Patterns of Brucellosis Infection Symptoms in Azerbaijan: A Latent Class Cluster Analysis

Brucellosis infection is a multisystem disease, with a broad spectrum of symptoms. We investigated the existence of clusters of infected patients according to their clinical presentation. Using national surveillance data from the Electronic-Integrated Disease Surveillance System, we applied a latent...

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Published in:Journal of Tropical Medicine
Main Authors: Rita Ismayilova, Emilya Nasirova, Colleen Hanou, Robert G. Rivard, Christian T. Bautista
Format: Article in Journal/Newspaper
Language:English
Published: Wiley 2014
Subjects:
Online Access:https://doi.org/10.1155/2014/593873
https://doaj.org/article/1b3ddc71114d4086b3b4237374ced167
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spelling ftdoajarticles:oai:doaj.org/article:1b3ddc71114d4086b3b4237374ced167 2024-09-09T19:25:58+00:00 Patterns of Brucellosis Infection Symptoms in Azerbaijan: A Latent Class Cluster Analysis Rita Ismayilova Emilya Nasirova Colleen Hanou Robert G. Rivard Christian T. Bautista 2014-01-01T00:00:00Z https://doi.org/10.1155/2014/593873 https://doaj.org/article/1b3ddc71114d4086b3b4237374ced167 EN eng Wiley http://dx.doi.org/10.1155/2014/593873 https://doaj.org/toc/1687-9686 https://doaj.org/toc/1687-9694 1687-9686 1687-9694 doi:10.1155/2014/593873 https://doaj.org/article/1b3ddc71114d4086b3b4237374ced167 Journal of Tropical Medicine, Vol 2014 (2014) Arctic medicine. Tropical medicine RC955-962 article 2014 ftdoajarticles https://doi.org/10.1155/2014/593873 2024-08-05T17:48:35Z Brucellosis infection is a multisystem disease, with a broad spectrum of symptoms. We investigated the existence of clusters of infected patients according to their clinical presentation. Using national surveillance data from the Electronic-Integrated Disease Surveillance System, we applied a latent class cluster (LCC) analysis on symptoms to determine clusters of brucellosis cases. A total of 454 cases reported between July 2011 and July 2013 were analyzed. LCC identified a two-cluster model and the Vuong-Lo-Mendell-Rubin likelihood ratio supported the cluster model. Brucellosis cases in the second cluster (19%) reported higher percentages of poly-lymphadenopathy, hepatomegaly, arthritis, myositis, and neuritis and changes in liver function tests compared to cases of the first cluster. Patients in the second cluster had a severe brucellosis disease course and were associated with longer delay in seeking medical attention. Moreover, most of them were from Beylagan, a region focused on sheep and goat livestock production in south-central Azerbaijan. Patients in cluster 2 accounted for one-quarter of brucellosis cases and had a more severe clinical presentation. Delay in seeking medical care may explain severe illness. Future work needs to determine the factors that influence brucellosis case seeking and identify brucellosis species, particularly among cases from Beylagan. Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic Rubin ENVELOPE(65.493,65.493,-73.438,-73.438) Journal of Tropical Medicine 2014 1 4
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic Arctic medicine. Tropical medicine
RC955-962
spellingShingle Arctic medicine. Tropical medicine
RC955-962
Rita Ismayilova
Emilya Nasirova
Colleen Hanou
Robert G. Rivard
Christian T. Bautista
Patterns of Brucellosis Infection Symptoms in Azerbaijan: A Latent Class Cluster Analysis
topic_facet Arctic medicine. Tropical medicine
RC955-962
description Brucellosis infection is a multisystem disease, with a broad spectrum of symptoms. We investigated the existence of clusters of infected patients according to their clinical presentation. Using national surveillance data from the Electronic-Integrated Disease Surveillance System, we applied a latent class cluster (LCC) analysis on symptoms to determine clusters of brucellosis cases. A total of 454 cases reported between July 2011 and July 2013 were analyzed. LCC identified a two-cluster model and the Vuong-Lo-Mendell-Rubin likelihood ratio supported the cluster model. Brucellosis cases in the second cluster (19%) reported higher percentages of poly-lymphadenopathy, hepatomegaly, arthritis, myositis, and neuritis and changes in liver function tests compared to cases of the first cluster. Patients in the second cluster had a severe brucellosis disease course and were associated with longer delay in seeking medical attention. Moreover, most of them were from Beylagan, a region focused on sheep and goat livestock production in south-central Azerbaijan. Patients in cluster 2 accounted for one-quarter of brucellosis cases and had a more severe clinical presentation. Delay in seeking medical care may explain severe illness. Future work needs to determine the factors that influence brucellosis case seeking and identify brucellosis species, particularly among cases from Beylagan.
format Article in Journal/Newspaper
author Rita Ismayilova
Emilya Nasirova
Colleen Hanou
Robert G. Rivard
Christian T. Bautista
author_facet Rita Ismayilova
Emilya Nasirova
Colleen Hanou
Robert G. Rivard
Christian T. Bautista
author_sort Rita Ismayilova
title Patterns of Brucellosis Infection Symptoms in Azerbaijan: A Latent Class Cluster Analysis
title_short Patterns of Brucellosis Infection Symptoms in Azerbaijan: A Latent Class Cluster Analysis
title_full Patterns of Brucellosis Infection Symptoms in Azerbaijan: A Latent Class Cluster Analysis
title_fullStr Patterns of Brucellosis Infection Symptoms in Azerbaijan: A Latent Class Cluster Analysis
title_full_unstemmed Patterns of Brucellosis Infection Symptoms in Azerbaijan: A Latent Class Cluster Analysis
title_sort patterns of brucellosis infection symptoms in azerbaijan: a latent class cluster analysis
publisher Wiley
publishDate 2014
url https://doi.org/10.1155/2014/593873
https://doaj.org/article/1b3ddc71114d4086b3b4237374ced167
long_lat ENVELOPE(65.493,65.493,-73.438,-73.438)
geographic Arctic
Rubin
geographic_facet Arctic
Rubin
genre Arctic
genre_facet Arctic
op_source Journal of Tropical Medicine, Vol 2014 (2014)
op_relation http://dx.doi.org/10.1155/2014/593873
https://doaj.org/toc/1687-9686
https://doaj.org/toc/1687-9694
1687-9686
1687-9694
doi:10.1155/2014/593873
https://doaj.org/article/1b3ddc71114d4086b3b4237374ced167
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container_title Journal of Tropical Medicine
container_volume 2014
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