Global landscape of SARS-CoV-2 genomic surveillance and data sharing

Reconciling data actionability and accountability in global health research: The case of SARS-CoV-2

The requirements for actionability and accountability in data infrastructures are often viewed as incompatible, creating a trade-off where enhancing one diminishes the other. Through a comparative analysis of two data infrastructures used to share genomic data about the SARS-CoV-2 virus, we argue that making data actionable for knowledge development involves a commitment to ensuring that the data in question are representative of the phenomena being studied and accountable to data subjects and users. This in turn presupposes that: (1) enough data are contributed by a wide and diverse set of relevant sources; (2) mechanisms of feedback and inclusion are set up to ensure that data contributors can participate in data governance and interpretation, thereby helping to adequately contextualise data; and (3) accountability extends to the ways in which data infrastructures are run, financed and positioned vis-à-vis the communities they are meant to serve. Such a model of data sharing can only work on the understanding that data do not need to be easily accessible to be actionable; rather, actionability depends on the responsiveness and accountability of data infrastructures, and the efforts invested in ensuring open communication among contributors.

Accurate predictions of SARS-CoV-2 infectivity from comprehensive analysis

An unprecedented amount of SARS-CoV-2 data has been accumulated compared with previous infectious diseases, enabling insights into its evolutionary process and more thorough analyses. This study investigates SARS-CoV-2 features as it evolved to evaluate its infectivity. We examined viral sequences and identified the polarity of amino acids in the receptor binding motif (RBM) region. We detected an increased frequency of amino acid substitutions to lysine (K) and arginine (R) in variants of concern (VOCs). As the virus evolved to Omicron, commonly occurring mutations became fixed components of the new viral sequence. Furthermore, at specific positions of VOCs, only one type of amino acid substitution and a notable absence of mutations at D467 were detected. We found that the binding affinity of SARS-CoV-2 lineages to the ACE2 receptor was impacted by amino acid substitutions. Based on our discoveries, we developed APESS, an evaluation model evaluating infectivity from biochemical and mutational properties. In silico evaluation using real-world sequences and in vitro viral entry assays validated the accuracy of APESS and our discoveries. Using Machine Learning, we predicted mutations that had the potential to become more prominent. We created AIVE, a web-based system, accessible at https://ai-ve.org to provide infectivity measurements of mutations entered by users. Ultimately, we established a clear link between specific viral properties and increased infectivity, enhancing our understanding of SARS-CoV-2 and enabling more accurate predictions of the virus.

Tracing the transmission of carbapenem-resistant Enterobacterales at the patient: ward environmental nexus

INTRODUCTION

Colonisation and infection with Carbapenem-resistant Enterobacterales (CRE) in healthcare settings poses significant risks, especially for vulnerable patients. Genomic analysis can be used to trace transmission routes, supporting antimicrobial stewardship and informing infection control strategies. Here we used genomic analysis to track the movement and transmission of CREs within clinical and environmental samples.

METHODS

25 isolates were cultured from clinical patient samples or swabs, that tested positive for OXA-48-like variants using the NG-Test® CARBA-5 test and whole genome sequenced (WGS) using Oxford Nanopore Technologies (ONT). 158 swabs and 52 wastewater samples were collected from the ward environment. 60 isolates (matching clinical isolate genera; Klebsiella, Enterobacter, Citrobacter and Escherichia) were isolated from the environmental samples using selective agar. Metagenomic sequencing was undertaken on 36 environmental wastewater and swab samples.

RESULTS

21/25 (84%) clinical isolates had > 1 blaOXA gene and 19/25 (76%) harboured > 1 blaNDM gene. Enterobacterales were most commonly isolated from environmental wastewater samples 27/52 (51.9%), then stick swabs 5/43 (11.6%) and sponge swabs 5/115 (4.3%). 11/60 (18%) environmental isolates harboured > 1 blaOXA gene and 1.9% (1/60) harboured blaNDM-1. blaOXA genes were found in 2/36 (5.5%) metagenomic environmental samples.

CONCLUSIONS

Potential for putative patient-patient and patient-ward transmission was shown. Metagenomic sampling needs optimization to improve sensitivity.

"The COVID-19 pandemic in BRICS: Milestones, interventions, and molecular epidemiology"

Brazil, Russia, India, China, and South Africa (BRICS) are a group of developing countries with shared economic, healthcare, and scientific interests. These countries navigate multiple syndemics, and the COVID-19 pandemic placed severe strain on already burdened BRICS' healthcare systems, hampering effective pandemic interventions. Genomic surveillance and molecular epidemiology remain indispensable tools for facilitating informed pandemic intervention. To evaluate the combined manner in which the pandemic unfolded in BRICS countries, we reviewed the BRICS pandemic epidemiological and genomic milestones, which included the first reported cases and deaths, and pharmaceutical and non-pharmaceutical interventions implemented in these countries. To assess the development of genomic surveillance capacity and efficiency over the pandemic, we analyzed the turnaround time from sample collection to data availability and the technologies used for genomic analysis. This data provided information on the laboratory capacities that enable the detection of emerging SARS-CoV-2 variants and highlight their potential for monitoring other pathogens in ongoing public health efforts. Our analyses indicated that BRICS suffered >105.6M COVID-19 infections, resulting in >1.7M deaths. BRICS countries detected intricate genetic combinations of SARS-CoV-2 variants that fueled country-specific pandemic waves. BRICS' genomic surveillance programs enabled the identification and characterization of the majority of globally circulating Variants of Concern (VOCs) and their descending lineages. Pandemic intervention strategies first implemented by BRICS countries included non-pharmaceutical interventions during the onset of the pandemic, such as nationwide lockdowns, quarantine procedures, the establishment of fever clinics, and mask mandates- which were emulated internationally. Vaccination rollout strategies complemented this, some representing the first of their kind. Improvements in BRICS sequencing and data generation turnaround time facilitated quicker detection of circulating and emerging variants, supported by investments in sequencing and bioinformatic infrastructure. Intra-BRICS cooperation contributed to the ongoing intervention in COVID-19 and other pandemics, enhancing collective capabilities in addressing these health challenges. The data generated continues to inform BRICS-centric pandemic intervention strategies and influences global health matters. The increased laboratory and bioinformatic capacity post-COVID-19 will support the detection of emerging pathogens.

SARS-CoV-2 introductions to the island of Ireland: a phylogenetic and geospatiotemporal study of infection dynamics

BACKGROUND

Ireland's COVID-19 response combined extensive SARS-CoV-2 testing to estimate incidence, with whole genome sequencing (WGS) for genome surveillance. As an island with two political jurisdictions-Northern Ireland (NI) and Republic of Ireland (RoI)-and access to detailed passenger travel data, Ireland provides a unique setting to study virus introductions and evaluate public health measures. Using a substantial Irish genomic dataset alongside global data from GISAID, this study aimed to trace the introduction and spread of SARS-CoV-2 across the island.

METHODS

We recursively searched for 29,518 SARS-CoV-2 genome sequences collected in Ireland from March 2020 to June 2022 within the global SARS-CoV-2 phylogenetic tree and identified clusters based on shared last common non-Irish ancestors. A maximum parsimony approach was used to assign a likely country of origin to each cluster. The geographic locations and collection dates of the samples in each introduction cluster were used to map the spread of the virus across Ireland. Downsampling was used to model the impact of varying levels of sequencing and normalisation for population permitted comparison between jurisdictions.

RESULTS

Six periods spanning the early introductions and the emergence of Alpha, Delta, and Omicron variants were studied in detail. Among 4439 SARS-CoV-2 introductions to Ireland, 2535 originated in England, with additional cases largely from the rest of Great Britain, United States of America, and Northwestern Europe. Introduction clusters ranged in size from a single to thousands of cases. Introductions were concentrated in the densely populated Dublin and Belfast areas, with many clusters spreading islandwide. Genetic phylogeny was able to effectively trace localised transmission patterns. Introduction rates were similar in NI and RoI for most variants, except for Delta, which was more frequently introduced to NI.

CONCLUSIONS

Tracking individual introduction events enables detailed modelling of virus spread patterns and clearer assessment of the effectiveness of control measures. Stricter travel restrictions in RoI likely reduced Delta introductions but not infection rates, which were similar across jurisdictions. Local and global sequencing levels influence the information available from phylogenomic analyses and we describe an approach to assess the ability of a chosen WGS level to detect virus introductions.

