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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 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 changes of the characteristics of Hemorrhagic fever with renal syndrome (HFRS) in Jingzhou City in different periods. Methods According to the HFRS epidemic data of Jingzhou City in 2009 - 2018, based on the incidence rate, the HFRS epidemic situation in Jingzhou City was divided into three periods: 2009 - 2012 (low), 2013 - 2016 (middle), and 2017 - 2018 (high). Descriptive epidemiological methods, standard deviation ellipse and spatio-temporal scanning analysis were used to analyze the time, region, population distribution and temporal and spatial trends of HFRS epidemic in the three periods. Results The incidence of HFRS in Jingzhou City in the three periods was seasonal and bimodal. The peak incidence included spring and summer peaks (May - July) and autumn-winter peaks (January, November - December). The HFRS cases in Jingzhou City were concentrated in Jianli County, Jiangling County and Honghu City in the three periods. The incidence rates were 0.48/100000, 1.98/100000, 0.84/100000, 0.89/100000, 1.88/100000, 1.20/100000; 4.82/100000, 13.37/100000, and 4.58/100000. The incidence of HFRS in males was higher than that in females in the three periods (χ2 = 43.38, P < 0.05); the occupations of HFRS in the three periods were mainly farmers, which were 56.26％(69/122), 69.61％ (126/181), 74.94％ (293/391), respectively. In 116 farmers, growing rice [48.28％ (56/116)] and shrimp rice [27.59％ (32/116)] were mostly. From the age point of view, the incidence rate in 2009 - 2017 was 55 to 64 years old; the incidence rate of 2018 was 60 to 69 years old. The results of standard deviation ellipse analysis showed that the expansion trend of HFRS epidemic areas in Jingzhou City was not obvious, and the center of gravity was located in Jianli County or Jiangling County. Spatio-temporal scans revealed that the first-class spatial-temporal clustering areas in the three periods were 2 towns and villages in Jiangling County, and the gathering time was from December 7, 2010 to January 2, 2011; in some townships in Jiangling County and Shacheng District, the gathering time was from December 7, 2016 to February 28, 2017; some townships in Jiangling County and surrounding counties, gathered from April 27, 2018 to July 16, 2018. Conclusions The HFRS epidemic season in Jingzhou City in different periods is basically the same; the high -incidence areas are basically the same, but there are local fluctuations; the population is mainly male farmers, and the age of high-incidence has shifted back. We should adapt to local conditions and formulate scientific and reasonable comprehensive prevention and control measures.
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Objective The aim is to analyze the spatial epidemiological characteristics for human infection with avian influenza H7N9 in Fujian Province, so as to provide scientific evidence for developing and adjusting related control strategies. Methods The epidemiological data of human infection with H7N9 avian influenza in Fujian Province, from 2013 to 2017 was analyzed by SAS 9.2, ArcGIS 10.3 and SaTScan 9.4 software.Results There were a total of 108 cases and 28 deaths reported in Fujian Province, up to December 31, 2017. The case fatality rate was 25.93%.96.30% of cases were sporadic. There were more incidences in winters and springs, more incidences in rural areas. The global spatial autocorrelation and high/low clustering analysis indicated that clusters at the county level were in the shore areas (Z=3.74, P<0.001; Z=5.26, P<0.001). The cities of Changle, Fuqing, Jinjiang and Siming were the high-high clustered areas and local hot-points. There were two clusters, from December 2014 to March 2015, the most likely cluster regions was centered around Zhangpu County with a radius of 63.04 km (RR=4.72, LLR=11.41, P<0.001). The secondary cluster regions was centered around Fuqing City with a radius of 81.98 km (RR=4.07, LLR=7.96, P=0.037). Conclusions Human infection with avian influenza H7N9 in Fujian Province is spatially and temporally clustered. The measures of prevention and control should be focused on high incidence seasons and key regions, and the surveillance of etiology should be strengthened.
