1
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Méder ZZ, Somogyi R. Optimal capacity sharing for global genomic surveillance. Epidemics 2023; 43:100690. [PMID: 37285794 DOI: 10.1016/j.epidem.2023.100690] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Revised: 03/10/2023] [Accepted: 05/21/2023] [Indexed: 06/09/2023] Open
Abstract
Recent technological advances and substantial cost reductions have made the genomic surveillance of pathogens during pandemics feasible. Our paper focuses on full genome sequencing as a tool that can serve two goals: the estimation of variant prevalences, and the identification of new variants. Assuming that capacity constraints limit the number of samples that can be sequenced, we solve for the optimal distribution of these capacities among countries. Our results show that if the principal goal of sequencing is prevalence estimation, then the optimal capacity distribution is less than proportional to the weights (e.g., sizes) of countries. If, however, the main aim of sequencing is the detection of new variants, capacities should be allocated to countries or regions that have the most infections. Applying our results to the sequencing of SARS-CoV-2 in 2021, we provide a comparison between the observed and a suggested optimal capacity distribution worldwide and in the EU. We believe that following such quantifiable guidance will increase the efficiency of genomic surveillance for pandemics.
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Affiliation(s)
- Zsombor Z Méder
- Institute of Psychology, Leiden University, P.O. Box 9555, 2300 RB Leiden, Netherlands.
| | - Robert Somogyi
- Faculty of Economic and Social Sciences, Budapest University of Technology and Economic. Muegyetem rkp. 3., H-1111 Budapest, Hungary; Institute of Economics, Centre for Economic and Regional Studies, Toth Kalman utca 4, H-1097 Budapest, Hungary.
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2
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Ong'era EM, Mohammed KS, Makori TO, Bejon P, Ocholla-Oyier LI, Nokes DJ, Agoti CN, Githinji G. High-throughput sequencing approaches applied to SARS-CoV-2. Wellcome Open Res 2023. [DOI: 10.12688/wellcomeopenres.18701.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/03/2023] Open
Abstract
High-throughput sequencing is crucial for surveillance and control of viral outbreaks. During the ongoing coronavirus disease 2019 (COVID-19) pandemic, advances in the high-throughput sequencing technology resources have enhanced diagnosis, surveillance, and vaccine discovery. From the onset of the pandemic in December 2019, several genome-sequencing approaches have been developed and supported across the major sequencing platforms such as Illumina, Oxford Nanopore, PacBio, MGI DNBSEQTM and Ion Torrent. Here, we share insights from the sequencing approaches developed for sequencing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) between December 2019 and October 2022.
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3
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Langan LM, O’Brien M, Lovin LM, Scarlett KR, Davis H, Henke AN, Seidel SE, Archer N, Lawrence E, Norman RS, Bojes HK, Brooks BW. Quantitative Reverse Transcription PCR Surveillance of SARS-CoV-2 Variants of Concern in Wastewater of Two Counties in Texas, United States. ACS ES&T WATER 2022; 2:2211-2224. [PMID: 37552718 PMCID: PMC9291321 DOI: 10.1021/acsestwater.2c00103] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/26/2022] [Revised: 06/10/2022] [Accepted: 06/13/2022] [Indexed: 06/02/2023]
Abstract
After its emergence in late November/December 2019, the severe acute respiratory syndrome coronavirus 2 virus (SARS-CoV-2) rapidly spread globally. Recognizing that this virus is shed in feces of individuals and that viral RNA is detectable in wastewater, testing for SARS-CoV-2 in sewage collections systems has allowed for the monitoring of a community's viral burden. Over a 9 month period, the influents of two regional wastewater treatment facilities were concurrently examined for wild-type SARS-CoV-2 along with variants B.1.1.7 and B.1.617.2 incorporated as they emerged. Epidemiological data including new confirmed COVID-19 cases and associated hospitalizations and fatalities were tabulated within each location. RNA from SARS-CoV-2 was detectable in 100% of the wastewater samples, while variant detection was more variable. Quantitative reverse transcription PCR (RT-qPCR) results align with clinical trends for COVID-19 cases, and increases in COVID-19 cases were positively related with increases in SARS-CoV-2 RNA load in wastewater, although the strength of this relationship was location specific. Our observations demonstrate that clinical and wastewater surveillance of SARS-CoV-2 wild type and constantly emerging variants of concern can be combined using RT-qPCR to characterize population infection dynamics. This may provide an early warning for at-risk communities and increases in COVID-19 related hospitalizations.
