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Objective • To explore the spatial distribution and spatial-temporal clustering of coronavirus disease 2019(COVID-19) in Jingzhou City. Methods • Data of COVID-19 cases in Jingzhou City from January 1 to March 12, 2020 were collected. Trend surface analysis, spatial autocorrelation and spatial-temporal scanning analysis were conducted to understand the spatial-temporal distribution of COVID-19 at town (street) level in Jingzhou City, and the spatial-temporal clustering characteristics of local cases and imported cases were compared. Results • Trend surface analysis showed that the incidence rate of COVID-19 in Jingzhou City was slightly "U" from west to east, slightly higher in the east, and inverted "U" from south to north, slightly higher in the south. Global autocorrelation showed that the incidence rate of COVID-19 in Jingzhou City was positively correlated (Moran's I=0.410, P=0.000). Local spatial autocorrelation analysis showed that the highly clustered areas and hot spot areas were mainly in Shashi District, Jingzhou District and the main urban area of Honghu City (Xindi Street) (P<0.05). Five clusters were found by spatial-temporal scanning of imported cases. The cluster time of the main cluster was from January 18 to February 3, 2020, and it was centered on Lianhe Street, covering 15 towns (streets) in Shashi District and Jingzhou District (LLR=174.944, RR=7.395, P=0.000). Five clusters were found by spatial-temporal scanning of local cases. The cluster time of the main cluster was from January 20 to February 24, 2020, which was located in Xindi Street, Honghu City (LLR=224.434, RR=16.133, P=0.000). Conclusion • Obvious spatialtemporal clustering of COVID-19 was found in Jingzhou City, and Shashi District, Jingzhou District and Honghu City were the most prevalent areas.
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Objective@#To analyze the spatial distribution and both hot and cold spots of incidence on Brucellosis in Gansu province from 2013 to 2018.@*Methods@#Based on data from the Infectious Disease Reporting Information System in China, data related to space-time distribution and both hot and cold spots of Brucellosis in Gansu province from 2013 to 2018 were analyzed, by using the ArcGIS 10.5 software and GeoDa 1.6 software.@*Results@#The trend surface analysis showed that the incidence of Brucellosis decreased gradually from the northern to southern parts with slightly higher in the west than in the east of Gansu. Global spatial autocorrelation analysis showed that the Moran’s I of Brucellosis in Gansu province from 2013 to 2018 were 0.242, 0.487, 0.424, 0.460, 0.427 and 0.468 (P<0.01), suggesting that the incidence of Brucellosis had spatial clustering features in Gansu province. Local global spatial autocorrelation analysis showed that the number of hot spots were declining in the eastern and north-central regions while the hot spots were increasing in the Hexi area (Wuwei, Zhangye, Jinchang and Jiuquan cities). The cold spots areas were mainly seen in the eastern, southeastern and south of central regions in Gansu province.@*Conclusions@#The incidence of Brucellosis showed obviously spatial clustering characteristics in Gansu province. The number of hot spots were decreasing in the eastern and north of central regions while the hot spots were increasing in the Hexi area, suggesting that the prevention and control measures for Brucellosis should be further strengthened in these areas.
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Objective To investigate the spatial correlation and spatial cluster pattern of hemorrhagic fever with renal syndrome (HFRS) in Jingzhou City,Hubei Province from 2013 to 2017.Methods The HFRS surveillance data during 2013-2017 were collected from China Disease Prevention and Control Information System.Software ArcGIS 10.3 was used to analyze the spatial distribution,and global autocorrelation analysis (Moran'sI) and hot spot analysis (Getis-Ord Gi) were used to analyze the spatial autocorrelation.Spatial cluster pattern was explored by trend surface analysis and directional distribution.Results In 2013-2017,the global Moran's I was 0.117 6 (P ＞ 0.05),0.349 8 (P ＜ 0.05),0.102 1 (P ＞ 0.05),0.276 3 (P ＜ 0.05),and 0.394 8 (P ＜ 0.05),respectively.The Getis-Ord Gi analysis showed that there were 7,8,8,8,15 hot areas with high incidence of HFRS during this period,respectively,which were part of townships in Jiangling County,Shashi District,Jianli County,and Honghu City.The cold spot area with low incidence of HFRS was only detected in 2015,and it was part of the township in Shashi District and Jingzhou District.The trend surface analysis showed that the inverted-U type curve could reflect the HFRS distribution from northern to southern,and it was also from eastern to western.The directional distribution showed that the HFRS cases were distributed in the north-central part of Jingzhou in 2013-2017,and they were inconsistent with the distribution of the Yangtze River system.Conclusions The incidence of HFRS has an obvious spatial clustering characteristic,and the areas at high risk are mainly in the north-central part of Jingzhou City.The spatial cluster pattern of HFRS has nothing to do with the Yangtze River system.
