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Morton L, Creppage K, Rahman N, Early J, Hartman L, Hydrick A, Kasper M. Challenges and Opportunities in Pathogen Agnostic Sequencing for Public Health Surveillance: Lessons Learned From the Global Emerging Infections Surveillance Program. Health Secur 2024; 22:16-24. [PMID: 38054950 PMCID: PMC10902267 DOI: 10.1089/hs.2023.0068] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/07/2023] Open
Affiliation(s)
- Lindsay Morton
- Lindsay Morton, MPH, MS, is a Senior Molecular Epidemiologist; GEIS Branch, Armed Forces Health Surveillance Division, Defense Health Agency, Silver Spring, MD
| | - Kathleen Creppage
- Kathleen Creppage, DrPH, MPH, is a Scientific Program Manager and Technical Lead; GEIS Branch, Armed Forces Health Surveillance Division, Defense Health Agency, Silver Spring, MD
| | - Nazia Rahman
- Nazia Rahman, MPH, is a Molecular Epidemiologist and Portfolio Manager; GEIS Branch, Armed Forces Health Surveillance Division, Defense Health Agency, Silver Spring, MD
| | - June Early
- June Early, MPH, is Global Emerging Infections Surveillance (GEIS) Deputy Chief; GEIS Branch, Armed Forces Health Surveillance Division, Defense Health Agency, Silver Spring, MD
| | - Laurie Hartman
- Laurie Hartman, MS, is a former Laboratory Support Specialist; GEIS Branch, Armed Forces Health Surveillance Division, Defense Health Agency, Silver Spring, MD
| | - Ashley Hydrick
- Ashley Hydrick, DVM, MPH, is a Major, US Army, and former GEIS Focus Area Chief; GEIS Branch, Armed Forces Health Surveillance Division, Defense Health Agency, Silver Spring, MD
| | - Matthew Kasper
- Matthew Kasper, PhD, is a Commander, US Navy, and GEIS Chief; GEIS Branch, Armed Forces Health Surveillance Division, Defense Health Agency, Silver Spring, MD
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Marais G, Valley-Omar Z, Marais S, McMullen K, Bateman K, der Westhuizen DV, Maseko M, Hardie D, Brink A. Clinical metagenomics in a resource-limited setting. J Infect 2023; 87:604-606. [PMID: 37852478 DOI: 10.1016/j.jinf.2023.10.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2023] [Revised: 10/11/2023] [Accepted: 10/13/2023] [Indexed: 10/20/2023]
Affiliation(s)
- Gert Marais
- Division of Medical Microbiology, University of Cape Town, Cape Town, Western Cape, South Africa; Groote Schuur Hospital National Health Laboratory Service Laboratory, Cape Town, Western Cape, South Africa.
| | - Ziyaad Valley-Omar
- Groote Schuur Hospital National Health Laboratory Service Laboratory, Cape Town, Western Cape, South Africa; Division of Medical Virology, University of Cape Town, Cape Town, Western Cape, South Africa
| | - Suzaan Marais
- Division of Neurology, Department of Medicine, University of Cape Town, Cape Town, Western Cape, South Africa; Neuroscience Institute, University of Cape Town, Cape Town, Western Cape, South Africa
| | - Kate McMullen
- Division of Neurology, Department of Medicine, University of Cape Town, Cape Town, Western Cape, South Africa
| | - Kathleen Bateman
- Division of Neurology, Department of Medicine, University of Cape Town, Cape Town, Western Cape, South Africa
| | - Diederick van der Westhuizen
- Groote Schuur Hospital National Health Laboratory Service Laboratory, Cape Town, Western Cape, South Africa; Division of Chemical Pathology, University of Cape Town, Cape Town, Western Cape, South Africa
| | - Moepeng Maseko
- Groote Schuur Hospital National Health Laboratory Service Laboratory, Cape Town, Western Cape, South Africa; Division of Medical Virology, University of Cape Town, Cape Town, Western Cape, South Africa
| | - Diana Hardie
- Groote Schuur Hospital National Health Laboratory Service Laboratory, Cape Town, Western Cape, South Africa; Division of Medical Virology, University of Cape Town, Cape Town, Western Cape, South Africa
| | - Adrian Brink
- Division of Medical Microbiology, University of Cape Town, Cape Town, Western Cape, South Africa; Groote Schuur Hospital National Health Laboratory Service Laboratory, Cape Town, Western Cape, South Africa; Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, Western Cape, South Africa
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Sharma S, Pannu J, Chorlton S, Swett JL, Ecker DJ. Threat Net: A Metagenomic Surveillance Network for Biothreat Detection and Early Warning. Health Secur 2023; 21:347-357. [PMID: 37367195 DOI: 10.1089/hs.2022.0160] [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] [Indexed: 06/28/2023] Open
Abstract
Early detection of novel pathogens can prevent or substantially mitigate biological incidents, including pandemics. Metagenomic next-generation sequencing (mNGS) of symptomatic clinical samples may enable detection early enough to contain outbreaks, limit international spread, and expedite countermeasure development. In this article, we propose a clinical mNGS architecture we call "Threat Net," which focuses on the hospital emergency department as a high-yield surveillance location. We develop a susceptible-exposed-infected-removed (SEIR) simulation model to estimate the effectiveness of Threat Net in detecting novel respiratory pathogen outbreaks. Our analysis serves to quantify the value of routine clinical mNGS for respiratory pandemic detection by estimating the cost and epidemiological effectiveness at differing degrees of hospital coverage across the United States. We estimate that a biological threat detection network such as Threat Net could be deployed across hospitals covering 30% of the population in the United States. Threat Net would cost between $400 million and $800 million annually and have a 95% chance of detecting a novel respiratory pathogen with traits of SARS-CoV-2 after 10 emergency department presentations and 79 infections across the United States. Our analyses suggest that implementing Threat Net could help prevent or substantially mitigate the spread of a respiratory pandemic pathogen in the United States.
