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Use of WHONET-SaTScan system for simulated real-time detection of antimicrobial resistance clusters in a hospital in Italy, 2012 to 2014.
Natale A, Stelling J, Meledandri M, Messenger LA, D'Ancona F. Natale A, et al. Euro Surveill. 2017 Mar 16;22(11):30484. doi: 10.2807/1560-7917.ES.2017.22.11.30484. Euro Surveill. 2017. PMID: 28333615 Free PMC article.
The WHONET-SaTScan identified 71 statistically significant clusters, some involving pathogens carrying multiple resistance phenotypes. Of these 71, three were also detected by the hospital system, while a further 15, detected by WHONET-SaTScan only, were considered …
The WHONET-SaTScan identified 71 statistically significant clusters, some involving pathogens carrying multiple resistance phenotypes …
Automated use of WHONET and SaTScan to detect outbreaks of Shigella spp. using antimicrobial resistance phenotypes.
Stelling J, Yih WK, Galas M, Kulldorff M, Pichel M, Terragno R, Tuduri E, Espetxe S, Binsztein N, O'Brien TF, Platt R; Collaborative Group WHONET-Argentina. Stelling J, et al. Epidemiol Infect. 2010 Jun;138(6):873-83. doi: 10.1017/S0950268809990884. Epub 2009 Oct 2. Epidemiol Infect. 2010. PMID: 19796449 Free PMC article.
Of the six known outbreaks reported to the Ministry of Health, four had good or suggestive agreement with SaTScan-detected events. The most discriminating analyses were those involving resistance phenotypes. ...
Of the six known outbreaks reported to the Ministry of Health, four had good or suggestive agreement with SaTScan-detected events. Th …
Statistical detection of geographic clusters of resistant Escherichia coli in a regional network with WHONET and SaTScan.
Park R, O'Brien TF, Huang SS, Baker MA, Yokoe DS, Kulldorff M, Barrett C, Swift J, Stelling J; Centers for Disease Control and Prevention Epicenters Program. Park R, et al. Expert Rev Anti Infect Ther. 2016 Nov;14(11):1097-1107. doi: 10.1080/14787210.2016.1220303. Epub 2016 Sep 6. Expert Rev Anti Infect Ther. 2016. PMID: 27530311 Free PMC article.
METHODS: Escherichia coli antimicrobial susceptibility data from a three-year period stored in WHONET were analyzed across ten facilities in a healthcare network utilizing SaTScan's spatial multinomial model with two models for defining geographic proximity. ...CONCLUSION: …
METHODS: Escherichia coli antimicrobial susceptibility data from a three-year period stored in WHONET were analyzed across ten facilities in …
Staphylococcus aureus antimicrobial susceptibility trends and cluster detection in Vermont: 2012-2018.
Stelling J, Read JS, Peters R, Clark A, Bokhari M, O'Brien TF. Stelling J, et al. Expert Rev Anti Infect Ther. 2021 Jun;19(6):777-785. doi: 10.1080/14787210.2021.1845653. Epub 2021 Jan 8. Expert Rev Anti Infect Ther. 2021. PMID: 33131354
Objectives: This study presents demographic and temporal trends in the isolation of Staphylococcus aureus in Vermont clinical microbiology laboratories and explores the use of statistical algorithms and multi-resistance phenotypes to improve outbreak detection.Methods: Routine mi …
Objectives: This study presents demographic and temporal trends in the isolation of Staphylococcus aureus in Vermont clinical microbiology l …
Automated detection of hospital outbreaks of multi-drug resistant pathogens in one Italian region.
Binello N, D'Ancona F, Forni S, D'Arienzo S, Gemmi F, Clark A, Stelling J. Binello N, et al. Expert Rev Anti Infect Ther. 2022 Sep;20(9):1233-1241. doi: 10.1080/14787210.2022.2098115. Epub 2022 Jul 13. Expert Rev Anti Infect Ther. 2022. PMID: 35786114
METHODS: Antimicrobial resistance surveillance data from all Tuscany hospitals between January 2018 and December 2020 were analyzed using WHONET. The SaTScan package was used to detect case clusters applying a simulated prospective approach and the space-time permutation a …
METHODS: Antimicrobial resistance surveillance data from all Tuscany hospitals between January 2018 and December 2020 were analyzed using WH …
Enhanced automated detection of outbreaks of a rare antimicrobial-resistant bacterial species.
Hosaka Y, Hirabayashi A, Clark A, Baker M, Sugai M, Stelling J, Yahara K. Hosaka Y, et al. PLoS One. 2024 Oct 24;19(10):e0312477. doi: 10.1371/journal.pone.0312477. eCollection 2024. PLoS One. 2024. PMID: 39446801 Free PMC article.
Previously, we developed a framework for automatic detection of clusters of AMR bacteria using SaTScan, a free cluster detection tool integrated into WHONET. WHONET is a free software used globally for microbiological surveillance data management. ...Our comparison reveale …
Previously, we developed a framework for automatic detection of clusters of AMR bacteria using SaTScan, a free cluster detection tool …
Automated detection of outbreaks of antimicrobial-resistant bacteria in Japan.
Tsutsui A, Yahara K, Clark A, Fujimoto K, Kawakami S, Chikumi H, Iguchi M, Yagi T, Baker MA, O'Brien T, Stelling J. Tsutsui A, et al. J Hosp Infect. 2019 Jun;102(2):226-233. doi: 10.1016/j.jhin.2018.10.005. Epub 2018 Oct 12. J Hosp Infect. 2019. PMID: 30321629 Free PMC article.
WHONET, a free software for the management of microbiology data, and SaTScan, a free cluster detection tool embedded in WHONET, were used to analyse 2015-2016 data of eligible hospitals. ...In two hospitals, clusters of more susceptible isolates were detected before outbre …
WHONET, a free software for the management of microbiology data, and SaTScan, a free cluster detection tool embedded in WHONET, were …
Automated detection of infectious disease outbreaks in hospitals: a retrospective cohort study.
Huang SS, Yokoe DS, Stelling J, Placzek H, Kulldorff M, Kleinman K, O'Brien TF, Calderwood MS, Vostok J, Dunn J, Platt R. Huang SS, et al. PLoS Med. 2010 Feb 23;7(2):e1000238. doi: 10.1371/journal.pmed.1000238. PLoS Med. 2010. PMID: 20186274 Free PMC article.
WHONET-SaTScan rapidly detected the two previously known gram-negative pathogen clusters. Compared to rule-based thresholds, WHONET-SaTScan considered only one of 73 previously designated MRSA clusters and 0 of 87 VRE clusters as episodes statistically unlikely to h …
WHONET-SaTScan rapidly detected the two previously known gram-negative pathogen clusters. Compared to rule-based thresholds, WHONET- …
Implementation and evaluation of an automated surveillance system to detect hospital outbreak.
Stachel A, Pinto G, Stelling J, Fulmer Y, Shopsin B, Inglima K, Phillips M. Stachel A, et al. Am J Infect Control. 2017 Dec 1;45(12):1372-1377. doi: 10.1016/j.ajic.2017.06.031. Epub 2017 Aug 23. Am J Infect Control. 2017. PMID: 28844384
Given the issues with manual review of hospital infections, a surveillance system to detect clusters in health care settings must use automated data capture, validated statistical methods, and include all significant pathogens, antimicrobial susceptibility patterns, patient care …
Given the issues with manual review of hospital infections, a surveillance system to detect clusters in health care settings must use automa …
11 results