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Geographical Clustering and Environmental Determinants of Schistosomiasis from 2007 to 2012 in Jianghan Plain, China
This study compared changes in the spatial clustering of schistosomiasis in Jianghan Plain, China by applying Kulldorff’s spatial scan statistic. The Geodetector software was employed to detect the environmental determinants of schistosomiasis annually from 2007 to 2012. The most likely spatial clus...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6068921/ https://www.ncbi.nlm.nih.gov/pubmed/30011795 http://dx.doi.org/10.3390/ijerph15071481 |
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author | Niu, Yingnan Li, Rendong Qiu, Juan Xu, Xingjian Huang, Duan Qu, Yubing |
author_facet | Niu, Yingnan Li, Rendong Qiu, Juan Xu, Xingjian Huang, Duan Qu, Yubing |
author_sort | Niu, Yingnan |
collection | PubMed |
description | This study compared changes in the spatial clustering of schistosomiasis in Jianghan Plain, China by applying Kulldorff’s spatial scan statistic. The Geodetector software was employed to detect the environmental determinants of schistosomiasis annually from 2007 to 2012. The most likely spatial cluster in 2007 covered the north-central part of Jianghan Plain, whereas those observed from 2008 to 2012 were toward the south, with extended coverage in generally the same areas across various periods, and some variation nevertheless in precise locations. Furthermore, the 2007 period was more likely to be clustered than any other period. We found that temperature, land use, and soil type were the most critical factors associated with infection rates in humans. In addition, land use and soil type had the greatest impact on the prevalence of schistosomiasis in 2009, whereas this effect was minimal in 2007. The effect of temperature on schistosomiasis prevalence reached its maximum in 2010, whereas in 2008, this effect was minimal. Differences observed in the effects of those two factors on the spatial distribution of human schistosomiasis were inconsistent, showing statistical significance in some years and a lack thereof in others. Moreover, when two factors operated simultaneously, a trend of enhanced interaction was consistently observed. High-risk areas with strong interactions of affected factors should be targeted for disease control interventions. |
format | Online Article Text |
id | pubmed-6068921 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-60689212018-08-07 Geographical Clustering and Environmental Determinants of Schistosomiasis from 2007 to 2012 in Jianghan Plain, China Niu, Yingnan Li, Rendong Qiu, Juan Xu, Xingjian Huang, Duan Qu, Yubing Int J Environ Res Public Health Article This study compared changes in the spatial clustering of schistosomiasis in Jianghan Plain, China by applying Kulldorff’s spatial scan statistic. The Geodetector software was employed to detect the environmental determinants of schistosomiasis annually from 2007 to 2012. The most likely spatial cluster in 2007 covered the north-central part of Jianghan Plain, whereas those observed from 2008 to 2012 were toward the south, with extended coverage in generally the same areas across various periods, and some variation nevertheless in precise locations. Furthermore, the 2007 period was more likely to be clustered than any other period. We found that temperature, land use, and soil type were the most critical factors associated with infection rates in humans. In addition, land use and soil type had the greatest impact on the prevalence of schistosomiasis in 2009, whereas this effect was minimal in 2007. The effect of temperature on schistosomiasis prevalence reached its maximum in 2010, whereas in 2008, this effect was minimal. Differences observed in the effects of those two factors on the spatial distribution of human schistosomiasis were inconsistent, showing statistical significance in some years and a lack thereof in others. Moreover, when two factors operated simultaneously, a trend of enhanced interaction was consistently observed. High-risk areas with strong interactions of affected factors should be targeted for disease control interventions. MDPI 2018-07-13 2018-07 /pmc/articles/PMC6068921/ /pubmed/30011795 http://dx.doi.org/10.3390/ijerph15071481 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 Niu, Yingnan Li, Rendong Qiu, Juan Xu, Xingjian Huang, Duan Qu, Yubing Geographical Clustering and Environmental Determinants of Schistosomiasis from 2007 to 2012 in Jianghan Plain, China |
title | Geographical Clustering and Environmental Determinants of Schistosomiasis from 2007 to 2012 in Jianghan Plain, China |
title_full | Geographical Clustering and Environmental Determinants of Schistosomiasis from 2007 to 2012 in Jianghan Plain, China |
title_fullStr | Geographical Clustering and Environmental Determinants of Schistosomiasis from 2007 to 2012 in Jianghan Plain, China |
title_full_unstemmed | Geographical Clustering and Environmental Determinants of Schistosomiasis from 2007 to 2012 in Jianghan Plain, China |
title_short | Geographical Clustering and Environmental Determinants of Schistosomiasis from 2007 to 2012 in Jianghan Plain, China |
title_sort | geographical clustering and environmental determinants of schistosomiasis from 2007 to 2012 in jianghan plain, china |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6068921/ https://www.ncbi.nlm.nih.gov/pubmed/30011795 http://dx.doi.org/10.3390/ijerph15071481 |
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