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Affiliation(s)
- Siddhanth Sharma
- Siddhanth Sharma, MD MPH, is a Public Health Registrar, Metropolitan Communicable Disease Control, Perth, Australia
| | - Jaspreet Pannu
- Jaspreet Pannu, MD, is a Resident Physician, Department of Medicine, Stanford University School of Medicine, Stanford, CA. Johns Hopkins Center for Health Security, Baltimore, MD
| | - Sam Chorlton
- Sam Chorlton, MD, D(ABMM), is Chief Executive Officer, BugSeq Bioinformatics, Vancouver, Canada
| | - Jacob L Swett
- Jacob L. Swett, DPhil, is Cofounder, altLabs, Inc., Berkeley, CA
| | - David J Ecker
- David J. Ecker, PhD, is Vice President of Strategic Innovation, Ionis Pharmaceuticals, Carlsbad, CA
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Batool M, Galloway-Peña J. Clinical metagenomics-challenges and future prospects. Front Microbiol 2023; 14:1186424. [PMID: 37448579 PMCID: PMC10337830 DOI: 10.3389/fmicb.2023.1186424] [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: 03/14/2023] [Accepted: 06/12/2023] [Indexed: 07/15/2023] Open
Abstract
Infections lacking precise diagnosis are often caused by a rare or uncharacterized pathogen, a combination of pathogens, or a known pathogen carrying undocumented or newly acquired genes. Despite medical advances in infectious disease diagnostics, many patients still experience mortality or long-term consequences due to undiagnosed or misdiagnosed infections. Thus, there is a need for an exhaustive and universal diagnostic strategy to reduce the fraction of undocumented infections. Compared to conventional diagnostics, metagenomic next-generation sequencing (mNGS) is a promising, culture-independent sequencing technology that is sensitive to detecting rare, novel, and unexpected pathogens with no preconception. Despite the fact that several studies and case reports have identified the effectiveness of mNGS in improving clinical diagnosis, there are obvious shortcomings in terms of sensitivity, specificity, costs, standardization of bioinformatic pipelines, and interpretation of findings that limit the integration of mNGS into clinical practice. Therefore, physicians must understand the potential benefits and drawbacks of mNGS when applying it to clinical practice. In this review, we will examine the current accomplishments, efficacy, and restrictions of mNGS in relation to conventional diagnostic methods. Furthermore, we will suggest potential approaches to enhance mNGS to its maximum capacity as a clinical diagnostic tool for identifying severe infections.
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A case for investment in clinical metagenomics in low-income and middle-income countries. THE LANCET. MICROBE 2023; 4:e192-e199. [PMID: 36563703 DOI: 10.1016/s2666-5247(22)00328-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Revised: 10/24/2022] [Accepted: 10/25/2022] [Indexed: 12/24/2022]
Abstract
Clinical metagenomics is the diagnostic approach with the broadest capacity to detect both known and novel pathogens. Clinical metagenomics is costly to run and requires infrastructure, but the use of next-generation sequencing for SARS-CoV-2 molecular epidemiology in low-income and middle-income countries (LMICs) offers an opportunity to direct this infrastructure to the establishment of clinical metagenomics programmes. Local implementation of clinical metagenomics is important to create relevant systems and evaluate cost-effective methodologies for its use, as well as to ensure that reference databases and result interpretation tools are appropriate to local epidemiology. Rational implementation, based on the needs of LMICs and the available resources, could ultimately improve individual patient care in instances in which available diagnostics are inadequate and supplement emerging infectious disease surveillance systems to ensure the next pandemic pathogen is quickly identified.
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