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Spatiotemporal Clustering Analysis of Malaria Infection in Pakistan

Despite tremendous progress, malaria remains a serious public health problem in Pakistan. Very few studies have been done on spatiotemporal evaluation of malaria infection in Pakistan. The study aimed to detect the spatiotemporal pattern of malaria infection at the district level in Pakistan, and to...

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Autores principales: Umer, Muhammad Farooq, Zofeen, Shumaila, Majeed, Abdul, Hu, Wenbiao, Qi, Xin, Zhuang, Guihua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6025434/
https://www.ncbi.nlm.nih.gov/pubmed/29880778
http://dx.doi.org/10.3390/ijerph15061202
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author Umer, Muhammad Farooq
Zofeen, Shumaila
Majeed, Abdul
Hu, Wenbiao
Qi, Xin
Zhuang, Guihua
author_facet Umer, Muhammad Farooq
Zofeen, Shumaila
Majeed, Abdul
Hu, Wenbiao
Qi, Xin
Zhuang, Guihua
author_sort Umer, Muhammad Farooq
collection PubMed
description Despite tremendous progress, malaria remains a serious public health problem in Pakistan. Very few studies have been done on spatiotemporal evaluation of malaria infection in Pakistan. The study aimed to detect the spatiotemporal pattern of malaria infection at the district level in Pakistan, and to identify the clusters of high-risk disease areas in the country. Annual data on malaria for two dominant species (Plasmodium falciparum, Plasmodium vivax) and mixed infections from 2011 to 2016 were obtained from the Directorate of Malaria Control Program, Pakistan. Population data were collected from the Pakistan Bureau of Statistics. A geographical information system was used to display the spatial distribution of malaria at the district level throughout Pakistan. Purely spatiotemporal clustering analysis was performed to identify the high-risk areas of malaria infection in Pakistan. A total of 1,593,409 positive cases were included in this study over a period of 6 years (2011–2016). The maximum number of P. vivax cases (474,478) were reported in Khyber Pakhtunkhwa (KPK). The highest burden of P. falciparum (145,445) was in Balochistan, while the highest counts of mixed Plasmodium cases were reported in Sindh (22,421) and Balochistan (22,229), respectively. In Balochistan, incidence of all three types of malaria was very high. Cluster analysis showed that primary clusters of P. vivax malaria were in the same districts in 2014, 2015 and 2016 (total 24 districts, 12 in Federally Administered Tribal Areas (FATA), 9 in KPK, 2 in Punjab and 1 in Balochistan); those of P. falciparum malaria were unchanged in 2012 and 2013 (total 18 districts, all in Balochistan), and mixed infections remained the same in 2014 and 2015 (total 7 districts, 6 in Balochistan and 1 in FATA). This study indicated that the transmission cycles of malaria infection vary in different spatiotemporal settings in Pakistan. Efforts in controlling P. vivax malaria in particular need to be enhanced in high-risk areas. Based on these findings, further research is needed to investigate the impact of risk factors on transmission of malaria in Pakistan.
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spelling pubmed-60254342018-07-16 Spatiotemporal Clustering Analysis of Malaria Infection in Pakistan Umer, Muhammad Farooq Zofeen, Shumaila Majeed, Abdul Hu, Wenbiao Qi, Xin Zhuang, Guihua Int J Environ Res Public Health Article Despite tremendous progress, malaria remains a serious public health problem in Pakistan. Very few studies have been done on spatiotemporal evaluation of malaria infection in Pakistan. The study aimed to detect the spatiotemporal pattern of malaria infection at the district level in Pakistan, and to identify the clusters of high-risk disease areas in the country. Annual data on malaria for two dominant species (Plasmodium falciparum, Plasmodium vivax) and mixed infections from 2011 to 2016 were obtained from the Directorate of Malaria Control Program, Pakistan. Population data were collected from the Pakistan Bureau of Statistics. A geographical information system was used to display the spatial distribution of malaria at the district level throughout Pakistan. Purely spatiotemporal clustering analysis was performed to identify the high-risk areas of malaria infection in Pakistan. A total of 1,593,409 positive cases were included in this study over a period of 6 years (2011–2016). The maximum number of P. vivax cases (474,478) were reported in Khyber Pakhtunkhwa (KPK). The highest burden of P. falciparum (145,445) was in Balochistan, while the highest counts of mixed Plasmodium cases were reported in Sindh (22,421) and Balochistan (22,229), respectively. In Balochistan, incidence of all three types of malaria was very high. Cluster analysis showed that primary clusters of P. vivax malaria were in the same districts in 2014, 2015 and 2016 (total 24 districts, 12 in Federally Administered Tribal Areas (FATA), 9 in KPK, 2 in Punjab and 1 in Balochistan); those of P. falciparum malaria were unchanged in 2012 and 2013 (total 18 districts, all in Balochistan), and mixed infections remained the same in 2014 and 2015 (total 7 districts, 6 in Balochistan and 1 in FATA). This study indicated that the transmission cycles of malaria infection vary in different spatiotemporal settings in Pakistan. Efforts in controlling P. vivax malaria in particular need to be enhanced in high-risk areas. Based on these findings, further research is needed to investigate the impact of risk factors on transmission of malaria in Pakistan. MDPI 2018-06-07 2018-06 /pmc/articles/PMC6025434/ /pubmed/29880778 http://dx.doi.org/10.3390/ijerph15061202 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Umer, Muhammad Farooq
Zofeen, Shumaila
Majeed, Abdul
Hu, Wenbiao
Qi, Xin
Zhuang, Guihua
Spatiotemporal Clustering Analysis of Malaria Infection in Pakistan
title Spatiotemporal Clustering Analysis of Malaria Infection in Pakistan
title_full Spatiotemporal Clustering Analysis of Malaria Infection in Pakistan
title_fullStr Spatiotemporal Clustering Analysis of Malaria Infection in Pakistan
title_full_unstemmed Spatiotemporal Clustering Analysis of Malaria Infection in Pakistan
title_short Spatiotemporal Clustering Analysis of Malaria Infection in Pakistan
title_sort spatiotemporal clustering analysis of malaria infection in pakistan
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6025434/
https://www.ncbi.nlm.nih.gov/pubmed/29880778
http://dx.doi.org/10.3390/ijerph15061202
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