Phylogenetic interpretation during outbreaks requires caution

Sequencing analysis of SARS-CoV-2 cases in Slovenian long-term care facilities to support outbreak control

Introduction

Residents of long-term care facilities (LTCFs) are at high risk of morbidity and mortality due to COVID-19, especially when new variants of concern (VOC) emerge. To provide intradisciplinary data in order to tailor public health interventions during future epidemics, available epidemiologic and genomic data from Slovenian LTCFs during the initial phases of the COVID-19 pandemic was analyzed.

Methods

The first part of the study included SARS-CoV-2 reverse-transcription Real-Time PCR (rtRT-PCR) positive LTCF residents, from 21 facilities with COVID-19 outbreaks occurring in October 2020. The second part of the study included SARS-CoV-2 rtRT-PCR positive LTCF residents and staff between January and April 2021, when VOC Alpha emerged in Slovenia. Next-generation sequencing (NGS) was used to acquire SARS-CoV-2 genomes, and lineage determination. In-depth phylogenetic and mutational profile analysis were performed and coupled with available field epidemiological data to assess the dynamics of SARS-CoV-2 introduction and transmission.

Results

370/498 SARS-CoV-2 positive residents as well as 558/699 SARS-CoV-2 positive residents and 301/358 staff were successfully sequenced in the first and second part of the study, respectively. In October 2020, COVID-19 outbreaks in the 21 LTCFs were caused by intra-facility transmission as well as multiple independent SARS-CoV-2 introductions. The Alpha variant was confirmed in the first LTCF resident approximately 1.5 months after the first Alpha case was identified in Slovenia. The data also showed a slower replacement of existing variants by Alpha in residents compared to staff and the general population.

Discussion

Multiple SARS CoV-2 introductions as well as intra-facility spreading impacted disease transmission in Slovenian LTCFs. Timely implementation of control measures aimed at limiting new introductions while controlling in-facility transmission are of paramount importance, especially as new VOCs emerge. Sequencing, in conjunction with epidemiological data, can facilitate the determination of the need for future improvements in control measures to protect LTCF residents from COVID-19 or other respiratory infections.

Genotype Sequencing and Phylogenetic Analysis Revealed the Origins of Citrus Yellow Vein Clearing Virus California Isolates

The Citrus yellow vein clearing virus (CYVCV) causes a viral disease that has been reported in some citrus-growing regions in countries in Eurasia including Pakistan, India, Türkiye, Iran, China, and South Korea. Recently, CYVCV was detected in a localized urban area in a town in the middle of California's citrus-growing region and marks the first occurrence of the virus in North America. CYVCV has been reported to be spread by aphid and whitefly vectors and is graft and mechanically transmitted. Hence, it is an invasive pathogen that presents a significant threat to the California citrus industry, especially lemons, which are highly symptomatic to CYVCV. To elucidate the origin of the CYVCV California strain, we used long-read sequencing technology and obtained the complete genomes of three California CYVCV isolates, CA1, CA2, and CA3. The sequences of these isolates exhibited intergenomic similarities ranging from 95.4% to 97.4% to 54 publicly available CYVCV genome sequences, which indicated a relatively low level of heterogeneity. However, CYVCV CA isolates formed a distinct clade from the other isolates when aligned against other CYVCV genomes and coat protein gene sequences as shown by the neighbor network analysis. Based on the rooted Maximum Likelihood phylogenetic trees, CYVCV CA isolates shared the most recent common ancestor with isolates from India/South Asia. Bayesian evolutionary inferences resulted in a spatiotemporal reconstruction, suggesting that the CYVCV CA lineage diverged from the Indian lineage possibly around 1995. This analysis placed the origin of all CYVCV to around 1990, with South Asia and/or Middle East as the most plausible geographic source, which matches to the first discovery of CYVCV in Pakistan in 1988. Moreover, the spatiotemporal phylogenetic analysis indicated an additional virus diffusion pathway: one from South Asia to China and South Korea. Collectively, our phylogenetic inferences offer insights into the probable dynamics of global CYVCV dissemination, emphasizing the need for citrus industries and regulatory agencies to closely monitor citrus commodities crossing state and international borders.

Approaches and challenges to inferring the geographical source of infectious disease outbreaks using genomic data

Genomic data hold increasing potential in the elucidation of transmission dynamics and geographical sources of infectious disease outbreaks. Phylogeographic methods that use epidemiological and genomic data obtained from surveillance enable us to infer the history of spatial transmission that is naturally embedded in the topology of phylogenetic trees as a record of the dispersal of infectious agents between geographical locations. In this Review, we provide an overview of phylogeographic approaches widely used for reconstructing the geographical sources of outbreaks of interest. These approaches can be classified into ancestral trait or state reconstruction and structured population models, with structured population models including popular structured coalescent and birth-death models. We also describe the major challenges associated with sequencing technologies, surveillance strategies, data sharing, and analysis frameworks that became apparent during the generation of large-scale genomic data in recent years, extending beyond inference approaches. Finally, we highlight the role of genomic data in geographical source inference and clarify how this enhances understanding and molecular investigations of outbreak sources.

Genomic surveillance reveals dynamic shifts in the connectivity of COVID-19 epidemics

The maturation of genomic surveillance in the past decade has enabled tracking of the emergence and spread of epidemics at an unprecedented level. During the COVID-19 pandemic, for example, genomic data revealed that local epidemics varied considerably in the frequency of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) lineage importation and persistence, likely due to a combination of COVID-19 restrictions and changing connectivity. Here, we show that local COVID-19 epidemics are driven by regional transmission, including across international boundaries, but can become increasingly connected to distant locations following the relaxation of public health interventions. By integrating genomic, mobility, and epidemiological data, we find abundant transmission occurring between both adjacent and distant locations, supported by dynamic mobility patterns. We find that changing connectivity significantly influences local COVID-19 incidence. Our findings demonstrate a complex meaning of "local" when investigating connected epidemics and emphasize the importance of collaborative interventions for pandemic prevention and mitigation.

Emergence of zoonotic sporotrichosis due to Sporothrix brasiliensis in Minas Gerais, Brazil: A molecular approach to the current animal disease

Sporotrichosis is a neglected fungal zoonosis with significant impacts on human and animal health. Accurate diagnosis, treatment, and understanding of the transmission dynamics of Sporothrix species are essential for mitigating the spread of sporotrichosis. This study aimed to identify the Sporothrix species involved in the ongoing outbreaks of animal sporotrichosis in the metropolitan region of Belo Horizonte, Minas Gerais, Brazil, and analyse the phylogenetic relationships between pathogenic species to investigate the outbreak origin. Additionally, to better understand the evolution of the disease, we conducted a retrospective survey of positive feline and canine cases from November 2017 to July 2021 with proven cultures for Sporothrix. A significant increase in animal cases over the last 4 years was observed, with cats being the most affected host. Sporothrix brasiliensis was the predominant agent in 100% of the clinical isolates (n = 180) molecularly identified. Phylogenetic and haplotype analysis points towards the cases isolated from Minas Gerais sharing the haplotype originating from a long-lasting outbreak of cat-transmitted sporotrichosis in Rio de Janeiro, however, with a secondary contribution from genotypes circulating in other outbreaks in Brazil. Thus, we present clear evidence of the circulation of different S. brasiliensis genotypes associated with animal sporotrichosis in the metropolitan region of Belo Horizonte. Genetic monitoring can contribute to understanding the causal agent for zoonotic sporotrichosis in epidemiological processes and help to implement disease prevention and control measures.

