SL5, and SL378 accounted for the majority (65%) of clinical cases. SL87 and SL378 were also predominant (57%) in food products. Five cgMLST clusters accounted for 57% clinical cases, suggesting unnoticed outbreaks spanning up to 6 years. Mandatory notification allowed identifying the magnitude of listeriosis in Taiwan. Continuous real-time genomic surveillance will allow reducing contaminating sources and disease burden. IMPORTANCE Understanding the phylogenetic relationship between clinical and food isolates is important to identify the transmission routes of foodborne diseases. Here, we performed a nationwide study between 2014 and 2019 of both clinical and food Listeria monocytogenes isolates and sequenced their genomes. We show a 9-fold increase in listeriosis reporting upon implementation of mandatory notification. We found that sublineages SL87 and SL378 predominated among both clinical (50%) and food (57%) isolates, and identified five cgMLST clusters accounting for 57% of clinical cases, suggestive of potential protracted sources of contamination over up to 6 years in Taiwan. These findings highlight that mandatory declaration is critical in identifying the burden of listeriosis, and the importance of genome sequencing for a detailed characterization of the pathogenic L. monocytogenes genotypes circulating in Asia.

Clinical, microbiological, and genomic characteristics of clade-III Candida auris colonization and infection in southern California, 2019-2022.

Candida auris is an emerging fungal pathogen causing outbreaks in healthcare facilities. Five distinctive genomic clades exhibit clade-unique characteristics, highlighting the importance of real-time genomic surveillance and incorporating genotypic information to inform infection prevention practices and treatment algorithms. Both active and passive surveillance were used to screen hospitalized patients. C. auris polymerase chain reaction (PCR) assay on inguinal-axillary swabs was performed on high-risk patients upon admission. All clinical yeast isolates were identified to the species level. C. auris isolates were characterized by both phenotypic antifungal susceptibility tests and whole-genome sequencing. From late 2019 to early 2022, we identified 45 patients with C. auris. Most had a tracheostomy or were from a facility with a known outbreak. Moreover, 7 patients (15%) were only identified through passive surveillance. Also, 8 (18%) of the patients had a history of severe COVID-19. The overall mortality was 18%. Invasive C. auris infections were identified in 13 patients (29%), 9 (69%) of whom had bloodstream infections. Patients with invasive infection were more likely to have a central line. All C. auris isolates were resistant to fluconazole but susceptible to echinocandins. Genomic analysis showed that 1 dominant clade-III lineage is circulating in Los Angeles, with very limited intrahost and interhost genetic diversity. We have demonstrated that a robust C. auris surveillance program can be established using both active and passive surveillance, with multidisciplinary efforts involving the microbiology laboratory and the hospital epidemiology team. In Los Angeles County, C. auris strains are highly related and echinocandins should be used for empiric therapy.

Urgent need for a non-discriminatory and non-stigmatizing nomenclature for monkeypox virus.

We propose a novel, non-discriminatory classification of monkeypox virus diversity. Together with the World Health Organization, we named three clades (I, IIa and IIb) in order of detection. Within IIb, the cause of the current global outbreak, we identified multiple lineages (A.1, A.2, A.1.1 and B.1) to support real-time genomic surveillance.

Evaluation of EPISEQ SARS-CoV-2 and a Fully Integrated Application to Identify SARS-CoV-2 Variants from Several Next-Generation Sequencing Approaches.

Whole-genome sequencing has become an essential tool for real-time genomic surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) worldwide. The handling of raw next-generation sequencing (NGS) data is a major challenge for sequencing laboratories. We developed an easy-to-use web-based application (EPISEQ SARS-CoV-2) to analyse SARS-CoV-2 NGS data generated on common sequencing platforms using a variety of commercially available reagents. This application performs in one click a quality check, a reference-based genome assembly, and the analysis of the generated consensus sequence as to coverage of the reference genome, mutation screening and variant identification according to the up-to-date Nextstrain clade and Pango lineage. In this study, we validated the EPISEQ SARS-CoV-2 pipeline against a reference pipeline and compared the performance of NGS data generated by different sequencing protocols using EPISEQ SARS-CoV-2. We showed a strong agreement in SARS-CoV-2 clade and lineage identification (>99%) and in spike mutation detection (>99%) between EPISEQ SARS-CoV-2 and the reference pipeline. The comparison of several sequencing approaches using EPISEQ SARS-CoV-2 revealed 100% concordance in clade and lineage classification. It also uncovered reagent-related sequencing issues with a potential impact on SARS-CoV-2 mutation reporting. Altogether, EPISEQ SARS-CoV-2 allows an easy, rapid and reliable analysis of raw NGS data to support the sequencing efforts of laboratories with limited bioinformatics capacity and those willing to accelerate genomic surveillance of SARS-CoV-2.

