Community recovery from a major natural hazard-related disaster can be a long process, and rebuilding likely does not occur uniformly across space and time. Spatial and temporal clustering may be evident in certain da...Community recovery from a major natural hazard-related disaster can be a long process, and rebuilding likely does not occur uniformly across space and time. Spatial and temporal clustering may be evident in certain data types that can be used to frame the progress of recovery following a disaster. Publically available building permit data from the city of Joplin, Missouri, were gathered for four permit types, including residential, commercial, roof repair, and demolition. The data were used to(1) compare the observed versus expected frequency(chi-square) of permit issuance before and after the EF5 2011 tornado;(2), determine if significant space-time clusters of permits existed using the SaTScan^(TM) cluster analysis program(version 9.7);and(3) fit any emergent cluster data to the widely-cited Kates 10-year recovery model. All permit types showed significant increases in issuance for at least 5 years following the event,and one(residential) showed significance for nine of the 10years. The cluster analysis revealed a total of 16 significant clusters across the 2011 damage area. The results of fitting the significant cluster data to the Kates model revealed that those data closely followed the model, with some variation in the residential permit data path.展开更多
目的分析2005—2018年江苏省流行性乙型脑炎(Japanese B encephalitis,JE)流行病学特征、聚集性以及JE发生与三带喙库蚊季节消长的相关性,为预防和控制JE提供科学依据。方法利用描述性流行病学方法、聚集性和相关性分析描述江苏省2005—...目的分析2005—2018年江苏省流行性乙型脑炎(Japanese B encephalitis,JE)流行病学特征、聚集性以及JE发生与三带喙库蚊季节消长的相关性,为预防和控制JE提供科学依据。方法利用描述性流行病学方法、聚集性和相关性分析描述江苏省2005—2018年JE的流行病学特征和风险地区。结果江苏省2005—2018年共报告本地JE病例495例,年均发病率为0.045/10万,JE发病率总体呈下降趋势(χ^(2)=–16.11,P<0.01)。1~14岁儿童是高危人群。JE发生具明显季节性,病例主要集中在7月7日—9月7日〔相对危险度(RR)=86.48,LLR=726.97,P<0.01)〕。苏南地区发病高峰为7月,苏北地区发病高峰为8月。单纯空间扫描分析结果显示,JE病例存在聚集性,聚集区主要分布在苏北的连云港市、宿迁市、淮安市和苏南的苏州市。2008—2018年江苏省JE月平均发病数与延后1个月的牲畜棚三带喙库蚊月平均密度呈统计学相关(r=0.79,P<0.01)。结论江苏省JE发生与三带喙库蚊季节消长密切相关,在做好15岁以下儿童免疫接种工作的基础上,JE高发地区应加强三带喙库蚊密度、带毒率监测和宿主感染率监测,三带喙库蚊季节高峰前采取有效防蚊灭蚊措施,减少JE病例的发生。展开更多
Background:Tuberculosis(TB)is still one of the most serious infectious diseases in the mainland of China.So it was urgent for the formulation of more effective measures to prevent and control it.Methods:The data of re...Background:Tuberculosis(TB)is still one of the most serious infectious diseases in the mainland of China.So it was urgent for the formulation of more effective measures to prevent and control it.Methods:The data of reported TB cases in 340 prefectures from the mainland of China were extracted from the China Information System for Disease Control and Prevention(CISDCP)during January 2005 to December 2015.The Kulldorff’s retrospective space-time scan statistics was used to identify the temporal,spatial and spatio-temporal clusters of reported TB in the mainland of China by using the discrete Poisson probability model.Spatio-temporal clusters of sputum smear-positive(SS+)reported TB and sputum smearnegative(SS-)reported TB were also detected at the prefecture level.Results:A total of 10200528 reported TB cases were collected from 2005 to 2015 in 340 prefectures,including 5283983 SS-TB cases and 4631734 SS+TB cases with specific sputum smear results,284811 cases without sputum smear test.Significantly TB clustering patterns in spatial,temporal and spatiotemporal were observed in this research.Results of the Kulldorff’s scan found twelve significant space-time clusters of reported TB.The most likely spatio-temporal cluster(RR=3.27,P<0.001)was mainly located in Xinjiang Uygur Autonomous Region of western China,covering five prefectures and clustering in the time frame from September 2012 to November 2015.The spatio-temporal clustering results of SS+TB and SS-TB also showed the most likely clusters distributed in the western China.However,the clustering time of SS+TB was concentrated before 2010 while SS-TB was mainly concentrated after 2010.Conclusions:This study identified the time and region of TB,SS+TB and SS-TB clustered easily in 340 prefectures in the mainland of China,which is helpful in prioritizing resource assignment in high-risk periods and high-risk areas,and to formulate powerful strategy to prevention and control TB.展开更多
文摘Community recovery from a major natural hazard-related disaster can be a long process, and rebuilding likely does not occur uniformly across space and time. Spatial and temporal clustering may be evident in certain data types that can be used to frame the progress of recovery following a disaster. Publically available building permit data from the city of Joplin, Missouri, were gathered for four permit types, including residential, commercial, roof repair, and demolition. The data were used to(1) compare the observed versus expected frequency(chi-square) of permit issuance before and after the EF5 2011 tornado;(2), determine if significant space-time clusters of permits existed using the SaTScan^(TM) cluster analysis program(version 9.7);and(3) fit any emergent cluster data to the widely-cited Kates 10-year recovery model. All permit types showed significant increases in issuance for at least 5 years following the event,and one(residential) showed significance for nine of the 10years. The cluster analysis revealed a total of 16 significant clusters across the 2011 damage area. The results of fitting the significant cluster data to the Kates model revealed that those data closely followed the model, with some variation in the residential permit data path.