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Affiliation(s)
- Laura M. Langan
- Department of Environmental Science,
Baylor University, One Bear Place #97266, Waco, Texas 76798,
United States
- Center for Reservoir and Aquatic Systems Research,
Baylor University, One Bear Place #97178, Waco, Texas 76798,
United States
| | - Megan O’Brien
- Department of Environmental Science,
Baylor University, One Bear Place #97266, Waco, Texas 76798,
United States
- Center for Reservoir and Aquatic Systems Research,
Baylor University, One Bear Place #97178, Waco, Texas 76798,
United States
- Department of Public Health, Baylor
University, One Bear Place #97343, Waco, Texas 76798, United
States
| | - Lea M. Lovin
- Department of Environmental Science,
Baylor University, One Bear Place #97266, Waco, Texas 76798,
United States
- Center for Reservoir and Aquatic Systems Research,
Baylor University, One Bear Place #97178, Waco, Texas 76798,
United States
| | - Kendall R. Scarlett
- Department of Environmental Science,
Baylor University, One Bear Place #97266, Waco, Texas 76798,
United States
- Center for Reservoir and Aquatic Systems Research,
Baylor University, One Bear Place #97178, Waco, Texas 76798,
United States
| | - Haley Davis
- Department of Environmental Science,
Baylor University, One Bear Place #97266, Waco, Texas 76798,
United States
- Center for Reservoir and Aquatic Systems Research,
Baylor University, One Bear Place #97178, Waco, Texas 76798,
United States
| | - Abigail N. Henke
- Department of Environmental Science,
Baylor University, One Bear Place #97266, Waco, Texas 76798,
United States
- Center for Reservoir and Aquatic Systems Research,
Baylor University, One Bear Place #97178, Waco, Texas 76798,
United States
- Department of Biology, Baylor
University, One Bear Place #97388, Waco, Texas 76798, United
States
| | - Sarah E. Seidel
- Center for Health
Statistics, Texas Department of State Health Services, Austin, Texas
78756, United States
| | - Natalie Archer
- Environmental Epidemiology and Disease Registries
Section, Texas Department of State Health Services, Austin,
Texas 78756, United States
| | - Eric Lawrence
- Environmental Epidemiology and Disease Registries
Section, Texas Department of State Health Services, Austin,
Texas 78756, United States
| | - R. Sean Norman
- Department of Environmental Health Sciences, Arnold School of
Public Health, University of South Carolina, 921 Assembly
Street Columbia, South Carolina 29208, United States
| | - Heidi K. Bojes
- Environmental Epidemiology and Disease Registries
Section, Texas Department of State Health Services, Austin,
Texas 78756, United States
| | - Bryan W. Brooks
- Department of Environmental Science,
Baylor University, One Bear Place #97266, Waco, Texas 76798,
United States
- Center for Reservoir and Aquatic Systems Research,
Baylor University, One Bear Place #97178, Waco, Texas 76798,
United States
- Department of Public Health, Baylor
University, One Bear Place #97343, Waco, Texas 76798, United
States
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4
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Chan ER, Jones LD, Linger M, Kovach JD, Torres-Teran MM, Wertz A, Donskey CJ, Zimmerman PA. COVID-19 infection and transmission includes complex sequence diversity. PLoS Genet 2022; 18:e1010200. [PMID: 36074769 PMCID: PMC9455841 DOI: 10.1371/journal.pgen.1010200] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Accepted: 07/27/2022] [Indexed: 12/16/2022] Open
Abstract
SARS-CoV-2 whole genome sequencing has played an important role in documenting the emergence of polymorphisms in the viral genome and its continuing evolution during the COVID-19 pandemic. Here we present data from over 360 patients to characterize the complex sequence diversity of individual infections identified during multiple variant surges (e.g., Alpha and Delta). Across our survey, we observed significantly increasing SARS-CoV-2 sequence diversity during the pandemic and frequent occurrence of multiple biallelic sequence polymorphisms in all infections. This sequence polymorphism shows that SARS-CoV-2 infections are heterogeneous mixtures. Convention for reporting microbial pathogens guides investigators to report a majority consensus sequence. In our study, we found that this approach would under-report sequence variation in all samples tested. As we find that this sequence heterogeneity is efficiently transmitted from donors to recipients, our findings illustrate that infection complexity must be monitored and reported more completely to understand SARS-CoV-2 infection and transmission dynamics. Many of the nucleotide changes that would not be reported in a majority consensus sequence have now been observed as lineage defining SNPs in Omicron BA.1 and/or BA.2 variants. This suggests that minority alleles in earlier SARS-CoV-2 infections may play an important role in the continuing evolution of new variants of concern.
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Affiliation(s)
- Ernest R. Chan
- Institute for Computational Biology, Case Western Reserve University, Cleveland, Ohio, United States of America
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Lucas D. Jones
- Department of Molecular Biology and Microbiology, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Marlin Linger
- The Center for Global Health & Diseases, Pathology Department, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Jeffrey D. Kovach
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio, United States of America
- The Center for Global Health & Diseases, Pathology Department, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Maria M. Torres-Teran
- Pathology Department, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Audric Wertz
- Biology Department, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Curtis J. Donskey
- Department of Molecular Biology and Microbiology, Case Western Reserve University, Cleveland, Ohio, United States of America
- Geriatric Research, Education, and Clinical Center, Louis Stokes Cleveland VA Medical Center, Cleveland, Ohio, United States of America
| | - Peter A. Zimmerman
- The Center for Global Health & Diseases, Pathology Department, Case Western Reserve University, Cleveland, Ohio, United States of America
- Master of Public Health Program, Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio, United States of America
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5
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Flechsler J, Eberle U, Dangel A, Hepner S, Wimmer C, Lutmayr J, Konrad R, Berger C, Weise L, Sprenger A, Zeitler J, Paravinja N, Angermeier H, Githure G, Schmidt S, Treis B, Okeyo M, Liebl B, Ackermann N, Sing A. Molecular SARS-CoV-2 surveillance in Bavaria shows no Omicron transmission before the end of November 2021. Infection 2022; 50:761-766. [PMID: 35230655 PMCID: PMC8886714 DOI: 10.1007/s15010-022-01767-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Accepted: 01/28/2022] [Indexed: 11/27/2022]
Abstract
BACKGROUND Five SARS-CoV-2 variants are currently considered as variants of concern (VOC). Omicron was declared a VOC at the end of November 2021. Based on different diagnostic methods, the occurrence of Omicron was reported by 52 countries worldwide on December 7 2021. First notified by South Africa with alarming reports on increasing infection rates, this new variant was soon suspected to replace the currently pre-dominating Delta variant leading to further infection waves worldwide. METHODS Using VOC PCR screening and Next Generation Sequencing (NGS) analysis of selected samples, we investigated the circulation of Omicron in the German federal state Bavaria. For this, we analyzed SARS-CoV-2 surveillance data from our laboratory generated from calendar week (CW) 01 to 49/2021. RESULTS So far, we have detected 69 Omicron cases in our laboratory from CW 47-49/2021 using RT-qPCR followed by melting curve analysis. The first 16 cases were analyzed by NGS and all were confirmed as Omicron. CONCLUSION Our data strongly support no circulation of the new Omicron variant before CW 47/2021.
