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  1. Article ; Online: Genome characterization of influenza A and B viruses in New South Wales, Australia, in 2019: A retrospective study using high-throughput whole genome sequencing.

    Wang, Xinye / Kim, Ki Wook / Walker, Gregory / Stelzer-Braid, Sacha / Scotch, Matthew / Rawlinson, William D

    Influenza and other respiratory viruses

    2024  Volume 18, Issue 1, Page(s) e13252

    Abstract: Background: During the 2019 severe influenza season, New South Wales (NSW) experienced the highest number of cases in Australia. This study retrospectively investigated the genetic characteristics of influenza viruses circulating in NSW in 2019 and ... ...

    Abstract Background: During the 2019 severe influenza season, New South Wales (NSW) experienced the highest number of cases in Australia. This study retrospectively investigated the genetic characteristics of influenza viruses circulating in NSW in 2019 and identified genetic markers related to antiviral resistance and potential virulence.
    Methods: The complete genomes of influenza A and B viruses were amplified using reverse transcription-polymerase chain reaction (PCR) and sequenced with an Illumina MiSeq platform.
    Results: When comparing the sequencing data with the vaccine strains and reference sequences, the phylogenetic analysis revealed that most NSW A/H3N2 viruses (n = 68; 94%) belonged to 3C.2a1b and a minority (n = 4; 6%) belonged to 3C.3a. These viruses all diverged from the vaccine strain A/Switzerland/8060/2017. All A/H1N1pdm09 viruses (n = 20) showed genetic dissimilarity from vaccine strain A/Michigan/45/2015, with subclades 6B.1A.5 and 6B.1A.2 identified. All B/Victoria-lineage viruses (n = 21) aligned with clade V1A.3, presenting triple amino acid deletions at positions 162-164 in the hemagglutinin protein, significantly diverging from the vaccine strain B/Colorado/06/2017. Multiple amino acid substitutions were also found in the internal proteins of influenza viruses, some of which have been previously reported in hospitalized influenza patients in Thailand. Notably, the oseltamivir-resistant marker H275Y was present in one immunocompromised patient infected with A/H1N1pdm09 and the resistance-related mutation I222V was detected in another A/H3N2-infected patient.
    Conclusions: Considering antigenic drift and the constant evolution of circulating A and B strains, we believe continuous monitoring of influenza viruses in NSW via the high-throughput sequencing approach provides timely and pivotal information for both public health surveillance and clinical treatment.
    MeSH term(s) Humans ; Influenza, Human ; Retrospective Studies ; Herpesvirus 1, Cercopithecine/genetics ; Influenza A Virus, H3N2 Subtype/genetics ; New South Wales/epidemiology ; Phylogeny ; Hemagglutinin Glycoproteins, Influenza Virus/genetics ; Influenza Vaccines ; Australia ; Seasons ; Whole Genome Sequencing
    Chemical Substances Hemagglutinin Glycoproteins, Influenza Virus ; Influenza Vaccines
    Language English
    Publishing date 2024-01-30
    Publishing country England
    Document type Journal Article
    ZDB-ID 2274538-5
    ISSN 1750-2659 ; 1750-2640
    ISSN (online) 1750-2659
    ISSN 1750-2640
    DOI 10.1111/irv.13252
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article: Patient-Related Metadata Reported in Sequencing Studies of SARS-CoV-2: Protocol for a Scoping Review and Bibliometric Analysis.

    O'Connor, Karen / Weissenbacher, Davy / Elyaderani, Amir / Lautenbach, Ebbing / Scotch, Matthew / Gonzalez-Hernandez, Graciela

    medRxiv : the preprint server for health sciences

    2024  

    Abstract: Background: There has been an unprecedented effort to sequence the SARS-CoV-2 virus and examine its molecular evolution. This has been facilitated by the availability of publicly accessible databases, the Global Initiative on Sharing All Influenza Data ( ...