文摘目的分析2005—2018年江苏省流行性乙型脑炎(Japanese B encephalitis,JE)流行病学特征、聚集性以及JE发生与三带喙库蚊季节消长的相关性,为预防和控制JE提供科学依据。方法利用描述性流行病学方法、聚集性和相关性分析描述江苏省2005—2018年JE的流行病学特征和风险地区。结果江苏省2005—2018年共报告本地JE病例495例,年均发病率为0.045/10万,JE发病率总体呈下降趋势(χ^(2)=–16.11,P<0.01)。1~14岁儿童是高危人群。JE发生具明显季节性,病例主要集中在7月7日—9月7日〔相对危险度(RR)=86.48,LLR=726.97,P<0.01)〕。苏南地区发病高峰为7月,苏北地区发病高峰为8月。单纯空间扫描分析结果显示,JE病例存在聚集性,聚集区主要分布在苏北的连云港市、宿迁市、淮安市和苏南的苏州市。2008—2018年江苏省JE月平均发病数与延后1个月的牲畜棚三带喙库蚊月平均密度呈统计学相关(r=0.79,P<0.01)。结论江苏省JE发生与三带喙库蚊季节消长密切相关,在做好15岁以下儿童免疫接种工作的基础上,JE高发地区应加强三带喙库蚊密度、带毒率监测和宿主感染率监测,三带喙库蚊季节高峰前采取有效防蚊灭蚊措施,减少JE病例的发生。
基金The research was supported by the National S&T Major Project(Grant No.2014ZX10004005–001).
文摘Background:Tuberculosis(TB)is still one of the most serious infectious diseases in the mainland of China.So it was urgent for the formulation of more effective measures to prevent and control it.Methods:The data of reported TB cases in 340 prefectures from the mainland of China were extracted from the China Information System for Disease Control and Prevention(CISDCP)during January 2005 to December 2015.The Kulldorff’s retrospective space-time scan statistics was used to identify the temporal,spatial and spatio-temporal clusters of reported TB in the mainland of China by using the discrete Poisson probability model.Spatio-temporal clusters of sputum smear-positive(SS+)reported TB and sputum smearnegative(SS-)reported TB were also detected at the prefecture level.Results:A total of 10200528 reported TB cases were collected from 2005 to 2015 in 340 prefectures,including 5283983 SS-TB cases and 4631734 SS+TB cases with specific sputum smear results,284811 cases without sputum smear test.Significantly TB clustering patterns in spatial,temporal and spatiotemporal were observed in this research.Results of the Kulldorff’s scan found twelve significant space-time clusters of reported TB.The most likely spatio-temporal cluster(RR=3.27,P<0.001)was mainly located in Xinjiang Uygur Autonomous Region of western China,covering five prefectures and clustering in the time frame from September 2012 to November 2015.The spatio-temporal clustering results of SS+TB and SS-TB also showed the most likely clusters distributed in the western China.However,the clustering time of SS+TB was concentrated before 2010 while SS-TB was mainly concentrated after 2010.Conclusions:This study identified the time and region of TB,SS+TB and SS-TB clustered easily in 340 prefectures in the mainland of China,which is helpful in prioritizing resource assignment in high-risk periods and high-risk areas,and to formulate powerful strategy to prevention and control TB.