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Affiliation(s)
- Jennifer Flechsler
- Department of Public Health Microbiology, Bavarian Health and Food Safety Authority (LGL), Veterinärstraße 2, 85764, Oberschleißheim, Germany
| | - Ute Eberle
- Unit of Virology, Bavarian Health and Food Safety Authority, Oberschleißheim, Germany
| | - Alexandra Dangel
- NGS Core Unit, Bavarian Health and Food Safety Authority, Oberschleißheim, Germany
| | - Sabrina Hepner
- NGS Core Unit, Bavarian Health and Food Safety Authority, Oberschleißheim, Germany
| | - Clara Wimmer
- Unit of Virology, Bavarian Health and Food Safety Authority, Oberschleißheim, Germany
| | - Johannes Lutmayr
- Unit of Virology, Bavarian Health and Food Safety Authority, Oberschleißheim, Germany
| | - Regina Konrad
- Department of Public Health Microbiology, Bavarian Health and Food Safety Authority (LGL), Veterinärstraße 2, 85764, Oberschleißheim, Germany
| | - Carola Berger
- NGS Core Unit, Bavarian Health and Food Safety Authority, Oberschleißheim, Germany
| | - Laura Weise
- NGS Core Unit, Bavarian Health and Food Safety Authority, Oberschleißheim, Germany
| | - Annika Sprenger
- NGS Core Unit, Bavarian Health and Food Safety Authority, Oberschleißheim, Germany
| | - Jörg Zeitler
- Unit of Virology, Bavarian Health and Food Safety Authority, Oberschleißheim, Germany
| | - Natali Paravinja
- Unit of Virology, Bavarian Health and Food Safety Authority, Oberschleißheim, Germany
| | - Hildegard Angermeier
- Unit of Virology, Bavarian Health and Food Safety Authority, Oberschleißheim, Germany
| | - George Githure
- Unit of Virology, Bavarian Health and Food Safety Authority, Oberschleißheim, Germany
| | - Sandra Schmidt
- Unit of Virology, Bavarian Health and Food Safety Authority, Oberschleißheim, Germany
| | - Bianca Treis
- Unit of Virology, Bavarian Health and Food Safety Authority, Oberschleißheim, Germany
| | - Mercy Okeyo
- Unit of Virology, Bavarian Health and Food Safety Authority, Oberschleißheim, Germany
| | - Bernhard Liebl
- State Institute of Health, Bavarian Health and Food Safety Authority, Oberschleißheim, Germany
- Ludwig Maximilians-Universität, Munich, Germany
| | - Nikolaus Ackermann
- Department of Public Health Microbiology, Bavarian Health and Food Safety Authority (LGL), Veterinärstraße 2, 85764, Oberschleißheim, Germany
- Unit of Virology, Bavarian Health and Food Safety Authority, Oberschleißheim, Germany
| | - Andreas Sing
- Department of Public Health Microbiology, Bavarian Health and Food Safety Authority (LGL), Veterinärstraße 2, 85764, Oberschleißheim, Germany.
- State Institute of Health, Bavarian Health and Food Safety Authority, Oberschleißheim, Germany.
- Ludwig Maximilians-Universität, Munich, Germany.
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6
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Identifying SARS-CoV-2 Variants of Concern through Saliva-Based RT-qPCR by Targeting Recurrent Mutation Sites. Microbiol Spectr 2022; 10:e0079722. [PMID: 35546574 PMCID: PMC9241879 DOI: 10.1128/spectrum.00797-22] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
SARS-CoV-2 variants of concern (VOCs) continue to pose a public health threat which necessitates a real-time monitoring strategy to complement whole genome sequencing. Thus, we investigated the efficacy of competitive probe RT-qPCR assays for six mutation sites identified in SARS-CoV-2 VOCs and, after validating the assays with synthetic RNA, performed these assays on positive saliva samples. When compared with whole genome sequence results, the SΔ69-70 and ORF1aΔ3675-3677 assays demonstrated 93.60 and 68.00% accuracy, respectively. The SNP assays (K417T, E484K, E484Q, L452R) demonstrated 99.20, 96.40, 99.60, and 96.80% accuracies, respectively. Lastly, we screened 345 positive saliva samples from 7 to 22 December 2021 using Omicron-specific mutation assays and were able to quickly identify rapid spread of Omicron in Upstate South Carolina. Our workflow demonstrates a novel approach for low-cost, real-time population screening of VOCs. IMPORTANCE SARS-CoV-2 variants of concern and their many sublineages can be characterized by mutations present within their genetic sequences. These mutations can provide selective advantages such as increased transmissibility and antibody evasion, which influences public health recommendations such as mask mandates, quarantine requirements, and treatment regimens. Our RT-qPCR workflow allows for strain identification of SARS-CoV-2 positive saliva samples by targeting common mutation sites shared between variants of concern and detecting single nucleotides present at the targeted location. This differential diagnostic system can quickly and effectively identify a wide array of SARS-CoV-2 strains, which can provide more informed public health surveillance strategies in the future.