Intra- and interhost genomic diversity of monkeypox virus

The impact and frequency of infectious disease outbreaks demonstrate the need for timely genomic surveillance to inform public health responses. In the largest known outbreak of mpox, genomic surveillance efforts have primarily focused on high-incidence nations in Europe and the Americas, with a paucity of data from South-East Asia and the Western Pacific. Here we analyzed 102 monkeypox virus (MPXV) genomes sampled from 56 individuals in Melbourne, Australia. All genomes fell within the 2022 MPXV outbreak lineage (B.1), with likely onward local transmission detected. We observed within-host diversity and instances of co-infection, and highlight further examples of structural variation and apolipoprotein B editing complex-driven micro-evolution in the current MPXV outbreak. Updating our understanding of MPXV emergence and diversification will inform public health measures and enable monitoring of the virus' evolutionary trajectory throughout the mpox outbreak.

Importation of Alpha and Delta variants during the SARS-CoV-2 epidemic in Switzerland: Phylogenetic analysis and intervention scenarios

The SARS-CoV-2 pandemic has led to the emergence of various variants of concern (VoCs) that are associated with increased transmissibility, immune evasion, or differences in disease severity. The emergence of VoCs fueled interest in understanding the potential impact of travel restrictions and surveillance strategies to prevent or delay the early spread of VoCs. We performed phylogenetic analyses and mathematical modeling to study the importation and spread of the VoCs Alpha and Delta in Switzerland in 2020 and 2021. Using a phylogenetic approach, we estimated between 383-1,038 imports of Alpha and 455-1,347 imports of Delta into Switzerland. We then used the results from the phylogenetic analysis to parameterize a dynamic transmission model that accurately described the subsequent spread of Alpha and Delta. We modeled different counterfactual intervention scenarios to quantify the potential impact of border closures and surveillance of travelers on the spread of Alpha and Delta. We found that implementing border closures after the announcement of VoCs would have been of limited impact to mitigate the spread of VoCs. In contrast, increased surveillance of travelers could prove to be an effective measure for delaying the spread of VoCs in situations where their severity remains unclear. Our study shows how phylogenetic analysis in combination with dynamic transmission models can be used to estimate the number of imported SARS-CoV-2 variants and the potential impact of different intervention scenarios to inform the public health response during the pandemic.

Analyses of Early ZIKV Genomes Are Consistent with Viral Spread from Northeast Brazil to the Americas

The Americas, particularly Brazil, were greatly impacted by the widespread Zika virus (ZIKV) outbreak in 2015 and 2016. Efforts were made to implement genomic surveillance of ZIKV as part of the public health responses. The accuracy of spatiotemporal reconstructions of the epidemic spread relies on the unbiased sampling of the transmission process. In the early stages of the outbreak, we recruited patients exhibiting clinical symptoms of arbovirus-like infection from Salvador and Campo Formoso, Bahia, in Northeast Brazil. Between May 2015 and June 2016, we identified 21 cases of acute ZIKV infection and subsequently recovered 14 near full-length sequences using the amplicon tiling multiplex approach with nanopore sequencing. We performed a time-calibrated discrete phylogeographic analysis to trace the spread and migration history of the ZIKV. Our phylogenetic analysis supports a consistent relationship between ZIKV migration from Northeast to Southeast Brazil and its subsequent dissemination beyond Brazil. Additionally, our analysis provides insights into the migration of ZIKV from Brazil to Haiti and the role Brazil played in the spread of ZIKV to other countries, such as Singapore, the USA, and the Dominican Republic. The data generated by this study enhances our understanding of ZIKV dynamics and supports the existing knowledge, which can aid in future surveillance efforts against 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.

Dynamic Epidemiological Networks: A Data Representation Framework for Modeling and Tracking of SARS-CoV-2 Variants

The large-scale real-time sequencing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes has allowed for rapid identification of concerning variants through phylogenetic analysis. However, the nature of phylogenetic reconstruction is typically static, in that the relationships between taxonomic units, once defined, are not subject to alterations. Furthermore, most phylogenetic methods are intrinsically batch mode in nature, requiring the presence of the entire data set. Finally, the emphasis of phylogenetics is on relating taxonomical units. These characteristics complicate the application of classical phylogenetics methods to represent relationships in molecular data collected from rapidly evolving strains of an etiological agent, such as SARS-CoV-2, since the molecular landscape is updated continuously as samples are collected. In such settings, variant definitions are subject to epistemological constraints and may change as data accumulate. Furthermore, representing within-variant molecular relationships may be as important as representing between variant relationships. This article describes a novel data representation framework called dynamic epidemiological networks (DENs) along with algorithms that underpin its construction to address these issues. The proposed representation is applied to study the molecular development underlying the spread of the COVID-19 (coronavirus disease 2019) pandemic in two countries: Israel and Portugal spanning a 2-year period from February 2020 to April 2022. The results demonstrate how this framework could be used to provide a multiscale representation of the data by capturing molecular relationships between samples as well as those between variants, automatically identifying the emergence of high frequency variants (lineages), including variants of concern such as Alpha and Delta, and tracking their growth. Additionally, we show how analyzing the evolution of the DEN can help identify changes in the viral population that could not be readily inferred from phylogenetic analysis.

Investigation of hospital discharge cases and SARS-CoV-2 introduction into Lothian care homes

BACKGROUND

The first epidemic wave of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Scotland resulted in high case numbers and mortality in care homes. In Lothian, over a third of care homes reported an outbreak while there was limited testing of hospital patients discharged to care homes.

AIM

Investigate hospital discharges as a source of SARS-CoV-2 introduction into care homes during the first epidemic wave.

METHODS

A clinical review was performed for all discharges from hospitals to care homes starting 1st March 2020 to 31st May 2020. Episodes were ruled out based on coronavirus disease (COVID-19) test history, clinical assessment at discharge, whole genome sequencing (WGS) data and an infectious period of 14 days. Clinical samples were processed for WGS, and consensus genomes generated were used for analysis by cluster investigation and virus epidemiological tool (CIVET). Patient timelines were obtained using electronic hospital records.

FINDINGS

In total 787 hospital discharges to care homes were identified. Out of these 776 (99%) were ruled out for hospital discharge introduction. However, for 10 episodes the results were inconclusive as there was low genomic diversity in consensus genomes or no sequencing data. Only one discharge episode had a genomic, time and location link to positive cases during hospital admission leading to 10 further positive cases in the care home.

