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Int. J. Environ. Res. Public Health 2016, 13(11), 1062; doi:10.3390/ijerph13111062

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)

1
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
2
Tianjin Institute of Surveying and Mapping, Tianjin 300381, China
3
Business School of Hohai University, Nanjing 211100, China
4
First Crust Deformation Monitoring and Application Center, China Earthquake Administration, Tianjin 300180, China
5
School of Information Studies of University of Wisconsin-Milwaukee, Milwaukee, WI 53211, USA
6
State Key Laboratory of Virology, Institute of Medical Virology, School of Medicine, Wuhan University, Wuhan 430079, China
7
Hubei Provincial Center for Disease Control and Prevention, Wuhan 430079, China
*
Author to whom correspondence should be addressed.
Academic Editor: Paul B. Tchounwou
Received: 23 August 2016 / Revised: 8 October 2016 / Accepted: 26 October 2016 / Published: 29 October 2016
View Full-Text   |   Download PDF [1491 KB, uploaded 29 October 2016]   |  

Abstract

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. View Full-Text
Keywords: HFRS; GWR-based models; GTWR; SD-GTWR; spatiotemporal pattern HFRS; GWR-based models; GTWR; SD-GTWR; spatiotemporal pattern
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MDPI and ACS Style

Ge, L.; Zhao, Y.; Sheng, Z.; Wang, N.; Zhou, K.; Mu, X.; Guo, L.; Wang, T.; Yang, Z.; Huo, X. 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). Int. J. Environ. Res. Public Health 2016, 13, 1062.

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