Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Ge, Liang, Zhao, Youlin, Sheng, Zhongjie, Wang, Ning, Zhou, Kui, Mu, Xiangming, Guo, Liqiang, Wang, Teng, Yang, Zhanqiu, Huo, Xixiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2016
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
_version_ 1782470560702267392
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
work_keys_str_mv AT geliang constructionofaseasonaldifferencegeographicallyandtemporallyweightedregressionsdgtwrmodelandcomparativeanalysiswithgwrbasedmodelsforhemorrhagicfeverwithrenalsyndromehfrsinhubeiprovincechina
AT zhaoyoulin constructionofaseasonaldifferencegeographicallyandtemporallyweightedregressionsdgtwrmodelandcomparativeanalysiswithgwrbasedmodelsforhemorrhagicfeverwithrenalsyndromehfrsinhubeiprovincechina
AT shengzhongjie constructionofaseasonaldifferencegeographicallyandtemporallyweightedregressionsdgtwrmodelandcomparativeanalysiswithgwrbasedmodelsforhemorrhagicfeverwithrenalsyndromehfrsinhubeiprovincechina
AT wangning constructionofaseasonaldifferencegeographicallyandtemporallyweightedregressionsdgtwrmodelandcomparativeanalysiswithgwrbasedmodelsforhemorrhagicfeverwithrenalsyndromehfrsinhubeiprovincechina
AT zhoukui constructionofaseasonaldifferencegeographicallyandtemporallyweightedregressionsdgtwrmodelandcomparativeanalysiswithgwrbasedmodelsforhemorrhagicfeverwithrenalsyndromehfrsinhubeiprovincechina
AT muxiangming constructionofaseasonaldifferencegeographicallyandtemporallyweightedregressionsdgtwrmodelandcomparativeanalysiswithgwrbasedmodelsforhemorrhagicfeverwithrenalsyndromehfrsinhubeiprovincechina
AT guoliqiang constructionofaseasonaldifferencegeographicallyandtemporallyweightedregressionsdgtwrmodelandcomparativeanalysiswithgwrbasedmodelsforhemorrhagicfeverwithrenalsyndromehfrsinhubeiprovincechina
AT wangteng constructionofaseasonaldifferencegeographicallyandtemporallyweightedregressionsdgtwrmodelandcomparativeanalysiswithgwrbasedmodelsforhemorrhagicfeverwithrenalsyndromehfrsinhubeiprovincechina
AT yangzhanqiu constructionofaseasonaldifferencegeographicallyandtemporallyweightedregressionsdgtwrmodelandcomparativeanalysiswithgwrbasedmodelsforhemorrhagicfeverwithrenalsyndromehfrsinhubeiprovincechina
AT huoxixiang constructionofaseasonaldifferencegeographicallyandtemporallyweightedregressionsdgtwrmodelandcomparativeanalysiswithgwrbasedmodelsforhemorrhagicfeverwithrenalsyndromehfrsinhubeiprovincechina