CONCLUSION

Majority of hospital discharges were ruled out for introduction into Lothian care homes highlighting the importance of screening all new admissions when faced with a novel emerging virus and no vaccine available.

Genomic Epidemiology of SARS-CoV-2 in Western Burkina Faso, West Africa

BACKGROUND

After its initial detection in Wuhan, China, in December 2019, SARS-CoV-2 has spread rapidly, causing successive epidemic waves worldwide. This study aims to provide a genomic epidemiology of SARS-CoV-2 in Burkina Faso.

METHODS

Three hundred and seventy-seven SARS-CoV-2 genomes obtained from PCR-positive nasopharyngeal samples (PCR cycle threshold score < 35) collected between 5 May 2020, and 31 January 2022 were analyzed. Genomic sequences were assigned to phylogenetic clades using NextClade and to Pango lineages using pangolin. Phylogenetic and phylogeographic analyses were performed to determine the geographical sources and time of virus introduction in Burkina Faso.

RESULTS

The analyzed SARS-CoV-2 genomes can be assigned to 10 phylogenetic clades and 27 Pango lineages already described worldwide. Our analyses revealed the important role of cross-border human mobility in the successive SARS-CoV-2 introductions in Burkina Faso from neighboring countries.

CONCLUSIONS

This study provides additional insights into the genomic epidemiology of SARS-CoV-2 in West Africa. It highlights the importance of land travel in the spread of the virus and the need to rapidly implement preventive policies. Regional cross-border collaborations and the adherence of the general population to government policies are key to prevent new epidemic waves.

Modeling approaches for early warning and monitoring of pandemic situations as well as decision support

The COVID-19 pandemic has highlighted the lack of preparedness of many healthcare systems against pandemic situations. In response, many population-level computational modeling approaches have been proposed for predicting outbreaks, spatiotemporally forecasting disease spread, and assessing as well as predicting the effectiveness of (non-) pharmaceutical interventions. However, in several countries, these modeling efforts have only limited impact on governmental decision-making so far. In light of this situation, the review aims to provide a critical review of existing modeling approaches and to discuss the potential for future developments.

Phylogenetic and phylodynamic approaches to understanding and combating the early SARS-CoV-2 pandemic

Determining the transmissibility, prevalence and patterns of movement of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections is central to our understanding of the impact of the pandemic and to the design of effective control strategies. Phylogenies (evolutionary trees) have provided key insights into the international spread of SARS-CoV-2 and enabled investigation of individual outbreaks and transmission chains in specific settings. Phylodynamic approaches combine evolutionary, demographic and epidemiological concepts and have helped track virus genetic changes, identify emerging variants and inform public health strategy. Here, we review and synthesize studies that illustrate how phylogenetic and phylodynamic techniques were applied during the first year of the pandemic, and summarize their contributions to our understanding of SARS-CoV-2 transmission and control.

Understanding early pandemic SARS-CoV-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.

Molecular Epidemiology Questions Transmission Pathways Identified During the Year 2000 Outbreak of Classical Swine Fever in the UK

The last outbreak of classical swine fever (CSF) in the UK occurred in 2000. A total of 16 domestic pig holdings in the East Anglia region were confirmed as infected over a 3-month period. Obtaining viral genome sequences has since become easier and more cost-effective and has accordingly been applied to trace viral transmission events for a variety of viruses. The rate of genetic evolution varies for different viruses and is influenced by different transmission events, which will vary according to the epidemiology of an outbreak. To examine if genetic changes over the course of any future CSF outbreak would occur to supplement epidemiological investigations and help to track virus movements, the E2 gene and full genome of the virus present in archived tonsil samples from 14 of these infected premises were sequenced. Insufficient changes occurred in the full E2 gene to discriminate between the viruses from the different premises. In contrast, between 5 and 14 nucleotide changes were detected between the genome sequence of the virus from the presumed index case and the sequences from the other 13 infected premises. Phylogenetic analysis of these full CSFV genome sequences identified clusters of closely related viruses that allowed to corroborate some of the transmission pathways inferred by epidemiological investigations at the time. However, other sequences were more distinct and raised questions about the virus transmission routes previously implicated. We are thus confident that in future outbreaks, real-time monitoring of the outbreak via full genome sequencing will be beneficial.

Early Emergence and Dispersal of Delta SARS-CoV-2 Lineage AY.99.2 in Brazil

The year of 2021 was marked by the emergence and dispersal of a number of SARS-CoV-2 lineages, resulting in the “third wave” of COVID-19 in several countries despite the level of vaccine coverage. Soon after the first confirmed cases of COVID-19 by the Delta variant in Brazil, at least seven Delta sub-lineages emerged, including the globally spread AY.101 and AY.99.2. In this study we performed a detailed analysis of the COVID-19 scenario in Brazil from April to December 2021 by using data collected by the largest private medical diagnostic company in Latin America (Dasa), and SARS-CoV-2 genomic sequences generated by its SARS-CoV-2 genomic surveillance project (GENOV). For phylogenetic and Bayesian analysis, SARS-CoV-2 genomes available at GISAID public database were also retrieved. We confirmed that the Brazilian AY.99.2 and AY.101 were the most prevalent lineages during this period, overpassing the Gamma variant in July/August. We also estimated that AY.99.2 likely emerged a few weeks after the entry of the B.1.617.2 in the country, at some point between late April and May and rapidly spread to other countries. Despite no increased fitness described for the AY.99.2 lineage, a rapid shift in the composition of Delta SARS-CoV-2 lineages prevalence in Brazil took place. Understanding the reasons leading the AY.99.2 to become the dominant lineage in the country is important to understand the process of lineage competitions that may inform future control measures.

Investigation of cross-regional spread and evolution of equine influenza H3N8 at US and global scales using Bayesian phylogeography based on balanced subsampling

Equine influenza virus (EIV) is a highly contagious pathogen of equids, and a well-known burden in global equine health. EIV H3N8 variants seasonally emerged and resulted in EIV outbreaks in the United States (US) and worldwide. The present study evaluated the pattern of cross-regional EIV H3N8 spread and evolutionary characteristics at US and global scales using Bayesian phylogeography with balanced subsampling based on regional horse population size. A total of 297 Haemagglutinin (HA) sequences of global EIV H3N8 were collected from 1963 to 2019 and subsampled to global subset (n = 67), raw US sequences (n = 100) and US subset (n = 44) datasets. Discrete trait phylogeography analysis was used to estimate the transmission history of EIV using four global and US genome datasets. The North American lineage was the major source of globally dominant EIV variants and spread to other global regions. The US EIV strains generally spread from the southern and midwestern regions to other regions. The EIV H3N8 accumulated approximately three nucleotide substitutions per year in the HA gene under heterogenous local positive selection. Our findings will guide better decision making of target intervention strategies of EIV H3N8 infection and provide the better scheme of genomic surveillance in the US and global equine health. This article is protected by copyright. All rights reserved.

