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@#Abstract: Objective To analyze the epidemic characteristics of soil-transmitted helminth (STH) by the spatial epidemiological method in Jiangxi Province. Methods Surveillance data of STH in Jiangxi Province from 2016 to 2019 were collected for descriptive epidemiological analysis. The space-time permutation distribution of STH infection areas was analyzed with spatial autocorrelation, hotspot analysis methods and retrospective space-time permutation scan statistics. Results The infection rates of STH were 1.32% (947/71 766), 1.14% (803/70 547), 0.87% (604/69 507) and 0.90% (628/69 620), respectively, and the differences were statistically significant in different years (P<0.01). The rates of hookworm infection were 0.65% (466/71 766), 0.64% (450/70 547), 0.48% (336/69 507) and 0.52% (362/69 620), respectively, and the differences were statistically significant (P<0.01). The infection rates of Ascaris lumbricoides were 0.55% (393/71 766), 0.41% (287/70 547), 0.32% (221/69 507) and 0.32% (225/69 620), respectively, and the differences were statistically significant in different years (P<0.01). The infection rates of Trichuris trichiura were 0.17% (125/71 766), 0.10% (74/70 547), 0.08% (57/69 507) and 0.07% (49/69 620), respectively, and the differences were statistically significant among different years (P<0.01). The results of global spatial autocorrelation analysis showed that there was a spatial autocorrelation index Moran's I value of hookworm infection rate in 2016, Trichuris trichiura infection rate in 2016, 2018 and 2019, with statistical significance (P<0.05). The results of hotspot analysis, SaTScan and FleXScan spatial and temporal scanning analysis showed that there were high-value aggregation regions for each species in each year. Conclusion The infection rates of STH, hookworm, Ascaris lumbricoides and Trichuris trichiura showed a decreasing trend and space-time clustering from 2016 to 2019. It should be taken into account in the formulation of control strategies.
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Objective To explore the spatial-temporal clustering distribution of schistosomiasis transmission risk in Yunnan Province from 2004 to 2015, so as to provide scientific evidence for the future schistosomiasis control and consolidation of the control achievements. Methods All data pertaining to endemic situation of human and bovine schistosomiasis and snail survey at a township level in Yunnan Province from 2004 to 2015 were collected. A descriptive epidemiological method and Joinpoint model were used to describe the changing trends of Schistosoma japonicum infections in humans, bovine and snails, and the hotspots and clusters of schistosomiasis transmission risk were identified using spatial autocorrelation analysis, hotspots analysis and retrospective space-time scan statistic in Yunnan Province from 2004 to 2015. Results The prevalence of S. japonicum infections appeared a continuous decline in humans, bovine and snails in Yunnan Province from 2004 to 2015, and the estimated number of schistosomiasis cases reduced from 43 056 in 2004 to 756 in 2015, with a decline rate of 98.24%. There were no acute cases since 2008 and no infected snails since 2014 in Yunnan Province. There were significant differences in the changing trends of human and bovine S. japonicum infections in Yunnan Province between 2012 and 2015 and between 2013 and 2015, respectively using the Joinpoint model (P < 0.05). In addition, there was a spatial autocorrelation in human S. japonicum infections in Yunnan Province from 2004 to 2013 (P < 0.01), and the hotspots areas for human S. japonicum infections were mainly distributed in some townships from Dali City, Weishan County and Eryuan County. Retrospective spatial-temporal scanning revealed that S. japonicum human, bovine and snail infections were clustered in 23, 15, 4 townships from Dali City, Weishan County, Eryuan County, Nanjian County and Heqing County, respectively, with relative risks of 6.25 to 28.75 (P < 0.01), which was almost consistent with the cluster areas detected by hotspots analysis. Conclusions The endemic situation of schistosomiasis significantly reduced in Yunnan Province from 2004 to 2015; however, there is still a risk of schistosomiasis transmission. The monitoring and control of schistosomiasis should be intensified in the future in Yunnan Province.