Genomic analysis of the early COVID-19 pandemic in Haiti reveals Caribbean-specific variant dynamics

Pathogen sequencing during the COVID-19 pandemic has generated more whole genome sequencing data than for any other epidemic, allowing epidemiologists to monitor the transmission and evolution of SARS-CoV-2. However, large parts of the world are heavily underrepresented in sequencing efforts, including the Caribbean islands. We performed genome sequencing of SARS-CoV-2 from upper respiratory tract samples collected in Haiti during the spring of 2020. We used phylogenetic analysis to assess the pandemic dynamics in the Caribbean region and observed that the epidemic in Haiti was seeded by multiple introductions, primarily from the United States. We identified the emergence of a SARS-CoV-2 lineage (B.1.478) from Haiti that spread into North America, as well as evidence of the undocumented spread of SARS-CoV-2 within the Caribbean. We demonstrate that the genomic analysis of a relatively modest number of samples from a severely under-sampled region can provide new insight on a previously unobserved spread of a specific lineage, demonstrating the importance of geographically widespread genomic epidemiology.

Trends and impacts of SARS-CoV-2 genome sharing: a comparative analysis of China and the global community, 2020-2023

Objective

The global sharing of pathogen genome sequences has been significantly expedited by the COVID-19 pandemic. This study aims to elucidate the global landscape of SARS-CoV-2 genome sharing between 2020 and 2023 with a focus on quantity, timeliness, and quality. Specifically, the characteristics of China are examined.

Methods

SARS-CoV-2 genomes along with associated metadata were sourced from GISAID database. The genomes were analyzed to evaluate the quantity, timeliness, and quality across different countries/regions. The metadata characteristics of shared genomes in China in 2023 were examined and compared with the actual demographic data of China in 2023.

Results

From 2020 to 2023, European countries consistently maintained high levels of genomic data sharing in terms of quantity, timeliness, and quality. In 2023, China made remarkable improvements in sequence sharing, ranking among the top 3.89% globally for quantity, 22.78% for timeliness, and 17.78% for quality. The genome sharing in China in 2023 covered all provinces with Shanghai Municipality contributing the most genomes. Human samples accounted for 99.73% of the shared genomes and exhibited three distinct peaks in collection dates. Males constituted 52.06%, while females constituted 47.94%. Notably, there was an increase in individuals aged 65 and above within the GISAID database compared to China's overall population in 2023.

Conclusion

The global sharing of SARS-CoV-2 genomes in 2020-2023 exhibited disparities in terms of quantity, timeliness, and quality. However, China has made significant advancements since 2023 by achieving comprehensive coverage across provinces, timely dissemination of data, and widespread population monitoring. Strengthening data sharing capabilities in countries like China during the SARS-CoV-2 pandemic will play a crucial role in containing and responding to future pandemics caused by emerging pathogens.

The Fitness of Molnupiravir-Signed SARS-CoV-2 Variants: Imputation Analysis Based on Prescription Counts and Global Initiative on Sharing All Influenza Data Analyses by Country

INTRODUCTION

Molnupiravir is one of the oral direct-acting antivirals against SARS-CoV-2, largely deployed during the COVID-19 pandemic since the 2022 Omicron wave. While efficacy has been questioned in post-marketing clinical trials (leading to the EMA withdrawing its authorization), growing concerns have mounted regarding its possible mutagenic effects on the virus. While it has been assumed that either all the host viral load was cleared by the drug or drug-generated variants were not fit enough to survive, several lineages with a high transition/transversion ratio (a signature of molnupiravir action) have been recently reported from GISAID.

METHODS

We report here a systematic analysis of the GISAID database for sequences showing a molnupiravir signature, exposing a public web-based interface (https://ukcovid.xyz/molnupiravir/), and performing an imputation analysis based on per-country prescription (corrected by sequencing).

RESULTS

Our analysis confirms a direct correlation between the number of molnupiravir courses and the number of mutationally signed sequences deposited in GISAID in individual countries.

CONCLUSIONS

Molnupiravir can generate fit SARS-CoV-2 variants that transmit in the general population.

Technological Barriers to Routine Genomic Surveillance for Vaccine Development Against SARS-CoV-2 in Africa: A Systematic Review

The Global Initiative on Sharing All Influenza Data, a public-access database for sharing severe acute respiratory syndrome coronavirus 2 genomic sequencing data, has received significantly less data from African countries compared to the global total. Furthermore, the contribution of these data was infrequent and, for some countries, non-existent. The primary aim of this review is to identify the technological barriers to routine genomic surveillance in Africa. PubMed and Google Scholar were searched for the relevant articles, and other eligible articles were identified from the reference list examination according to the PRISMA checklist. Eighty-four full-text articles were analysed for eligibility, and 49 published full-texted articles were included in the final qualitative analysis. The main technological barriers identified were limited genomic surveillance capacity, limited genomic sequencing infrastructure, lack of resources and skilled or trained scientists, and the high cost of importing, establishing, and maintaining a genomic sequencing facility. The Africa Pathogen Genomics Initiative aims to improve genomic surveillance capacity across Africa, through resources, training, education, infrastructure, and regional sequencing centres. Furthermore, collaborations between African governments and international partners or national, private, and academic institutions are imperative to sustain genomic surveillance in Africa, and investment in genomic sequencing and research and development is paramount. Longer turnaround times interfere with global viral evolution monitoring and national implementation of effective policies to reduce the burden and disease. Establishing effective genomic surveillance systems guides public health responses and vaccine development for diseases endemic in Africa.

The PHA4GE Microbial Data-Sharing Accord: establishing baseline consensus microbial data-sharing norms to facilitate cross-sectoral collaboration

Microbial data sharing underlies evidence-based microbial research, as well as pathogen surveillance and analysis essential to public health. While the need for data sharing was highlighted during the SARS-CoV-2 pandemic, some concerns regarding secondary data use have also surfaced. Although general guidelines are available for data sharing, we note the absence of a set of established, universal, unambiguous and accessible principles to guide the secondary use of microbial data. Here, we propose the Public Health Alliance for Genomic Epidemiology (PHA4GE) Microbial Data-Sharing Accord to consolidate consensus norms and accepted practices for the secondary use of microbial data. The Accord provides a set of seven simple, baseline principles to address key concerns that may arise for researchers providing microbial datasets for secondary use and to guide responsible use by data users. By providing clear rules for secondary use of microbial data, the Accord can increase confidence in sharing by data providers and protect against data mis-use during secondary analyses.

Extracorporeal Membrane Oxygenation for COVID-19 During the Delta and Omicron Waves in North America

Clinical outcomes for patients with severe acute respiratory failure caused by different variants of the coronavirus disease 2019 (COVID-19) supported with extracorporeal membrane oxygenation (ECMO) are incompletely understood. Clinical characteristics, pre-ECMO management, and hospital mortality at 90 days for adults with COVID-19 who received venovenous ECMO (VV-ECMO) at North American centers during waves predominated by Delta (August 16 to December 12, 2021) and Omicron (January 31 to May 31, 2022) severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants were compared in a competing risks framework. One thousand seven hundred and sixty-six patients (1,580 Delta, 186 Omicron) received VV-ECMO for COVID-19 during the Delta- and Omicron-predominant waves in North American centers. In the unadjusted competing risks model, no significant difference was observed in risk of hospital mortality at 90 days between patients during the Delta- versus Omicron-predominant wave (subhazard ratio [sHR], 0.94; 95% confidence interval [CI], 0.74-1.19), but patients supported with VV-ECMO during the Omicron-predominant wave had a significantly lower adjusted risk of hospital mortality at 90 days (subhazard ratio, 0.71; 95% CI, 0.51-0.99). Patients receiving VV-ECMO during the Omicron-predominant wave had a similar unadjusted risk of hospital mortality at 90 days, but a significantly lower adjusted risk of hospital mortality at 90 days than those receiving VV-ECMO during the Delta-predominant wave.