The role of viral genomics in understanding COVID-19 outbreaks in long-term care facilities

We reviewed all genomic epidemiology studies on COVID-19 in long-term care facilities (LTCFs) that had been published to date. We found that staff and residents were usually infected with identical, or near identical, SARS-CoV-2 genomes. Outbreaks usually involved one predominant cluster, and the same lineages persisted in LTCFs despite infection control measures. Outbreaks were most commonly due to single or few introductions followed by a spread rather than a series of seeding events from the community into LTCFs. The sequencing of samples taken consecutively from the same individuals at the same facilities showed the persistence of the same genome sequence, indicating that the sequencing technique was robust over time. When combined with local epidemiology, genomics allowed probable transmission sources to be better characterised. The transmission between LTCFs was detected in multiple studies. The mortality rate among residents was high in all facilities, regardless of the lineage. Bioinformatics methods were inadequate in a third of the studies reviewed, and reproducing the analyses was difficult because sequencing data were not available in many facilities.

Genomic epidemiology reveals multiple introductions of SARS-CoV-2 followed by community and nosocomial spread, Germany, February to May 2020

Background

In the SARS-CoV-2 pandemic, viral genomes are available at unprecedented speed, but spatio-temporal bias in genome sequence sampling precludes phylogeographical inference without additional contextual data.

Aim

We applied genomic epidemiology to trace SARS-CoV-2 spread on an international, national and local level, to illustrate how transmission chains can be resolved to the level of a single event and single person using integrated sequence data and spatio-temporal metadata.

Methods

We investigated 289 COVID-19 cases at a university hospital in Munich, Germany, between 29 February and 27 May 2020. Using the ARTIC protocol, we obtained near full-length viral genomes from 174 SARS-CoV-2-positive respiratory samples. Phylogenetic analyses using the Auspice software were employed in combination with anamnestic reporting of travel history, interpersonal interactions and perceived high-risk exposures among patients and healthcare workers to characterise cluster outbreaks and establish likely scenarios and timelines of transmission.

Results

We identified multiple independent introductions in the Munich Metropolitan Region during the first weeks of the first pandemic wave, mainly by travellers returning from popular skiing areas in the Alps. In these early weeks, the rate of presumable hospital-acquired infections among patients and in particular healthcare workers was high (9.6% and 54%, respectively) and we illustrated how transmission chains can be dissected at high resolution combining virus sequences and spatio-temporal networks of human interactions.

Conclusions

Early spread of SARS-CoV-2 in Europe was catalysed by superspreading events and regional hotspots during the winter holiday season. Genomic epidemiology can be employed to trace viral spread and inform effective containment strategies.

Emergence of an early SARS-CoV-2 epidemic in the United States

The emergence of the COVID-19 epidemic in the United States (U.S.) went largely undetected due to inadequate testing. New Orleans experienced one of the earliest and fastest accelerating outbreaks, coinciding with Mardi Gras. To gain insight into the emergence of SARS-CoV-2 in the U.S. and how large-scale events accelerate transmission, we sequenced SARS-CoV-2 genomes during the first wave of the COVID-19 epidemic in Louisiana. We show that SARS-CoV-2 in Louisiana had limited diversity compared to other U.S. states and that one introduction of SARS-CoV-2 led to almost all of the early transmission in Louisiana. By analyzing mobility and genomic data, we show that SARS-CoV-2 was already present in New Orleans before Mardi Gras, and the festival dramatically accelerated transmission. Our study provides an understanding of how superspreading during large-scale events played a key role during the early outbreak in the U.S. and can greatly accelerate epidemics.

Leveraging Pathogen Sequence and Contact Tracing Data to Enhance Vaccine Trials in Emerging Epidemics

INTRODUCTION

Advance planning of vaccine trials conducted during outbreaks increases our ability to rapidly define the efficacy and potential impact of a vaccine. Vaccine efficacy against infectiousness (VEI) is an important measure for understanding a vaccine's full impact, yet it is currently not identifiable in many trial designs because it requires knowledge of infectors' vaccination status. Recent advances in genomics have improved our ability to reconstruct transmission networks. We aim to assess if augmenting trials with pathogen sequence and contact tracing data can permit them to estimate VEI.

METHODS

We develop a transmission model with a vaccine trial in an outbreak setting, incorporate pathogen sequence data and contact tracing data, and assign probabilities to likely infectors. We then propose and evaluate the performance of an estimator of VEI.

RESULTS

We find that under perfect knowledge of infector-infectee pairs, we are able to accurately estimate VEI. Use of sequence data results in imperfect reconstruction of transmission networks, biasing estimates of VEI towards the null, with approaches using deep sequence data performing better than approaches using consensus sequence data. Inclusion of contact tracing data reduces the bias.

CONCLUSION

Pathogen genomics enhance identifiability of VEI, but imperfect transmission network reconstruction biases estimate toward the null and limits our ability to detect VEI. Given the consistent direction of the bias, estimates obtained from trials using these methods will provide lower bounds on the true VEI. A combination of sequence and epidemiologic data results in the most accurate estimates, underscoring the importance of contact tracing.

Testing at scale during the COVID-19 pandemic

Assembly and publication of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome in January 2020 enabled the immediate development of tests to detect the new virus. This began the largest global testing programme in history, in which hundreds of millions of individuals have been tested to date. The unprecedented scale of testing has driven innovation in the strategies, technologies and concepts that govern testing in public health. This Review describes the changing role of testing during the COVID-19 pandemic, including the use of genomic surveillance to track SARS-CoV-2 transmission around the world, the use of contact tracing to contain disease outbreaks and testing for the presence of the virus circulating in the environment. Despite these efforts, widespread community transmission has become entrenched in many countries and has required the testing of populations to identify and isolate infected individuals, many of whom are asymptomatic. The diagnostic and epidemiological principles that underpin such population-scale testing are also considered, as are the high-throughput and point-of-care technologies that make testing feasible on a massive scale.

Rapid feedback on hospital onset SARS-CoV-2 infections combining epidemiological and sequencing data

Background

Rapid identification and investigation of healthcare-associated infections (HCAIs) is important for suppression of SARS-CoV-2, but the infection source for hospital onset COVID-19 infections (HOCIs) cannot always be readily identified based only on epidemiological data. Viral sequencing data provides additional information regarding potential transmission clusters, but the low mutation rate of SARS-CoV-2 can make interpretation using standard phylogenetic methods difficult.

Methods

We developed a novel statistical method and sequence reporting tool (SRT) that combines epidemiological and sequence data in order to provide a rapid assessment of the probability of HCAI among HOCI cases (defined as first positive test >48 hr following admission) and to identify infections that could plausibly constitute outbreak events. The method is designed for prospective use, but was validated using retrospective datasets from hospitals in Glasgow and Sheffield collected February-May 2020.

Results

We analysed data from 326 HOCIs. Among HOCIs with time from admission ≥8 days, the SRT algorithm identified close sequence matches from the same ward for 160/244 (65.6%) and in the remainder 68/84 (81.0%) had at least one similar sequence elsewhere in the hospital, resulting in high estimated probabilities of within-ward and within-hospital transmission. For HOCIs with time from admission 3-7 days, the SRT probability of healthcare acquisition was >0.5 in 33/82 (40.2%).

