Publications by authors named "Duncan Maccannell"

Article Synopsis
  • The CDC is monitoring the evolution of SARS-CoV-2, particularly the Omicron variant and its offspring, using national genomic surveillance data from May 2023 to September 2024.
  • During this period, descendants of the Omicron variants, especially XBB and JN.1, emerged and became prevalent, with several lineages showing immune escape traits.
  • The rise of the JN.1 variant led to a significant increase in COVID-19 cases during winter 2024, underscoring the need for ongoing genomic monitoring to inform vaccine development and public health strategies.*
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The COVID-19 pandemic has highlighted the need to upgrade systems for infectious disease surveillance and forecasting and modeling of the spread of infection, both of which inform evidence-based public health guidance and policies. Here, we discuss requirements for an effective surveillance system to support decision making during a pandemic, drawing on the lessons of COVID-19 in the U.S.

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As public health laboratories expand their genomic sequencing and bioinformatics capacity for the surveillance of different pathogens, labs must carry out robust validation, training, and optimization of wet- and dry-lab procedures. Achieving these goals for algorithms, pipelines and instruments often requires that lower quality datasets be made available for analysis and comparison alongside those of higher quality. This range of data quality in reference sets can complicate the sharing of sub-optimal datasets that are vital for the community and for the reproducibility of assays.

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Fast, efficient public health actions require well-organized and coordinated systems that can supply timely and accurate knowledge. Public databases of pathogen genomic data, such as the International Nucleotide Sequence Database Collaboration (INSDC), have become essential tools for efficient public health decisions. However, these international resources began primarily for academic purposes, rather than for surveillance or interventions.

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Nearly a century after the beginning of the antibiotic era, which has been associated with unparalleled improvements in human health and reductions in mortality associated with infection, the dwindling pipeline for new antibiotic classes coupled with the inevitable spread of antimicrobial resistance (AMR) poses a major global challenge. Historically, surveillance of bacteria with AMR typically relied on phenotypic analysis of isolates taken from infected individuals, which provides only a low-resolution view of the epidemiology behind an individual infection or wider outbreak. Recent years have seen increasing adoption of powerful new genomic technologies with the potential to revolutionise AMR surveillance by providing a high-resolution picture of the AMR profile of the bacteria causing infections and providing real-time actionable information for treating and preventing infection.

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Article Synopsis
  • * The CDC utilizes various surveillance methods, including genomic analysis and wastewater sampling, to monitor and track the spread of these variants.
  • * BA.2.86 was first reported in Israel in August 2023 and has since been identified in multiple U.S. states and at least 32 countries, emphasizing the need for ongoing monitoring and research on its public health impact.
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Article Synopsis
  • The CDC has been tracking SARS-CoV-2 variants, particularly the Omicron variant, through national genomic surveillance since December 2020, with a report summarizing trends from January 2022 to May 2023.
  • Throughout this period, various Omicron descendant lineages, such as BA.1.1, BA.2, and BA.5, rose and fell in prevalence, often correlating with spikes in COVID-19 cases.
  • By May 2023, the variant XBB.1.5 dominated, underscoring the ongoing evolution of variants and the necessity for genomic surveillance to aid in vaccine and therapeutic strategies.
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Article Synopsis
  • * The Alpha variant, which emerged in late 2020, featured a S-gene deletion leading to a testing anomaly called S-gene target failure (SGTF).
  • * Recently, the XBB.1.5 sublineage with S-gene target presence (SGTP) has emerged, showing rapid growth in the northeastern U.S. during the dominance of the Omicron BA.5 variants exhibiting SGTF.
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Article Synopsis
  • Effective detection of SARS-CoV-2 variants through wastewater analysis can complement existing clinical testing methods, especially in resource-limited areas where traditional testing may be biased.* -
  • The study implemented improved virus concentration techniques and software to enhance the sequencing of multiple virus strains from wastewater, resulting in high-resolution data over 295 days at a university and its surrounding county.* -
  • Wastewater surveillance identified emerging variants up to 14 days earlier than clinical methods and revealed instances of virus spread that clinical testing missed, highlighting its potential for public health monitoring.*
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We enrolled arriving international air travelers in a severe acute respiratory syndrome coronavirus 2 genomic surveillance program. We used molecular testing of pooled nasal swabs and sequenced positive samples for sublineage. Traveler-based surveillance provided early-warning variant detection, reporting the first US Omicron BA.