Genomics and Bioinformatics in One Health: Transdisciplinary Approaches for Health Promotion and Disease Prevention

The One Health concept underscores the interconnectedness of human, animal, and environmental health, necessitating an integrated, transdisciplinary approach to tackle contemporary health challenges. This perspective paper explores the pivotal role of genomics and bioinformatics in advancing One Health initiatives. By leveraging genomic technologies and bioinformatics tools, researchers can decode complex biological data, enabling comprehensive insights into pathogen evolution, transmission dynamics, and host-pathogen interactions across species and environments (or ecosystems). These insights are crucial for predicting and mitigating zoonotic disease outbreaks, understanding antimicrobial resistance patterns, and developing targeted interventions for health promotion and disease prevention. Furthermore, integrating genomic data with environmental and epidemiological information enhances the precision of public health responses. Here we discuss case studies demonstrating successful applications of genomics and bioinformatics in One Health contexts, such as including data integration, standardization, and ethical considerations in genomic research. By fostering collaboration among geneticists, bioinformaticians, epidemiologists, zoologists, and data scientists, the One Health approach can harness the full potential of genomics and bioinformatics to safeguard global health. This perspective underscores the necessity of continued investment in interdisciplinary education, research infrastructure, and policy frameworks to effectively employ these technologies in the service of a healthier planet.

Pathogen genomic surveillance status among lower resource settings in Asia

Asia remains vulnerable to new and emerging infectious diseases. Understanding how to improve next generation sequencing (NGS) use in pathogen surveillance is an urgent priority for regional health security. Here we developed a pathogen genomic surveillance assessment framework to assess capacity in low-resource settings in South and Southeast Asia. Data collected between June 2022 and March 2023 from 42 institutions in 13 countries showed pathogen genomics capacity exists, but use is limited and under-resourced. All countries had NGS capacity and seven countries had strategic plans integrating pathogen genomics into wider surveillance efforts. Several pathogens were prioritized for human surveillance, but NGS application to environmental and human-animal interface surveillance was limited. Barriers to NGS implementation include reliance on external funding, supply chain challenges, trained personnel shortages and limited quality assurance mechanisms. Coordinated efforts are required to support national planning, address capacity gaps, enhance quality assurance and facilitate data sharing for decision making.

Timely vaccine strain selection and genomic surveillance improves evolutionary forecast accuracy of seasonal influenza A/H3N2

For the last decade, evolutionary forecasting models have influenced seasonal influenza vaccine design. These models attempt to predict which genetic variants circulating at the time of vaccine strain selection will be dominant 12 months later in the influenza season targeted by vaccination campaign. Forecasting models depend on hemagglutinin (HA) sequences from the WHO's Global Influenza Surveillance and Response System to identify currently circulating groups of related strains (clades) and estimate clade fitness for forecasts. However, the average lag between collection of a clinical sample and the submission of its sequence to the Global Initiative on Sharing All Influenza Data (GISAID) EpiFlu database is ~3 months. Submission lags complicate the already difficult 12-month forecasting problem by reducing understanding of current clade frequencies at the time of forecasting. These constraints of a 12-month forecast horizon and 3-month average submission lags create an upper bound on the accuracy of any long-term forecasting model. The global response to the SARS-CoV-2 pandemic revealed that modern vaccine technology like mRNA vaccines can reduce how far we need to forecast into the future to 6 months or less and that expanded support for sequencing can reduce submission lags to GISAID to 1 month on average. To determine whether these recent advances could also improve long-term forecasts for seasonal influenza, we quantified the effects of reducing forecast horizons and submission lags on the accuracy of forecasts for A/H3N2 populations. We found that reducing forecast horizons from 12 months to 6 or 3 months reduced average absolute forecasting errors to 25% and 50% of the 12-month average, respectively. Reducing submission lags provided little improvement to forecasting accuracy but decreased the uncertainty in current clade frequencies by 50%. These results show the potential to substantially improve the accuracy of existing influenza forecasting models by modernizing influenza vaccine development and increasing global sequencing capacity.

Surveillance strategies for the detection of new pathogen variants across epidemiological contexts

Surveillance systems that monitor pathogen genome sequences are critical for rapidly detecting the introduction and emergence of pathogen variants. To evaluate how interactions between surveillance capacity, variant properties, and the epidemiological context influence the timeliness of pathogen variant detection, we developed a geographically explicit stochastic compartmental model to simulate the transmission of a novel SARS-CoV-2 variant in New York City. We measured the impact of (1) testing and sequencing volume, (2) geographic targeting of testing, (3) the timing and location of variant emergence, and (4) the relative variant transmissibility on detection speed and on the undetected disease burden. Improvements in detection times and reduction of undetected infections were driven primarily by increases in the number of sequenced samples. The relative transmissibility of the new variant and the epidemic context of variant emergence also influenced detection times, showing that individual surveillance strategies can result in a wide range of detection outcomes, depending on the underlying dynamics of the circulating variants. These findings help contextualize the design, interpretation, and trade-offs of genomic surveillance strategies of pandemic respiratory pathogens.

The Emergence and Evolution of SARS-CoV-2

The origin of SARS-CoV-2 has evoked heated debate and strong accusations, yet seemingly little resolution. I review the scientific evidence on the origin of SARS-CoV-2 and its subsequent spread through the human population. The available data clearly point to a natural zoonotic emergence within, or closely linked to, the Huanan Seafood Wholesale Market in Wuhan. There is no direct evidence linking the emergence of SARS-CoV-2 to laboratory work conducted at the Wuhan Institute of Virology. The subsequent global spread of SARS-CoV-2 was characterized by a gradual adaptation to humans, with dual increases in transmissibility and virulence until the emergence of the Omicron variant. Of note has been the frequent transmission of SARS-CoV-2 from humans to other animals, marking it as a strongly host generalist virus. Unless lessons from the origin of SARS-CoV-2 are learned, it is inevitable that more zoonotic events leading to more epidemics and pandemics will plague human populations.

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

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

Retrospective Analysis of Omicron in Minas Gerais, Brazil: Emergence, Dissemination, and Diversification

Brazil is one of the countries most affected by COVID-19, with the highest number of deaths recorded. Brazilian Health Institutions have reported four main peaks of positive COVID-19 cases. The last two waves were characterized by the emergence of the VOC Omicron and its sublineages. This study aimed to conduct a retrospective surveillance study illustrating the emergence, dissemination, and diversification of the VOC Omicron in 15 regional health units (RHUs) in MG, the second most populous state in Brazil, by combining epidemiological and genomic data. A total of 5643 confirmed positive COVID-19 samples were genotyped using the panels TaqMan SARS-CoV-2 Mutation and 4Plex SC2/VOC Bio-Manguinhos to define mutations classifying the BA.1, BA.2, BA.4, and BA.5 sublineages. While sublineages BA.1 and BA.2 were more prevalent during the third wave, BA.4 and BA.5 dominated the fourth wave in the state. Epidemiological and viral genome data suggest that age and vaccination with booster doses were the main factors related to clinical outcomes, reducing the number of deaths, irrespective of the Omicron sublineages. Complete genome sequencing of 253 positive samples confirmed the circulation of the BA.1, BA.2, BA.4, and BA.5 subvariants, and phylogenomic analysis demonstrated that the VOC Omicron was introduced through multiple international events, followed by transmission within the state of MG. In addition to the four subvariants, other lineages have been identified at low frequency, including BQ.1.1 and XAG. This integrative study reinforces that the evolution of Omicron sublineages was the most significant factor driving the highest peaks of positive COVID-19 cases without an increase in more severe cases, prevented by vaccination boosters.

SARS-CoV-2 Omicron subvariant genomic variation associations with immune evasion in Northern California: A retrospective cohort study

Background

The possibility of association between SARS-CoV-2 genomic variation and immune evasion is not known among persons with Omicron variant SARS-CoV-2 infection.

Methods

In a retrospective cohort, using Poisson regression adjusting for sociodemographic variables and month of infection, we examined associations between individual non-lineage defining mutations and SARS-CoV-2 immunity status, defined as a) no prior recorded infection, b) not vaccinated but with at least one prior recorded infection, c) complete primary series vaccination, and/or d) primary series vaccination and ≥ 1 booster. We identified all non-synonymous single nucleotide polymorphisms (SNPs), insertions and deletions in SARS-CoV-2 genomes with ≥5% allelic frequency and population frequency of ≥5% and ≤95%. We also examined correlations between the presence of SNPs with each other, with subvariants, and over time.

Results

Seventy-nine mutations met inclusion criteria. Among 15,566 persons infected with Omicron SARS-CoV-2, 1,825 (12%) were unvaccinated with no prior recorded infection, 360 (2%) were unvaccinated with a recorded prior infection, 13,381 (86%) had a complete primary series vaccination, and 9,172 (58%) had at least one booster. After examining correlation between SNPs, 79 individual non-lineage defining mutations were organized into 38 groups. After correction for multiple testing, no individual SNPs or SNP groups were significantly associated with immunity status levels.