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7
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Bhakta S, Sanghavi DK, Johnson PW, Kunze KL, Neville MR, Wadei HM, Bosch W, Carter RE, Shah SZ, Pollock BD, Oman SP, Speicher L, Siegel J, Libertin CR, Matson MW, Franco PM, Cowart JB. Clinical and Laboratory Profiles of SARS-CoV-2 Delta Variant Compared to Pre-Delta Variants. Int J Infect Dis 2022; 120:88-95. [PMID: 35487339 PMCID: PMC9040426 DOI: 10.1016/j.ijid.2022.04.050] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 04/20/2022] [Accepted: 04/21/2022] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND The emergence of SARS-CoV-2 variants of concern has led to significant phenotypical changes in transmissibility, virulence, and public health measures. Our study used clinical data to compare characteristics between a Delta variant wave and a pre-Delta variant wave of hospitalized patients. METHODS This single-center retrospective study defined a wave as an increasing number of COVID-19 hospitalizations, which peaked and later decreased. Data from the United States Department of Health and Human Services was used to identify the waves' primary variant. Wave 1 (08/08/20-04/01/21) was characterized by heterogeneous variants, while Wave 2 (06/26/21-10/18/21) was predominantly Delta variant. Descriptive statistics, regression techniques, and machine learning approaches supported the comparisons between waves. RESULTS From the cohort(n=1318), Wave 2 patients(n=665) were more likely to be younger, have fewer comorbidities, require more ICU care, and show an inflammatory profile with higher C-reactive protein, lactate dehydrogenase, ferritin, fibrinogen, prothrombin time, activated thromboplastin time, and INR compared to Wave 1. The gradient boosting model showed an area under the ROC curve of 0.854(sensitivity 86.4%;specificity 61.5%;positive predictive value 73.8%; negative predictive value 78.3%). CONCLUSIONS Clinical and laboratory characteristics can be used to estimate the COVID-19 variant regardless of genomic testing availability. This finding has implications for variant-driven treatment protocols and further research.
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Affiliation(s)
- Shivang Bhakta
- Department of Critical Care Medicine, Mayo Clinic, Jacksonville, Florida, USA.
| | - Devang K Sanghavi
- Department of Critical Care Medicine, Mayo Clinic, Jacksonville, Florida, USA
| | - Patrick W Johnson
- Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, Florida, USA
| | - Katie L Kunze
- Department of Quantitative Health Sciences, Mayo Clinic, Scottsdale, Arizona, USA
| | - Matthew R Neville
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Jacksonville, Florida, USA
| | - Hani M Wadei
- Department of Transplantation, Mayo Clinic, Jacksonville, Florida, USA
| | - Wendelyn Bosch
- Division of Infectious Diseases, Mayo Clinic, Jacksonville, Florida, USA
| | - Rickey E Carter
- Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, Florida, USA
| | - Sadia Z Shah
- Department of Transplantation, Mayo Clinic, Jacksonville, Florida, USA
| | - Benjamin D Pollock
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Jacksonville, Florida, USA
| | - Sven P Oman
- Division of Hospital Internal Medicine, Mayo Clinic, Jacksonville, Florida, USA
| | - Leigh Speicher
- Division of General Internal Medicine, Mayo Clinic, Jacksonville, Florida, USA
| | - Jason Siegel
- Department of Critical Care Medicine, Mayo Clinic, Jacksonville, Florida, USA; Department of Neurology, Mayo Clinic, Jacksonville, Florida, USA
| | - Claudia R Libertin
- Division of Infectious Diseases, Mayo Clinic, Jacksonville, Florida, USA
| | - Mark W Matson
- Center for Digital Health - Data & Analytics, Mayo Clinic, Rochester, Minnesota, USA
| | - Pablo Moreno Franco
- Department of Critical Care Medicine, Mayo Clinic, Jacksonville, Florida, USA; Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Jacksonville, Florida, USA; Department of Transplantation, Mayo Clinic, Jacksonville, Florida, USA
| | - Jennifer B Cowart
- Division of Hospital Internal Medicine, Mayo Clinic, Jacksonville, Florida, USA.