Conclusions

The methodology developed can provide rapid feedback on HOCIs that could be useful for infection prevention and control teams, and warrants further prospective evaluation. The integration of epidemiological and sequence data is important given the low mutation rate of SARS-CoV-2 and its variable incubation period.

Funding

COG-UK HOCI funded by COG-UK consortium, supported by funding from UK Research and Innovation, National Institute of Health Research and Wellcome Sanger Institute.

Hepatitis C Virus Transmission Clusters in Public Health and Correctional Settings, Wisconsin, USA, 2016-20171

Ending the hepatitis C virus (HCV) epidemic requires stopping transmission among networks of persons who inject drugs. Identifying transmission networks by using genomic epidemiology may inform community responses that can quickly interrupt transmission. We retrospectively identified HCV RNA–positive specimens corresponding to 459 persons in settings that use the state laboratory, including correctional facilities and syringe services programs, in Wisconsin, USA, during 2016–2017. We conducted next-generation sequencing of HCV and analyzed it for phylogenetic linkage by using the Centers for Disease Control and Prevention Global Hepatitis Outbreak Surveillance Technology platform. Analysis showed that 126 persons were linked across 42 clusters. Phylogenetic clustering was higher in rural communities and associated with female sex and younger age among rural residents. These data highlight that HCV transmission could be reduced by expanding molecular-based surveillance strategies to rural communities affected by the opioid crisis.

Using Neisseria meningitidis genomic diversity to inform outbreak strain identification

Meningococcal disease is a life-threatening illness caused by the human-restricted bacterium Neisseria meningitidis. Outbreaks in the USA involve at least two cases in an organization or community caused by the same serogroup within three months. Genome comparisons, including phylogenetic analysis and quantification of genome distances can provide confirmatory evidence of pathogen transmission during an outbreak. Interpreting genome distances depends on understanding their distribution both among isolates from outbreaks and among those not from outbreaks. Here, we identify outbreak strains based on phylogenetic relationships among 141 N. meningitidis isolates collected from 28 outbreaks in the USA during 2010-2017 and 1516 non-outbreak isolates collected through contemporaneous meningococcal surveillance. We show that genome distance thresholds based on the maximum SNPs and allele distances among isolates in the phylogenetically defined outbreak strains are sufficient to separate most pairs of non-outbreak isolates into separate strains. Non-outbreak isolate pairs that could not be distinguished from each other based on genetic distances were concentrated in the clonal complexes CC11, CC103, and CC32. Within each of these clonal complexes, phylodynamic analysis identified a group of isolates with extremely low diversity, collected over several years and multiple states. Clusters of isolates with low genetic diversity could indicate increased pathogen transmission, potentially resulting in local outbreaks or nationwide clonal expansions.

Phylogenetic Analysis of SARS-CoV-2 Data Is Difficult

Numerous studies covering some aspects of SARS-CoV-2 data analyses are being published on a daily basis, including a regularly updated phylogeny on nextstrain.org. Here, we review the difficulties of inferring reliable phylogenies by example of a data snapshot comprising a quality-filtered subset of 8,736 out of all 16,453 virus sequences available on May 5, 2020 from gisaid.org. We find that it is difficult to infer a reliable phylogeny on these data due to the large number of sequences in conjunction with the low number of mutations. We further find that rooting the inferred phylogeny with some degree of confidence either via the bat and pangolin outgroups or by applying novel computational methods on the ingroup phylogeny does not appear to be credible. Finally, an automatic classification of the current sequences into subclasses using the mPTP tool for molecular species delimitation is also, as might be expected, not possible, as the sequences are too closely related. We conclude that, although the application of phylogenetic methods to disentangle the evolution and spread of COVID-19 provides some insight, results of phylogenetic analyses, in particular those conducted under the default settings of current phylogenetic inference tools, as well as downstream analyses on the inferred phylogenies, should be considered and interpreted with extreme caution.

Genomic epidemiology of SARS-CoV-2 transmission lineages in Ecuador

Characterisation of SARS-CoV-2 genetic diversity through space and time can reveal trends in virus importation and domestic circulation, and permit the exploration of questions regarding the early transmission dynamics. Here we present a detailed description of SARS-CoV-2 genomic epidemiology in Ecuador, one of the hardest hit countries during the early stages of the COVID-19 pandemic. We generate and analyse 160 whole genome sequences sampled from all provinces of Ecuador in 2020. Molecular clock and phylgeographic analysis of these sequences in the context of global SARS-CoV-2 diversity enable us to identify and characterise individual transmission lineages within Ecuador, explore their spatiotemporal distributions, and consider their introduction and domestic circulation. Our results reveal a pattern of multiple international importations across the country, with apparent differences between key provinces. Transmission lineages were mostly introduced before the implementation of non-pharmaceutical interventions (NPIs), with differential degrees of persistence and national dissemination.

Temporal dynamics of SARS-CoV-2 mutation accumulation within and across infected hosts

Analysis of SARS-CoV-2 genetic diversity within infected hosts can provide insight into the generation and spread of new viral variants and may enable high resolution inference of transmission chains. However, little is known about temporal aspects of SARS-CoV-2 intrahost diversity and the extent to which shared diversity reflects convergent evolution as opposed to transmission linkage. Here we use high depth of coverage sequencing to identify within-host genetic variants in 325 specimens from hospitalized COVID-19 patients and infected employees at a single medical center. We validated our variant calling by sequencing defined RNA mixtures and identified viral load as a critical factor in variant identification. By leveraging clinical metadata, we found that intrahost diversity is low and does not vary by time from symptom onset. This suggests that variants will only rarely rise to appreciable frequency prior to transmission. Although there was generally little shared variation across the sequenced cohort, we identified intrahost variants shared across individuals who were unlikely to be related by transmission. These variants did not precede a rise in frequency in global consensus genomes, suggesting that intrahost variants may have limited utility for predicting future lineages. These results provide important context for sequence-based inference in SARS-CoV-2 evolution and epidemiology.

VERSO: A comprehensive framework for the inference of robust phylogenies and the quantification of intra-host genomic diversity of viral samples

We introduce VERSO, a two-step framework for the characterization of viral evolution from sequencing data of viral genomes, which is an improvement on phylogenomic approaches for consensus sequences. VERSO exploits an efficient algorithmic strategy to return robust phylogenies from clonal variant profiles, also in conditions of sampling limitations. It then leverages variant frequency patterns to characterize the intra-host genomic diversity of samples, revealing undetected infection chains and pinpointing variants likely involved in homoplasies. On simulations, VERSO outperforms state-of-the-art tools for phylogenetic inference. Notably, the application to 6,726 amplicon and RNA sequencing samples refines the estimation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) evolution, while co-occurrence patterns of minor variants unveil undetected infection paths, which are validated with contact tracing data. Finally, the analysis of SARS-CoV-2 mutational landscape uncovers a temporal increase of overall genomic diversity and highlights variants transiting from minor to clonal state and homoplastic variants, some of which fall on the spike gene. Available at: https://github.com/BIMIB-DISCo/VERSO.