Conclusions

Genomic variation identified within SARS-CoV-2 Omicron specimens was not significantly associated with immunity status, suggesting that contribution of non-lineage defining SNPs to immune evasion is minimal. Larger-scale surveillance of SARS-CoV-2 genomes linked with clinical data can help provide information to inform future vaccine development.

Detection of SARS-CoV-2 variants in hospital wastewater in Peru, 2022

OBJECTIVE.

To identify the presence of the SARS-CoV-2 virus in wastewater from hospitals in Peru.

MATERIALS AND METHODS.

Water samples were collected from the effluents of nine hospitals in Peru during March and September 2022. SARS-CoV-2 was identified by using Illumina sequencing. Variant, lineage and clade assignments were carried out using the Illumina and Nextclado tools. We verified whether the SARS-CoV-2 variants obtained from wastewater were similar to those reported by the National Institute of Health of Peru from patients during the same period and region.

RESULTS.

Eighteen of the 20 hospital wastewater samples (90%) provided sequences of sufficient quality to be classified as the Omicron variant according to the WHO classification. Among them, six (30%) were assigned by Nextclade to clades 21K lineage BA.1.1 (n=1), 21L lineage BA.2 (n=2), and 22B lineages BA.5.1 (n=2) and BA .5.5 (n=1).

CONCLUSIONS.

SARS-CoV-2 variants were found in hospital wastewater samples and were similar to those reported by the surveillance system in patients during the same weeks and geographic areas. Wastewater monitoring could provide information on the environmental and temporal variation of viruses such as SARS-CoV-2.

Motivation for the study. To contribute to the surveillance of environmental samples from hospital effluents in order to achieve early warning of possible infectious disease outbreaks. Main findings. The Omicron variant of the COVID-19 virus was detected in wastewater from hospitals in Puno, Cuzco and Cajamarca; these results are similar to the reports by the Peruvian National Institute of Health based on nasopharyngeal swab samples. Implications. The presence of the Omicron variant in hospital wastewater during the third wave of the pandemic should raise awareness of the treatment system before wastewater is discharged into the public sewer system.

Tracking the prevalence and emergence of SARS-CoV-2 variants of concern using a regional genomic surveillance program

SARS-CoV-2 molecular testing coupled with whole-genome sequencing is instrumental for real-time genomic surveillance. Genomic surveillance is critical for monitoring the spread of variants of concern (VOCs) as well as discovery of novel variants. Since the beginning of the pandemic, millions of SARS-CoV-2 genomes have been deposited into public sequence databases. This is the result of efforts of both national and regional diagnostic laboratories. In this study, we describe the results of SARS-CoV-2 genomic surveillance from February 2021 to June 2022 at a metropolitan hospital in the United States. We demonstrate that consistent daily sampling is sufficient to track the regional prevalence and emergence of VOCs and recapitulate national trends. Similar sampling efforts should be considered a viable option for local SARS-CoV-2 genomic surveillance at other regional laboratories.

IMPORTANCE

In our manuscript, we describe the results of SARS-CoV-2 genomic surveillance from February 2021 to June 2022 at a metropolitan hospital in the United States. We demonstrate that consistent daily sampling is sufficient to track the regional prevalence and emergence of variants of concern (VOCs). Similar sampling efforts should be considered a viable option for local SARS-CoV-2 genomic surveillance at other regional laboratories. While the SARS-CoV-2 pandemic has evolved into a more endemic form, we still believe that additional real-world information about sampling, procedures, and data interpretation is valuable for ongoing as well as future genomic surveillance efforts. Our study should be of substantial interest to clinical virologists.

A Dynamic Prognostic Model for Identifying Vulnerable COVID-19 Patients at High Risk of Rapid Deterioration

PURPOSE

We aimed to validate and, if performance was unsatisfactory, update the previously published prognostic model to predict clinical deterioration in patients hospitalized for COVID-19, using data following vaccine availability.

METHODS

Using electronic health records of patients ≥18 years, with laboratory-confirmed COVID-19, from a large care-delivery network in Massachusetts, USA, from March 2020 to November 2021, we tested the performance of the previously developed prediction model and updated the prediction model by incorporating data after availability of COVID-19 vaccines. We randomly divided data into development (70%) and validation (30%) cohorts. We built a model predicting worsening in a published severity scale in 24 h by LASSO regression and evaluated performance by c-statistic and Brier score.

RESULTS

Our study cohort consisted of 8185 patients (Development: 5730 patients [mean age: 62; 44% female] and Validation: 2455 patients [mean age: 62; 45% female]). The previously published model had suboptimal performance using data after November 2020 (N = 4973, c-statistic = 0.60. Brier score = 0.11). After retraining with the new data, the updated model included 38 predictors including 18 changing biomarkers. Patients hospitalized after Jun 1st, 2021 (when COVID-19 vaccines became widely available in Massachusetts) were younger and had fewer comorbidities than those hospitalized before. The c-statistic and Brier score were 0.77 and 0.13 in the development cohort, and 0.73 and 0.14 in the validation cohort.

CONCLUSION

The characteristics of patients hospitalized for COVID-19 differed substantially over time. We developed a new dynamic model for rapid progression with satisfactory performance in the validation set.

Early mutational signatures and transmissibility of SARS-CoV-2 Gamma and Lambda variants in Chile

Genomic surveillance (GS) programmes were crucial in identifying and quantifying the mutating patterns of SARS-CoV-2 during the COVID-19 pandemic. In this work, we develop a Bayesian framework to quantify the relative transmissibility of different variants tailored for regions with limited GS. We use it to study the relative transmissibility of SARS-CoV-2 variants in Chile. Among the 3443 SARS-CoV-2 genomes collected between January and June 2021, where sampling was designed to be representative, the Gamma (P.1), Lambda (C.37), Alpha (B.1.1.7), B.1.1.348, and B.1.1 lineages were predominant. We found that Lambda and Gamma variants' reproduction numbers were 5% (95% CI: [1%, 14%]) and 16% (95% CI: [11%, 21%]) larger than Alpha's, respectively. Besides, we observed a systematic mutation enrichment in the Spike gene for all circulating variants, which strongly correlated with variants' transmissibility during the studied period (r = 0.93, p-value = 0.025). We also characterised the mutational signatures of local samples and their evolution over time and with the progress of vaccination, comparing them with those of samples collected in other regions worldwide. Altogether, our work provides a reliable method for quantifying variant transmissibility under subsampling and emphasises the importance of continuous genomic surveillance.

SARS-CoV-2 Genomic Epidemiology Dashboards: A Review of Functionality and Technological Frameworks for the Public Health Response

During the coronavirus disease 2019 (COVID-19) pandemic, the number and types of dashboards produced increased to convey complex information using digestible visualizations. The pandemic saw a notable increase in genomic surveillance data, which genomic epidemiology dashboards presented in an easily interpretable manner. These dashboards have the potential to increase the transparency between the scientists producing pathogen genomic data and policymakers, public health stakeholders, and the public. This scoping review discusses the data presented, functional and visual features, and the computational architecture of six publicly available SARS-CoV-2 genomic epidemiology dashboards. We found three main types of genomic epidemiology dashboards: phylogenetic, genomic surveillance, and mutational. We found that data were sourced from different databases, such as GISAID, GenBank, and specific country databases, and these dashboards were produced for specific geographic locations. The key performance indicators and visualization used were specific to the type of genomic epidemiology dashboard. The computational architecture of the dashboards was created according to the needs of the end user. The genomic surveillance of pathogens is set to become a more common tool used to track ongoing and future outbreaks, and genomic epidemiology dashboards are powerful and adaptable resources that can be used in the public health response.

Community methicillin-resistant Staphylococcus aureus outbreaks in areas of low prevalence

BACKGROUND

Community-acquired (CA), community-onset methicillin-resistant Staphylococcus aureus (CO-MRSA) infection presents a significant public health challenge, even where MRSA rates are historically lower. Despite successes in reducing hospital-onset MRSA, CO-MRSA rates are increasing globally, with a need to understand this trend, and the potential risk factors for re-emergence.

OBJECTIVES

This review aims to explore the characteristics of outbreaks of community-acquired community-onset methicillin-resistant Staphylococcus aureus in low-prevalence areas, to understand the factors involved in its rise, and to translate this knowledge into public health policy and further research needs.

