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Construction of a Seasonal Difference-Geographically and Temporally Weighted Regression (SD-GTWR) Model and Comparative Analysis with GWR-Based Models for Hemorrhagic Fever with Renal Syndrome (HFRS) in Hubei Province (China)
Hemorrhagic fever with renal syndrome (HFRS) is considered a globally distributed infectious disease which results in many deaths annually in Hubei Province, China. In order to conduct a better analysis and accurately predict HFRS incidence in Hubei Province, a new model named Seasonal Difference-Ge...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5129272/ https://www.ncbi.nlm.nih.gov/pubmed/27801870 http://dx.doi.org/10.3390/ijerph13111062 |
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author | Ge, Liang Zhao, Youlin Sheng, Zhongjie Wang, Ning Zhou, Kui Mu, Xiangming Guo, Liqiang Wang, Teng Yang, Zhanqiu Huo, Xixiang |
author_facet | Ge, Liang Zhao, Youlin Sheng, Zhongjie Wang, Ning Zhou, Kui Mu, Xiangming Guo, Liqiang Wang, Teng Yang, Zhanqiu Huo, Xixiang |
author_sort | Ge, Liang |
collection | PubMed |
description | Hemorrhagic fever with renal syndrome (HFRS) is considered a globally distributed infectious disease which results in many deaths annually in Hubei Province, China. In order to conduct a better analysis and accurately predict HFRS incidence in Hubei Province, a new model named Seasonal Difference-Geographically and Temporally Weighted Regression (SD-GTWR) was constructed. The SD-GTWR model, which integrates the analysis and relationship of seasonal difference, spatial and temporal characteristics of HFRS (HFRS was characterized by spatiotemporal heterogeneity and it is seasonally distributed), was designed to illustrate the latent relationships between the spatio-temporal pattern of the HFRS epidemic and its influencing factors. Experiments from the study demonstrated that SD-GTWR model is superior to traditional models such as GWR- based models in terms of the efficiency and the ability of providing influencing factor analysis. |
format | Online Article Text |
id | pubmed-5129272 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-51292722016-12-11 Construction of a Seasonal Difference-Geographically and Temporally Weighted Regression (SD-GTWR) Model and Comparative Analysis with GWR-Based Models for Hemorrhagic Fever with Renal Syndrome (HFRS) in Hubei Province (China) Ge, Liang Zhao, Youlin Sheng, Zhongjie Wang, Ning Zhou, Kui Mu, Xiangming Guo, Liqiang Wang, Teng Yang, Zhanqiu Huo, Xixiang Int J Environ Res Public Health Article Hemorrhagic fever with renal syndrome (HFRS) is considered a globally distributed infectious disease which results in many deaths annually in Hubei Province, China. In order to conduct a better analysis and accurately predict HFRS incidence in Hubei Province, a new model named Seasonal Difference-Geographically and Temporally Weighted Regression (SD-GTWR) was constructed. The SD-GTWR model, which integrates the analysis and relationship of seasonal difference, spatial and temporal characteristics of HFRS (HFRS was characterized by spatiotemporal heterogeneity and it is seasonally distributed), was designed to illustrate the latent relationships between the spatio-temporal pattern of the HFRS epidemic and its influencing factors. Experiments from the study demonstrated that SD-GTWR model is superior to traditional models such as GWR- based models in terms of the efficiency and the ability of providing influencing factor analysis. MDPI 2016-10-29 2016-11 /pmc/articles/PMC5129272/ /pubmed/27801870 http://dx.doi.org/10.3390/ijerph13111062 Text en © 2016 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 Ge, Liang Zhao, Youlin Sheng, Zhongjie Wang, Ning Zhou, Kui Mu, Xiangming Guo, Liqiang Wang, Teng Yang, Zhanqiu Huo, Xixiang Construction of a Seasonal Difference-Geographically and Temporally Weighted Regression (SD-GTWR) Model and Comparative Analysis with GWR-Based Models for Hemorrhagic Fever with Renal Syndrome (HFRS) in Hubei Province (China) |
title | Construction of a Seasonal Difference-Geographically and Temporally Weighted Regression (SD-GTWR) Model and Comparative Analysis with GWR-Based Models for Hemorrhagic Fever with Renal Syndrome (HFRS) in Hubei Province (China) |
title_full | Construction of a Seasonal Difference-Geographically and Temporally Weighted Regression (SD-GTWR) Model and Comparative Analysis with GWR-Based Models for Hemorrhagic Fever with Renal Syndrome (HFRS) in Hubei Province (China) |
title_fullStr | Construction of a Seasonal Difference-Geographically and Temporally Weighted Regression (SD-GTWR) Model and Comparative Analysis with GWR-Based Models for Hemorrhagic Fever with Renal Syndrome (HFRS) in Hubei Province (China) |
title_full_unstemmed | Construction of a Seasonal Difference-Geographically and Temporally Weighted Regression (SD-GTWR) Model and Comparative Analysis with GWR-Based Models for Hemorrhagic Fever with Renal Syndrome (HFRS) in Hubei Province (China) |
title_short | Construction of a Seasonal Difference-Geographically and Temporally Weighted Regression (SD-GTWR) Model and Comparative Analysis with GWR-Based Models for Hemorrhagic Fever with Renal Syndrome (HFRS) in Hubei Province (China) |
title_sort | construction of a seasonal difference-geographically and temporally weighted regression (sd-gtwr) model and comparative analysis with gwr-based models for hemorrhagic fever with renal syndrome (hfrs) in hubei province (china) |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5129272/ https://www.ncbi.nlm.nih.gov/pubmed/27801870 http://dx.doi.org/10.3390/ijerph13111062 |
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