ReviewAntimicrobial stewardship & healthcare epidemiology : ASHE2022
Whole-genome sequencing surveillance and machine learning for healthcare outbreak detection and investigation: A systematic review and summary.
Review in Antimicrobial stewardship & healthcare epidemiology : ASHE, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
17 citing papers in PubMed.
- Clinical and genomic determinants associated with emergent ceftazidime-avibactam plus aztreonam non-susceptibility in ceftazidime-avibactam resistantAntimicrobial agents and chemotherapy · 2026Article
- Real-Time Genomic Surveillance for Enhanced Healthcare Outbreak Detection and Control: Clinical and Economic Impact.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2026Article
- Artificial intelligence enhances genomic surveillance in healthcare outbreak investigations.Infection control and hospital epidemiology · 2026Article
- Regional VRE surveillance using routine centralised, multicentre whole genome sequencing.PloS one · 2026Article
- Global evolutionary dynamics of peste des petits ruminants virus reveals geographic lineage structuring and clade-defining mutational signatures.Frontiers in microbiology · 2026Article
- Integrating epidemiology with genomic tracing to uncover concealed transmission networks in a brucellosis outbreak, Shandong, China.Frontiers in cellular and infection microbiology · 2026Article
- Persistent multispecies dissemination ofJournal of clinical microbiology · 2025Article
- Genomic sequencing surveillance of patients colonized with vancomycin-resistant enterococci improves detection of healthcare-associated transmission.BMC global and public health · 2025Article
- Pathogen genomics in healthcare: overcoming barriers to proactive surveillance.Antimicrobial agents and chemotherapy · 2025Article
- Whole-genome sequencing-based source tracing and infection control ofFrontiers in microbiology · 2025Article
- Genomic Surveillance for Enhanced Healthcare Outbreak Detection and Control.medRxiv : the preprint server for health sciences · 2024Article
- Incidence and transmission associated with respiratory viruses in an acute care facility: An observational study.Infection control and hospital epidemiology · 2024Observational
- Real-time genomic epidemiologic investigation of a multispecies plasmid-associated hospital outbreak of NDM-5-producing Enterobacterales infections.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2024Article
- Evaluating the impact of genomic epidemiology of methicillin-resistantMicrobial genomics · 2024Article
- Status check: next-generation sequencing for infectious-disease diagnostics.The Journal of clinical investigation · 2024Article
- Impact of discontinuation of contact precautions on surveillance- and whole genome sequencing-defined methicillin-resistantAntimicrobial stewardship & healthcare epidemiology : ASHE · 2024Article
- The future of automated infection detection: Innovation to transform practice (Part III/III).Antimicrobial stewardship & healthcare epidemiology : ASHE · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Whole-genome sequencing (WGS) has traditionally been used in infection prevention to confirm or refute the presence of an outbreak after it has occurred. Due to decreasing costs of WGS, an increasing number of institutions have been utilizing WGS-based surveillance. Additionally, machine learning or statistical modeling to supplement infection prevention practice have also been used. We systematically reviewed the use of WGS surveillance and machine learning to detect and investigate outbreaks in healthcare settings. Methods: We performed a PubMed search using separate terms for WGS surveillance and/or machine-learning technologies for infection prevention through March 15, 2021. Results: Of 767 studies returned using the WGS search terms, 42 articles were included for review. Only 2 studies (4.8%) were performed in real time, and 39 (92.9%) studied only 1 pathogen. Nearly all studies (n = 41, 97.6%) found genetic relatedness between some isolates collected. Across all studies, 525 outbreaks were detected among 2,837 related isolates (average, 5.4 isolates per outbreak). Also, 35 studies (83.3%) only utilized geotemporal clustering to identify outbreak transmission routes. Of 21 studies identified using the machine-learning search terms, 4 were included for review. In each study, machine learning aided outbreak investigations by complementing methods to gather epidemiologic data and automating identification of transmission pathways. Conclusions: WGS surveillance is an emerging method that can enhance outbreak detection. Machine learning has the potential to identify novel routes of pathogen transmission. Broader incorporation of WGS surveillance into infection prevention practice has the potential to transform the detection and control of healthcare outbreaks.
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.