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Esser E, Schulte EC, Graf A, Karollus A, Smith NH, Michler T, Dvoretskii S, Angelov A, Sonnabend M, Peter S, Engesser C, Radonic A, Thürmer A, von Kleist M, Gebhardt F, da Costa CP, Busch DH, Muenchhoff M, Blum H, Keppler OT, Gagneur J, Protzer U. Viral genome sequencing to decipher in-hospital SARS-CoV-2 transmission events. Sci Rep 2024; 14:5768. [PMID: 38459123 PMCID: PMC10923895 DOI: 10.1038/s41598-024-56162-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Accepted: 03/02/2024] [Indexed: 03/10/2024] Open
Abstract
The SARS-CoV-2 pandemic has highlighted the need to better define in-hospital transmissions, a need that extends to all other common infectious diseases encountered in clinical settings. To evaluate how whole viral genome sequencing can contribute to deciphering nosocomial SARS-CoV-2 transmission 926 SARS-CoV-2 viral genomes from 622 staff members and patients were collected between February 2020 and January 2021 at a university hospital in Munich, Germany, and analysed along with the place of work, duration of hospital stay, and ward transfers. Bioinformatically defined transmission clusters inferred from viral genome sequencing were compared to those inferred from interview-based contact tracing. An additional dataset collected at the same time at another university hospital in the same city was used to account for multiple independent introductions. Clustering analysis of 619 viral genomes generated 19 clusters ranging from 3 to 31 individuals. Sequencing-based transmission clusters showed little overlap with those based on contact tracing data. The viral genomes were significantly more closely related to each other than comparable genomes collected simultaneously at other hospitals in the same city (n = 829), suggesting nosocomial transmission. Longitudinal sampling from individual patients suggested possible cross-infection events during the hospital stay in 19.2% of individuals (14 of 73 individuals). Clustering analysis of SARS-CoV-2 whole genome sequences can reveal cryptic transmission events missed by classical, interview-based contact tracing, helping to decipher in-hospital transmissions. These results, in line with other studies, advocate for viral genome sequencing as a pathogen transmission surveillance tool in hospitals.
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Affiliation(s)
- Elisabeth Esser
- Institute of Virology, School of Medicine & Health, Technical University of Munich/Helmholtz Munich, Munich, Germany
- School of Computation, Information and Technology, Technical University of Munich, Garching, Germany
| | - Eva C Schulte
- Institute of Virology, School of Medicine & Health, Technical University of Munich/Helmholtz Munich, Munich, Germany
- Department of Psychiatry, University Hospital, LMU Munich, Munich, Germany
- Institute of Psychiatric Phenomics and Genomics, University Hospital, LMU Munich, Munich, Germany
- Department of Psychiatry, University Hospital, Medical Faculty, University of Bonn, Bonn, Germany
- Institute of Human Genetics, University Hospital, Medical Faculty, University of Bonn, Bonn, Germany
| | - Alexander Graf
- Laboratory for Functional Genome Analysis, Gene Center, LMU Munich, Munich, Germany
| | - Alexander Karollus
- School of Computation, Information and Technology, Technical University of Munich, Garching, Germany
| | - Nicholas H Smith
- School of Computation, Information and Technology, Technical University of Munich, Garching, Germany
| | - Thomas Michler
- Institute of Virology, School of Medicine & Health, Technical University of Munich/Helmholtz Munich, Munich, Germany
- Institute of Laboratory Medicine, University Hospital, LMU Munich, Munich, Germany
| | - Stefan Dvoretskii
- School of Computation, Information and Technology, Technical University of Munich, Garching, Germany
| | - Angel Angelov
- NGS Competence Center, University of Tübingen, Tübingen, Germany
| | | | - Silke Peter
- NGS Competence Center, University of Tübingen, Tübingen, Germany
| | | | - Aleksandar Radonic
- Method development, Research Infrastructure & IT (MFI), Robert-Koch Institute (RKI), Berlin, Germany
| | - Andrea Thürmer
- Method development, Research Infrastructure & IT (MFI), Robert-Koch Institute (RKI), Berlin, Germany