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8
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Chen Z, Azman AS, Chen X, Zou J, Tian Y, Sun R, Xu X, Wu Y, Lu W, Ge S, Zhao Z, Yang J, Leung DT, Domman DB, Yu H. Global landscape of SARS-CoV-2 genomic surveillance and data sharing. Nat Genet 2022; 54:499-507. [PMID: 35347305 PMCID: PMC9005350 DOI: 10.1038/s41588-022-01033-y] [Citation(s) in RCA: 115] [Impact Index Per Article: 57.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Accepted: 02/11/2022] [Indexed: 12/02/2022]
Abstract
Genomic surveillance has shaped our understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants. We performed a global landscape analysis on SARS-CoV-2 genomic surveillance and genomic data using a collection of country-specific data. Here, we characterize increasing circulation of the Alpha variant in early 2021, subsequently replaced by the Delta variant around May 2021. SARS-CoV-2 genomic surveillance and sequencing availability varied markedly across countries, with 45 countries performing a high level of routine genomic surveillance and 96 countries with a high availability of SARS-CoV-2 sequencing. We also observed a marked heterogeneity of sequencing percentage, sequencing technologies, turnaround time and completeness of released metadata across regions and income groups. A total of 37% of countries with explicit reporting on variants shared less than half of their sequences of variants of concern (VOCs) in public repositories. Our findings indicate an urgent need to increase timely and full sharing of sequences, the standardization of metadata files and support for countries with limited sequencing and bioinformatics capacity.
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Affiliation(s)
- Zhiyuan Chen
- Department of Infectious Diseases, Huashan Hospital, School of Public Health, Fudan University, Shanghai, China
- Key Laboratory of Public Health Safety, Fudan University, Ministry of Education, Shanghai, China
| | - Andrew S Azman
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Xinhua Chen
- Department of Infectious Diseases, Huashan Hospital, School of Public Health, Fudan University, Shanghai, China
- Key Laboratory of Public Health Safety, Fudan University, Ministry of Education, Shanghai, China
| | - Junyi Zou
- Department of Infectious Diseases, Huashan Hospital, School of Public Health, Fudan University, Shanghai, China
- Key Laboratory of Public Health Safety, Fudan University, Ministry of Education, Shanghai, China
| | - Yuyang Tian
- Department of Infectious Diseases, Huashan Hospital, School of Public Health, Fudan University, Shanghai, China
- Key Laboratory of Public Health Safety, Fudan University, Ministry of Education, Shanghai, China
| | - Ruijia Sun
- Department of Infectious Diseases, Huashan Hospital, School of Public Health, Fudan University, Shanghai, China
- Key Laboratory of Public Health Safety, Fudan University, Ministry of Education, Shanghai, China
| | - Xiangyanyu Xu
- Department of Infectious Diseases, Huashan Hospital, School of Public Health, Fudan University, Shanghai, China
- Key Laboratory of Public Health Safety, Fudan University, Ministry of Education, Shanghai, China
| | - Yani Wu
- School of Public Health, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Wanying Lu
- Department of Infectious Diseases, Huashan Hospital, School of Public Health, Fudan University, Shanghai, China
- Key Laboratory of Public Health Safety, Fudan University, Ministry of Education, Shanghai, China
| | - Shijia Ge
- Department of Infectious Diseases, Huashan Hospital, School of Public Health, Fudan University, Shanghai, China
| | - Zeyao Zhao
- Department of Infectious Diseases, Huashan Hospital, School of Public Health, Fudan University, Shanghai, China
- Key Laboratory of Public Health Safety, Fudan University, Ministry of Education, Shanghai, China
| | - Juan Yang
- Department of Infectious Diseases, Huashan Hospital, School of Public Health, Fudan University, Shanghai, China
- Key Laboratory of Public Health Safety, Fudan University, Ministry of Education, Shanghai, China
| | - Daniel T Leung
- Division of Infectious Diseases, University of Utah School of Medicine, Salt Lake City, UT, USA
- Division of Microbiology & Immunology, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Daryl B Domman
- Center for Global Health, Department of Internal Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM, USA
| | - Hongjie Yu
- Department of Infectious Diseases, Huashan Hospital, School of Public Health, Fudan University, Shanghai, China.
- Key Laboratory of Public Health Safety, Fudan University, Ministry of Education, Shanghai, China.
- Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, China.
- National Medical Center for Infectious Diseases, Huashan Hospital, Fudan University, Shanghai, China.
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9
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Ham RE, Smothers AR, Che R, Sell KJ, Peng CA, Dean D. Identifying SARS-CoV-2 Variants of Concern through saliva-based RT-qPCR by targeting recurrent mutation sites.. [PMID: 35262087 PMCID: PMC8902870 DOI: 10.1101/2022.03.02.22271785] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
AbstractSARS-CoV-2 variants of concern (VOCs) continue to pose a public health threat which necessitates a real-time monitoring strategy to compliment whole genome sequencing. Thus, we investigated the efficacy of competitive probe RT-qPCR assays for six mutation sites identified in SARS-CoV-2 VOCs and, after validating the assays with synthetic RNA, performed these assays on positive saliva samples. When compared with whole genome sequence results, the SΔ69-70 and ORF1aΔ3675-3677 assays demonstrated 93.60% and 68.00% accuracy, respectively. The SNP assays (K417T, E484K, E484Q, L452R) demonstrated 99.20%, 96.40%, 99.60%, and 96.80% accuracies, respectively. Lastly, we screened 345 positive saliva samples from December 7-22, 2021 using Omicron-specific mutation assays and were able to quickly identify rapid spread of Omicron in Upstate South Carolina. Our workflow demonstrates a novel approach for low-cost, real-time population screening of VOCs.ImportanceSARS-CoV-2 variants of concern and their many sublineages can be characterized by mutations present within their genetic sequences. These mutations can provide selective advantages such as increased transmissibility and antibody evasion, which influences public health recommendations such as mask mandates, quarantine requirements, and treatment regimens. Our real-time RT-qPCR workflow allows for strain identification of SARS-CoV-2 positive saliva samples by targeting common mutation sites shared between VOCs and detecting single nucleotides present at the targeted location. This differential diagnostic system can quickly and effectively identify a wide array of SARS-CoV-2 strains, which can provide more informed public health surveillance strategies in the future.
