首页|Geographically and Temporally Weighted Regression in Assessing Dengue Fever Spread Factors in Yunnan Border Regions
Geographically and Temporally Weighted Regression in Assessing Dengue Fever Spread Factors in Yunnan Border Regions
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Objective This study employs the Geographically and Temporally Weighted Regression(GTWR)model to assess the impact of meteorological elements and imported cases on dengue fever outbreaks,emphasizing the spatial-temporal variability of these factors in border regions.Methods We conducted a descriptive analysis of dengue fever's temporal-spatial distribution in Yunnan border areas.Utilizing annual data from 2013 to 2019,with each county in the Yunnan border serving as a spatial unit,we constructed a GTWR model to investigate the determinants of dengue fever and their spatio-temporal heterogeneity in this region.Results The GTWR model,proving more effective than Ordinary Least Squares(OLS)analysis,identified significant spatial and temporal heterogeneity in factors influencing dengue fever's spread along the Yunnan border.Notably,the GTWR model revealed a substantial variation in the relationship between indigenous dengue fever incidence,meteorological variables,and imported cases across different counties.Conclusion In the Yunnan border areas,local dengue incidence is affected by temperature,humidity,precipitation,wind speed,and imported cases,with these factors'influence exhibiting notable spatial and temporal variation.
Dengue feverMeteorological factorGeographically and temporally weighted regression
ZHU Xiao Xiang、WANG Song Wang、LI Yan Fei、ZHANG Ye Wu、SU Xue Mei、ZHAO Xiao Tao
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National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases,Chinese Center for Disease Control and Prevention,Beijing 102211,China
Yunnan Institute of Parasitic Diseases,Pu'er 665000,Yunnan,China
National Science and Technology Infrastructure Platform National Population and Health Science Data Sharing Service Platform Pub
NETL
NSTL
万方数据
