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Development and Evaluation of Statewide Prospective Spatiotemporal Legionellosis Cluster Surveillance, New Jersey, USA

Incidence of Legionnaires’ disease is increasing, particularly in the Mid-Atlantic states in the United States; since 2015, New Jersey has documented ≈250–350 legionellosis cases per year. We used SaTScan software to develop a semiautomated surveillance tool for prospectively detecting legionellosis...

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Detalles Bibliográficos
Autores principales: Gleason, Jessie A., Ross, Kathleen M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Centers for Disease Control and Prevention 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8888220/
https://www.ncbi.nlm.nih.gov/pubmed/35202521
http://dx.doi.org/10.3201/eid2803.211147
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author Gleason, Jessie A.
Ross, Kathleen M.
author_facet Gleason, Jessie A.
Ross, Kathleen M.
author_sort Gleason, Jessie A.
collection PubMed
description Incidence of Legionnaires’ disease is increasing, particularly in the Mid-Atlantic states in the United States; since 2015, New Jersey has documented ≈250–350 legionellosis cases per year. We used SaTScan software to develop a semiautomated surveillance tool for prospectively detecting legionellosis clusters in New Jersey. We varied temporal window size and baseline period to evaluate optimal parameter selections. The surveillance system detected 3 community clusters of Legionnaires’ disease that were subsequently investigated. Other, smaller clusters were detected, but standard epidemiologic data did not identify common sources or new cases. The semiautomated processing is straightforward and replicable in other jurisdictions, likely by persons with even basic programming skills.
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spelling pubmed-88882202022-03-02 Development and Evaluation of Statewide Prospective Spatiotemporal Legionellosis Cluster Surveillance, New Jersey, USA Gleason, Jessie A. Ross, Kathleen M. Emerg Infect Dis Research Incidence of Legionnaires’ disease is increasing, particularly in the Mid-Atlantic states in the United States; since 2015, New Jersey has documented ≈250–350 legionellosis cases per year. We used SaTScan software to develop a semiautomated surveillance tool for prospectively detecting legionellosis clusters in New Jersey. We varied temporal window size and baseline period to evaluate optimal parameter selections. The surveillance system detected 3 community clusters of Legionnaires’ disease that were subsequently investigated. Other, smaller clusters were detected, but standard epidemiologic data did not identify common sources or new cases. The semiautomated processing is straightforward and replicable in other jurisdictions, likely by persons with even basic programming skills. Centers for Disease Control and Prevention 2022-03 /pmc/articles/PMC8888220/ /pubmed/35202521 http://dx.doi.org/10.3201/eid2803.211147 Text en https://creativecommons.org/licenses/by/4.0/Emerging Infectious Diseases is a publication of the U.S. Government. This publication is in the public domain and is therefore without copyright. All text from this work may be reprinted freely. Use of these materials should be properly cited.
spellingShingle Research
Gleason, Jessie A.
Ross, Kathleen M.
Development and Evaluation of Statewide Prospective Spatiotemporal Legionellosis Cluster Surveillance, New Jersey, USA
title Development and Evaluation of Statewide Prospective Spatiotemporal Legionellosis Cluster Surveillance, New Jersey, USA
title_full Development and Evaluation of Statewide Prospective Spatiotemporal Legionellosis Cluster Surveillance, New Jersey, USA
title_fullStr Development and Evaluation of Statewide Prospective Spatiotemporal Legionellosis Cluster Surveillance, New Jersey, USA
title_full_unstemmed Development and Evaluation of Statewide Prospective Spatiotemporal Legionellosis Cluster Surveillance, New Jersey, USA
title_short Development and Evaluation of Statewide Prospective Spatiotemporal Legionellosis Cluster Surveillance, New Jersey, USA
title_sort development and evaluation of statewide prospective spatiotemporal legionellosis cluster surveillance, new jersey, usa
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8888220/
https://www.ncbi.nlm.nih.gov/pubmed/35202521
http://dx.doi.org/10.3201/eid2803.211147
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