Rapid Replacement of SARS-CoV-2 Variants by Delta and Subsequent Arrival of Omicron, Uganda, 2021.

Genomic surveillance in Uganda showed rapid replacement of severe acute respiratory syndrome coronavirus 2 over time by variants, dominated by Delta. However, detection of the more transmissible Omicron variant among travelers and increasing community transmission highlight the need for near–real-time genomic surveillance and adherence to infection control measures to prevent future pandemic waves.

Large Scale SARS-CoV-2 Molecular Testing and Genomic Surveillance Reveal Prolonged Infections, Protracted RNA shedding, and Viral Reinfections.

Large-scale SARS-CoV-2 molecular testing coupled with whole genome sequencing in the diagnostic laboratories is instrumental for real-time genomic surveillance. The extensive genomic, laboratory, and clinical data provide a valuable resource for understanding cases of reinfection versus prolonged RNA shedding and protracted infections. In this study, data from a total of 22,292 clinical specimens, positive by SARS-CoV-2 molecular diagnosis at Johns Hopkins clinical virology laboratory between March 11th 2020 to September 23rd 2021, were used to identify patients with two or more positive results. A total of 3,650 samples collected from 1,529 patients who had between 2 and 20 positive results were identified in a time frame that extended up to 403 days from the first positive. Cycle threshold values (Ct) were available for 1,622 samples, the median of which was over 30 by 11 days after the first positive. Extended recovery of infectious virus on cell culture was notable for up to 70 days after the first positive in immunocompromised patients. Whole genome sequencing data generated as a part of our SARS-CoV-2 genomic surveillance was available for 1,027 samples from patients that had multiple positive tests. Positive samples collected more than 10 days after initial positive with high quality sequences (coverage >90% and mean depth >100), were more likely to be from unvaccinated, or immunosuppressed patients. Reinfections with viral variants of concern were found in 3 patients more than 130 days from prior infections with a different viral clade. In 75 patients that had 2 or more high quality sequences, the acquisition of more substitutions or deletions was associated with lack of vaccination and longer time between the recovered viruses. Our study highlights the value of integrating genomic, laboratory, and clinical data for understanding the biology of SARS-CoV-2 as well as for setting a precedent for future epidemics and pandemics.

Population Genomics Approaches for Genetic Characterization of SARS-CoV-2 Lineages.

The genome of the Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2), the pathogen that causes coronavirus disease 2019 (COVID-19), has been sequenced at an unprecedented scale leading to a tremendous amount of viral genome sequencing data. To assist in tracing infection pathways and design preventive strategies, a deep understanding of the viral genetic diversity landscape is needed. We present here a set of genomic surveillance tools from population genetics which can be used to better understand the evolution of this virus in humans. To illustrate the utility of this toolbox, we detail an in depth analysis of the genetic diversity of SARS-CoV-2 in first year of the COVID-19 pandemic. We analyzed 329,854 high-quality consensus sequences published in the GISAID database during the pre-vaccination phase. We demonstrate that, compared to standard phylogenetic approaches, haplotype networks can be computed efficiently on much larger datasets. This approach enables real-time lineage identification, a clear description of the relationship between variants of concern, and efficient detection of recurrent mutations. Furthermore, time series change of Tajima's D by haplotype provides a powerful metric of lineage expansion. Finally, principal component analysis (PCA) highlights key steps in variant emergence and facilitates the visualization of genomic variation in the context of SARS-CoV-2 diversity. The computational framework presented here is simple to implement and insightful for real-time genomic surveillance of SARS-CoV-2 and could be applied to any pathogen that threatens the health of populations of humans and other organisms.