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Risk mapping of clonorchiasis in the People’s Republic of China: A systematic review and Bayesian geostatistical analysis
BACKGROUND: Clonorchiasis, one of the most important food-borne trematodiases, affects more than 12 million people in the People’s Republic of China (P.R. China). Spatially explicit risk estimates of Clonorchis sinensis infection are needed in order to target control interventions. METHODOLOGY: Geor...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5416880/ https://www.ncbi.nlm.nih.gov/pubmed/28253272 http://dx.doi.org/10.1371/journal.pntd.0005239 |
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author | Lai, Ying-Si Zhou, Xiao-Nong Pan, Zhi-Heng Utzinger, Jürg Vounatsou, Penelope |
author_facet | Lai, Ying-Si Zhou, Xiao-Nong Pan, Zhi-Heng Utzinger, Jürg Vounatsou, Penelope |
author_sort | Lai, Ying-Si |
collection | PubMed |
description | BACKGROUND: Clonorchiasis, one of the most important food-borne trematodiases, affects more than 12 million people in the People’s Republic of China (P.R. China). Spatially explicit risk estimates of Clonorchis sinensis infection are needed in order to target control interventions. METHODOLOGY: Georeferenced survey data pertaining to infection prevalence of C. sinensis in P.R. China from 2000 onwards were obtained via a systematic review in PubMed, ISI Web of Science, Chinese National Knowledge Internet, and Wanfang Data from January 1, 2000 until January 10, 2016, with no restriction of language or study design. Additional disease data were provided by the National Institute of Parasitic Diseases, Chinese Center for Diseases Control and Prevention in Shanghai. Environmental and socioeconomic proxies were extracted from remote-sensing and other data sources. Bayesian variable selection was carried out to identify the most important predictors of C. sinensis risk. Geostatistical models were applied to quantify the association between infection risk and the predictors of the disease, and to predict the risk of infection across P.R. China at high spatial resolution (over a grid with grid cell size of 5×5 km). PRINCIPAL FINDINGS: We obtained clonorchiasis survey data at 633 unique locations in P.R. China. We observed that the risk of C. sinensis infection increased over time, particularly from 2005 onwards. We estimate that around 14.8 million (95% Bayesian credible interval 13.8–15.8 million) people in P.R. China were infected with C. sinensis in 2010. Highly endemic areas (≥ 20%) were concentrated in southern and northeastern parts of the country. The provinces with the highest risk of infection and the largest number of infected people were Guangdong, Guangxi, and Heilongjiang. CONCLUSIONS/SIGNIFICANCE: Our results provide spatially relevant information for guiding clonorchiasis control interventions in P.R. China. The trend toward higher risk of C. sinensis infection in the recent past urges the Chinese government to pay more attention to the public health importance of clonorchiasis and to target interventions to high-risk areas. |
format | Online Article Text |
id | pubmed-5416880 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-54168802017-05-14 Risk mapping of clonorchiasis in the People’s Republic of China: A systematic review and Bayesian geostatistical analysis Lai, Ying-Si Zhou, Xiao-Nong Pan, Zhi-Heng Utzinger, Jürg Vounatsou, Penelope PLoS Negl Trop Dis Research Article BACKGROUND: Clonorchiasis, one of the most important food-borne trematodiases, affects more than 12 million people in the People’s Republic of China (P.R. China). Spatially explicit risk estimates of Clonorchis sinensis infection are needed in order to target control interventions. METHODOLOGY: Georeferenced survey data pertaining to infection prevalence of C. sinensis in P.R. China from 2000 onwards were obtained via a systematic review in PubMed, ISI Web of Science, Chinese National Knowledge Internet, and Wanfang Data from January 1, 2000 until January 10, 2016, with no restriction of language or study design. Additional disease data were provided by the National Institute of Parasitic Diseases, Chinese Center for Diseases Control and Prevention in Shanghai. Environmental and socioeconomic proxies were extracted from remote-sensing and other data sources. Bayesian variable selection was carried out to identify the most important predictors of C. sinensis risk. Geostatistical models were applied to quantify the association between infection risk and the predictors of the disease, and to predict the risk of infection across P.R. China at high spatial resolution (over a grid with grid cell size of 5×5 km). PRINCIPAL FINDINGS: We obtained clonorchiasis survey data at 633 unique locations in P.R. China. We observed that the risk of C. sinensis infection increased over time, particularly from 2005 onwards. We estimate that around 14.8 million (95% Bayesian credible interval 13.8–15.8 million) people in P.R. China were infected with C. sinensis in 2010. Highly endemic areas (≥ 20%) were concentrated in southern and northeastern parts of the country. The provinces with the highest risk of infection and the largest number of infected people were Guangdong, Guangxi, and Heilongjiang. CONCLUSIONS/SIGNIFICANCE: Our results provide spatially relevant information for guiding clonorchiasis control interventions in P.R. China. The trend toward higher risk of C. sinensis infection in the recent past urges the Chinese government to pay more attention to the public health importance of clonorchiasis and to target interventions to high-risk areas. Public Library of Science 2017-03-02 /pmc/articles/PMC5416880/ /pubmed/28253272 http://dx.doi.org/10.1371/journal.pntd.0005239 Text en © 2017 Lai et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Lai, Ying-Si Zhou, Xiao-Nong Pan, Zhi-Heng Utzinger, Jürg Vounatsou, Penelope Risk mapping of clonorchiasis in the People’s Republic of China: A systematic review and Bayesian geostatistical analysis |
title | Risk mapping of clonorchiasis in the People’s Republic of China: A systematic review and Bayesian geostatistical analysis |
title_full | Risk mapping of clonorchiasis in the People’s Republic of China: A systematic review and Bayesian geostatistical analysis |
title_fullStr | Risk mapping of clonorchiasis in the People’s Republic of China: A systematic review and Bayesian geostatistical analysis |
title_full_unstemmed | Risk mapping of clonorchiasis in the People’s Republic of China: A systematic review and Bayesian geostatistical analysis |
title_short | Risk mapping of clonorchiasis in the People’s Republic of China: A systematic review and Bayesian geostatistical analysis |
title_sort | risk mapping of clonorchiasis in the people’s republic of china: a systematic review and bayesian geostatistical analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5416880/ https://www.ncbi.nlm.nih.gov/pubmed/28253272 http://dx.doi.org/10.1371/journal.pntd.0005239 |
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