SOURCES

PubMed, EMBASE, and Google Scholar were searched using combinations of the terms 'transmission', 'acquisition', 'community-acquired', 'MRSA', 'CA-MRSA', 'low prevalence', 'genomic', 'outbreak', 'colonisation', and 'carriage'. Wherever evidence was limited, additional articles were sought specifically, via PubMed searches. Papers where materials were not available in English were excluded.

CONTENT

Challenges in defining low-prevalence areas and the significance of exposure to various risk factors for community acquisition, such as healthcare settings, travel, livestock, and environmental factors, are discussed. The importance of genomic surveillance in identifying outbreak strains and understanding the transmission dynamics is highlighted, along with the need for robust public health policies and control measures.

IMPLICATIONS

The findings emphasise the complexity of CO-MRSA transmission and the necessity of a multifaceted approach in low-prevalence areas. This includes integrated and systematic surveillance of hospital-onset-, CO-, and livestock-associated MRSA, as has been effective in some Northern European countries. The evolution of CO-MRSA underscores the need for global collaboration, routine genomic surveillance, and comprehensive antimicrobial stewardship to mitigate the rise of CO-MRSA and address the broader challenge of antimicrobial resistance. These efforts are crucial for maintaining low MRSA prevalence and managing the increasing burden of CO-MRSA in both low and higher prevalence regions.

Online dashboards for SARS-CoV-2 wastewater-based epidemiology

Aim: Wastewater-based epidemiology (WBE) is increasingly used to monitor pandemics. In this manuscript, we review methods and limitations of WBE, as well as their online dashboards. Materials & methods: Online dashboards were retrieved using PubMed and search engines, and annotated for timeliness, availability of English version, details on SARS-CoV-2 sublineages, normalization by population and PPMoV load, availability of case/hospitalization count charts and of raw data for export. Results: We retrieved 51 web portals, half of them from Europe. Africa is represented from South Africa only, and only seven portals are available from Asia. Conclusion: WBS provides near-real-time cost-effective monitoring of analytes across space and time in populations. However, tremendous heterogeneity still persists in the SARS-CoV-2 WBE literature.

Ongoing Cooperative Engagement Facilitates Agile Pandemic and Outbreak Response: Lessons Learned Through Cooperative Engagement Between Uganda and the United States

Pathogens threaten human lives and disrupt economies around the world. This has been clearly illustrated by the current COVID-19 pandemic and outbreaks in livestock and food crops. To manage pathogen emergence and spread, cooperative engagement programs develop and strengthen biosafety, biosecurity, and biosurveillance capabilities among local researchers to detect pathogens. In this case study, we describe the efforts of a collaboration between the Los Alamos National Laboratory and the Uganda Virus Research Institute, the primary viral diagnostic laboratory in Uganda, to implement and ensure the sustainability of sequencing for biosurveillance. We describe the process of establishing this capability along with the lessons learned from both sides of the partnership to inform future cooperative engagement efforts in low- and middle-income countries. We found that by strengthening sequencing capabilities at the Uganda Virus Research Institute before the COVID-19 pandemic, the institute was able to successfully sequence SARS-CoV-2 samples and provide data to the scientific community. We highlight the need to strengthen and sustain capabilities through in-country training, collaborative research projects, and trust.

Sequencing and characterization of human bocavirus genomes from patients diagnosed in Southern France between 2017 and 2022

The diversity and evolution of the genomes of human bocavirus (HBoV), which causes respiratory diseases, have been scarcely studied. Here, we aimed to obtain and characterize HBoV genomes from patients's nasopharyngeal samples collected between 2017 and 2022 period (5 years and 7 months). Next-generation sequencing (NGS) used Illumina technology after having implemented using GEMI an in-house multiplex PCR amplification strategy. Genomes were assembled and analyzed with CLC Genomics, Mafft, BioEdit, MeV, Nextclade, MEGA, and iTol. A total of 213 genomes were obtained. Phylogeny classified them all as of Bocavirus 1 (HBoV1) species. Five HBoV1 genotypic clusters determined by hierarchical clustering analysis of 27 variable genome positions were scattered over the study period although with differences in yearly prevalence. A total of 167 amino acid substitutions were detected. Besides, coinfection was observed for 52% of the samples, rhinoviruses then adenoviruses (HAdVs) being the most common viruses. Principal component analysis showed that HBoV1 genotypic cluster α tended to be correlated with HAdV co-infection. Subsequent HAdV typing for HBoV1-positive samples and negative controls demonstrated that HAdVC species predominated but HAdVB was that significantly HBoV1-associated. Overall, we described here the first HBoV1 genomes sequenced for France. HBoV1 and HAdVB association deserves further investigation.

Most accurate mutations in SARS-CoV-2 genomes identified in Uzbek patients show novel amino acid changes

Purpose

The rapid changes in the coronavirus genomes created new strains after the first variation was found in Wuhan in 2019. SARS-CoV-2 genotypes should periodically undergo whole genome sequencing to control it because it has been extremely helpful in combating the virus. Many diagnoses, treatments, and vaccinations have been developed against it based on genome sequencing. With its practical implications, this study aimed to determine changes in the delta variant of SARS-CoV-2 widespread in Uzbekistan during the pandemic by genome sequencing, thereby providing crucial insights for developing effective control strategies that can be directly applied in the field.

Design

We meticulously generated 17 high-quality whole-genome sequence data from 48 SARS-CoV-2 genotypes of COVID-19 patients who tested positive by PCR in Tashkent, Uzbekistan. Our rigorous approach, which includes stringent quality control measures and multiple rounds of verification, ensures the accuracy and reliability of our findings.

Methods

Our study employed a unique combination of genome sequencing and bioinformatics web tools to analyze amino acid (AA) changes in the virus genomes. This approach allowed us to understand the genetic changes in the delta variant of SARS-CoV-2 widespread in Uzbekistan during the pandemic.

Results

Our study revealed significant nucleotide polymorphisms, including non-synonymous (missense) and synonymous mutations in the coding regions of the sequenced sample genomes. These findings, categorized by phylogenetic analysis into the G clade (or GK sub-clade), contribute to our understanding of the delta variant of SARS-CoV-2 widespread in Uzbekistan during the pandemic. A total of 134 mutations were identified, consisting of 65 shared and 69 unique mutations. These nucleotide changes, including one frameshift mutation, one conservative and disruptive insertion-deletion, four upstream region mutations, four downstream region mutations, 39 synonymous mutations, and 84 missense mutations, are crucial in the ongoing battle against the virus.

Conclusion

The comprehensive whole-genome sequencing data presented in this study aids in tracing the origins and sources of circulating SARS-CoV-2 variants and analyzing emerging variations within Uzbekistan and globally. The genome sequencing of SARS-CoV-2 from samples collected in Uzbekistan in late 2021, during the peak of the pandemic's second wave nationwide, is detailed here. Following acquiring these sequences, research efforts have focused on developing DNA and plant-based edible vaccines utilizing prevalent SARS-CoV-2 strains in Uzbekistan, which are currently undergoing clinical trials.

Efficient SARS-CoV-2 variant detection and monitoring with Spike Screen next-generation sequencing

The emergence and rapid spread of SARS-CoV-2 prompted the global community to identify innovative approaches to diagnose infection and sequence the viral genome because at several points in the pandemic positive case numbers exceeded the laboratory capacity to characterize sufficient samples to adequately respond to the spread of emerging variants. From week 10, 2020, to week 13, 2023, Slovenian routine complete genome sequencing (CGS) surveillance network yielded 41 537 complete genomes and revealed a typical molecular epidemiology with early lineages gradually being replaced by Alpha, Delta, and finally Omicron. We developed a targeted next-generation sequencing based variant surveillance strategy dubbed Spike Screen through sample pooling and selective SARS-CoV-2 spike gene amplification in conjunction with CGS of individual cases to increase throughput and cost-effectiveness. Spike Screen identifies variant of concern (VOC) and variant of interest (VOI) signature mutations, analyses their frequencies in sample pools, and calculates the number of VOCs/VOIs at the population level. The strategy was successfully applied for detection of specific VOC/VOI mutations prior to their confirmation by CGS. Spike Screen complemented CGS efforts with an additional 22 897 samples sequenced in two time periods: between week 42, 2020, and week 24, 2021, and between week 37, 2021, and week 2, 2022. The results showed that Spike Screen can be applied to monitor VOC/VOI mutations among large volumes of samples in settings with limited sequencing capacity through reliable and rapid detection of novel variants at the population level and can serve as a basis for public health policy planning.

