Clustering of HIV Patients in Ethiopia

Wondimu Biressaw,1 Habtamu Tilaye,2 Dessie Melese2 1Benishangul-Gumuz, Wombera Sineor Secondary and Preparatory School, Benishangul, Ethiopia; 2University of Gondar, College of Natural and Computational Science, Departmentof Statistics, Gondar, EthiopiaCorrespondence: Dessie MeleseDepartment of Stat...

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Autores principales:	Biressaw W, Tilaye H, Melese D
Formato:	article
Lenguaje:	EN
Publicado:	Dove Medical Press 2021
Materias:	ethiopian demographic health survey cluster analysis principal component analysis hiv patients Immunologic diseases. Allergy RC581-607
Acceso en línea:	https://doaj.org/article/d306b1d88d5045859837b181fdb0634a
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spelling	oai:doaj.org-article:d306b1d88d5045859837b181fdb0634a2021-12-02T16:51:55ZClustering of HIV Patients in Ethiopia1179-1373https://doaj.org/article/d306b1d88d5045859837b181fdb0634a2021-05-01T00:00:00Zhttps://www.dovepress.com/clustering-of-hiv-patients-in-ethiopia-peer-reviewed-fulltext-article-HIVhttps://doaj.org/toc/1179-1373Wondimu Biressaw,1 Habtamu Tilaye,2 Dessie Melese2 1Benishangul-Gumuz, Wombera Sineor Secondary and Preparatory School, Benishangul, Ethiopia; 2University of Gondar, College of Natural and Computational Science, Departmentof Statistics, Gondar, EthiopiaCorrespondence: Dessie MeleseDepartment of Statistics, College Natural and Computational Science, University of Gondar, P.O. Box 196, Gondar, EthiopiaEmail dessie.melese1@uog.edu.etBackground: Among the many worldwide health problems, HIV/AIDS has caused severe health problems in several countries. The problem is also widely seen in Ethiopia. The general objective of the study is to cluster HIV patients and to find out the factors that mostly affect the prevalence of HIV within a group (cluster) and between groups (clusters) of HIV patients.Methods: The study is made based on the 2016 Ethiopian Demographic Health Survey (EDHS) which was collected by the Central Statistical Agency (CSA) of Ethiopia, and the survey collected a total of 26,753 samples, of which 14,785 were women and 11,968 were men and the age group was between 15 and 49 years for both. Binary logistic regression, principal component analysis, cluster analysis, and ANOVA were applied to analyze the data.Results: The result from binary logistic regression reveals that 15 factors such as ever heard of AIDS, region, water not available for at least a day in the last 2 weeks, has a radio, family members wash their hands, location of the source of water, everything completed to water to make it harmless to drink, food cooked in the house/separate house/outside, has a mobile telephone, has a table, type of place of residence, highest education level attained, current marital status, sex of household members, and age of household members are all significant factors that affect HIV status.Conclusion: Using these significant variables, 12 principal components are identified which describe 78% of the variation in the data. The result of HIV patients are clustered into 3 clusters and determine the status of HIV levels. Mainly, cluster 2 accounts for 50% of HIV patients whereas cluster 3 and 1 accounts for 40% and 10%, respectively.Keywords: Ethiopian Demographic Health Survey; EDHS, cluster analysis, principal component analysis, HIV patientsBiressaw WTilaye HMelese DDove Medical Pressarticleethiopian demographic health surveycluster analysisprincipal component analysishiv patientsImmunologic diseases. AllergyRC581-607ENHIV/AIDS: Research and Palliative Care, Vol Volume 13, Pp 581-592 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	ethiopian demographic health survey cluster analysis principal component analysis hiv patients Immunologic diseases. Allergy RC581-607
spellingShingle	ethiopian demographic health survey cluster analysis principal component analysis hiv patients Immunologic diseases. Allergy RC581-607 Biressaw W Tilaye H Melese D Clustering of HIV Patients in Ethiopia
description	Wondimu Biressaw,1 Habtamu Tilaye,2 Dessie Melese2 1Benishangul-Gumuz, Wombera Sineor Secondary and Preparatory School, Benishangul, Ethiopia; 2University of Gondar, College of Natural and Computational Science, Departmentof Statistics, Gondar, EthiopiaCorrespondence: Dessie MeleseDepartment of Statistics, College Natural and Computational Science, University of Gondar, P.O. Box 196, Gondar, EthiopiaEmail dessie.melese1@uog.edu.etBackground: Among the many worldwide health problems, HIV/AIDS has caused severe health problems in several countries. The problem is also widely seen in Ethiopia. The general objective of the study is to cluster HIV patients and to find out the factors that mostly affect the prevalence of HIV within a group (cluster) and between groups (clusters) of HIV patients.Methods: The study is made based on the 2016 Ethiopian Demographic Health Survey (EDHS) which was collected by the Central Statistical Agency (CSA) of Ethiopia, and the survey collected a total of 26,753 samples, of which 14,785 were women and 11,968 were men and the age group was between 15 and 49 years for both. Binary logistic regression, principal component analysis, cluster analysis, and ANOVA were applied to analyze the data.Results: The result from binary logistic regression reveals that 15 factors such as ever heard of AIDS, region, water not available for at least a day in the last 2 weeks, has a radio, family members wash their hands, location of the source of water, everything completed to water to make it harmless to drink, food cooked in the house/separate house/outside, has a mobile telephone, has a table, type of place of residence, highest education level attained, current marital status, sex of household members, and age of household members are all significant factors that affect HIV status.Conclusion: Using these significant variables, 12 principal components are identified which describe 78% of the variation in the data. The result of HIV patients are clustered into 3 clusters and determine the status of HIV levels. Mainly, cluster 2 accounts for 50% of HIV patients whereas cluster 3 and 1 accounts for 40% and 10%, respectively.Keywords: Ethiopian Demographic Health Survey; EDHS, cluster analysis, principal component analysis, HIV patients
format	article
author	Biressaw W Tilaye H Melese D
author_facet	Biressaw W Tilaye H Melese D
author_sort	Biressaw W
title	Clustering of HIV Patients in Ethiopia
title_short	Clustering of HIV Patients in Ethiopia
title_full	Clustering of HIV Patients in Ethiopia
title_fullStr	Clustering of HIV Patients in Ethiopia
title_full_unstemmed	Clustering of HIV Patients in Ethiopia
title_sort	clustering of hiv patients in ethiopia
publisher	Dove Medical Press
publishDate	2021
url	https://doaj.org/article/d306b1d88d5045859837b181fdb0634a
work_keys_str_mv	AT biressaww clusteringofhivpatientsinethiopia AT tilayeh clusteringofhivpatientsinethiopia AT melesed clusteringofhivpatientsinethiopia
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Clustering of HIV Patients in Ethiopia

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