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10
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Aggarwal D, Page AJ, Schaefer U, Savva GM, Myers R, Volz E, Ellaby N, Platt S, Groves N, Gallagher E, Tumelty NM, Le Viet T, Hughes GJ, Chen C, Turner C, Logan S, Harrison A, Peacock SJ, Chand M, Harrison EM. Genomic assessment of quarantine measures to prevent SARS-CoV-2 importation and transmission. Nat Commun 2022; 13:1012. [PMID: 35197443 PMCID: PMC8866425 DOI: 10.1038/s41467-022-28371-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Accepted: 01/18/2022] [Indexed: 01/16/2023] Open
Abstract
Mitigation of SARS-CoV-2 transmission from international travel is a priority. We evaluated the effectiveness of travellers being required to quarantine for 14-days on return to England in Summer 2020. We identified 4,207 travel-related SARS-CoV-2 cases and their contacts, and identified 827 associated SARS-CoV-2 genomes. Overall, quarantine was associated with a lower rate of contacts, and the impact of quarantine was greatest in the 16-20 age-group. 186 SARS-CoV-2 genomes were sufficiently unique to identify travel-related clusters. Fewer genomically-linked cases were observed for index cases who returned from countries with quarantine requirement compared to countries with no quarantine requirement. This difference was explained by fewer importation events per identified genome for these cases, as opposed to fewer onward contacts per case. Overall, our study demonstrates that a 14-day quarantine period reduces, but does not completely eliminate, the onward transmission of imported cases, mainly by dissuading travel to countries with a quarantine requirement.
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Affiliation(s)
- Dinesh Aggarwal
- University of Cambridge, Department of Medicine, Cambridge, UK. .,Public Health England, 61 Colindale Ave, London, NW9 5EQ, UK. .,Cambridge University Hospital NHS Foundation Trust, Cambridge, UK. .,Wellcome Sanger Institute, Hinxton, Cambridge, UK.
| | - Andrew J Page
- Quadram Institute Bioscience, Norwich Research Park, Norwich, NR4 7UQ, UK
| | - Ulf Schaefer
- Public Health England, 61 Colindale Ave, London, NW9 5EQ, UK
| | - George M Savva
- Quadram Institute Bioscience, Norwich Research Park, Norwich, NR4 7UQ, UK
| | - Richard Myers
- Public Health England, 61 Colindale Ave, London, NW9 5EQ, UK
| | - Erik Volz
- Imperial College London, Department of Infectious Disease Epidemiology, London, UK
| | - Nicholas Ellaby
- Public Health England, 61 Colindale Ave, London, NW9 5EQ, UK
| | - Steven Platt
- Public Health England, 61 Colindale Ave, London, NW9 5EQ, UK
| | - Natalie Groves
- Public Health England, 61 Colindale Ave, London, NW9 5EQ, UK
| | | | - Niamh M Tumelty
- University of Cambridge, Cambridge University Libraries, Cambridge, UK
| | - Thanh Le Viet
- Quadram Institute Bioscience, Norwich Research Park, Norwich, NR4 7UQ, UK
| | - Gareth J Hughes
- Public Health England National Infections Service, Field Service, Leeds, UK
| | - Cong Chen
- Public Health England, 61 Colindale Ave, London, NW9 5EQ, UK
| | - Charlie Turner
- Public Health England, 61 Colindale Ave, London, NW9 5EQ, UK
| | - Sophie Logan
- Public Health England, National Infections Service, Field Service, Nottingham, UK
| | - Abbie Harrison
- Public Health England, 61 Colindale Ave, London, NW9 5EQ, UK
| | | | - Sharon J Peacock
- University of Cambridge, Department of Medicine, Cambridge, UK.,Public Health England, 61 Colindale Ave, London, NW9 5EQ, UK.,Cambridge University Hospital NHS Foundation Trust, Cambridge, UK.,Wellcome Sanger Institute, Hinxton, Cambridge, UK
| | - Meera Chand
- Public Health England, 61 Colindale Ave, London, NW9 5EQ, UK
| | - Ewan M Harrison
- University of Cambridge, Department of Medicine, Cambridge, UK. .,Public Health England, 61 Colindale Ave, London, NW9 5EQ, UK. .,Wellcome Sanger Institute, Hinxton, Cambridge, UK. .,University of Cambridge, Department of Public Health and Primary Care, Cambridge, UK.