Assessing eco-geographic influences on COVID-19 transmission: a global analysis

COVID-19 has been massively transmitted for almost 3 years, and its multiple variants have caused serious health problems and an economic crisis. Our goal was to identify the influencing factors that reduce the threshold of disease transmission and to analyze the epidemiological patterns of COVID-19. This study served as an early assessment of the epidemiological characteristics of COVID-19 using the MaxEnt species distribution algorithm using the maximum entropy model. The transmission of COVID-19 was evaluated based on human factors and environmental variables, including climate, terrain and vegetation, along with COVID-19 daily confirmed case location data. The results of the SDM model indicate that population density was the major factor influencing the spread of COVID-19. Altitude, land cover and climatic factor showed low impact. We identified a set of practical, high-resolution, multi-factor-based maximum entropy ecological niche risk prediction systems to assess the transmission risk of the COVID-19 epidemic globally. This study provided a comprehensive analysis of various factors influencing the transmission of COVID-19, incorporating both human and environmental variables. These findings emphasize the role of different types of influencing variables in disease transmission, which could have implications for global health regulations and preparedness strategies for future outbreaks.

INSaFLU-TELEVIR: an open web-based bioinformatics suite for viral metagenomic detection and routine genomic surveillance

BACKGROUND

Implementation of clinical metagenomics and pathogen genomic surveillance can be particularly challenging due to the lack of bioinformatics tools and/or expertise. In order to face this challenge, we have previously developed INSaFLU, a free web-based bioinformatics platform for virus next-generation sequencing data analysis. Here, we considerably expanded its genomic surveillance component and developed a new module (TELEVIR) for metagenomic virus identification.

RESULTS

The routine genomic surveillance component was strengthened with new workflows and functionalities, including (i) a reference-based genome assembly pipeline for Oxford Nanopore technologies (ONT) data; (ii) automated SARS-CoV-2 lineage classification; (iii) Nextclade analysis; (iv) Nextstrain phylogeographic and temporal analysis (SARS-CoV-2, human and avian influenza, monkeypox, respiratory syncytial virus (RSV A/B), as well as a "generic" build for other viruses); and (v) algn2pheno for screening mutations of interest. Both INSaFLU pipelines for reference-based consensus generation (Illumina and ONT) were benchmarked against commonly used command line bioinformatics workflows for SARS-CoV-2, and an INSaFLU snakemake version was released. In parallel, a new module (TELEVIR) for virus detection was developed, after extensive benchmarking of state-of-the-art metagenomics software and following up-to-date recommendations and practices in the field. TELEVIR allows running complex workflows, covering several combinations of steps (e.g., with/without viral enrichment or host depletion), classification software (e.g., Kaiju, Kraken2, Centrifuge, FastViromeExplorer), and databases (RefSeq viral genome, Virosaurus, etc.), while culminating in user- and diagnosis-oriented reports. Finally, to potentiate real-time virus detection during ONT runs, we developed findONTime, a tool aimed at reducing costs and the time between sample reception and diagnosis.

CONCLUSIONS

The accessibility, versatility, and functionality of INSaFLU-TELEVIR are expected to supply public and animal health laboratories and researchers with a user-oriented and pan-viral bioinformatics framework that promotes a strengthened and timely viral metagenomic detection and routine genomics surveillance. INSaFLU-TELEVIR is compatible with Illumina, Ion Torrent, and ONT data and is freely available at https://insaflu.insa.pt/ (online tool) and https://github.com/INSaFLU (code).

SARS-CoV-2 resistance to monoclonal antibodies and small-molecule drugs

Over four years have passed since the beginning of the COVID-19 pandemic. The scientific response has been rapid and effective, with many therapeutic monoclonal antibodies and small molecules developed for clinical use. However, given the ability for viruses to become resistant to antivirals, it is perhaps no surprise that the field has identified resistance to nearly all of these compounds. Here, we provide a comprehensive review of the resistance profile for each of these therapeutics. We hope that this resource provides an atlas for mutations to be aware of for each agent, particularly as a springboard for considerations for the next generation of antivirals. Finally, we discuss the outlook and thoughts for moving forward in how we continue to manage this, and the next, pandemic.

Next-generation sequencing of host genetics risk factors associated with COVID-19 severity and long-COVID in Colombian population

Coronavirus disease 2019 (COVID-19) was considered a major public health burden worldwide. Multiple studies have shown that susceptibility to severe infections and the development of long-term symptoms is significantly influenced by viral and host factors. These findings have highlighted the potential of host genetic markers to identify high-risk individuals and develop target interventions to reduce morbimortality. Despite its importance, genetic host factors remain largely understudied in Latin-American populations. Using a case-control design and a custom next-generation sequencing (NGS) panel encompassing 81 genetic variants and 74 genes previously associated with COVID-19 severity and long-COVID, we analyzed 56 individuals with asymptomatic or mild COVID-19 and 56 severe and critical cases. In agreement with previous studies, our results support the association between several clinical variables, including male sex, obesity and common symptoms like cough and dyspnea, and severe COVID-19. Remarkably, thirteen genetic variants showed an association with COVID-19 severity. Among these variants, rs11385942 (p < 0.01; OR = 10.88; 95% CI = 1.36-86.51) located in the LZTFL1 gene, and rs35775079 (p = 0.02; OR = 8.53; 95% CI = 1.05-69.45) located in CCR3 showed the strongest associations. Various respiratory and systemic symptoms, along with the rs8178521 variant (p < 0.01; OR = 2.51; 95% CI = 1.27-4.94) in the IL10RB gene, were significantly associated with the presence of long-COVID. The results of the predictive model comparison showed that the mixed model, which incorporates genetic and non-genetic variables, outperforms clinical and genetic models. To our knowledge, this is the first study in Colombia and Latin-America proposing a predictive model for COVID-19 severity and long-COVID based on genomic analysis. Our study highlights the usefulness of genomic approaches to studying host genetic risk factors in specific populations. The methodology used allowed us to validate several genetic variants previously associated with COVID-19 severity and long-COVID. Finally, the integrated model illustrates the importance of considering genetic factors in precision medicine of infectious diseases.

Utilizing cost-effective portable equipment to enhance COVID-19 variant tracking both on-site and at a large scale

Despite optimistic predictions on the eventual end of COVID-19 (Coronavirus Disease 2019), caution is necessary regarding the emergence of new variants to sustain a positive outlook and effectively address any potential future outbreaks. However, ongoing efforts to track COVID-19 variants are concentrated in developed countries and unique social practices and remote habitats of indigenous peoples present additional challenges. By combining small-sized equipment that is easily accessible and inexpensive, we performed SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) whole genome sequencing and measured the sample-to-answer time and accuracy of this portable variant tracking tool. Our portable design determined the variant of SARS-CoV-2 in an infected individual within 9 hours and 15 minutes without external power or internet connection, surpassing the speed of previous portable tools. It took only 16 minutes to complete sequencing run, whole genome assembly, and lineage determination using a single standalone laptop. We then demonstrated the capability to produce 289 SARS-CoV-2 whole genome sequences in a single portable sequencing run, representing a significant improvement over an existing throughput of 96 sequences per run. We verified the accuracy of portable sequencing by comparison with two other independent sequencing methods. We showed that our high-throughput data consistently represented the circulating variants in Los Angeles, United States, when compared with publicly available sequences. Our scheme is designed to be flexible, rapid, and accurate, making it a valuable tool for large-scale surveillance operations in low- and middle-income countries as well as targeted surveys for vulnerable populations in remote locations.IMPORTANCEThere have been significant efforts to track COVID-19 (Coronavirus Disease 2019) variants, accumulating over 15 million SARS-CoV-2 sequences as of 2023. However, the distribution of global survey data is highly skewed, with nearly half of all countries having inadequate or low levels of genomic surveillance. In addition, indigenous peoples face more severe threats from COVID-19, due to their generally remote residence and unique social practices. Cost-effective portable sequencing tools have been used to investigate Ebola and Zika outbreaks. However, these tools have a sample-to-answer time of around 24 hours and require an internet connection for data transfer to an off-site cloud server. In our study, we rapidly determined COVID-19 variants using only small and inexpensive equipment, with a completion time of 9 hours and 15 minutes. Furthermore, we produced 289 near-full-length SARS-CoV-2 genome sequences from a single portable Nanopore sequencing run, representing a threefold increase in throughput compared with existing Nanopore sequencing methods.