    Abstract Background: There has been an unprecedented effort to sequence the SARS-CoV-2 virus and examine its molecular evolution. This has been facilitated by the availability of publicly accessible databases, the Global Initiative on Sharing All Influenza Data (GISAID) and GenBank, which collectively hold millions of SARS-CoV-2 sequence records. Genomic epidemiology, however, seeks to go beyond phylogenetic analysis by linking genetic information to patient characteristics and disease outcomes, enabling a comprehensive understanding of transmission dynamics and disease impact.While these repositories include fields reflecting patient-related metadata for a given sequence, inclusion of these demographic and clinical details is scarce. The extent to which patient-related metadata is reported in published sequencing studies and its quality remains largely unexplored.
    Methods: The NIH's LitCovid collection will be used for automated classification of articles reporting having deposited SARS-CoV-2 sequences in public repositories, while an independent search will be conducted in PubMed for validation. Data extraction will be conducted using Covidence. The extracted data will be synthesized and summarized to quantify the availability of patient metadata in the published literature of SARS-CoV-2 sequencing studies. For the bibliometric analysis, relevant data points, such as author affiliations and citation metrics will be extracted.
    Discussion: This scoping review will report on the extent and types of patient-related metadata reported in genomic viral sequencing studies of SARS-CoV-2, identify gaps in this reporting, and make recommendations for improving the quality and consistency of reporting in this area. The bibliometric analysis will uncover trends and patterns in the reporting of patient-related metadata, including differences in reporting based on study types or geographic regions. Co-occurrence networks of author keywords will also be presented. The insights gained from this study may help improve the quality and consistency of reporting patient metadata, enhancing the utility of sequence metadata and facilitating future research on infectious diseases.
    Language English
    Publishing date 2024-03-05
    Publishing country United States
    Document type Preprint
    DOI 10.1101/2023.07.14.23292681
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Going back to the roots: Evaluating Bayesian phylogeographic models with discrete trait uncertainty.

    Vaiente, Matteo A / Scotch, Matthew

    Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases

    2020  Volume 85, Page(s) 104501

    Abstract: Phylogeography is a popular way to analyze virus sequences annotated with discrete, epidemiologically-relevant, trait data. For applied public health surveillance, a key quantity of interest is often the state at the root of the inferred phylogeny. In ... ...

    Abstract Phylogeography is a popular way to analyze virus sequences annotated with discrete, epidemiologically-relevant, trait data. For applied public health surveillance, a key quantity of interest is often the state at the root of the inferred phylogeny. In epidemiological terms, this represents the geographic origin of the observed outbreak. Since determining the origin of an outbreak is often critical for public health intervention, it is prudent to understand how well phylogeographic models perform this root state classification task under various analytical scenarios. Specifically, we investigate how discrete state space and sequence data set influence the root state classification accuracy. We performed phylogeographic inference on several simulated DNA data sets while i) increasing the number of sequences and ii) increasing the total number of possible discrete trait values. We show that phylogeographic models tend to perform best at intermediate sequence data set sizes. Further, we demonstrate that a popular metric used for evaluation of phylogeographic models, the Kullback-Leibler (KL) divergence, both increases with discrete state space and data set sizes. Further, by modeling phylogeographic root state classification accuracy using logistic regression, we show that KL is not supported as a predictor of model accuracy, indicating its limited utility for assessing phylogeographic model performance on empirical data. These results suggest that relying solely on the KL metric may lead to artificially inflated support for models with finer discretization schemes and larger data set sizes. These results will be important for public health practitioners seeking to use phylogeographic models for applied infectious disease surveillance.
    MeSH term(s) Bayes Theorem ; Disease Outbreaks/statistics & numerical data ; Genetic Variation ; Guidelines as Topic ; Humans ; Models, Genetic ; Models, Theoretical ; Phenotype ; Phylogeny ; Phylogeography/methods ; Research Design/standards ; Virus Diseases/epidemiology ; Virus Diseases/genetics
    Language English
    Publishing date 2020-08-13
    Publishing country Netherlands
    Document type Journal Article ; Research Support, N.I.H., Extramural
    ZDB-ID 2037068-4
    ISSN 1567-7257 ; 1567-1348
    ISSN (online) 1567-7257
    ISSN 1567-1348
    DOI 10.1016/j.meegid.2020.104501
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Reply to comments on "Identifying mitigation strategies for COVID-19 superspreading on flights using models that account for passenger movement".

    Namilae, Sirish / Wu, Yuxuan / Mubayi, Anuj / Srinivasan, Ashok / Scotch, Matthew

    Travel medicine and infectious disease

    2022  Volume 51, Page(s) 102453

    Language English
    Publishing date 2022-09-23
    Publishing country Netherlands
    Document type Letter
    ZDB-ID 2170891-5
    ISSN 1873-0442 ; 1477-8939
    ISSN (online) 1873-0442
    ISSN 1477-8939
    DOI 10.1016/j.tmaid.2022.102453
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: Correction to: A systematic review of spatial decision support systems in public health informatics supporting the identification of high risk areas for zoonotic disease outbreaks.

    Beard, Rachel / Wentz, Elizabeth / Scotch, Matthew

    International journal of health geographics

    2021  Volume 20, Issue 1, Page(s) 39

    Language English
    Publishing date 2021-08-24
    Publishing country England
    Document type Published Erratum
    ISSN 1476-072X
    ISSN (online) 1476-072X
    DOI 10.1186/s12942-021-00293-x
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: Direct detection of canine picornavirus complete coding sequence in wastewater using long-range reverse-transcriptase polymerase chain reaction and long-read sequencing.

