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Tran M, Smurthwaite KS, Nghiem S, Cribb DM, Zahedi A, Ferdinand AD, Andersson P, Kirk MD, Glass K, Lancsar E. Economic evaluations of whole-genome sequencing for pathogen identification in public health surveillance and health-care-associated infections: a systematic review. THE LANCET. MICROBE 2023; 4:e953-e962. [PMID: 37683688 DOI: 10.1016/s2666-5247(23)00180-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Revised: 05/31/2023] [Accepted: 06/05/2023] [Indexed: 09/10/2023]
Abstract
Whole-genome sequencing (WGS) has resulted in improvements to pathogen characterisation for the rapid investigation and management of disease outbreaks and surveillance. We conducted a systematic review to synthesise the economic evidence of WGS implementation for pathogen identification and surveillance. Of the 2285 unique publications identified through online database searches, 19 studies met the inclusion criteria. The economic evidence to support the broader application of WGS as a front-line pathogen characterisation and surveillance tool is insufficient and of low quality. WGS has been evaluated in various clinical settings, but these evaluations are predominantly investigations of a single pathogen. There are also considerable variations in the evaluation approach. Economic evaluations of costs, effectiveness, and cost-effectiveness are needed to support the implementation of WGS in public health settings.
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Affiliation(s)
- My Tran
- National Centre for Epidemiology and Population Health, Australian National University, Canberra ACT, Australia.
| | - Kayla S Smurthwaite
- National Centre for Epidemiology and Population Health, Australian National University, Canberra ACT, Australia
| | - Son Nghiem
- National Centre for Epidemiology and Population Health, Australian National University, Canberra ACT, Australia
| | - Danielle M Cribb
- National Centre for Epidemiology and Population Health, Australian National University, Canberra ACT, Australia
| | - Alireza Zahedi
- Public Health Microbiology, Forensic and Scientific Services, Queensland Health, Brisbane QLD, Australia
| | - Angeline D Ferdinand
- Microbiological Diagnostic Unit, Peter Doherty Institute, University of Melbourne, Melbourne VIC, Australia
| | - Patiyan Andersson
- Microbiological Diagnostic Unit, Peter Doherty Institute, University of Melbourne, Melbourne VIC, Australia
| | - Martyn D Kirk
- National Centre for Epidemiology and Population Health, Australian National University, Canberra ACT, Australia
| | - Kathryn Glass
- National Centre for Epidemiology and Population Health, Australian National University, Canberra ACT, Australia
| | - Emily Lancsar
- National Centre for Epidemiology and Population Health, Australian National University, Canberra ACT, Australia
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Forde BM, Bergh H, Cuddihy T, Hajkowicz K, Hurst T, Playford EG, Henderson BC, Runnegar N, Clark J, Jennison AV, Moss S, Hume A, Leroux H, Beatson SA, Paterson DL, Harris PNA. Clinical Implementation of Routine Whole-genome Sequencing for Hospital Infection Control of Multi-drug Resistant Pathogens. Clin Infect Dis 2023; 76:e1277-e1284. [PMID: 36056896 DOI: 10.1093/cid/ciac726] [Citation(s) in RCA: 22] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 08/25/2022] [Accepted: 08/30/2022] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND Prospective whole-genome sequencing (WGS)-based surveillance may be the optimal approach to rapidly identify transmission of multi-drug resistant (MDR) bacteria in the healthcare setting. METHODS We prospectively collected methicillin-resistant Staphylococcus aureus (MRSA), vancomycin-resistant enterococci (VRE), carbapenem-resistant Acinetobacter baumannii (CRAB), extended-spectrum beta-lactamase (ESBL-E), and carbapenemase-producing Enterobacterales (CPE) isolated from blood cultures, sterile sites, or screening specimens across three large tertiary referral hospitals (2 adult, 1 paediatric) in Brisbane, Australia. WGS was used to determine in silico multi-locus sequence typing (MLST) and resistance gene profiling via a bespoke genomic analysis pipeline. Putative transmission events were identified by comparison of core genome single nucleotide polymorphisms (SNPs). Relevant clinical meta-data were combined with genomic analyses via customised automation, collated into hospital-specific reports regularly distributed to infection control teams. RESULTS Over 4 years (April 2017 to July 2021) 2660 isolates were sequenced. This included MDR gram-negative bacilli (n = 293 CPE, n = 1309 ESBL), MRSA (n = 620), and VRE (n = 433). A total of 379 clinical reports were issued. Core genome SNP data identified that 33% of isolates formed 76 distinct clusters. Of the 76 clusters, 43 were contained to the 3 target hospitals, suggesting ongoing transmission within the clinical environment. The remaining 33 clusters represented possible inter-hospital transmission events or strains circulating in the community. In 1 hospital, proven negligible transmission of non-multi-resistant MRSA enabled changes to infection control policy. CONCLUSIONS Implementation of routine WGS for MDR pathogens in clinical laboratories is feasible and can enable targeted infection prevention and control interventions.
