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Using ecological niche modeling to predict the potential distribution of scrub typhus in Fujian Province, China
BACKGROUND: Despite the increasing number of cases of scrub typhus and its expanding geographical distribution in China, its potential distribution in Fujian Province, which is endemic for the disease, has yet to be investigated. METHODS: A negative binomial regression model for panel data mainly co...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9887782/ https://www.ncbi.nlm.nih.gov/pubmed/36721181 http://dx.doi.org/10.1186/s13071-023-05668-6 |
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author | Li, Xuan Wei, Xianyu Yin, Wenwu Soares Magalhaes, Ricardo J. Xu, Yuanyong Wen, Liang Peng, Hong Qian, Quan Sun, Hailong Zhang, Wenyi |
author_facet | Li, Xuan Wei, Xianyu Yin, Wenwu Soares Magalhaes, Ricardo J. Xu, Yuanyong Wen, Liang Peng, Hong Qian, Quan Sun, Hailong Zhang, Wenyi |
author_sort | Li, Xuan |
collection | PubMed |
description | BACKGROUND: Despite the increasing number of cases of scrub typhus and its expanding geographical distribution in China, its potential distribution in Fujian Province, which is endemic for the disease, has yet to be investigated. METHODS: A negative binomial regression model for panel data mainly comprising meteorological, socioeconomic and land cover variables was used to determine the risk factors for the occurrence of scrub typhus. Maximum entropy modeling was used to identify the key predictive variables of scrub typhus and their ranges, map the suitability of different environments for the disease, and estimate the proportion of the population at different levels of infection risk. RESULTS: The final multivariate negative binomial regression model for panel data showed that the annual mean normalized difference vegetation index had the strongest correlation with the number of scrub typhus cases. With each 0.1% rise in shrubland and 1% rise in barren land there was a 75.0% and 37.0% increase in monthly scrub typhus cases, respectively. In contrast, each unit rise in mean wind speed in the previous 2 months and each 1% increase in water bodies corresponded to a decrease of 40.0% and 4.0% in monthly scrub typhus cases, respectively. The predictions of the maximum entropy model were robust, and the average area under the curve value was as high as 0.864. The best predictive variables for scrub typhus occurrence were population density, annual mean normalized difference vegetation index, and land cover types. The projected potentially most suitable areas for scrub typhus were widely distributed across the eastern coastal area of Fujian Province, with highly suitable and moderately suitable areas accounting for 16.14% and 9.42%, respectively. Of the total human population of the province, 81.63% reside in highly suitable areas for scrub typhus. CONCLUSIONS: These findings could help deepen our understanding of the risk factors of scrub typhus, and provide information for public health authorities in Fujian Province to develop more effective surveillance and control strategies in identified high risk areas in Fujian Province. SUPPLEMENTARY INFORMATION: The online version contains supplementary material, which is available at 10.1186/s13071-023-05668-6. |
format | Online Article Text |
id | pubmed-9887782 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-98877822023-02-01 Using ecological niche modeling to predict the potential distribution of scrub typhus in Fujian Province, China Li, Xuan Wei, Xianyu Yin, Wenwu Soares Magalhaes, Ricardo J. Xu, Yuanyong Wen, Liang Peng, Hong Qian, Quan Sun, Hailong Zhang, Wenyi Parasit Vectors Research BACKGROUND: Despite the increasing number of cases of scrub typhus and its expanding geographical distribution in China, its potential distribution in Fujian Province, which is endemic for the disease, has yet to be investigated. METHODS: A negative binomial regression model for panel data mainly comprising meteorological, socioeconomic and land cover variables was used to determine the risk factors for the occurrence of scrub typhus. Maximum entropy modeling was used to identify the key predictive variables of scrub typhus and their ranges, map the suitability of different environments for the disease, and estimate the proportion of the population at different levels of infection risk. RESULTS: The final multivariate negative binomial regression model for panel data showed that the annual mean normalized difference vegetation index had the strongest correlation with the number of scrub typhus cases. With each 0.1% rise in shrubland and 1% rise in barren land there was a 75.0% and 37.0% increase in monthly scrub typhus cases, respectively. In contrast, each unit rise in mean wind speed in the previous 2 months and each 1% increase in water bodies corresponded to a decrease of 40.0% and 4.0% in monthly scrub typhus cases, respectively. The predictions of the maximum entropy model were robust, and the average area under the curve value was as high as 0.864. The best predictive variables for scrub typhus occurrence were population density, annual mean normalized difference vegetation index, and land cover types. The projected potentially most suitable areas for scrub typhus were widely distributed across the eastern coastal area of Fujian Province, with highly suitable and moderately suitable areas accounting for 16.14% and 9.42%, respectively. Of the total human population of the province, 81.63% reside in highly suitable areas for scrub typhus. CONCLUSIONS: These findings could help deepen our understanding of the risk factors of scrub typhus, and provide information for public health authorities in Fujian Province to develop more effective surveillance and control strategies in identified high risk areas in Fujian Province. SUPPLEMENTARY INFORMATION: The online version contains supplementary material, which is available at 10.1186/s13071-023-05668-6. BioMed Central 2023-01-31 /pmc/articles/PMC9887782/ /pubmed/36721181 http://dx.doi.org/10.1186/s13071-023-05668-6 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Li, Xuan Wei, Xianyu Yin, Wenwu Soares Magalhaes, Ricardo J. Xu, Yuanyong Wen, Liang Peng, Hong Qian, Quan Sun, Hailong Zhang, Wenyi Using ecological niche modeling to predict the potential distribution of scrub typhus in Fujian Province, China |
title | Using ecological niche modeling to predict the potential distribution of scrub typhus in Fujian Province, China |
title_full | Using ecological niche modeling to predict the potential distribution of scrub typhus in Fujian Province, China |
title_fullStr | Using ecological niche modeling to predict the potential distribution of scrub typhus in Fujian Province, China |
title_full_unstemmed | Using ecological niche modeling to predict the potential distribution of scrub typhus in Fujian Province, China |
title_short | Using ecological niche modeling to predict the potential distribution of scrub typhus in Fujian Province, China |
title_sort | using ecological niche modeling to predict the potential distribution of scrub typhus in fujian province, china |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9887782/ https://www.ncbi.nlm.nih.gov/pubmed/36721181 http://dx.doi.org/10.1186/s13071-023-05668-6 |
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