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Can slide positivity rates predict malaria transmission?

BACKGROUND: Malaria is a significant threat to population health in the border areas of Yunnan Province, China. How to accurately measure malaria transmission is an important issue. This study aimed to examine the role of slide positivity rates (SPR) in malaria transmission in Mengla County, Yunnan...

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Detalles Bibliográficos
Autores principales: Bi, Yan, Hu, Wenbiao, Liu, Huaxin, Xiao, Yujiang, Guo, Yuming, Chen, Shimei, Zhao, Laifa, Tong, Shilu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3416572/
https://www.ncbi.nlm.nih.gov/pubmed/22513123
http://dx.doi.org/10.1186/1475-2875-11-117
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author Bi, Yan
Hu, Wenbiao
Liu, Huaxin
Xiao, Yujiang
Guo, Yuming
Chen, Shimei
Zhao, Laifa
Tong, Shilu
author_facet Bi, Yan
Hu, Wenbiao
Liu, Huaxin
Xiao, Yujiang
Guo, Yuming
Chen, Shimei
Zhao, Laifa
Tong, Shilu
author_sort Bi, Yan
collection PubMed
description BACKGROUND: Malaria is a significant threat to population health in the border areas of Yunnan Province, China. How to accurately measure malaria transmission is an important issue. This study aimed to examine the role of slide positivity rates (SPR) in malaria transmission in Mengla County, Yunnan Province, China. METHODS: Data on annual malaria cases, SPR and socio-economic factors for the period of 1993 to 2008 were obtained from the Center for Disease Control and Prevention (CDC) and the Bureau of Statistics, Mengla, China. Multiple linear regression models were conducted to evaluate the relationship between socio-ecologic factors and malaria incidence. RESULTS: The results show that SPR was significantly positively associated with the malaria incidence rates. The SPR (β = 1.244, p = 0.000) alone and combination (SPR, β = 1.326, p < 0.001) with other predictors can explain about 85% and 95% of variation in malaria transmission, respectively. Every 1% increase in SPR corresponded to an increase of 1.76/100,000 in malaria incidence rates. CONCLUSION: SPR is a strong predictor of malaria transmission, and can be used to improve the planning and implementation of malaria elimination programmes in Mengla and other similar locations. SPR might also be a useful indicator of malaria early warning systems in China.
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spelling pubmed-34165722012-08-13 Can slide positivity rates predict malaria transmission? Bi, Yan Hu, Wenbiao Liu, Huaxin Xiao, Yujiang Guo, Yuming Chen, Shimei Zhao, Laifa Tong, Shilu Malar J Research BACKGROUND: Malaria is a significant threat to population health in the border areas of Yunnan Province, China. How to accurately measure malaria transmission is an important issue. This study aimed to examine the role of slide positivity rates (SPR) in malaria transmission in Mengla County, Yunnan Province, China. METHODS: Data on annual malaria cases, SPR and socio-economic factors for the period of 1993 to 2008 were obtained from the Center for Disease Control and Prevention (CDC) and the Bureau of Statistics, Mengla, China. Multiple linear regression models were conducted to evaluate the relationship between socio-ecologic factors and malaria incidence. RESULTS: The results show that SPR was significantly positively associated with the malaria incidence rates. The SPR (β = 1.244, p = 0.000) alone and combination (SPR, β = 1.326, p < 0.001) with other predictors can explain about 85% and 95% of variation in malaria transmission, respectively. Every 1% increase in SPR corresponded to an increase of 1.76/100,000 in malaria incidence rates. CONCLUSION: SPR is a strong predictor of malaria transmission, and can be used to improve the planning and implementation of malaria elimination programmes in Mengla and other similar locations. SPR might also be a useful indicator of malaria early warning systems in China. BioMed Central 2012-04-18 /pmc/articles/PMC3416572/ /pubmed/22513123 http://dx.doi.org/10.1186/1475-2875-11-117 Text en Copyright ©2012 Bi et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Bi, Yan
Hu, Wenbiao
Liu, Huaxin
Xiao, Yujiang
Guo, Yuming
Chen, Shimei
Zhao, Laifa
Tong, Shilu
Can slide positivity rates predict malaria transmission?
title Can slide positivity rates predict malaria transmission?
title_full Can slide positivity rates predict malaria transmission?
title_fullStr Can slide positivity rates predict malaria transmission?
title_full_unstemmed Can slide positivity rates predict malaria transmission?
title_short Can slide positivity rates predict malaria transmission?
title_sort can slide positivity rates predict malaria transmission?
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3416572/
https://www.ncbi.nlm.nih.gov/pubmed/22513123
http://dx.doi.org/10.1186/1475-2875-11-117
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