    Faleye, Temitope O C / Driver, Erin M / Wright, Jillian M / Halden, Rolf U / Varsani, Arvind / Scotch, Matthew

    Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases

    2024  Volume 118, Page(s) 105550

    Abstract: We describe four complete coding sequence (cCDS) of canine picornavirus from wastewater in Arizona, USA detected by coupling cCDS single-contig (∼7.5 kb) reverse-transcriptase polymerase chain reaction (RT-PCR) and low-cost long-read high-throughput ... ...

    Abstract We describe four complete coding sequence (cCDS) of canine picornavirus from wastewater in Arizona, USA detected by coupling cCDS single-contig (∼7.5 kb) reverse-transcriptase polymerase chain reaction (RT-PCR) and low-cost long-read high-throughput sequencing. For viruses of medical/veterinary importance, this workflow expands possibilities of wastewater based genomic epidemiology for exploring virus evolutionary dynamics especially in low-resource settings.
    MeSH term(s) Animals ; Dogs ; Picornaviridae Infections ; Reverse Transcriptase Polymerase Chain Reaction ; Wastewater ; Picornaviridae/genetics ; Phylogeny
    Chemical Substances Wastewater
    Language English
    Publishing date 2024-01-08
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 2037068-4
    ISSN 1567-7257 ; 1567-1348
    ISSN (online) 1567-7257
    ISSN 1567-1348
    DOI 10.1016/j.meegid.2024.105550
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: Detection of respiratory viruses directly from clinical samples using next-generation sequencing: A literature review of recent advances and potential for routine clinical use.

    Wang, Xinye / Stelzer-Braid, Sacha / Scotch, Matthew / Rawlinson, William D

    Reviews in medical virology

    2022  Volume 32, Issue 5, Page(s) e2375

    Abstract: Acute respiratory infection is the third most frequent cause of mortality worldwide, causing over 4.25 million deaths annually. Although most diagnosed acute respiratory infections are thought to be of viral origin, the aetiology often remains unclear. ... ...

    Abstract Acute respiratory infection is the third most frequent cause of mortality worldwide, causing over 4.25 million deaths annually. Although most diagnosed acute respiratory infections are thought to be of viral origin, the aetiology often remains unclear. The advent of next-generation sequencing (NGS) has revolutionised the field of virus discovery and identification, particularly in the detection of unknown respiratory viruses. We systematically reviewed the application of NGS technologies for detecting respiratory viruses from clinical samples and outline potential barriers to the routine clinical introduction of NGS. The five databases searched for studies published in English from 01 January 2010 to 01 February 2021, which led to the inclusion of 52 studies. A total of 14 different models of NGS platforms were summarised from included studies. Among these models, second-generation sequencing platforms (e.g., Illumina sequencers) were used in the majority of studies (41/52, 79%). Moreover, NGS platforms have proven successful in detecting a variety of respiratory viruses, including influenza A/B viruses (9/52, 17%), SARS-CoV-2 (21/52, 40%), parainfluenza virus (3/52, 6%), respiratory syncytial virus (1/52, 2%), human metapneumovirus (2/52, 4%), or a viral panel including other respiratory viruses (16/52, 31%). The review of NGS technologies used in previous studies indicates the advantages of NGS technologies in novel virus detection, virus typing, mutation identification, and infection cluster assessment. Although there remain some technical and ethical challenges associated with NGS use in clinical laboratories, NGS is a promising future tool to improve understanding of respiratory viruses and provide a more accurate diagnosis with simultaneous virus characterisation.
    MeSH term(s) COVID-19 ; High-Throughput Nucleotide Sequencing ; Humans ; Influenza A virus ; Influenza B virus ; Respiratory Tract Infections/diagnosis ; SARS-CoV-2
    Language English
    Publishing date 2022-07-01
    Publishing country England
    Document type Journal Article ; Review ; Systematic Review ; Research Support, Non-U.S. Gov't
    ZDB-ID 1086043-5
    ISSN 1099-1654 ; 1052-9276
    ISSN (online) 1099-1654
    ISSN 1052-9276
    DOI 10.1002/rmv.2375
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: Identifying mitigation strategies for COVID-19 superspreading on flights using models that account for passenger movement.

    Namilae, Sirish / Wu, Yuxuan / Mubayi, Anuj / Srinivasan, Ashok / Scotch, Matthew

    Travel medicine and infectious disease

    2022  Volume 47, Page(s) 102313

    Abstract: Background: Despite commercial airlines mandating masks, there have been multiple documented events of COVID-19 superspreading on flights. Conventional models do not adequately explain superspreading patterns on flights, with infection spread wider than ...