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As SARS-CoV-2 continues to spread and evolve, detecting emerging variants early is critical for public health interventions. Inferring lineage prevalence by clinical testing is infeasible at scale, especially in areas with limited resources, participation, or testing/sequencing capacity, which can also introduce biases. SARS-CoV-2 RNA concentration in wastewater successfully tracks regional infection dynamics and provides less biased abundance estimates than clinical testing.

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Background: The Public Health Alliance for Genomic Epidemiology (PHA4GE) (https://pha4ge.org) is a global coalition that is actively working to establish consensus standards, document and share best practices, improve the availability of critical bioinformatics tools and resources, and advocate for greater openness, interoperability, accessibility, and reproducibility in public health microbial bioinformatics. In the face of the current pandemic, PHA4GE has identified a need for a fit-for-purpose, open-source SARS-CoV-2 contextual data standard.

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Article Synopsis
  • Genomic surveillance is essential for monitoring emerging SARS-CoV-2 variants, which can impact public health by affecting transmissibility and immune response.
  • Between June 2021 and January 2022, the CDC enhanced its data collection methods to provide more accurate estimates of variant proportions by utilizing public repositories and refining analysis techniques.
  • During this time, the Delta variant initially dominated infections but was quickly supplanted by the Omicron variant, which accounted for nearly all U.S. cases by January 2022, highlighting the need for ongoing surveillance in pandemic response.
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Background: Coronavirus disease 2019 (COVID-19) has had high incidence rates at institutions of higher education (IHE) in the United States, but the transmission dynamics in these settings are poorly understood. It remains unclear to what extent IHE-associated outbreaks have contributed to transmission in nearby communities.

Methods: We implemented high-density prospective genomic surveillance to investigate these dynamics at the University of Michigan and the surrounding community during the Fall 2020 semester (August 16-November 24).

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Coronavirus disease has disproportionately affected persons in congregate settings and high-density workplaces. To determine more about the transmission patterns of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in these settings, we performed whole-genome sequencing and phylogenetic analysis on 319 (14.4%) samples from 2,222 SARS-CoV-2-positive persons associated with 8 outbreaks in Minnesota, USA, during March-June 2020.

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SARS-CoV-2, the virus that causes COVID-19, is constantly mutating, leading to new variants (1). Variants have the potential to affect transmission, disease severity, diagnostics, therapeutics, and natural and vaccine-induced immunity. In November 2020, CDC established national surveillance for SARS-CoV-2 variants using genomic sequencing.

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Article Synopsis
  • * Research using various data shows key entry points for this variant and highlights areas with possible underreporting of cases in the US.
  • * The study predicts that B.1.1.7 will likely become the dominant variant in multiple states by mid to late March 2021, emphasizing the urgent need for improved genomic monitoring to support public health efforts.
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On December 14, 2020, the United Kingdom reported a SARS-CoV-2 variant of concern (VOC), lineage B.1.1.

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After its emergence in Wuhan, China, in late November or early December 2019, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus rapidly spread globally. Genome sequencing of SARS-CoV-2 allows the reconstruction of its transmission history, although this is contingent on sampling. We analyzed 453 SARS-CoV-2 genomes collected between 20 February and 15 March 2020 from infected patients in Washington state in the United States.

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Article Synopsis
  • Metagenomics involves sequencing techniques to identify and analyze genetic material from all organisms in a sample, offering improved taxonomic resolution compared to traditional methods.
  • Key applications include detecting pathogens, characterizing species, identifying antimicrobial resistance, and studying the microbiome's impact on health.
  • A panel of international experts has created reporting guidelines to address technical challenges in metagenomics, emphasizing the need for careful methodology, quality assurance, and ethical considerations in research.
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Increasingly, public-health agencies are using pathogen genomic sequence data to support surveillance and epidemiological investigations. As access to whole-genome sequencing has grown, greater amounts of molecular data have helped improve the ability to detect and track outbreaks of diseases such as COVID-19, investigate transmission chains and explore large-scale population dynamics, such as the spread of antibiotic resistance. However, the wide adoption of whole-genome sequencing also poses new challenges for public-health agencies that must adapt to support a new set of expertise, which means that the capacity to perform genomic data assembly and analysis has not expanded as widely as the adoption of sequencing itself.

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