| | - Max von Kleist
- Department of Mathematics and Computer Science, Freie Universität (FU) Berlin, Berlin, Germany
- Project Groups, Robert-Koch Institute (RKI), Berlin, Germany
| | - Friedemann Gebhardt
- Institute for Medical Microbiology, Immunology and Hygiene, School of Medicine, Technical University of Munich, Munich, Germany
| | - Clarissa Prazeres da Costa
- Institute for Medical Microbiology, Immunology and Hygiene, School of Medicine, Technical University of Munich, Munich, Germany
- German Center for Infection Research (DZIF), Munich Partner Site, Munich, Germany
| | - Dirk H Busch
- Institute for Medical Microbiology, Immunology and Hygiene, School of Medicine, Technical University of Munich, Munich, Germany
- German Center for Infection Research (DZIF), Munich Partner Site, Munich, Germany
| | - Maximilian Muenchhoff
- German Center for Infection Research (DZIF), Munich Partner Site, Munich, Germany
- Max Von Pettenkofer Institute and Gene Center, Virology, National Reference Center for Retroviruses, Faculty of Medicine, LMU Munich, Munich, Germany
| | - Helmut Blum
- Laboratory for Functional Genome Analysis, Gene Center, LMU Munich, Munich, Germany
| | - Oliver T Keppler
- German Center for Infection Research (DZIF), Munich Partner Site, Munich, Germany
- Max Von Pettenkofer Institute and Gene Center, Virology, National Reference Center for Retroviruses, Faculty of Medicine, LMU Munich, Munich, Germany
| | - Julien Gagneur
- School of Computation, Information and Technology, Technical University of Munich, Garching, Germany.
- Institute of Human Genetics, School of Medicine & Health, Technical University of Munich, Munich, Germany.
- Computational Health Center, Helmholtz Center Munich, Neuherberg, Germany.
| | - Ulrike Protzer
- Institute of Virology, School of Medicine & Health, Technical University of Munich/Helmholtz Munich, Munich, Germany.
- German Center for Infection Research (DZIF), Munich Partner Site, Munich, Germany.
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Kawamura H, Arimura S, Saida R, Murata N, Shigemi A, Kodama Y, Nakamura M, Obama Y, Fukuyama R, Hamada Y, Shinkawa N, Sunagawa T, Kamiya H, Nishi J. Enhanced measures, including PCR-based screening and syndromic surveillance for nosocomial outbreaks of the COVID-19 Omicron variant, using descriptive epidemiology and whole-genome sequencing in a Japanese tertiary care hospital. J Infect Chemother 2024; 30:104-110. [PMID: 37717606 DOI: 10.1016/j.jiac.2023.09.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 08/21/2023] [Accepted: 09/13/2023] [Indexed: 09/19/2023]
Abstract
INTRODUCTION In this study, we aimed to analyze the effectiveness of enhanced preventive measures against nosocomial COVID-19 Omicron outbreaks based on those encountered. METHODS We introduced PCR-based screening and syndromic surveillance, in addition to standard and transmission-based precautions, during a COVID-19 outbreak in three wards of Kagoshima University Hospital, a Japanese tertiary care hospital, in February 2022, amid the Omicron variant endemic. Furthermore, we analyzed the descriptive epidemiology and whole-genome sequencing (WGS) of positive SARS-CoV-2 PCR samples from this outbreak. RESULTS PCR-based screening tests were conducted following the identification of three cases through syndromic surveillance. As a result, 30 individuals tested positive for SARS-CoV-2, including 13 inpatients, five attendant family members, and 12 healthcare workers across the three wards. Notably, no new infections were observed within eight days following the implementation of preventive measures. Among the SARS-CoV-2 genomes analyzed (n = 16; 53.3%), all strains were identified as belonged to BA.1.1 variant. Detailed analysis of descriptive and molecular epidemiology, incorporating single-nucleotide polymorphism analysis of WGS and clarification of transmission links, considering two potential entry routes to the hospital. CONCLUSIONS Introduction of additional preventive measures, including PCR-based screening and syndromic surveillance, in addition to WGS and descriptive epidemiology, is useful for the early intervention of nosocomial outbreaks and for revealing the transmission route of the COVID-19 Omicron variant.