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Affiliation(s)
- Brian M Forde
- Faculty of Medicine, UQ Centre for Clinical Research, University of Queensland, Brisbane, QLD, Australia
| | - Haakon Bergh
- Central Microbiology, Pathology Queensland, Royal Brisbane & Women's Hospital, Brisbane, QLD, Australia
| | - Thom Cuddihy
- Faculty of Medicine, UQ Centre for Clinical Research, University of Queensland, Brisbane, QLD, Australia
| | - Krispin Hajkowicz
- Infectious Diseases Unit, Royal Brisbane and Women's Hospital, Herston, QLD, Australia
| | - Trish Hurst
- Infectious Diseases Unit, Royal Brisbane and Women's Hospital, Herston, QLD, Australia
| | - E Geoffrey Playford
- Infection Management Services, Princess Alexandra Hospital, Metro South Hospital and Health Service, Brisbane, QLD, Australia
| | - Belinda C Henderson
- Infection Management Services, Princess Alexandra Hospital, Metro South Hospital and Health Service, Brisbane, QLD, Australia
| | - Naomi Runnegar
- Infection Management Services, Princess Alexandra Hospital, Metro South Hospital and Health Service, Brisbane, QLD, Australia.,Faculty of Medicine, PA-Southside Clinical School, University of Queensland, Brisbane, QLD, Australia
| | - Julia Clark
- Infection Management and Prevention Service, Queensland Children's Hospital, Brisbane, QLD, Australia.,Centre for Children's Health Research, Children's Health Queensland, Brisbane, Australia
| | - Amy V Jennison
- Public Health Microbiology, Forensic and Scientific Services, Queensland Health, Brisbane, QLD, Australia
| | - Susan Moss
- Public Health Microbiology, Forensic and Scientific Services, Queensland Health, Brisbane, QLD, Australia
| | - Anna Hume
- Central Microbiology, Pathology Queensland, Royal Brisbane & Women's Hospital, Brisbane, QLD, Australia.,Infectious Diseases Unit, Royal Brisbane and Women's Hospital, Herston, QLD, Australia
| | - Hugo Leroux
- Australian e-Health Research Centre, CSIRO, Brisbane, QLD, Australia
| | - Scott A Beatson
- School of Chemistry and Molecular Biosciences, University of Queensland, Brisbane, QLD, Australia
| | - David L Paterson
- Faculty of Medicine, UQ Centre for Clinical Research, University of Queensland, Brisbane, QLD, Australia.,Infectious Diseases Unit, Royal Brisbane and Women's Hospital, Herston, QLD, Australia
| | - Patrick N A Harris
- Faculty of Medicine, UQ Centre for Clinical Research, University of Queensland, Brisbane, QLD, Australia.,Central Microbiology, Pathology Queensland, Royal Brisbane & Women's Hospital, Brisbane, QLD, Australia
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Meumann EM, Krause VL, Baird R, Currie BJ. Using Genomics to Understand the Epidemiology of Infectious Diseases in the Northern Territory of Australia. Trop Med Infect Dis 2022; 7:tropicalmed7080181. [PMID: 36006273 PMCID: PMC9413455 DOI: 10.3390/tropicalmed7080181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Revised: 08/09/2022] [Accepted: 08/11/2022] [Indexed: 11/16/2022] Open
Abstract
The Northern Territory (NT) is a geographically remote region of northern and central Australia. Approximately a third of the population are First Nations Australians, many of whom live in remote regions. Due to the physical environment and climate, and scale of social inequity, the rates of many infectious diseases are the highest nationally. Molecular typing and genomic sequencing in research and public health have provided considerable new knowledge on the epidemiology of infectious diseases in the NT. We review the applications of genomic sequencing technology for molecular typing, identification of transmission clusters, phylogenomics, antimicrobial resistance prediction, and pathogen detection. We provide examples where these methodologies have been applied to infectious diseases in the NT and discuss the next steps in public health implementation of this technology.