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11
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Peloso GM, Tcheandjieu C, McGeary JE, Posner DC, Ho YL, Zhou JJ, Hilliard AT, Joseph J, O’Donnell CJ, Efird JT, Crawford DC, Wu WC, Arjomandi M, Sun YV, Assimes TL, Huffman JE. Genetic Loci Associated With COVID-19 Positivity and Hospitalization in White, Black, and Hispanic Veterans of the VA Million Veteran Program. Front Genet 2022; 12:777076. [PMID: 35222515 PMCID: PMC8864634 DOI: 10.3389/fgene.2021.777076] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Accepted: 12/27/2021] [Indexed: 12/13/2022] Open
Abstract
SARS-CoV-2 has caused symptomatic COVID-19 and widespread death across the globe. We sought to determine genetic variants contributing to COVID-19 susceptibility and hospitalization in a large biobank linked to a national United States health system. We identified 19,168 (3.7%) lab-confirmed COVID-19 cases among Million Veteran Program participants between March 1, 2020, and February 2, 2021, including 11,778 Whites, 4,893 Blacks, and 2,497 Hispanics. A multi-population genome-wide association study (GWAS) for COVID-19 outcomes identified four independent genetic variants (rs8176719, rs73062389, rs60870724, and rs73910904) contributing to COVID-19 positivity, including one novel locus found exclusively among Hispanics. We replicated eight of nine previously reported genetic associations at an alpha of 0.05 in at least one population-specific or the multi-population meta-analysis for one of the four MVP COVID-19 outcomes. We used rs8176719 and three additional variants to accurately infer ABO blood types. We found that A, AB, and B blood types were associated with testing positive for COVID-19 compared with O blood type with the highest risk for the A blood group. We did not observe any genome-wide significant associations for COVID-19 severity outcomes among those testing positive. Our study replicates prior GWAS findings associated with testing positive for COVID-19 among mostly White samples and extends findings at three loci to Black and Hispanic individuals. We also report a new locus among Hispanics requiring further investigation. These findings may aid in the identification of novel therapeutic agents to decrease the morbidity and mortality of COVID-19 across all major ancestral populations.
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Affiliation(s)
- Gina M. Peloso
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA, United States
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
| | - Catherine Tcheandjieu
- VA Palo Alto Healthcare System, Palo Alto, CA, United States
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, United States
- Stanford Cardiovascular Institute, Stanford University, Stanford, CA, United States
| | - John E. McGeary
- Providence VA Healthcare System, Providence, RI, United States
- Department of Psychiatry and Human Behavior, Brown University, Providence, RI, United States
| | - Daniel C. Posner
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA, United States
| | - Yuk-Lam Ho
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA, United States
| | - Jin J. Zhou
- Phoenix VA Health Care System, Phoenix, AZ, United States
- Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, United States
| | | | - Jacob Joseph
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA, United States
- Cardiology Section, VA Boston Healthcare System, Boston, MA, United States
- Department of Medicine, Brigham and Women’s Hospital, Boston, MA, United States
| | - Christopher J. O’Donnell
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA, United States
- Cardiology Section, VA Boston Healthcare System, Boston, MA, United States
- Department of Medicine, Brigham and Women’s Hospital, Boston, MA, United States
| | - Jimmy T. Efird
- Cooperative Studies Program Epidemiology Center-Durham, Durham VA Health Care System, Durham, NC, United States
| | - Dana C. Crawford
- Louis Stokes Cleveland VA Medical Center, Cleveland, OH, United States
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, United States
- Department of Genetics and Genome Sciences, Case Western Reserve University, Cleveland, OH, United States
- Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, United States
| | - Wen-Chih Wu
- Providence VA Healthcare System, Providence, RI, United States
- Department of Medicine, Alpert Medical School, Brown University, Providence, RI, United States
| | - Mehrdad Arjomandi
- Medical Service, San Francisco VA Medical Center, San Francisco, CA, United States
- Department of Medicine, University of California, San Francisco, San Francisco, CA, United States
| | | | - Yan V. Sun
- Atlanta VA Health Care System, Decatur, GA, United States
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, United States
| | - Themistocles L Assimes
- VA Palo Alto Healthcare System, Palo Alto, CA, United States
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, United States
- Stanford Cardiovascular Institute, Stanford University, Stanford, CA, United States
| | - Jennifer E. Huffman
- Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA, United States
- *Correspondence: Jennifer E. Huffman,
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12
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Graf EH. Finding the Middle Ground with the Clinical Laboratory's Role in SARS-CoV-2 Genomic Surveillance. J Clin Microbiol 2021; 59:e0181621. [PMID: 34550811 PMCID: PMC8601223 DOI: 10.1128/jcm.01816-21] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Continued replacement of the dominant severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) lineages, and associated surges, highlights the importance of genomic surveillance to identify the next possible threats. Despite concerted efforts between clinical laboratories and public health to generate sequence data, the United States has lagged in percentage of SARS-CoV-2 cases sequenced. A more simple and cost-effective option is needed to allow front-line clinical laboratories to perform high-throughput surveillance and refer important samples for slow and expensive next-generation sequencing (NGS). In this issue of the Journal of Clinical Microbiology, A. Babiker, K. Immergluck, S. D. Stampfer, A. Rao, et al. (J Clin Microbiol 59:e01446-21, 2021, https://doi.org/10.1128/JCM.01446-21) describe a rapid and flexible multiplex single-nucleotide polymorphism (SNP) assay targeting mutations associated with Alpha, Beta/Gamma, and, added later, Delta variants. They show 100% accuracy in characterized variant pools and clinical samples confirmed by NGS. Such an approach could be a happy medium in the role of front-line laboratories to assist with critically needed high-throughput genomic surveillance.
