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@#Abstract: Objective To explore the spatial epidemiological characteristics of severe cases hand, foot and mouth disease (HFMD) in Guangxi, China, from 2014 to 2018, and to provide a basis for identifying the high-risk regions as well as the prevention and control of severe cases of HFMD in Guangxi. Methods Spatial-temporal scanning analysis, global and local spatial autocorrelation analysis were used to analyze the spatial clustering of HFMD. The trend surface analysis was used to evaluate the spatial distribution trend of HFMD. Results From 2014 to 2018, the incidence and severe case fatality rates of HFMD were 3.89/100 000 and 4.23%, respectively. Monte Carlo scanning analysis showed that the first cluster region was Cenxi City, the second cluster was mainly concentrated in northwest of Guangxi, and the aggregation time was mainly concentrated in April to May and August to October. The global spatial autocorrelation analysis showed that the severe HFMD was significant clustering distribution, and the Moran's I coefficients of the sever cases, severe morbidity and severe case fatality rate were 0.088, 0.118, 0.197, respectively (P<0.05). Local spatial autocorrelation analysis showed that hotspots of severe HFMD cases were concentrated in the southern Guangxi, mainly in Lingshan County. Anselin local Moran's I clustering and outlier analysis indicated that 5 high-high (H-H) clustering regions for fatality were Lingshan, Pubei, Zhongshan, Zhaoping and Pinggui County. There were 6 high-high (H-H) clustering regions for severe incidence rate, namely Lingshan, Qinnan, Lingyun, Youjiang, Bama Yao Autonomous and Pinggui County, and 1 high-low (H-L) clustering region, Cenxi County. The trend surface analysis showed that the overall number of severe cases of death decreased from east or west to the middle, and increased from north to middle, and then decreased to south. Conclusions Severe HFMD cases in Guangxi have obvious spatial-temporal clustering, and the hop spots are mainly concentrated in southern Guangxi. The prevention and control of HFMD in areas with high incidence of severe cases should be strengthened to reduce the burden of HFMD cases.
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Objective To explore spatial clustering of mumps in Hubei Province during 2010-2020, and to provide evidence for mumps prevention and control. Methods The surveillance data of mumps during 2010-2020 in Hubei Province was obtained from the national infectious diseases reporting information system. Trend surface analysis and spatial autocorrelation analysis of mumps incidences at county/district levels were performed using ArcGIS10.5 software. Results Mumps incidence rates in Hubei Province during 2010-2018 ranged from 8.70 per 100 000 to 44.99 per 100 000. The trend surface analysis showed that mumps incidences gradually decreased from west to east, and was low in the middle and high at the north-south direction. Global spatial autocorrelation showed that there were positive spatial correlations in every year except 2012 and 2014 (Morans I> 0, P <0.05). Local autocorrelation analysis showed that the hotspots of mumps incidences varied every year from 2010 to 2020. Conclusions According to the spatial analysis, mumps incidences had obvious spatial clustering in Hubei Province. The hotspots were mainly concentrated in the northwestern region of Hubei, but the hot spots also extended to the urban areas of eastern, central and northern Hubei. It is necessary to take appropriate prevention and control measures in the high-incidence areas.
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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 analyze the exposure level and the geographical distribution trend of toxicological indicators of rural drinking water in Shandong Province.@*Methods@#The drawing method was used to randomly select no less than 60% villages and towns from 137 counties (cities, districts) of 17 cities in Shandong Province in 2015, and then 1-3 rural centralized water supply units were selected according to the circumstance of rural centralized water supply units in each village and town. In total, 735 villages and towns, 1 473 rural centralized water supply units were selected, and 1 473 water samples were collected. The water treatment process, water supply population and other circumstances of the rural centralized water supply units were investigated, the water quality was monitored, the content of toxicological indicators of drinking water in different areas was compared, and the trend surface isogram of excessive toxicological indicators was drawn.@*Results@#The qualified rate of toxicological indicators in 1 473 water samples was 83.64% (n=1 232). The main toxicological indicators that affected the qualified rate of toxicological indicators of drinking water in rural areas in Shandong Province were nitrate and fluoride. The excessive rate of fluoride was 5.70% (n=84) and the exposed population was 1 736 709 (4.22%). The excessive rate of nitrate (as nitrogen) was 12.29% (n=181) and the exposed population was 1 393 612 (3.39%). The P50 content of fluoride in the eastern, middle and western regions was 0.24, 0.29 and 0.59 mg/L, respective;which was higher in the western region than in the east and the middle regions (P<0.05). There was no significant difference between the eastern and the middle regions (P>0.05). The P50 content of nitrate (as nitrogen) in the eastern, middle and western regions was 8.00, 7.48, and 2.00 mg/L, which was higher in the eastern and middle regions than in the west region (P<0.05), there was no significant difference between the eastern and the middle regions (P>0.05). The trend surface isogram of nitrate and fluoride content showed that the content of nitrate (as nitrogen) in rural drinking water in the eastern region was significantly higher than that in the western region, especially there was a high peak area in the northeastern region, and this high content distribution extended diagonally to the central region, while the other regions were in a relatively low range. The content of fluoride in rural drinking water in the western region was significantly higher than that in the eastern region, and there were high peaks in the southwest and northwest regions, and the other regions were in a relatively low range.@*Conclusion@#The high exposed toxicological indicators in rural drinking water in Shandong Province were nitrate (as nitrogen) and fluoride, and their distribution showed obvious geographical distribution trend.
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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.