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A study on the epidemiological characteristics and infectious forecast model of malaria at Guangzhou Airport among Chinese returnees from Africa

BACKGROUND: Cross-border malaria transmission in China is a major component of Chinese imported malaria cases. Such cases mostly are travellers returning from malaria endemic countries in Africa. By investigating malaria infectious status among Chinese worker in Africa, this study analysed the malar...

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Autores principales: Wu, Hui-ming, Fang, Zhi-qiang, Zhao, Dang, Chen, Yan-ling, Liu, Chuan-ge, Liang, Xi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5496372/
https://www.ncbi.nlm.nih.gov/pubmed/28676111
http://dx.doi.org/10.1186/s12936-017-1927-4
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author Wu, Hui-ming
Fang, Zhi-qiang
Zhao, Dang
Chen, Yan-ling
Liu, Chuan-ge
Liang, Xi
author_facet Wu, Hui-ming
Fang, Zhi-qiang
Zhao, Dang
Chen, Yan-ling
Liu, Chuan-ge
Liang, Xi
author_sort Wu, Hui-ming
collection PubMed
description BACKGROUND: Cross-border malaria transmission in China is a major component of Chinese imported malaria cases. Such cases mostly are travellers returning from malaria endemic countries in Africa. By investigating malaria infectious status among Chinese worker in Africa, this study analysed the malaria risk factors, in order to establish infectious forecast model. METHODS: Chinese returnees data from Africa were collected at Guangzhou Baiyun International Airport, Guangzhou, China between August 2015 and March 2016 and were included in the cross-sectional and retrospective survey. RESULTS: A total of 1492 respondents were included in the study with the majority consisting of junior middle school educated male. Most of them are manual and technical workers hired by companies, with average of 37.04 years of age. Overall malaria incidence rate of the population was 8.98% (134/1492), and there were no significant differences regarding age, gender, occupation, or team. Forecast model was developed on the basis of malaria risk factors including working country, local ecological environment type, work duration and intensity of mosquito bite prevention. CONCLUSIONS: The survey suggested that malaria incidence was high among Chinese travellers who had worked in Africa countries of heavy malaria burden. Further research on the frequency and severity of clinical episodes among Chinese travellers having worked in Africa is needed.
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spelling pubmed-54963722017-07-05 A study on the epidemiological characteristics and infectious forecast model of malaria at Guangzhou Airport among Chinese returnees from Africa Wu, Hui-ming Fang, Zhi-qiang Zhao, Dang Chen, Yan-ling Liu, Chuan-ge Liang, Xi Malar J Research BACKGROUND: Cross-border malaria transmission in China is a major component of Chinese imported malaria cases. Such cases mostly are travellers returning from malaria endemic countries in Africa. By investigating malaria infectious status among Chinese worker in Africa, this study analysed the malaria risk factors, in order to establish infectious forecast model. METHODS: Chinese returnees data from Africa were collected at Guangzhou Baiyun International Airport, Guangzhou, China between August 2015 and March 2016 and were included in the cross-sectional and retrospective survey. RESULTS: A total of 1492 respondents were included in the study with the majority consisting of junior middle school educated male. Most of them are manual and technical workers hired by companies, with average of 37.04 years of age. Overall malaria incidence rate of the population was 8.98% (134/1492), and there were no significant differences regarding age, gender, occupation, or team. Forecast model was developed on the basis of malaria risk factors including working country, local ecological environment type, work duration and intensity of mosquito bite prevention. CONCLUSIONS: The survey suggested that malaria incidence was high among Chinese travellers who had worked in Africa countries of heavy malaria burden. Further research on the frequency and severity of clinical episodes among Chinese travellers having worked in Africa is needed. BioMed Central 2017-07-04 /pmc/articles/PMC5496372/ /pubmed/28676111 http://dx.doi.org/10.1186/s12936-017-1927-4 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Wu, Hui-ming
Fang, Zhi-qiang
Zhao, Dang
Chen, Yan-ling
Liu, Chuan-ge
Liang, Xi
A study on the epidemiological characteristics and infectious forecast model of malaria at Guangzhou Airport among Chinese returnees from Africa
title A study on the epidemiological characteristics and infectious forecast model of malaria at Guangzhou Airport among Chinese returnees from Africa
title_full A study on the epidemiological characteristics and infectious forecast model of malaria at Guangzhou Airport among Chinese returnees from Africa
title_fullStr A study on the epidemiological characteristics and infectious forecast model of malaria at Guangzhou Airport among Chinese returnees from Africa
title_full_unstemmed A study on the epidemiological characteristics and infectious forecast model of malaria at Guangzhou Airport among Chinese returnees from Africa
title_short A study on the epidemiological characteristics and infectious forecast model of malaria at Guangzhou Airport among Chinese returnees from Africa
title_sort study on the epidemiological characteristics and infectious forecast model of malaria at guangzhou airport among chinese returnees from africa
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5496372/
https://www.ncbi.nlm.nih.gov/pubmed/28676111
http://dx.doi.org/10.1186/s12936-017-1927-4
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