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Affiliation(s)
- Hideki Kawamura
- Department of Infection Control and Prevention, Kagoshima University Hospital, 8-35-1 Sakuragaoka, Kagoshima, 890-8520, Japan.
| | - Shoko Arimura
- Department of Infection Control and Prevention, Kagoshima University Hospital, 8-35-1 Sakuragaoka, Kagoshima, 890-8520, Japan
| | - Ryuichi Saida
- Department of Infection Control and Prevention, Kagoshima University Hospital, 8-35-1 Sakuragaoka, Kagoshima, 890-8520, Japan
| | - Nao Murata
- Department of Infection Control and Prevention, Kagoshima University Hospital, 8-35-1 Sakuragaoka, Kagoshima, 890-8520, Japan
| | - Akari Shigemi
- Department of Infection Control and Prevention, Kagoshima University Hospital, 8-35-1 Sakuragaoka, Kagoshima, 890-8520, Japan
| | - Yuichi Kodama
- Department of Infection Control and Prevention, Kagoshima University Hospital, 8-35-1 Sakuragaoka, Kagoshima, 890-8520, Japan
| | - Masatoshi Nakamura
- Clinical Laboratory, Kagoshima University Hospital, 8-35-1 Sakuragaoka, Kagoshima, 890-8520, Japan
| | - Yuki Obama
- Clinical Laboratory, Kagoshima University Hospital, 8-35-1 Sakuragaoka, Kagoshima, 890-8520, Japan
| | - Ryuko Fukuyama
- Clinical Laboratory, Kagoshima University Hospital, 8-35-1 Sakuragaoka, Kagoshima, 890-8520, Japan
| | - Yuka Hamada
- Kagoshima Prefectural Institute for Environmental Research and Public Health, 11-40 Kinko-cho, Kagoshima, 892-0835, Japan
| | - Naomi Shinkawa
- Kagoshima Prefectural Institute for Environmental Research and Public Health, 11-40 Kinko-cho, Kagoshima, 892-0835, Japan
| | - Tomimasa Sunagawa
- Center for Field Epidemiology Intelligence, Research, and Professional Development, National Institute of Infectious Diseases, Toyama 1-23-1, Shinjuku-ku, Tokyo, 162-8640, Japan
| | - Hajime Kamiya
- Center for Surveillance, Immunization and Epidemiologic Research, National Institute of Infectious Diseases, Toyama 1-23-1, Shinjuku-ku, Tokyo, 162-8640, Japan
| | - Junichiro Nishi
- Department of Infection Control and Prevention, Kagoshima University Hospital, 8-35-1 Sakuragaoka, Kagoshima, 890-8520, Japan
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Barton A, Colijn C. Genomic, clinical and immunity data join forces for public health. Nat Rev Microbiol 2023; 21:639. [PMID: 37592055 DOI: 10.1038/s41579-023-00965-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/19/2023]
Affiliation(s)
- Amber Barton
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK.
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Hare D, Dembicka KM, Brennan C, Campbell C, Sutton-Fitzpatrick U, Stapleton PJ, De Gascun CF, Dunne CP. Whole-genome sequencing to investigate transmission of SARS-CoV-2 in the acute healthcare setting: a systematic review. J Hosp Infect 2023; 140:139-155. [PMID: 37562592 DOI: 10.1016/j.jhin.2023.08.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 07/03/2023] [Accepted: 08/04/2023] [Indexed: 08/12/2023]
Abstract
BACKGROUND Whole-genome sequencing (WGS) has been used widely to elucidate transmission of SARS-CoV-2 in acute healthcare settings, and to guide infection, prevention, and control (IPC) responses. AIM To systematically appraise available literature, published between January 1st, 2020 and June 30th, 2022, describing the implementation of WGS in acute healthcare settings to characterize nosocomial SARS-CoV-2 transmission. METHODS Searches of the PubMed, Embase, Ovid MEDLINE, EBSCO MEDLINE, and Cochrane Library databases identified studies in English reporting the use of WGS to investigate SARS-CoV-2 transmission in acute healthcare environments. Publications involved data collected up to December 31st, 2021, and findings were reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. FINDINGS In all, 3088 non-duplicate records were retrieved; 97 met inclusion criteria, involving 62 outbreak analyses and 35 genomic surveillance studies. No publications from low-income countries were identified. In 87/97 (90%), WGS supported hypotheses for nosocomial transmission, while in 46 out of 97 (47%) suspected transmission events were excluded. An IPC intervention was attributed to the use of WGS in 18 out of 97 (18%); however, only three (3%) studies reported turnaround times ≤7 days facilitating near real-time IPC action, and none reported an impact on the incidence of nosocomial COVID-19 attributable to WGS. CONCLUSION WGS can elucidate transmission of SARS-CoV-2 in acute healthcare settings to enhance epidemiological investigations. However, evidence was not identified to support sequencing as an intervention to reduce the incidence of SARS-CoV-2 in hospital or to alter the trajectory of active outbreaks.