Evolutionary Dynamics and Dissemination Pattern of the SARS-CoV-2 Lineage B.1.1.33 During the Early Pandemic Phase in Brazil

A previous study demonstrates that most of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) Brazilian strains fell in three local clades that were introduced from Europe around late February 2020. Here we investigated in more detail the origin of the major and most widely disseminated SARS-CoV-2 Brazilian lineage B.1.1.33. We recovered 190 whole viral genomes collected from 13 Brazilian states from February 29 to April 31, 2020 and combined them with other B.1.1 genomes collected globally. Our genomic survey confirms that lineage B.1.1.33 is responsible for a variable fraction of the community viral transmissions in Brazilian states, ranging from 2% of all SARS-CoV-2 genomes from Pernambuco to 80% of those from Rio de Janeiro. We detected a moderate prevalence (5-18%) of lineage B.1.1.33 in some South American countries and a very low prevalence (<1%) in North America, Europe, and Oceania. Our study reveals that lineage B.1.1.33 evolved from an ancestral clade, here designated B.1.1.33-like, that carries one of the two B.1.1.33 synapomorphic mutations. The B.1.1.33-like lineage may have been introduced from Europe or arose in Brazil in early February 2020 and a few weeks later gave origin to the lineage B.1.1.33. These SARS-CoV-2 lineages probably circulated during February 2020 and reached all Brazilian regions and multiple countries around the world by mid-March, before the implementation of air travel restrictions in Brazil. Our phylodynamic analysis also indicates that public health interventions were partially effective to control the expansion of lineage B.1.1.33 in Rio de Janeiro because its median effective reproductive number (R e ) was drastically reduced by about 66% during March 2020, but failed to bring it to below one. Continuous genomic surveillance of lineage B.1.1.33 might provide valuable information about epidemic dynamics and the effectiveness of public health interventions in some Brazilian states.

Establishment and lineage dynamics of the SARS-CoV-2 epidemic in the UK

The United Kingdom's COVID-19 epidemic during early 2020 was one of world's largest and was unusually well represented by virus genomic sampling. We determined the fine-scale genetic lineage structure of this epidemic through analysis of 50,887 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes, including 26,181 from the UK sampled throughout the country's first wave of infection. Using large-scale phylogenetic analyses combined with epidemiological and travel data, we quantified the size, spatiotemporal origins, and persistence of genetically distinct UK transmission lineages. Rapid fluctuations in virus importation rates resulted in >1000 lineages; those introduced prior to national lockdown tended to be larger and more dispersed. Lineage importation and regional lineage diversity declined after lockdown, whereas lineage elimination was size-dependent. We discuss the implications of our genetic perspective on transmission dynamics for COVID-19 epidemiology and control.

Emergence of an early SARS-CoV-2 epidemic in the United States

The emergence of the early COVID-19 epidemic in the United States (U.S.) went largely undetected, due to a lack of adequate testing and mitigation efforts. The city of New Orleans, Louisiana experienced one of the earliest and fastest accelerating outbreaks, coinciding with the annual Mardi Gras festival, which went ahead without precautions. To gain insight into the emergence of SARS-CoV-2 in the U.S. and how large, crowded events may have accelerated early transmission, we sequenced SARS-CoV-2 genomes during the first wave of the COVID-19 epidemic in Louisiana. We show that SARS-CoV-2 in Louisiana initially had limited sequence diversity compared to other U.S. states, and that one successful introduction of SARS-CoV-2 led to almost all of the early SARS-CoV-2 transmission in Louisiana. By analyzing mobility and genomic data, we show that SARS-CoV-2 was already present in New Orleans before Mardi Gras and that the festival dramatically accelerated transmission, eventually leading to secondary localized COVID-19 epidemics throughout the Southern U.S.. Our study provides an understanding of how superspreading during large-scale events played a key role during the early outbreak in the U.S. and can greatly accelerate COVID-19 epidemics on a local and regional scale.

Genomic epidemiology of the early stages of the SARS-CoV-2 outbreak in Russia

The ongoing pandemic of SARS-CoV-2 presents novel challenges and opportunities for the use of phylogenetics to understand and control its spread. Here, we analyze the emergence of SARS-CoV-2 in Russia in March and April 2020. Combining phylogeographic analysis with travel history data, we estimate that the sampled viral diversity has originated from at least 67 closely timed introductions into Russia, mostly in late February to early March. All but one of these introductions were not from China, suggesting that border closure with China has helped delay establishment of SARS-CoV-2 in Russia. These introductions resulted in at least 9 distinct Russian lineages corresponding to domestic transmission. A notable transmission cluster corresponded to a nosocomial outbreak at the Vreden hospital in Saint Petersburg; phylodynamic analysis of this cluster reveals multiple (2-3) introductions each giving rise to a large number of cases, with a high initial effective reproduction number of 3.0 [1.9, 4.3].

Temporal dynamics of SARS-CoV-2 mutation accumulation within and across infected hosts

Analysis of SARS-CoV-2 genetic diversity within infected hosts can provide insight into the generation and spread of new viral variants and may enable high resolution inference of transmission chains. However, little is known about temporal aspects of SARS-CoV-2 intrahost diversity and the extent to which shared diversity reflects convergent evolution as opposed to transmission linkage. Here we use high depth of coverage sequencing to identify within-host genetic variants in 325 specimens from hospitalized COVID-19 patients and infected employees at a single medical center. We validated our variant calling by sequencing defined RNA mixtures and identified a viral load threshold that minimizes false positives. By leveraging clinical metadata, we found that intrahost diversity is low and does not vary by time from symptom onset. This suggests that variants will only rarely rise to appreciable frequency prior to transmission. Although there was generally little shared variation across the sequenced cohort, we identified intrahost variants shared across individuals who were unlikely to be related by transmission. These variants did not precede a rise in frequency in global consensus genomes, suggesting that intrahost variants may have limited utility for predicting future lineages. These results provide important context for sequence-based inference in SARS-CoV-2 evolution and epidemiology.

Genomic epidemiology of SARS-CoV-2 reveals multiple lineages and early spread of SARS-CoV-2 infections in Lombardy, Italy

From February to April 2020, Lombardy (Italy) reported the highest numbers of SARS-CoV-2 cases worldwide. By analyzing 346 whole SARS-CoV-2 genomes, we demonstrate the presence of seven viral lineages in Lombardy, frequently sustained by local transmission chains and at least two likely to have originated in Italy. Six single nucleotide polymorphisms (five of them non-synonymous) characterized the SARS-CoV-2 sequences, none of them affecting N-glycosylation sites. The seven lineages, and the presence of local transmission clusters within three of them, revealed that sustained community transmission was underway before the first COVID-19 case had been detected in Lombardy.

