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
Background Cutaneous leishmaniasis(CL)is a wide-reaching infection of major public health concern.Iran is one of the six most endemic countries in the world.This study aims to provide a spatiotemporal visualization of...Background Cutaneous leishmaniasis(CL)is a wide-reaching infection of major public health concern.Iran is one of the six most endemic countries in the world.This study aims to provide a spatiotemporal visualization of CL cases in Iran at the county level from 2011 to 2020,detecting high-risk zones,while also noting the movement of high-risk clusters.Methods On the basis of clinical observations and parasitological tests,data of 154,378 diagnosed patients were obtained from the Iran Ministry of Health and Medical Education.Utilizing spatial scan statistics,we investigated the disease’s purely temporal,purely spatial,spatial variation in temporal trends and spatiotemporal patterns.At P=0.05 level,the null hypothesis was rejected in every instance.Results In general,the number of new CL cases decreased over the course of the 9-year research period.From 2011 to 2020,a regular seasonal pattern,with peaks in the fall and troughs in the spring,was found.The period of September–February of 2014–2015 was found to hold the highest risk in terms of CL incidence rate in the whole country[relative risk(RR)=2.24,P<0.001)].In terms of location,six signifcant high-risk CL clusters covering 40.6%of the total area of the country were observed,with the RR ranging from 1.87 to 9.69.In addition,spatial variation in the temporal trend analysis found 11 clusters as potential high-risk areas that highlighted certain regions with an increasing tendency.Finally,fve space-time clusters were found.The geographical displacement and spread of the disease followed a moving pattern over the 9-year study period afecting many regions of the country.Conclusions Our study has revealed signifcant regional,temporal,and spatiotemporal patterns of CL distribution in Iran.Over the years,there have been multiple shifts in spatiotemporal clusters,encompassing many diferent parts of the country from 2011 to 2020.The results reveal the formation of clusters across counties that cover certain parts of provinces,indicating the importance of conducting spatiotemporal analyses at the county level for studies that encompass entire countries.Such analyses,at a fner geographical scale,such as county level,might provide more precise results than analyses at the scale of the province.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
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Background Cutaneous leishmaniasis(CL)is a wide-reaching infection of major public health concern.Iran is one of the six most endemic countries in the world.This study aims to provide a spatiotemporal visualization of CL cases in Iran at the county level from 2011 to 2020,detecting high-risk zones,while also noting the movement of high-risk clusters.Methods On the basis of clinical observations and parasitological tests,data of 154,378 diagnosed patients were obtained from the Iran Ministry of Health and Medical Education.Utilizing spatial scan statistics,we investigated the disease’s purely temporal,purely spatial,spatial variation in temporal trends and spatiotemporal patterns.At P=0.05 level,the null hypothesis was rejected in every instance.Results In general,the number of new CL cases decreased over the course of the 9-year research period.From 2011 to 2020,a regular seasonal pattern,with peaks in the fall and troughs in the spring,was found.The period of September–February of 2014–2015 was found to hold the highest risk in terms of CL incidence rate in the whole country[relative risk(RR)=2.24,P<0.001)].In terms of location,six signifcant high-risk CL clusters covering 40.6%of the total area of the country were observed,with the RR ranging from 1.87 to 9.69.In addition,spatial variation in the temporal trend analysis found 11 clusters as potential high-risk areas that highlighted certain regions with an increasing tendency.Finally,fve space-time clusters were found.The geographical displacement and spread of the disease followed a moving pattern over the 9-year study period afecting many regions of the country.Conclusions Our study has revealed signifcant regional,temporal,and spatiotemporal patterns of CL distribution in Iran.Over the years,there have been multiple shifts in spatiotemporal clusters,encompassing many diferent parts of the country from 2011 to 2020.The results reveal the formation of clusters across counties that cover certain parts of provinces,indicating the importance of conducting spatiotemporal analyses at the county level for studies that encompass entire countries.Such analyses,at a fner geographical scale,such as county level,might provide more precise results than analyses at the scale of the province.
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。