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Affiliation(s)
- D Hare
- UCD National Virus Reference Laboratory, University College Dublin, Ireland; School of Medicine, University of Limerick, Limerick, Ireland.
| | - K M Dembicka
- School of Medicine, University of Limerick, Limerick, Ireland
| | - C Brennan
- UCD National Virus Reference Laboratory, University College Dublin, Ireland
| | - C Campbell
- UCD National Virus Reference Laboratory, University College Dublin, Ireland
| | | | | | - C F De Gascun
- UCD National Virus Reference Laboratory, University College Dublin, Ireland
| | - C P Dunne
- School of Medicine, University of Limerick, Limerick, Ireland; Centre for Interventions in Infection, Inflammation & Immunity (4i), University of Limerick, Limerick, Ireland
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Haanappel CP, Oude Munnink BB, Sikkema RS, Voor In 't Holt AF, de Jager H, de Boever R, Koene HHHT, Boter M, Chestakova IV, van der Linden A, Molenkamp R, Osbak KK, Arcilla MS, Vos MC, Koopmans MPG, Severin JA. Combining epidemiological data and whole genome sequencing to understand SARS-CoV-2 transmission dynamics in a large tertiary care hospital during the first COVID-19 wave in The Netherlands focusing on healthcare workers. Antimicrob Resist Infect Control 2023; 12:46. [PMID: 37165456 PMCID: PMC10170429 DOI: 10.1186/s13756-023-01247-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Accepted: 04/29/2023] [Indexed: 05/12/2023] Open
Abstract
BACKGROUND Healthcare facilities have been challenged by the risk of SARS-CoV-2 transmission between healthcare workers (HCW) and patients. During the first wave of the COVID-19 pandemic, infections among HCW were observed, questioning infection prevention and control (IPC) measures implemented at that time. AIM This study aimed to identify nosocomial transmission routes of SARS-CoV-2 between HCW and patients in a tertiary care hospital. METHODS All SARS-CoV-2 PCR positive HCW and patients identified between 1 March and 19 May 2020, were included in the analysis. Epidemiological data were collected from patient files and HCW contact tracing interviews. Whole genome sequences of SARS-CoV-2 were generated using Nanopore sequencing (WGS). Epidemiological clusters were identified, whereafter WGS and epidemiological data were combined for re-evaluation of epidemiological clusters and identification of potential transmission clusters. HCW infections were further classified into categories based on the likelihood that the infection was acquired via nosocomial transmission. Secondary cases were defined as COVID-19 cases in our hospital, part of a transmission cluster, of which the index case was either a patient or HCW from our hospital. FINDINGS The study population consisted of 293 HCW and 245 patients. Epidemiological data revealed 36 potential epidemiological clusters, with an estimated 222 (75.7%) HCW as secondary cases. WGS results were available for 195 HCW (88.2%) and 20 patients (12.8%) who belonged to an epidemiological cluster. Re-evaluation of the epidemiological clusters, with the available WGS data identified 31 transmission clusters with 65 (29.4%) HCW as secondary cases. Transmission clusters were all part of 18 (50.0%) previously determined epidemiological clusters, demonstrating that several larger outbreaks actually consisted, of several smaller transmission clusters. A total of 21 (7.2%) HCW infections were classified as from confirmed nosocomial, of which 18 were acquired from another HCW and 3 from a patient. CONCLUSION The majority of SARS-CoV-2 infections among HCW could be attributed to community-acquired infection. Infections among HCW that could be classified as due to nosocomial transmission, were mainly caused by HCW-to-HCW transmission rather than patient-to-HCW transmission. It is important to recognize the uncertainties of cluster analyses based solely on epidemiological data.