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Affiliation(s)
- Erin H. Graf
- Department of Laboratory Medicine and Pathology, Mayo Clinic Arizona, Phoenix, Arizona, USA
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13
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Yu H, Chen Z, Azman A, Chen X, Zou J, Tian Y, Sun R, Xu X, Wu Y, Lu W, Ge S, Zhao Z, Yang J, Leung D, Domman D. Global landscape of SARS-CoV-2 genomic surveillance, public availability extent of genomic data, and epidemic shaped by variants. RESEARCH SQUARE 2021:rs.3.rs-927070. [PMID: 34611660 PMCID: PMC8491853 DOI: 10.21203/rs.3.rs-927070/v1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
Genomic surveillance has shaped our understanding of SARS-CoV-2 variants, which have proliferated globally in 2021.We collected country-specific data on SARS-CoV-2 genomic surveillance, sequencing capabilities, public genomic data from multiple public repositories, and aggregated publicly available variant data. Then, different proxies were used to estimate the sequencing coverage and public availability extent of genomic data, in addition to describing the global dissemination of variants. We found that the COVID-19 global epidemic clearly featured increasing circulation of Alpha since the start of 2021, which was rapidly replaced by the Delta variant starting around May 2021. SARS-CoV-2 genomic surveillance and sequencing availability varied markedly across countries, with 63 countries performing routine genomic surveillance and 79 countries with high availability of SARS-CoV-2 sequencing. We also observed a marked heterogeneity of sequenced coverage across regions and countries. Across different variants, 21-46% of countries with explicit reporting on variants shared less than half of their variant sequences in public repositories. Our findings indicated an urgent need to expand sequencing capacity of virus isolates, enhance the sharing of sequences, the standardization of metadata files, and supportive networks for countries with no sequencing capability.
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Affiliation(s)
| | | | - Andrew Azman
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | | | | | | | | | | | | | | | | | | | | | - Daniel Leung
- University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Daryl Domman
- Center for Global Health, Department of Internal Medicine, University of New Mexico Health Sciences Center, New Mexico, USA
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14
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Jacob Machado D, White RA, Kofsky J, Janies DA. Fundamentals of genomic epidemiology, lessons learned from the coronavirus disease 2019 (COVID-19) pandemic, and new directions. ANTIMICROBIAL STEWARDSHIP & HEALTHCARE EPIDEMIOLOGY : ASHE 2021; 1:e60. [PMID: 36168505 PMCID: PMC9495640 DOI: 10.1017/ash.2021.222] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Accepted: 10/15/2021] [Indexed: 04/19/2023]
Abstract
The coronavirus disease 2019 (COVID-19) pandemic was one of the significant causes of death worldwide in 2020. The disease is caused by severe acute coronavirus syndrome (SARS) coronavirus 2 (SARS-CoV-2), an RNA virus of the subfamily Orthocoronavirinae related to 2 other clinically relevant coronaviruses, SARS-CoV and MERS-CoV. Like other coronaviruses and several other viruses, SARS-CoV-2 originated in bats. However, unlike other coronaviruses, SARS-CoV-2 resulted in a devastating pandemic. The SARS-CoV-2 pandemic rages on due to viral evolution that leads to more transmissible and immune evasive variants. Technology such as genomic sequencing has driven the shift from syndromic to molecular epidemiology and promises better understanding of variants. The COVID-19 pandemic has exposed critical impediments that must be addressed to develop the science of pandemics. Much of the progress is being applied in the developed world. However, barriers to the use of molecular epidemiology in low- and middle-income countries (LMICs) remain, including lack of logistics for equipment and reagents and lack of training in analysis. We review the molecular epidemiology literature to understand its origins from the SARS epidemic (2002-2003) through influenza events and the current COVID-19 pandemic. We advocate for improved genomic surveillance of SARS-CoV and understanding the pathogen diversity in potential zoonotic hosts. This work will require training in phylogenetic and high-performance computing to improve analyses of the origin and spread of pathogens. The overarching goals are to understand and abate zoonosis risk through interdisciplinary collaboration and lowering logistical barriers.
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Affiliation(s)
- Denis Jacob Machado
- University of North Carolina at Charlotte, College of Computing and Informatics, Department of Bioinformatics and Genomics, Charlotte, North Carolina
- Author for correspondence: Denis Jacob Machado, PhD, Department of Bioinformatics and Genomics, College of Computing and Informatics, University of North Carolina at Charlotte, 9331 Robert D. Snyder Rd, BINF 224, Charlotte, NC28223. E-mail:
| | - Richard Allen White
- University of North Carolina at Charlotte, College of Computing and Informatics, Department of Bioinformatics and Genomics, Charlotte, North Carolina
- University of North Carolina at Charlotte, North Carolina Research Campus (NCRC), Kannapolis, North Carolina
| | - Janice Kofsky
- University of North Carolina at Charlotte, College of Computing and Informatics, Department of Bioinformatics and Genomics, Charlotte, North Carolina
| | - Daniel A. Janies
- University of North Carolina at Charlotte, College of Computing and Informatics, Department of Bioinformatics and Genomics, Charlotte, North Carolina
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