Postpandemic Sentinel Surveillance of Respiratory Diseases in the Context of the World Health Organization Mosaic Framework: Protocol for a Development and Evaluation Study Involving the English Primary Care Network 2023-2024

BACKGROUND

Prepandemic sentinel surveillance focused on improved management of winter pressures, with influenza-like illness (ILI) being the key clinical indicator. The World Health Organization (WHO) global standards for influenza surveillance include monitoring acute respiratory infection (ARI) and ILI. The WHO's mosaic framework recommends that the surveillance strategies of countries include the virological monitoring of respiratory viruses with pandemic potential such as influenza. The Oxford-Royal College of General Practitioner Research and Surveillance Centre (RSC) in collaboration with the UK Health Security Agency (UKHSA) has provided sentinel surveillance since 1967, including virology since 1993.

OBJECTIVE

We aim to describe the RSC's plans for sentinel surveillance in the 2023-2024 season and evaluate these plans against the WHO mosaic framework.

METHODS

Our approach, which includes patient and public involvement, contributes to surveillance objectives across all 3 domains of the mosaic framework. We will generate an ARI phenotype to enable reporting of this indicator in addition to ILI. These data will support UKHSA's sentinel surveillance, including vaccine effectiveness and burden of disease studies. The panel of virology tests analyzed in UKHSA's reference laboratory will remain unchanged, with additional plans for point-of-care testing, pneumococcus testing, and asymptomatic screening. Our sampling framework for serological surveillance will provide greater representativeness and more samples from younger people. We will create a biomedical resource that enables linkage between clinical data held in the RSC and virology data, including sequencing data, held by the UKHSA. We describe the governance framework for the RSC.

RESULTS

We are co-designing our communication about data sharing and sampling, contextualized by the mosaic framework, with national and general practice patient and public involvement groups. We present our ARI digital phenotype and the key data RSC network members are requested to include in computerized medical records. We will share data with the UKHSA to report vaccine effectiveness for COVID-19 and influenza, assess the disease burden of respiratory syncytial virus, and perform syndromic surveillance. Virological surveillance will include COVID-19, influenza, respiratory syncytial virus, and other common respiratory viruses. We plan to pilot point-of-care testing for group A streptococcus, urine tests for pneumococcus, and asymptomatic testing. We will integrate test requests and results with the laboratory-computerized medical record system. A biomedical resource will enable research linking clinical data to virology data. The legal basis for the RSC's pseudonymized data extract is The Health Service (Control of Patient Information) Regulations 2002, and all nonsurveillance uses require research ethics approval.

CONCLUSIONS

The RSC extended its surveillance activities to meet more but not all of the mosaic framework's objectives. We have introduced an ARI indicator. We seek to expand our surveillance scope and could do more around transmissibility and the benefits and risks of nonvaccine therapies.

Hybrid-Capture Target Enrichment in Human Pathogens: Identification, Evolution, Biosurveillance, and Genomic Epidemiology

High-throughput sequencing (HTS) has revolutionised the field of pathogen genomics, enabling the direct recovery of pathogen genomes from clinical and environmental samples. However, pathogen nucleic acids are often overwhelmed by those of the host, requiring deep metagenomic sequencing to recover sufficient sequences for downstream analyses (e.g., identification and genome characterisation). To circumvent this, hybrid-capture target enrichment (HC) is able to enrich pathogen nucleic acids across multiple scales of divergences and taxa, depending on the panel used. In this review, we outline the applications of HC in human pathogens-bacteria, fungi, parasites and viruses-including identification, genomic epidemiology, antimicrobial resistance genotyping, and evolution. Importantly, we explored the applicability of HC to clinical metagenomics, which ultimately requires more work before it is a reliable and accurate tool for clinical diagnosis. Relatedly, the utility of HC was exemplified by COVID-19, which was used as a case study to illustrate the maturity of HC for recovering pathogen sequences. As we unravel the origins of COVID-19, zoonoses remain more relevant than ever. Therefore, the role of HC in biosurveillance studies is also highlighted in this review, which is critical in preparing us for the next pandemic. We also found that while HC is a popular tool to study viruses, it remains underutilised in parasites and fungi and, to a lesser extent, bacteria. Finally, weevaluated the future of HC with respect to bait design in the eukaryotic groups and the prospect of combining HC with long-read HTS.

Genomic and transcriptomic analysis of the recent Mpox outbreak

The Mpox (formerly named Monkeypox) virus is the etiological cause of a recent multi-country outbreak, with thousands of distinct cases detected outside the endemic areas of Africa as of December 2023. In this article, we analyze the sequences of full genomes of Mpox virus from Europe and compare them with all available Mpox sequences of historical relevance, annotated by year and geographic origin, as well as related Cowpox and Variola (smallpox) virus sequences. Our results show that the recent outbreak is most likely originating from the West African clade of Mpox, with >99 % sequence identity with sequences derived from historical and recent cases, dating from 1971 to 2017. We analyze specific mutations occurring in viral proteins between the current outbreak, previous Mpox and Cowpox sequences, and the historical Variola virus. Genome-wide sequence analysis of the recent outbreak and other Mpox/Cowpox/Variola viruses shows a very high conservation, with 97.9 % (protein-based) and 97.8 % (nucleotide-based) sequence identity. We identified significant correlation in human transcriptional responses as well, with a conserved immune pathway response induced in human cell cultures by the three families of Pox virus. The similarities identified between the major strains of Pox viruses, as well as within the Mpox clades, both at the genomic and transcriptomic levels, provide a molecular basis for the observed efficacy of Variola vaccines in other Poxviruses.

Genomic Surveillance of SARS-CoV-2: Data Analysis and Assessment of Tunisian Strategy from January 2021 to February 2022

Due to the emergence of the SARS-CoV-2 B.1.1.7 (Alpha) variant in the UK in 2020 and its risk of increased transmission, the Ministry of Health in Tunisia implemented a sequencing surveillance strategy for SARS-CoV-2. The aim of this study was to analyze SARS-CoV-2 genomic surveillance data in Tunisia (January 2021-February 2022) and to assess the implementation of the sequencing strategy for SARS-CoV-2 in accordance with national recommendations and the guidance for SARS-CoV-2 genomic surveillance for public health goals. A descriptive study of all sequenced RT-PCR samples sequenced (January 2021-February2022). An internal audit was also done to assess the compliance against standards covering national recommendations and the Guidance for SARS-CoV-2 genomic surveillance for public health goals. A total of 12 simple or composite requirements related to the following areas were included in the audit standards: sampling (one requirements); data collection/analysis (six requirements); partnership (one requirement); and ethical considerations (one requirement). A total of 4819 samples were sent to laboratories and 4278 samples were sequenced. A total of 3648 samples were classified. Positive variants of concern (VOC) samples were 80.92%, differentiated as follows: Alpha, 40.24%; Beta, 0.24%; Gamma, 0.03%; Delta, 45.26%; and Omicron, 14.19%. Three principal phases of VOCs per ISO-week were shown: Alpha 3/2021-25/2021; Delta 26/2021-2/2022; and Omicron 3/2022-6/2022. Levels of compliance were identified; from a total of 12 requirements, 7 were considered as "not met", 4 as "partially met", and 1 as "fully met" but including not totally achieved objectives. In conclusion, the internal audit of the national SARS-CoV-2 sequencing strategy revealed an overall "not met" level of compliance. The results offered a trigger to collaborate with all stakeholders to develop a surveillance strategy for early detection and response to outbreaks caused by VOCs.

Mobilisation and analyses of publicly available SARS-CoV-2 data for pandemic responses

The COVID-19 pandemic has seen large-scale pathogen genomic sequencing efforts, becoming part of the toolbox for surveillance and epidemic research. This resulted in an unprecedented level of data sharing to open repositories, which has actively supported the identification of SARS-CoV-2 structure, molecular interactions, mutations and variants, and facilitated vaccine development and drug reuse studies and design. The European COVID-19 Data Platform was launched to support this data sharing, and has resulted in the deposition of several million SARS-CoV-2 raw reads. In this paper we describe (1) open data sharing, (2) tools for submission, analysis, visualisation and data claiming (e.g. ORCiD), (3) the systematic analysis of these datasets, at scale via the SARS-CoV-2 Data Hubs as well as (4) lessons learnt. This paper describes a component of the Platform, the SARS-CoV-2 Data Hubs, which enable the extension and set up of infrastructure that we intend to use more widely in the future for pathogen surveillance and pandemic preparedness.