The Lombardy region of Italy was heavily affected early in the SARS-CoV-2 pandemic. Here, the authors use whole genome sequencing and show that there were multiple introductions into the region, with transmission occurring before the first case was detected.

Genomic epidemiology of SARS-CoV-2 transmission lineages in Ecuador

Characterisation of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) genetic diversity through space and time can reveal trends in virus importation and domestic circulation and permit the exploration of questions regarding the early transmission dynamics. Here, we present a detailed description of SARS-CoV-2 genomic epidemiology in Ecuador, one of the hardest hit countries during the early stages of the coronavirus-19 pandemic. We generated and analysed 160 whole genome sequences sampled from all provinces of Ecuador in 2020. Molecular clock and phylogeographic analysis of these sequences in the context of global SARS-CoV-2 diversity enable us to identify and characterise individual transmission lineages within Ecuador, explore their spatiotemporal distributions, and consider their introduction and domestic circulation. Our results reveal a pattern of multiple international importations across the country, with apparent differences between key provinces. Transmission lineages were mostly introduced before the implementation of non-pharmaceutical interventions, with differential degrees of persistence and national dissemination.

Full genome viral sequences inform patterns of SARS-CoV-2 spread into and within Israel

Full genome sequences are increasingly used to track the geographic spread and transmission dynamics of viral pathogens. Here, with a focus on Israel, we sequence 212 SARS-CoV-2 sequences and use them to perform a comprehensive analysis to trace the origins and spread of the virus. We find that travelers returning from the United States of America significantly contributed to viral spread in Israel, more than their proportion in incoming infected travelers. Using phylodynamic analysis, we estimate that the basic reproduction number of the virus was initially around 2.5, dropping by more than two-thirds following the implementation of social distancing measures. We further report high levels of transmission heterogeneity in SARS-CoV-2 spread, with between 2-10% of infected individuals resulting in 80% of secondary infections. Overall, our findings demonstrate the effectiveness of social distancing measures for reducing viral spread.

Full genome viral sequences inform patterns of SARS-CoV-2 spread into and within Israel

Full genome sequences are increasingly used to track the geographic spread and transmission dynamics of viral pathogens. Here, with a focus on Israel, we sequence 212 SARS-CoV-2 sequences and use them to perform a comprehensive analysis to trace the origins and spread of the virus. We find that travelers returning from the United States of America significantly contributed to viral spread in Israel, more than their proportion in incoming infected travelers. Using phylodynamic analysis, we estimate that the basic reproduction number of the virus was initially around 2.5, dropping by more than two-thirds following the implementation of social distancing measures. We further report high levels of transmission heterogeneity in SARS-CoV-2 spread, with between 2-10% of infected individuals resulting in 80% of secondary infections. Overall, our findings demonstrate the effectiveness of social distancing measures for reducing viral spread.

Substitutions in Spike and Nucleocapsid proteins of SARS-CoV-2 circulating in South America

SARS-CoV-2 is a new member of the genus Betacoronavirus, responsible for the COVID-19 pandemic. The virus crossed the species barrier and established in the human population taking advantage of the spike protein high affinity for the ACE receptor to infect the lower respiratory tract. The Nucleocapsid (N) and Spike (S) are highly immunogenic structural proteins and most commercial COVID-19 diagnostic assays target these proteins. In an unpredictable epidemic, it is essential to know about their genetic variability. The objective of this study was to describe the substitution frequency of the S and N proteins of SARS-CoV-2 in South America. A total of 504 amino acid and nucleotide sequences of the S and N proteins of SARS-CoV-2 from seven South American countries (Argentina, Brazil, Chile, Ecuador, Peru, Uruguay, and Colombia), reported as of June 3, and corresponding to samples collected between March and April 2020, were compared through substitution matrices using the Muscle algorithm. Forty-three sequences from 13 Colombian departments were obtained in this study using the Oxford Nanopore and Illumina MiSeq technologies, following the amplicon-based ARTIC network protocol. The substitutions D614G in S and R203K/G204R in N were the most frequent in South America, observed in 83% and 34% of the sequences respectively. Strikingly, genomes with the conserved position D614 were almost completely replaced by genomes with the G614 substitution between March to April 2020. A similar replacement pattern was observed with R203K/G204R although more marked in Chile, Argentina and Brazil, suggesting similar introduction history and/or control strategies of SARS-CoV-2 in these countries. It is necessary to continue with the genomic surveillance of S and N proteins during the SARS-CoV-2 pandemic as this information can be useful for developing vaccines, therapeutics and diagnostic tests.

Sequencing identifies multiple early introductions of SARS-CoV-2 to the New York City region

Effective public response to a pandemic relies upon accurate measurement of the extent and dynamics of an outbreak. Viral genome sequencing has emerged as a powerful approach to link seemingly unrelated cases, and large-scale sequencing surveillance can inform on critical epidemiological parameters. Here, we report the analysis of 864 SARS-CoV-2 sequences from cases in the New York City metropolitan area during the COVID-19 outbreak in spring 2020. The majority of cases had no recent travel history or known exposure, and genetically linked cases were spread throughout the region. Comparison to global viral sequences showed that early transmission was most linked to cases from Europe. Our data are consistent with numerous seeds from multiple sources and a prolonged period of unrecognized community spreading. This work highlights the complementary role of genomic surveillance in addition to traditional epidemiological indicators.

Analysis of Genomic Characteristics and Transmission Routes of Patients With Confirmed SARS-CoV-2 in Southern California During the Early Stage of the US COVID-19 Pandemic

Importance

In late December 2019, an outbreak of a novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in Wuhan, China. Data on the routes of transmission to Los Angeles, California, the US West Coast epicenter for coronavirus disease 2019 (COVID-19), and subsequent community spread are limited.

Objective

To determine the transmission routes of SARS-CoV-2 to Southern California and elucidate local community spread within the Los Angeles metropolitan area.

Design, Setting, and Participants

This case series included 192 consecutive patients with reverse transcription-polymerase chain reaction (RT-PCR) test results positive for SARS-CoV-2 who were evaluated at Cedars-Sinai Medical Center in Los Angeles, California, from March 22 to April 15, 2020. Data analysis was performed from April to May 2020.

Main Outcomes and Measures

SARS-CoV-2 viral genomes were sequenced. Los Angeles isolates were compared with genomes from global subsampling and from New York, New York; Washington state; and China to determine potential sources of viral dissemination. Demographic data and outcomes were collected.

Results

The cohort included 192 patients (median [interquartile range] age, 59.5 [43-75] years; 110 [57.3%] men). The genetic characterization of SARS-CoV-2 isolates in the Los Angeles population pinpointed community transmission of 13 patients within a 3.81 km2 radius. Variation landscapes of this case series also revealed a cluster of 10 patients that contained 5 residents at a skilled nursing facility, 1 resident of a nearby skilled nursing facility, 3 health care workers, and a family member of a resident of one of the skilled nursing facilities. Person-to-person transmission was detected in a cluster of 5 patients who shared the same single-nucleotide variation in their SARS-CoV-2 genomes. High viral genomic diversity was identified: 20 Los Angeles isolates (15.0%) resembled SARS-CoV-2 genomes from Asia, while 109 Los Angeles isolates (82.0%) were similar to isolates originating from Europe. Analysis of other common respiratory viral pathogens did not reveal coinfection in the cohort.

