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      Characterization of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infection Clusters Based on Integrated Genomic Surveillance, Outbreak Analysis and Contact Tracing in an Urban Setting

      research-article
      1 , 2 , 2 , 3 , 4 , 2 , 1 , 2 , 1 , 2 , 2 , 2 , 2 , 2 , 3 , 1 , 1 , 1 , 5 , 5 , 2 , 4 , 3 , 2 , 1 , 2 , 6 , 7 , German COVID-19 OMICS Initiative (DeCOI)
      Clinical Infectious Diseases: An Official Publication of the Infectious Diseases Society of America
      Oxford University Press
      genomic epidemiology, infection chain, community transmission, rapid sequencing, Nanopore sequencing

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          Abstract

          Background

          Tracing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission chains is still a major challenge for public health authorities, when incidental contacts are not recalled or are not perceived as potential risk contacts. Viral sequencing can address key questions about SARS-CoV-2 evolution and may support reconstruction of viral transmission networks by integration of molecular epidemiology into classical contact tracing.

          Methods

          In collaboration with local public health authorities, we set up an integrated system of genomic surveillance in an urban setting, combining a) viral surveillance sequencing, b) genetically based identification of infection clusters in the population, c) integration of public health authority contact tracing data, and d) a user-friendly dashboard application as a central data analysis platform.

          Results

          Application of the integrated system from August to December 2020 enabled a characterization of viral population structure, analysis of 4 outbreaks at a maximum care hospital, and genetically based identification of 5 putative population infection clusters, all of which were confirmed by contact tracing. The system contributed to the development of improved hospital infection control and prevention measures and enabled the identification of previously unrecognized transmission chains, involving a martial arts gym and establishing a link between the hospital to the local population.

          Conclusions

          Integrated systems of genomic surveillance could contribute to the monitoring and, potentially, improved management of SARS-CoV-2 transmission in the population.

          Abstract

          Tracing of SARS-CoV-2 population transmission chains is still a major challenge. We present an integrated system of genomic surveillance and show it to be capable of detecting infection chains in a large city during ongoing community transmission.

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          Most cited references29

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          A pneumonia outbreak associated with a new coronavirus of probable bat origin

          Since the outbreak of severe acute respiratory syndrome (SARS) 18 years ago, a large number of SARS-related coronaviruses (SARSr-CoVs) have been discovered in their natural reservoir host, bats 1–4 . Previous studies have shown that some bat SARSr-CoVs have the potential to infect humans 5–7 . Here we report the identification and characterization of a new coronavirus (2019-nCoV), which caused an epidemic of acute respiratory syndrome in humans in Wuhan, China. The epidemic, which started on 12 December 2019, had caused 2,794 laboratory-confirmed infections including 80 deaths by 26 January 2020. Full-length genome sequences were obtained from five patients at an early stage of the outbreak. The sequences are almost identical and share 79.6% sequence identity to SARS-CoV. Furthermore, we show that 2019-nCoV is 96% identical at the whole-genome level to a bat coronavirus. Pairwise protein sequence analysis of seven conserved non-structural proteins domains show that this virus belongs to the species of SARSr-CoV. In addition, 2019-nCoV virus isolated from the bronchoalveolar lavage fluid of a critically ill patient could be neutralized by sera from several patients. Notably, we confirmed that 2019-nCoV uses the same cell entry receptor—angiotensin converting enzyme II (ACE2)—as SARS-CoV.
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            A new coronavirus associated with human respiratory disease in China

            Emerging infectious diseases, such as severe acute respiratory syndrome (SARS) and Zika virus disease, present a major threat to public health 1–3 . Despite intense research efforts, how, when and where new diseases appear are still a source of considerable uncertainty. A severe respiratory disease was recently reported in Wuhan, Hubei province, China. As of 25 January 2020, at least 1,975 cases had been reported since the first patient was hospitalized on 12 December 2019. Epidemiological investigations have suggested that the outbreak was associated with a seafood market in Wuhan. Here we study a single patient who was a worker at the market and who was admitted to the Central Hospital of Wuhan on 26 December 2019 while experiencing a severe respiratory syndrome that included fever, dizziness and a cough. Metagenomic RNA sequencing 4 of a sample of bronchoalveolar lavage fluid from the patient identified a new RNA virus strain from the family Coronaviridae, which is designated here ‘WH-Human 1’ coronavirus (and has also been referred to as ‘2019-nCoV’). Phylogenetic analysis of the complete viral genome (29,903 nucleotides) revealed that the virus was most closely related (89.1% nucleotide similarity) to a group of SARS-like coronaviruses (genus Betacoronavirus, subgenus Sarbecovirus) that had previously been found in bats in China 5 . This outbreak highlights the ongoing ability of viral spill-over from animals to cause severe disease in humans.
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              Nextstrain: real-time tracking of pathogen evolution

              Abstract Summary Understanding the spread and evolution of pathogens is important for effective public health measures and surveillance. Nextstrain consists of a database of viral genomes, a bioinformatics pipeline for phylodynamics analysis, and an interactive visualization platform. Together these present a real-time view into the evolution and spread of a range of viral pathogens of high public health importance. The visualization integrates sequence data with other data types such as geographic information, serology, or host species. Nextstrain compiles our current understanding into a single accessible location, open to health professionals, epidemiologists, virologists and the public alike. Availability and implementation All code (predominantly JavaScript and Python) is freely available from github.com/nextstrain and the web-application is available at nextstrain.org.
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                Author and article information

                Journal
                Clin Infect Dis
                Clin Infect Dis
                cid
                Clinical Infectious Diseases: An Official Publication of the Infectious Diseases Society of America
                Oxford University Press (US )
                1058-4838
                1537-6591
                28 June 2021
                28 June 2021
                : ciab588
                Affiliations
                [1 ]Institute of Virology, University Hospital Düsseldorf, Heinrich Heine University Düsseldorf , Düsseldorf, Germany
                [2 ]Institute of Medical Microbiology and Hospital Hygiene, Heinrich Heine University Düsseldorf , Düsseldorf, Germany
                [3 ]Zotz | Klimas , Düsseldorf, Germany
                [4 ]Düsseldorf Health Department (Gesundheitsamt Düsseldorf) , Düsseldorf, Germany
                [5 ]SeqIT GmbH , Pfaffplatz 10, 67655 Kaiserslautern, Germany
                [6 ]Institute of Medical Statistics and Computational Biology, University of Cologne , Cologne, Germany
                [7 ]Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne , Cologne, Germany
                Author notes
                Correspondence: A. Dilthey, Institute of Medical Microbiology and Hospital Hygiene, Heinrich Heine University Düsseldorf, Universitätsstr. 2, 40225 Düsseldorf, Germany ( dilthey@ 123456hhu.de ).

                A. W., T. H., P. F., and L. E. contributed equally to this work.

                Article
                ciab588
                10.1093/cid/ciab588
                8406867
                34181711
                282b01c9-705d-4415-a656-d8cc6b732fa0
                © The Author(s) 2021. Published by Oxford University Press for the Infectious Diseases Society of America.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence ( http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                : 19 April 2021
                : 22 June 2021
                : 06 August 2021
                Page count
                Pages: 8
                Funding
                Funded by: Jürgen Manchot Foundation German Research Foundation;
                Award ID: 428994620
                Funded by: German Federal Ministry of Education and Research;
                Award ID: 031L0184B
                Categories
                Major Article
                AcademicSubjects/MED00290
                Custom metadata
                PAP
                corrected-proof

                Infectious disease & Microbiology
                genomic epidemiology,infection chain,community transmission,rapid sequencing,nanopore sequencing

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