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Objective To explore the spatial-temporal clustering distribution of schistosomiasis transmission risk in Yunnan Province from 2004 to 2015, so as to provide scientific evidence for the future schistosomiasis control and consolidation of the control achievements. Methods All data pertaining to endemic situation of human and bovine schistosomiasis and snail survey at a township level in Yunnan Province from 2004 to 2015 were collected. A descriptive epidemiological method and Joinpoint model were used to describe the changing trends of Schistosoma japonicum infections in humans, bovine and snails, and the hotspots and clusters of schistosomiasis transmission risk were identified using spatial autocorrelation analysis, hotspots analysis and retrospective space-time scan statistic in Yunnan Province from 2004 to 2015. Results The prevalence of S. japonicum infections appeared a continuous decline in humans, bovine and snails in Yunnan Province from 2004 to 2015, and the estimated number of schistosomiasis cases reduced from 43 056 in 2004 to 756 in 2015, with a decline rate of 98.24%. There were no acute cases since 2008 and no infected snails since 2014 in Yunnan Province. There were significant differences in the changing trends of human and bovine S. japonicum infections in Yunnan Province between 2012 and 2015 and between 2013 and 2015, respectively using the Joinpoint model (P < 0.05). In addition, there was a spatial autocorrelation in human S. japonicum infections in Yunnan Province from 2004 to 2013 (P < 0.01), and the hotspots areas for human S. japonicum infections were mainly distributed in some townships from Dali City, Weishan County and Eryuan County. Retrospective spatial-temporal scanning revealed that S. japonicum human, bovine and snail infections were clustered in 23, 15, 4 townships from Dali City, Weishan County, Eryuan County, Nanjian County and Heqing County, respectively, with relative risks of 6.25 to 28.75 (P < 0.01), which was almost consistent with the cluster areas detected by hotspots analysis. Conclusions The endemic situation of schistosomiasis significantly reduced in Yunnan Province from 2004 to 2015; however, there is still a risk of schistosomiasis transmission. The monitoring and control of schistosomiasis should be intensified in the future in Yunnan Province.
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Objective@#To analyze the spatial-temporal characteristics of other infectious diarrhea (OID) in Jiangsu province from 2010 to 2017, and to provide evidence for setting up prevention and control programs of the disease.@*Methods@#Data was from the Chinese Center for Disease Control and Prevention and the Statistics Bureau of Jiangsu province. Descriptive methods were used to illustrate the epidemiological characteristics of OID from 2010 to 2017. Global autocorrelation statistics method (Moran’s I) was used to detect the spatial autocorrelation of OID, annually. Kulldorff M spatiotemporal scan statistics was used to analyze the spatial-temporal clustering of OID. ArcGIS 10.0 software, SaTScan 9.4 software and Excel 2017 software were also applied.@*Results@#A total of 126 341 OID cases were found in Jiangsu province from 2010 to 2017 with an average annual incidence as 19.96/100 000. Children under five accounted for 55.08% (69 590/126 341) of the total cases. Obvious seasonal backshift with the increasing trends of the OID was noticed. There appeared four areas with high incidence of OID in the whole province, including Wuxi, Suzhou, Yancheng and Xuzhou. OID showed positive spatial autocorrelation at the county level with higher Moran’s I from 0.19 to 0.33 (P<0.01). There appeared four positive clusters, all occurred in the high incidence period of OID, including the cluster area from the intersection areas of Changzhou and Wuxi (RR=7.61, LLR=2 605.80, P<0.01), respectively.@*Conclusion@#With the increasing trends and the seasonal backshift of OID cases, pathogen surveillance programs set for those scattered children under five, in clustered regions and epidemic seasons should be strengthened.