Investigating the rise of Omicron variant through genomic surveillance of SARS-CoV-2 infections in a highly vaccinated university population

Novel variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continue to emerge as the coronavirus disease 2019 (COVID-19) pandemic extends into its fourth year. Understanding SARS-CoV-2 circulation in university populations is vital for effective interventions in higher education settings and will inform public health policy during pandemics. In this study, we generated 793 whole-genome sequences collected over an entire academic year in a university population in Indiana, USA. We clearly captured the rapidity with which Delta variant was wholly replaced by Omicron variant across the West Lafayette campus over the length of two academic semesters in a community with high vaccination rates. This mirrored the emergence of Omicron throughout the state of Indiana and the USA. Further, phylogenetic analyses demonstrated that there was a more diverse set of potential geographic origins for Omicron viruses introduction into campus when compared to Delta. Lastly, statistics indicated that there was a more significant role for international and out-of-state migration in the establishment of Omicron variants at Purdue. This surveillance workflow, coupled with viral genomic sequencing and phylogeographic analyses, provided critical insights into SARS-CoV-2 transmission dynamics and variant arrival.

A decade of clinical microbiology: top 10 advances in 10 years: what every infection preventionist and antimicrobial steward should know

The past 10 years have brought paradigm-shifting changes to clinical microbiology. This paper explores the top 10 transformative innovations across the diagnostic spectrum, including not only state of the art technologies but also preanalytic and post-analytic advances. Clinical decision support tools have reshaped testing practices, curbing unnecessary tests. Innovations like broad-range polymerase chain reaction and metagenomic sequencing, whole genome sequencing, multiplex molecular panels, rapid phenotypic susceptibility testing, and matrix-assisted laser desorption ionization time-of-flight mass spectrometry have all expanded our diagnostic armamentarium. Rapid home-based testing has made diagnostic testing more accessible than ever. Enhancements to clinician-laboratory interfaces allow for automated stewardship interventions and education. Laboratory restructuring and consolidation efforts are reshaping the field of microbiology, presenting both opportunities and challenges for the future of clinical microbiology laboratories. Here, we review key innovations of the last decade.

Systematic Genomic Surveillance of SARS-CoV-2 at Xiamen International Airport and the Port of Xiamen Reveals the Importance of Incoming Travelers in Lineage Diversity

Sever Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is still a threat to human health globally despite the World Health Organization (WHO) announcing the end of the COVID-19 pandemic. Continued surveillance of SARS-CoV-2 at national borders would be helpful in understanding the epidemics of novel imported variants and updating local strategies for disease prevention and treatment. This study focuses on the surveillance of imported SARS-CoV-2 variants among travelers entering Xiamen International Airport and the Port of Xiamen from February to August 2023. A total of 97 imported SARS-CoV-2 sequences among travelers from 223 cases collected from 12 different countries and regions were identified by real-time RT-PCR. Next-generation sequencing was used to generate high-quality complete sequences for phylogenetic and population dynamic analysis. The study revealed a dominant shift in variant distribution, in which the XBB subvariant (XBB.1.5, XBB.1.16, XBB.1.9, XBB.2.3, and EG.5.1) accounted for approximately 88.8% of the sequenced samples. In detail, clades 23D and 23E accounted for 26.2% and 21.4% of the sequenced samples, respectively, while clades 23B (13.6%) and 23F (10.7%) took the third and fourth spots in the order of imported sequences, respectively. Additionally, the XBB.2.3 variants were first identified in imported cases from the mainland of Xiamen, China on 27 February 2023. The spatiotemporal analyses of recent viral genome sequences from a limited number of travelers into Xiamen provide valuable insights into the situation surrounding SARS-CoV-2 and highlight the importance of sentinel surveillance of SARS-CoV-2 variants in the national border screening of incoming travelers, which serves as an early warning system for the presence of highly transmissible circulating SARS-CoV-2 lineages.

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.

Circulation, viral diversity and genomic rearrangement in mpox virus in the Netherlands during the 2022 outbreak and beyond

Mpox is an emerging zoonotic disease which has now spread to over 113 countries as of August 2023, with over 89,500 confirmed human cases. The Netherlands had one of the highest incidence rates in Europe during the peak of the outbreak. In this study, we generated 158 near-complete mpox virus (MPXV) genomes (12.4% of nationwide cases) that were collected throughout the Netherlands from the start of the outbreak in May 2022 to August 2023 to track viral evolution and investigate outbreak dynamics. We detected 14 different viral lineages, suggesting multiple introductions followed by rapid initial spread within the country. The estimated evolutionary rate was relatively high compared to previously described in orthopoxvirus literature, with an estimated 11.58 mutations per year. Genomic rearrangement events occurred at a rate of 0.63% and featured a large deletion event. In addition, based on phylogenetics, we identified multiple potential transmission clusters which could be supported by direct source- and contact tracing data. This led to the identification of at least two main transmission locations at the beginning of the outbreak. We conclude that whole genome sequencing of MPXV is essential to enhance our understanding of outbreak dynamics and evolution of a relatively understudied and emerging zoonotic pathogen.

Motifs in SARS-CoV-2 evolution

We present a novel framework enhancing the prediction of whether novel lineage poses the threat of eventually dominating the viral population. The framework is based purely on genomic sequence data, without requiring prior established biological analysis. Its building blocks are sets of coevolving sites in the alignment (motifs), identified via coevolutionary signals. The collection of such motifs forms a relational structure over the polymorphic sites. Motifs are constructed using distances quantifying the coevolutionary coupling of pairs and manifest as coevolving clusters of sites. We present an approach to genomic surveillance based on this notion of relational structure. Our system will issue an alert regarding a lineage, based on its contribution to drastic changes in the relational structure. We then conduct a comprehensive retrospective analysis of the COVID-19 pandemic based on SARS-CoV-2 genomic sequence data in GISAID from October 2020 to September 2022, across 21 lineages and 27 countries with weekly resolution. We investigate the performance of this surveillance system in terms of its accuracy, timeliness, and robustness. Lastly, we study how well each lineage is classified by such a system.

Genomic surveillance of SARS-CoV-2 reveals highest severity and mortality of delta over other variants: evidence from Cameroon

While the SARS-CoV-2 dynamic has been described globally, there is a lack of data from Sub-Saharan Africa. We herein report the dynamics of SARS-CoV-2 lineages from March 2020 to March 2022 in Cameroon. Of the 760 whole-genome sequences successfully generated by the national genomic surveillance network, 74% were viral sub-lineages of origin and non-variants of concern, 15% Delta, 6% Omicron, 3% Alpha and 2% Beta variants. The pandemic was driven by SARS-CoV-2 lineages of origin in wave 1 (16 weeks, 2.3% CFR), the Alpha and Beta variants in wave 2 (21 weeks, 1.6% CFR), Delta variants in wave 3 (11 weeks, 2.0% CFR), and omicron variants in wave 4 (8 weeks, 0.73% CFR), with a declining trend over time (p = 0.01208). Even though SARS-CoV-2 heterogeneity did not seemingly contribute to the breadth of transmission, the viral lineages of origin and especially the Delta variants appeared as drivers of COVID-19 severity in Cameroon.

Introduction, Dispersal, and Predominance of SARS-CoV-2 Delta Variant in Rio Grande do Sul, Brazil: A Retrospective Analysis

Mutations in the SARS-CoV-2 genome can alter the virus' fitness, leading to the emergence of variants of concern (VOC). In Brazil, the Gamma variant dominated the pandemic in the first half of 2021, and from June onwards, the first cases of Delta infection were documented. Here, we investigate the introduction and dispersal of the Delta variant in the RS state by sequencing 1077 SARS-CoV-2-positive samples from June to October 2021. Of these samples, 34.7% were identified as Gamma and 65.3% as Delta. Notably, 99.2% of Delta sequences were clustered within the 21J lineage, forming a significant Brazilian clade. The estimated clock rate was 5.97 × 10-4 substitutions per site per year. The Delta variant was first reported on 17 June in the Vinhedos Basalto microregion and rapidly spread, accounting for over 70% of cases within nine weeks. Despite this, the number of cases and deaths remained stable, possibly due to vaccination, prior infections, and the continued mandatory mask use. In conclusion, our study provides insights into the Delta variant circulating in the RS state, highlighting the importance of genomic surveillance for monitoring viral evolution, even when the impact of new variants may be less severe in a given region.