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Objective@#To analyze the changes of the characteristics of Hemorrhagic fever with renal syndrome (HFRS) in Jingzhou City in different periods.@*Methods@#According to the HFRS epidemic data of Jingzhou City in 2009-2018, based on the incidence rate, the HFRS epidemic situation in Jingzhou City was divided into three periods: 2009-2012 (low), 2013-2016 (middle), and 2017-2018 (high). Descriptive epidemiological methods, standard deviation ellipse and spatio-temporal scanning analysis were used to analyze the time, region, population distribution and temporal and spatial trends of HFRS epidemic in the three periods.@*Results@#The incidence of HFRS in Jingzhou City in the three periods was seasonal and bimodal. The peak incidence included spring and summer peaks (May-July) and autumn-winter peaks (January, November-December). The HFRS cases in Jingzhou City were concentrated in Jianli County, Jiangling County and Honghu City in the three periods. The incidence rates were 0.48/100 000, 1.98/100 000, 0.84/100 000, 0.89/100 000, 1.88/100 000, 1.20/100 000; 4.82/100 000, 13.37/100 000, and 4.58/100 000. The incidence of HFRS in males was higher than that in females in the three periods (χ2=43.38, P < 0.05); the occupations of HFRS in the three periods were mainly farmers, which were 56.26%(69/122), 69.61% (126/181), 74.94% (293/391), respectively. In 116 farmers, growing rice [48.28% (56/116)] and shrimp rice [27.59% (32/116)] were mostly. From the age point of view, the incidence rate in 2009-2017 was 55 to 64 years old; the incidence rate of 2018 was 60 to 69 years old. The results of standard deviation ellipse analysis showed that the expansion trend of HFRS epidemic areas in Jingzhou City was not obvious, and the center of gravity was located in Jianli County or Jiangling County. Spatio-temporal scans revealed that the first-class spatial-temporal clustering areas in the three periods were 2 towns and villages in Jiangling County, and the gathering time was from December 7, 2010 to January 2, 2011; in some townships in Jiangling County and Shacheng District, the gathering time was from December 7, 2016 to February 28, 2017; some townships in Jiangling County and surrounding counties, gathered from April 27, 2018 to July 16, 2018.@*Conclusions@#The HFRS epidemic season in Jingzhou City in different periods is basically the same; the high-incidence areas are basically the same, but there are local fluctuations; the population is mainly male farmers, and the age of high-incidence has shifted back. We should adapt to local conditions and formulate scientific and reasonable comprehensive prevention and control measures.
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Objective To analyze the epidemiological characteristics and spatial distribution of human brucellosis in Fujian province during 2011-2016,and provide evidence for the prevention and control of the disease.Methods The surveillance data of human brucellosis in Fujian during 2011-2016 was analyzed with software R 3.3.1,ArcGIS 10.3.1,GeoDa 1.8.8 and SaTScan 9.4.3.Results During 2011-2016,a total of 319 human brucellosis cases were reported,the incidence increased year by year (F=11.838,P=0.026) with the annual incidence of 0.14/100 000.The male to female rate ratio of the incidence was 2.50 ∶ 1.Farmers and herdsmen accounted for 57.37％.The incidence was 0.40/100 000 in Zhangzhou and 0.32/100 000 in Nanping,which were higher than other areas.The number of affected counties (district) increased from 12 in 2011 to 28 in 2016,showing a significant increase (F=13.447,P=0.021).The Moran' s I of brucellosis in Fujian between January 2011 and December 2016 was 0.045,indicating the presence of a high value or low value clustering areas.Local spatial autocorrelation analysis showed that,high-high clustering area (hot spots) were distributed in Zhangpu,Longhai,Longwen,etc,while high-low clustering areas were distributed in Nan' an and Jiaocheng,etc.Temporal scanning showed that there were three clustering areas in areas with high incidence,the most possible clustering,occurring during January 1,2013-December 31,2015,covered 6 counties,including Yunxiao,Pinghe,Longhai,etc,and Zhangpu was the center,(RR =7.96,LLR=92.62,P＜0.001).Conclusions The epidemic of human brucellosis in Fujian is becoming serious,and has spread to general population and non-epidemic areas.It is necessary to strengthen the prevention and control of human brucellosis in areas at high risk.
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Objective To analyze the epidemiological characteristics and spatial distribution of human brucellosis in Fujian province during 2011-2016,and provide evidence for the prevention and control of the disease.Methods The surveillance data of human brucellosis in Fujian during 2011-2016 was analyzed with software R 3.3.1,ArcGIS 10.3.1,GeoDa 1.8.8 and SaTScan 9.4.3.Results During 2011-2016,a total of 319 human brucellosis cases were reported,the incidence increased year by year (F=11.838,P=0.026) with the annual incidence of 0.14/100 000.The male to female rate ratio of the incidence was 2.50 ∶ 1.Farmers and herdsmen accounted for 57.37％.The incidence was 0.40/100 000 in Zhangzhou and 0.32/100 000 in Nanping,which were higher than other areas.The number of affected counties (district) increased from 12 in 2011 to 28 in 2016,showing a significant increase (F=13.447,P=0.021).The Moran' s I of brucellosis in Fujian between January 2011 and December 2016 was 0.045,indicating the presence of a high value or low value clustering areas.Local spatial autocorrelation analysis showed that,high-high clustering area (hot spots) were distributed in Zhangpu,Longhai,Longwen,etc,while high-low clustering areas were distributed in Nan' an and Jiaocheng,etc.Temporal scanning showed that there were three clustering areas in areas with high incidence,the most possible clustering,occurring during January 1,2013-December 31,2015,covered 6 counties,including Yunxiao,Pinghe,Longhai,etc,and Zhangpu was the center,(RR =7.96,LLR=92.62,P＜0.001).Conclusions The epidemic of human brucellosis in Fujian is becoming serious,and has spread to general population and non-epidemic areas.It is necessary to strengthen the prevention and control of human brucellosis in areas at high risk.