Conclusions and Relevance

These findings highlight the precision of detecting person-to-person transmission and accurate contact tracing directly through SARS-CoV-2 genome isolation and sequencing. Development and application of phylogenetic analyses from the Los Angeles population established connections between COVID-19 clusters locally and throughout the US.

SARS-CoV-2 and COVID-19: A genetic, epidemiological, and evolutionary perspective

In less than five months, COVID-19 has spread from a small focus in Wuhan, China, to more than 5 million people in almost every country in the world, dominating the concern of most governments and public health systems. The social and political distresses caused by this epidemic will certainly impact our world for a long time to come. Here, we synthesize lessons from a range of scientific perspectives rooted in epidemiology, virology, genetics, ecology and evolutionary biology so as to provide perspective on how this pandemic started, how it is developing, and how best we can stop it.

Mapping genome variation of SARS-CoV-2 worldwide highlights the impact of COVID-19 super-spreaders

The human pathogen severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the major pandemic of the twenty-first century. We analyzed more than 4700 SARS-CoV-2 genomes and associated metadata retrieved from public repositories. SARS-CoV-2 sequences have a high sequence identity (>99.9%), which drops to >96% when compared to bat coronavirus genome. We built a mutation-annotated reference SARS-CoV-2 phylogeny with two main macro-haplogroups, A and B, both of Asian origin, and more than 160 sub-branches representing virus strains of variable geographical origins worldwide, revealing a rather uniform mutation occurrence along branches that could have implications for diagnostics and the design of future vaccines. Identification of the root of SARS-CoV-2 genomes is not without problems, owing to conflicting interpretations derived from either using the bat coronavirus genomes as an outgroup or relying on the sampling chronology of the SARS-CoV-2 genomes and TMRCA estimates; however, the overall scenario favors haplogroup A as the ancestral node. Phylogenetic analysis indicates a TMRCA for SARS-CoV-2 genomes dating to November 12, 2019, thus matching epidemiological records. Sub-haplogroup A2 most likely originated in Europe from an Asian ancestor and gave rise to subclade A2a, which represents the major non-Asian outbreak, especially in Africa and Europe. Multiple founder effect episodes, most likely associated with super-spreader hosts, might explain COVID-19 pandemic to a large extent.

Tracking the onset date of the community spread of SARS-CoV-2 in western countries

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) rapidly spread around the world during 2020, but the precise time in which the virus began to spread locally is difficult to trace for most countries. Here, we estimate the probable onset date of the community spread of SARS-CoV-2 for heavily affected countries from Western Europe and the Americas on the basis of the cumulative number of deaths reported during the early stage of the epidemic. Our results support that SARS-CoV-2 probably started to spread locally in all western countries analysed between mid-January and mid-February 2020, thus long before community transmission was officially recognised and control measures were implemented.

Genetic grouping of SARS-CoV-2 coronavirus sequences using informative subtype markers for pandemic spread visualization

We propose an efficient framework for genetic subtyping of SARS-CoV-2, the novel coronavirus that causes the COVID-19 pandemic. Efficient viral subtyping enables visualization and modeling of the geographic distribution and temporal dynamics of disease spread. Subtyping thereby advances the development of effective containment strategies and, potentially, therapeutic and vaccine strategies. However, identifying viral subtypes in real-time is challenging: SARS-CoV-2 is a novel virus, and the pandemic is rapidly expanding. Viral subtypes may be difficult to detect due to rapid evolution; founder effects are more significant than selection pressure; and the clustering threshold for subtyping is not standardized. We propose to identify mutational signatures of available SARS-CoV-2 sequences using a population-based approach: an entropy measure followed by frequency analysis. These signatures, Informative Subtype Markers (ISMs), define a compact set of nucleotide sites that characterize the most variable (and thus most informative) positions in the viral genomes sequenced from different individuals. Through ISM compression, we find that certain distant nucleotide variants covary, including non-coding and ORF1ab sites covarying with the D614G spike protein mutation which has become increasingly prevalent as the pandemic has spread. ISMs are also useful for downstream analyses, such as spatiotemporal visualization of viral dynamics. By analyzing sequence data available in the GISAID database, we validate the utility of ISM-based subtyping by comparing spatiotemporal analyses using ISMs to epidemiological studies of viral transmission in Asia, Europe, and the United States. In addition, we show the relationship of ISMs to phylogenetic reconstructions of SARS-CoV-2 evolution, and therefore, ISMs can play an important complementary role to phylogenetic tree-based analysis, such as is done in the Nextstrain project. The developed pipeline dynamically generates ISMs for newly added SARS-CoV-2 sequences and updates the visualization of pandemic spatiotemporal dynamics, and is available on Github at https://github.com/EESI/ISM (Jupyter notebook), https://github.com/EESI/ncov_ism (command line tool) and via an interactive website at https://covid19-ism.coe.drexel.edu/.

Sequencing identifies multiple early introductions of SARS-CoV-2 to the New York City Region

Effective public response to a pandemic relies upon accurate measurement of the extent and dynamics of an outbreak. Viral genome sequencing has emerged as a powerful approach to link seemingly unrelated cases, and large-scale sequencing surveillance can inform on critical epidemiological parameters. Here, we report the analysis of 864 SARS-CoV-2 sequences from cases in the New York City metropolitan area during the COVID-19 outbreak in Spring 2020. The majority of cases had no recent travel history or known exposure, and genetically linked cases were spread throughout the region. Comparison to global viral sequences showed that early transmission was most linked to cases from Europe. Our data are consistent with numerous seeds from multiple sources and a prolonged period of unrecognized community spreading. This work highlights the complementary role of genomic surveillance in addition to traditional epidemiological indicators.

Response to comment on "genetic variants and source of introduction of SARS-CoV-2 in South America"

During a pandemic, science needs data to generate helpful evidence, and researchers assume this responsibility despite the risk of potential bias. This is the response to the comment made by Pedro Romero, who argued that our manuscript did not use reassembling and mapping strategies for corroborating mutations, and lacked bootstrap support in the phylogenetic analysis.

Real-time public health communication of local SARS-CoV-2 genomic epidemiology

Genomic epidemiology can provide a unique, real-time understanding of SARS-CoV-2 transmission patterns. Yet the potential for genomic analyses to guide local policy and community-based behavioral decisions is limited because they are often oriented towards specially trained scientists and conducted on a national or global scale. Here, we propose a new paradigm: Phylogenetic analyses performed on a local level (municipal, county, or state), with results communicated in a clear, timely, and actionable manner to strengthen public health responses. We believe that presenting results rapidly, and tailored to a non-expert audience, can serve as a template for effective public health response to COVID-19 and other emerging viral diseases.