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Affiliation(s)
- Cynthia P Haanappel
- Department of Medical Microbiology and Infectious Diseases, Erasmus MC University Medical Center Rotterdam, 3000 CA, Rotterdam, The Netherlands
| | - Bas B Oude Munnink
- Department of Viroscience, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Reina S Sikkema
- Department of Viroscience, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Anne F Voor In 't Holt
- Department of Medical Microbiology and Infectious Diseases, Erasmus MC University Medical Center Rotterdam, 3000 CA, Rotterdam, The Netherlands
| | - Herbert de Jager
- Department of Occupational Health Services, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Rieneke de Boever
- Department of Medical Microbiology and Infectious Diseases, Erasmus MC University Medical Center Rotterdam, 3000 CA, Rotterdam, The Netherlands
| | - Heidy H H T Koene
- Department of Medical Microbiology and Infectious Diseases, Erasmus MC University Medical Center Rotterdam, 3000 CA, Rotterdam, The Netherlands
| | - Marjan Boter
- Department of Viroscience, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Irina V Chestakova
- Department of Viroscience, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Anne van der Linden
- Department of Viroscience, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Richard Molenkamp
- Department of Viroscience, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Kara K Osbak
- Department of Medical Microbiology and Infectious Diseases, Erasmus MC University Medical Center Rotterdam, 3000 CA, Rotterdam, The Netherlands
| | - Maris S Arcilla
- Department of Medical Microbiology and Infectious Diseases, Erasmus MC University Medical Center Rotterdam, 3000 CA, Rotterdam, The Netherlands
| | - Margreet C Vos
- Department of Medical Microbiology and Infectious Diseases, Erasmus MC University Medical Center Rotterdam, 3000 CA, Rotterdam, The Netherlands
| | - Marion P G Koopmans
- Department of Viroscience, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Juliëtte A Severin
- Department of Medical Microbiology and Infectious Diseases, Erasmus MC University Medical Center Rotterdam, 3000 CA, Rotterdam, The Netherlands.
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Beck-Friis T, Kärmander A, Nyström K, Wang H, Gisslén M, Andersson LM, Norder H. Comparison of SARS-CoV-2 spike RNA sequences in feces and nasopharynx indicates intestinal replication. Gut Pathog 2022; 14:35. [PMID: 35987708 PMCID: PMC9392503 DOI: 10.1186/s13099-022-00509-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Accepted: 07/25/2022] [Indexed: 11/10/2022] Open
Abstract
Background Little is known of possible selection and replication of SARS-CoV-2 in the intestines and if viral load in feces is associated with severity of disease. Therefore, sequence variations of the spike region in strains collected from feces and nasopharynx (NPH) from the same patients were compared. It was also investigated whether viral load in feces related to severity of COVID-19 in hospitalized patients. Results SARS-CoV-2 RNA was found in 88 (79%) fecal samples from 112 patients. The complete spike region could be sequenced in 15 fecal and 14 NPH samples. Fourteen Alpha-variants and one Beta-variant of SARS-CoV-2 were identified. The majority of the viral genetic variants (viral populations) in two fecal samples, but none in NPH, had a reversion of the H69/V70 amino acid deletion normally seen in the Alpha variants. Nine fecal samples contained up to nine minority variants, each which may constitute a separate viral population. Five NPH samples had one genetic variant each, and one NPH sample contained nine minority populations of SARS-CoV-2 spike genes. Conclusions The higher genomic diversity of SARS-CoV-2 in feces compared to NPH, and the reversion of the H69/V70 deletion in Alpha variants from feces indicate a selection of viral strains and replication of SARS-CoV-2 in the gastrointestinal tract. Supplementary Information The online version contains supplementary material available at 10.1186/s13099-022-00509-w.
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Kim MH, Ryu UH, Heo SJ, Kim YC, Park YS. Potential Role of an Adjunctive Real Time Locating System in Preventing Secondary Transmission of SARS-CoV-2 in a Hospital Environment: A Retrospective Case-control Study (Preprint). J Med Internet Res 2022; 24:e41395. [PMID: 36197844 PMCID: PMC9580994 DOI: 10.2196/41395] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Revised: 09/09/2022] [Accepted: 09/26/2022] [Indexed: 11/13/2022] Open
Affiliation(s)
- Min Hyung Kim
- Division of Infectious Diseases, Department of Internal Medicine, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin-si, Republic of Korea
| | - Un Hyoung Ryu
- Division of Planning and Management, Office of Medical Information Technology, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin-si, Republic of Korea
| | - Seok-Jae Heo
- Division of Biostatistics, Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Yong Chan Kim
- Division of Infectious Diseases, Department of Internal Medicine, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin-si, Republic of Korea
| | - Yoon Soo Park
- Division of Infectious Diseases, Department of Internal Medicine, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin-si, Republic of Korea
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