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Objective To analyze the spatial distribution and identify the high risk areas of pulmonary tuberculosis at the township level in Beijing during 2005-2015.Methods Data on pulmonary tuberculosis cases was collected from the tuberculosis information management system.Global autocorrelation analysis,local indicators of spatial association and Kulldorff's Scan Statistics were applied to map the spatial distribution and detect the space-time clusters of the pulmonary tuberculosis cases during 2005-2015.Results Spatial analysis on the incidence of pulmonary tuberculosis at the township level demonstrated that the spatial autocorrelation was positive during the study period.The values of Moran's I ranged from 0.224 3 to 0.291 8 with all the P values less than 0.05.Hotspots were primarily distributed in 8 towns/streets as follows:Junzhuang,Wangping,Yongding and Tanzhesi in Mentougou district,Yancun in Fangshan district,Wangzuo town in Fengtai district,Tianqiao street in Xicheng district and Tianzhu town in Shunyi district.Spatiotemporal clusters across the entire study period were identified by using Kulldorff's spatiotemporal scan statistic.The primary cluster was located in Chaoyang and Shunyi districts,including 17 towns/streets,as follows:Cuigezhuang,Maizidian,Dongfeng,Taiyanggong,Zuojiazhuang,Hepingjie,Xiaoguan,Xiangheyuan,Dongba,Jiangtai,Wangjing,Jinzhan,Jiuxianqiao,Laiguangying,Sunhe towns/streets in Chaoyang district,Houshayu and Tianzhu town in Shunyi district,during January to December 2005.Conclusion Incidence rates of pulmonary tuberculosis displayed spatial and temporal clusterings at the township level in Beijing during 2005-2015,with high risk areas relatively concentrated in the central and southern parts of Beijing.
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Objective To analyze the spatial and temporal distributions of bacillary dysentery in Chongqing,Yichang and Enshi (the Three Gorges Area) from 2005 to 2016,and provide evidence for the disease prevention and control.Methods The incidence data of bacillary dysentery in the Three Gorges Area during this period were collected from National Notifiable Infectious Disease Reporting System.The spatial-temporal scan statistic was conducted with software SaTScan 9.4 and bacillary dysentery clusters were visualized with software ArcGIS 10.3.Results A total of 126 196 cases were reported in the Three Gorges Area during 2005-2016,with an average incidence rate of 29.67/100 000.The overall incidence was in a downward trend,with an average annual decline rate of 4.74％.Cases occurred all the year round but with an obvious seasonal increase between May and October.Among the reported cases,44.71％ (56 421/126 196) were children under 5-year-old,the cases in children outside child care settings accounted for 41.93％ (52 918/126 196) of the total.The incidence rates in districts of Yuzhong,Dadukou,Jiangbei,Shapingba,Jiulongpo,Nanan,Yubei,Chengkou of Chongqing and districts of Xiling and Wujiagang of Yichang city of Hubei province were high,ranging from 60.20/100 000 to 114.81/100 000.Spatial-temporal scan statistic for the spatial and temporal distributions of bacillary dysentery during this period revealed that the temporal distribution was during May-October,and there were 12 class Ⅰ clusters,35 class Ⅱ clusters,and 9 clusters without statistical significance in counties with high incidence.All the class Ⅰ clusters were in urban area of Chongqing (Yuzhong,Dadukou,Jiangbei,Shapingba,Jiulongpo,Nanan,Beibei,Yubei,Banan)and surrounding counties,and the class Ⅱ clusters transformed from concentrated distribution to scattered distribution.Conclusions Temporal and spatial cluster of bacillary dysentery incidence existed in the three gorges area during 2005-2016.It is necessary to strengthen the bacillary dysentery prevention and control in urban areas of Chongqing and Yichang.
