{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T20:34:29Z","timestamp":1772138069051,"version":"3.50.1"},"reference-count":29,"publisher":"Oxford University Press (OUP)","issue":"7","license":[{"start":{"date-parts":[[2024,7,2]],"date-time":"2024-07-02T00:00:00Z","timestamp":1719878400000},"content-version":"vor","delay-in-days":1,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Health and Medical Research Council of Australia","award":["1146938"],"award-info":[{"award-number":["1146938"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,7,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Summary<\/jats:title>\n                    <jats:p>The reliable and timely recognition of outbreaks is a key component of public health surveillance for foodborne diseases. Whole genome sequencing (WGS) offers high resolution typing of foodborne bacterial pathogens and facilitates the accurate detection of outbreaks. This detection relies on grouping WGS data into clusters at an appropriate genetic threshold. However, methods and tools for selecting and adjusting such thresholds according to the required resolution of surveillance and epidemiological context are lacking. Here we present DODGE (Dynamic Outbreak Detection for Genomic Epidemiology), an algorithm to dynamically select and compare these genetic thresholds. DODGE can analyse expanding datasets over time and clusters that are predicted to correspond to outbreaks (or \u201cinvestigation clusters\u201d) can be named with established genomic nomenclature systems to facilitate integrated analysis across jurisdictions. DODGE was tested in two real-world Salmonella genomic surveillance datasets of different duration, 2 months from Australia and 9 years from the United Kingdom. In both cases only a minority of isolates were identified as investigation clusters. Two known outbreaks in the United Kingdom dataset were detected by DODGE and were recognized at an earlier timepoint than the outbreaks were reported. These findings demonstrated the potential of the DODGE approach to improve the effectiveness and timeliness of genomic surveillance for foodborne diseases and the effectiveness of the algorithm developed.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>DODGE is freely available at https:\/\/github.com\/LanLab\/dodge and can easily be installed using Conda.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btae427","type":"journal-article","created":{"date-parts":[[2024,7,2]],"date-time":"2024-07-02T19:50:14Z","timestamp":1719949814000},"source":"Crossref","is-referenced-by-count":6,"title":["DODGE: automated point source bacterial outbreak detection using cumulative long term genomic surveillance"],"prefix":"10.1093","volume":"40","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1911-7033","authenticated-orcid":false,"given":"Michael","family":"Payne","sequence":"first","affiliation":[{"name":"School of Biotechnology and Biomolecular Sciences, University of New South Wales , Sydney, NSW 2052, Australia"}]},{"given":"Dalong","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Biotechnology and Biomolecular Sciences, University of New South Wales , Sydney, NSW 2052, Australia"}]},{"given":"Qinning","family":"Wang","sequence":"additional","affiliation":[{"name":"Centre for Infectious Diseases and Microbiology\u2014Public Health, Institute of Clinical Pathology and Medical Research\u2014NSW Health Pathology, Westmead Hospital , Sydney, NSW 2145, Australia"}]},{"given":"Geraldine","family":"Sullivan","sequence":"additional","affiliation":[{"name":"Centre for Infectious Diseases and Microbiology\u2014Public Health, Institute of Clinical Pathology and Medical Research\u2014NSW Health Pathology, Westmead Hospital , Sydney, NSW 2145, Australia"}]},{"given":"Rikki M","family":"Graham","sequence":"additional","affiliation":[{"name":"Public Health Microbiology, Queensland Health Forensic and Scientific Services, Coopers Plains , Brisbane, QLD 4108, Australia"}]},{"given":"Irani U","family":"Rathnayake","sequence":"additional","affiliation":[{"name":"Public Health Microbiology, Queensland Health Forensic and Scientific Services, Coopers Plains , Brisbane, QLD 4108, Australia"}]},{"given":"Amy V","family":"Jennison","sequence":"additional","affiliation":[{"name":"Public Health Microbiology, Queensland Health Forensic and Scientific Services, Coopers Plains , Brisbane, QLD 4108, Australia"}]},{"given":"Vitali","family":"Sintchenko","sequence":"additional","affiliation":[{"name":"Centre for Infectious Diseases and Microbiology\u2014Public Health, Institute of Clinical Pathology and Medical Research\u2014NSW Health Pathology, Westmead Hospital , Sydney, NSW 2145, Australia"},{"name":"Sydney Institute for Infectious Diseases, Sydney Medical School, University of Sydney , Sydney, NSW 2006, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9834-5258","authenticated-orcid":false,"given":"Ruiting","family":"Lan","sequence":"additional","affiliation":[{"name":"School of Biotechnology and Biomolecular Sciences, University of New South Wales , Sydney, NSW 2052, Australia"}]}],"member":"286","published-online":{"date-parts":[[2024,7,2]]},"reference":[{"key":"2024071218162637600_btae427-B1","doi-asserted-by":"crossref","first-page":"01692","DOI":"10.1128\/JCM.01692-19","article-title":"Persistent transmission of shigellosis in England is associated with a recently emerged multidrug-resistant strain of Shigella sonnei","volume":"58","author":"Bardsley","year":"2020","journal-title":"J Clin 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