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Affiliation(s)
- Ella M. Meumann
- Global and Tropical Health Division, Menzies School of Health Research, Charles Darwin University, Darwin 0810, Australia
- Department of Infectious Diseases, Division of Medicine, Royal Darwin Hospital, Darwin 0810, Australia
- Correspondence:
| | - Vicki L. Krause
- Northern Territory Centre for Disease Control, Northern Territory Government, Darwin 0810, Australia
| | - Robert Baird
- Territory Pathology, Royal Darwin Hospital, Darwin 0810, Australia
| | - Bart J. Currie
- Global and Tropical Health Division, Menzies School of Health Research, Charles Darwin University, Darwin 0810, Australia
- Department of Infectious Diseases, Division of Medicine, Royal Darwin Hospital, Darwin 0810, Australia
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Cost-effectiveness analysis of whole-genome sequencing during an outbreak of carbapenem-resistant Acinetobacter baumannii. ANTIMICROBIAL STEWARDSHIP & HEALTHCARE EPIDEMIOLOGY 2021; 1:e62. [PMID: 36168472 PMCID: PMC9495627 DOI: 10.1017/ash.2021.233] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Revised: 10/25/2021] [Accepted: 10/25/2021] [Indexed: 11/12/2022]
Abstract
Background: Whole-genome sequencing (WGS) shotgun metagenomics (metagenomics) attempts to sequence the entire genetic content straight from the sample. Diagnostic advantages lie in the ability to detect unsuspected, uncultivatable, or very slow-growing organisms. Objective: To evaluate the clinical and economic effects of using WGS and metagenomics for outbreak management in a large metropolitan hospital. Design: Cost-effectiveness study. Setting: Intensive care unit and burn unit of large metropolitan hospital. Patients: Simulated intensive care unit and burn unit patients. Methods: We built a complex simulation model to estimate pathogen transmission, associated hospital costs, and quality-adjusted life years (QALYs) during a 32-month outbreak of carbapenem-resistant Acinetobacter baumannii (CRAB). Model parameters were determined using microbiology surveillance data, genome sequencing results, hospital admission databases, and local clinical knowledge. The model was calibrated to the actual pathogen spread within the intensive care unit and burn unit (scenario 1) and compared with early use of WGS (scenario 2) and early use of WGS and metagenomics (scenario 3) to determine their respective cost-effectiveness. Sensitivity analyses were performed to address model uncertainty. Results: On average compared with scenario 1, scenario 2 resulted in 14 fewer patients with CRAB, 59 additional QALYs, and $75,099 cost savings. Scenario 3, compared with scenario 1, resulted in 18 fewer patients with CRAB, 74 additional QALYs, and $93,822 in hospital cost savings. The likelihoods that scenario 2 and scenario 3 were cost-effective were 57% and 60%, respectively. Conclusions: The use of WGS and metagenomics in infection control processes were predicted to produce favorable economic and clinical outcomes.
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