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Objective To analyze the spatial distribution and identify the high risk areas of pulmonary tuberculosis at the township level in Beijing during 2005-2015.Methods Data on pulmonary tuberculosis cases was collected from the tuberculosis information management system.Global autocorrelation analysis,local indicators of spatial association and Kulldorff's Scan Statistics were applied to map the spatial distribution and detect the space-time clusters of the pulmonary tuberculosis cases during 2005-2015.Results Spatial analysis on the incidence of pulmonary tuberculosis at the township level demonstrated that the spatial autocorrelation was positive during the study period.The values of Moran's I ranged from 0.224 3 to 0.291 8 with all the P values less than 0.05.Hotspots were primarily distributed in 8 towns/streets as follows:Junzhuang,Wangping,Yongding and Tanzhesi in Mentougou district,Yancun in Fangshan district,Wangzuo town in Fengtai district,Tianqiao street in Xicheng district and Tianzhu town in Shunyi district.Spatiotemporal clusters across the entire study period were identified by using Kulldorff's spatiotemporal scan statistic.The primary cluster was located in Chaoyang and Shunyi districts,including 17 towns/streets,as follows:Cuigezhuang,Maizidian,Dongfeng,Taiyanggong,Zuojiazhuang,Hepingjie,Xiaoguan,Xiangheyuan,Dongba,Jiangtai,Wangjing,Jinzhan,Jiuxianqiao,Laiguangying,Sunhe towns/streets in Chaoyang district,Houshayu and Tianzhu town in Shunyi district,during January to December 2005.Conclusion Incidence rates of pulmonary tuberculosis displayed spatial and temporal clusterings at the township level in Beijing during 2005-2015,with high risk areas relatively concentrated in the central and southern parts of Beijing.
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Objective To analyze the spatial and temporal distributions of bacillary dysentery in Chongqing,Yichang and Enshi (the Three Gorges Area) from 2005 to 2016,and provide evidence for the disease prevention and control.Methods The incidence data of bacillary dysentery in the Three Gorges Area during this period were collected from National Notifiable Infectious Disease Reporting System.The spatial-temporal scan statistic was conducted with software SaTScan 9.4 and bacillary dysentery clusters were visualized with software ArcGIS 10.3.Results A total of 126 196 cases were reported in the Three Gorges Area during 2005-2016,with an average incidence rate of 29.67/100 000.The overall incidence was in a downward trend,with an average annual decline rate of 4.74％.Cases occurred all the year round but with an obvious seasonal increase between May and October.Among the reported cases,44.71％ (56 421/126 196) were children under 5-year-old,the cases in children outside child care settings accounted for 41.93％ (52 918/126 196) of the total.The incidence rates in districts of Yuzhong,Dadukou,Jiangbei,Shapingba,Jiulongpo,Nanan,Yubei,Chengkou of Chongqing and districts of Xiling and Wujiagang of Yichang city of Hubei province were high,ranging from 60.20/100 000 to 114.81/100 000.Spatial-temporal scan statistic for the spatial and temporal distributions of bacillary dysentery during this period revealed that the temporal distribution was during May-October,and there were 12 class Ⅰ clusters,35 class Ⅱ clusters,and 9 clusters without statistical significance in counties with high incidence.All the class Ⅰ clusters were in urban area of Chongqing (Yuzhong,Dadukou,Jiangbei,Shapingba,Jiulongpo,Nanan,Beibei,Yubei,Banan)and surrounding counties,and the class Ⅱ clusters transformed from concentrated distribution to scattered distribution.Conclusions Temporal and spatial cluster of bacillary dysentery incidence existed in the three gorges area during 2005-2016.It is necessary to strengthen the bacillary dysentery prevention and control in urban areas of Chongqing and Yichang.
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Objective To detect the spatial temporal distribution of mumps in Gansu by means of spatial statistics.Methods The county-based incidence of mumps from 2009 to 2013 was used to calculate the global Moran' s I and local G statistics, and analyze its spatial temporal distribution characteristics.Results The incidence of mumps in Gansu were spatial auto-correlated from 2009 to 2013 respectively (P＜0.001), and the hot spots were mainly distributed in Hexi area,while the cold spots were distributed in Tianshui, Longnan and Qingyang.Spatial temporal analysis showed that the high incidence of mumps was most likely to be detect in Hexi area (RR=3.05, LLR=4 670.995, P＜0.001), and the low incidence was most likely to be detect in Longdong area (RR=0.36,LLR=1 980.686,P＜0.001).Conclusion The spatial and spatial temporal clustering of mumps existed in Gansu from 2009 to 2013, the results can be used in the development of mumps prevention and control measure in Gansu.