    Abstract Background: Despite commercial airlines mandating masks, there have been multiple documented events of COVID-19 superspreading on flights. Conventional models do not adequately explain superspreading patterns on flights, with infection spread wider than expected from proximity based on passenger seating. An important reason for this is that models typically do not consider the movement of passengers during the flight, boarding, or deplaning. Understanding the risks for each of these aspects could provide insight into effective mitigation measures.
    Methods: We modeled infection risk from seating and fine-grained movement patterns - boarding, deplaning, and inflight movement. We estimated infection model parameters from a prior superspreading event. We validated the model and the impact of interventions using available data from three flights, including cabin layout and seat locations of infected and uninfected passengers, to suggest interventions to mitigate COVID-19 superspreading events during air travel. Specifically, we studied: 1) London to Hanoi with 201 passengers, including 13 secondary infections among passengers; 2) Singapore to Hangzhou with 321 passengers, including 12 to 14 secondary infections; 3) a non-superspreading event on a private jet in Japan with 9 passengers and no secondary infections.
    Results: Our results show that the inclusion of passenger movement better explains the infection spread patterns than conventional models do. We also found that FFP2/N95 mask usage would have reduced infection by 95-100%, while cloth masks would have reduced it by only 40-80%. Results indicate that leaving the middle seat vacant is effective in reducing infection, and the effectiveness increases when combined with good quality masks. However, with a good mask, the risk is quite low even without the middle seats being empty.
    Conclusions: Our results suggest the need for more stringent guidelines to reduce aviation-related superspreading events of COVID-19.
    MeSH term(s) Air Travel ; Aircraft ; COVID-19/epidemiology ; COVID-19/prevention & control ; Coinfection ; Humans ; Movement
    Language English
    Publishing date 2022-03-16
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 2170891-5
    ISSN 1873-0442 ; 1477-8939
    ISSN (online) 1873-0442
    ISSN 1477-8939
    DOI 10.1016/j.tmaid.2022.102313
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article ; Online: Identifying current and emerging resources and tools utilized for detection, prediction, and visualization of viral zoonotic disease clusters: a Delphi study.

    Beard, Rachel / Scotch, Matthew

    JAMIA open

    2019  Volume 2, Issue 3, Page(s) 306–311

    Abstract: Zoonotic disease surveillance presents a substantial problem in the management of public health. Globally, zoonoses have the potential to spread and negatively impact population health economic growth, and security. This research was conducted to ... ...

    Abstract Zoonotic disease surveillance presents a substantial problem in the management of public health. Globally, zoonoses have the potential to spread and negatively impact population health economic growth, and security. This research was conducted to investigate the current data sources, analytical methods, and limitations for cluster detection and prediction with particular interest in emerging bioinformatics tools and resources to inform the development of zoonotic surveillance spatial decision support systems. We recruited 10 local health personnel to participate in a Delphi study. Participants agreed cluster detection is a priority, though mathematical modeling methods and bioinformatics resources are not commonly used toward this endeavor. However, participants indicated a desire to utilize preventative measures. We identified many limitations for identifying clusters including software availability, appropriateness, training, and usage of emerging genetic data. Future decision support system development should focus on state health personnel priorities and tasks to better utilize emerging developments and available data.
    Language English
    Publishing date 2019-05-28
    Publishing country United States
    Document type Case Reports
    ISSN 2574-2531
    ISSN (online) 2574-2531
    DOI 10.1093/jamiaopen/ooz015
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: The effects of random taxa sampling schemes in Bayesian virus phylogeography.

    Magee, Daniel / Scotch, Matthew

    Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases

    2018  Volume 64, Page(s) 225–230

    Abstract: Public health researchers are often tasked with accurately and quickly identifying the location and time when an epidemic originated from a representative sample of nucleotide sequences. In this paper, we investigate multiple approaches to subsampling ... ...

    Abstract Public health researchers are often tasked with accurately and quickly identifying the location and time when an epidemic originated from a representative sample of nucleotide sequences. In this paper, we investigate multiple approaches to subsampling the sequence set when employing a Bayesian phylogeographic generalized linear model. Our results indicate that near-categorical posterior MCC estimates on the root can be obtained with replicate runs using 25-50% of the sequence data, and that including 90% of sequences does not necessarily entail more accurate inferences. We present the first analysis of predictor signal suppression and show how the ability to detect the influence of predictor variables is limited when sample size predictors are included in the models.
    MeSH term(s) Bayes Theorem ; Databases, Genetic ; Epidemics ; Humans ; Phylogeny ; Phylogeography ; United States/epidemiology ; Virus Diseases/epidemiology ; Virus Diseases/virology ; Viruses/classification ; Viruses/genetics
    Language English
    Publishing date 2018-07-04
    Publishing country Netherlands
    Document type Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
    ZDB-ID 2037068-4
    ISSN 1567-7257 ; 1567-1348
    ISSN (online) 1567-7257
    ISSN 1567-1348
    DOI 10.1016/j.meegid.2018.07.003
    Database MEDical Literature Analysis and Retrieval System OnLINE

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