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Objective To study the geographical distribution of the HIV/AIDS epidemic in C city .Methods Based on the theory of multiple regression analysis ,trend surface regression mathematical model was constructed .The latitude and longitude coordinates of different districts and data of HIV/AIDS were collected in the model and the results by ArcGIS software were got ,the trend sur-face analysis chart was drawed at last .Results HIV/AIDS infection rates trend surface regression mathematical model of C city was statistically significant difference(P< 0 .05) ,its goodness-of-fit was 53 .18% .Regions exsisted abnormal residual value and should be the paid attention to explore protective or risk factors in these regions .Conclusion The method can be used in the analy-sis of C city HIV/AIDS epidemic systematic variation in the geographic distribution and local district ,and provide some clues for the local epidemic prevention and controlling of HIV/AIDS .
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Objective To investigate the spatial distribution and growing trend of 438 human infection with the H7N9 avian influenza virus in mainland China,and to provide evidence for developing scientific prevention and control strategies.Methods 438 human infection with the avian influenza A (H7N9) cases from February 2013 to May 2014 in mainland China were studied and data collected to establish a database for the development of geographic information system.Trend surface analysis and spatial autocorrelation analysis were used to study the spatial distribution.Descriptive epidemiological method was utilized to analyze the demographic characteristic.Results From June 2013 to May 2014,cases had an overall national increase,but significantly decreasing in Shanghai.A trend surface was established for human infection with avian influenza A (H7N9) in the mainland of China,showing that the incidence was increasing obviously from north to south and the line slope declined from west to east.Distribution pattern of the cases varied within different time series and regional levels.The overall Moran' s I coefficient of the provincial level from February to May in 2013 and the coefficient of the city level from June 2013 to May 2014 were 0.144 718 and 0.117 468,respectively,with the differences statistically significant (P＜0.05).According to the analysis of the local autocorrelation and hot spot,northern Zhejiang and southern Guangdong showed high spatial clusters of human infection with avian influenza A(H7N9) (Z＞2.58).Conclusion From February 2013 to May 2014,the spatial correlation at the provincial level decreased.However,the spatial correlation and the numbers of hot spots at the city level were both increasing.Effective measures should be taken accordingly,following the distributive characteristics.
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Objective To analyze the spatial distribution of AIDS in every city of Jiangsu province, trying to describe the geographic characteristics of AIDS and to develop a prediction model.Methods Numbers of patients in Jiangsu province were collected, to establish the database for the geographic information system, then setting up a 'risk map' of the disease. Spatial, autocorrelation.Linear spatial analyses were used to study the patients' numbers. Results (1)Results from the autocorrelation analysis showed that the distribution of AIDS was clustered at some places and was at random on the whole. The results also indicated that the distribution of AIDS in Nanjing was of negative correlation, while that in Suzhou and Wuxi were of positive correlation but in Tongshan, Wujiang, Pukou, Nanjing, Lishui, Wuxi and Suzhou showed seven locations of clusters with disease was more severe in the southern than in the northern parts of Jiangsu province. (3)Ordinary Least Squares method was finally used in the linear spatial regression and the results were: t=-1.045 103 (P=0.299 904); t=-1.443 668 (P=0.153 714) respectively. Conclusion According to the feature spatial distribution of the disease, effective measures should be taken to prevent and to keep the prevalence of AIDS under control.
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Objective:To study the distribution of the rate of infertility in Chongqing city.Methods:The geographical distribution of infertilities of different regions in Chongqing city was investigated based on the methods of the trend-surface analysis.Result:In the east part of Chongqing city the rate of infertility is lower in north,in the west part the rate is lower in south,and the rate is lowest in the northeast.Conclusion:The infertility has geographical distribution trends in Chongqing city.Research should be performed on the difference of the environment and 1iving habit.