{"title":"津巴布韦HIV感染率与社会经济因素的空间异质性关联","authors":"T. Manyangadze, M. Chimbari, E. Mavhura","doi":"10.30564/jgr.v4i3.3466","DOIUrl":null,"url":null,"abstract":"This study examined the spatial heterogeneity association of HIV incidence and socio-economic factors including poverty severity index,permanently employed females and males, unemployed females, percentage of poor households i.e., poverty prevalence, night lights index, literacy rate,household food security, and Gini index at district level in Zimbabwe.A mix of spatial analysis methods including Poisson model based on original log likelihood ratios (LLR), global Moran’s I, local indicator of spatial association - LISA were employed to determine the HIV hotspots.Geographically Weighted Poisson Regression (GWPR) and semi-parametric GWPR (s-GWPR) were used to determine the spatial association between HIV incidence and socio-economic factors. HIV incidence (number of cases per 1000) ranged from 0.6 (Buhera district) to 13.30 (Mangwe district). Spatial clustering of HIV incidence was observed (Global Moran’s I = - 0.150; Z score 3.038; p-value 0.002). Significant clusters of HIV were observed at district level. HIV incidence and its association with socioeconomic factors varied across the districts except percentage of females unemployed. Intervention programmes to reduce HIV incidence should address the identified socio-economic factors at district level.","PeriodicalId":165093,"journal":{"name":"Journal of Geographical Research","volume":"8 8","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Spatial Heterogeneity Association of HIV Incidence with Socio-economic Factors in Zimbabwe\",\"authors\":\"T. Manyangadze, M. Chimbari, E. Mavhura\",\"doi\":\"10.30564/jgr.v4i3.3466\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study examined the spatial heterogeneity association of HIV incidence and socio-economic factors including poverty severity index,permanently employed females and males, unemployed females, percentage of poor households i.e., poverty prevalence, night lights index, literacy rate,household food security, and Gini index at district level in Zimbabwe.A mix of spatial analysis methods including Poisson model based on original log likelihood ratios (LLR), global Moran’s I, local indicator of spatial association - LISA were employed to determine the HIV hotspots.Geographically Weighted Poisson Regression (GWPR) and semi-parametric GWPR (s-GWPR) were used to determine the spatial association between HIV incidence and socio-economic factors. HIV incidence (number of cases per 1000) ranged from 0.6 (Buhera district) to 13.30 (Mangwe district). Spatial clustering of HIV incidence was observed (Global Moran’s I = - 0.150; Z score 3.038; p-value 0.002). Significant clusters of HIV were observed at district level. HIV incidence and its association with socioeconomic factors varied across the districts except percentage of females unemployed. Intervention programmes to reduce HIV incidence should address the identified socio-economic factors at district level.\",\"PeriodicalId\":165093,\"journal\":{\"name\":\"Journal of Geographical Research\",\"volume\":\"8 8\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Geographical Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.30564/jgr.v4i3.3466\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Geographical Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.30564/jgr.v4i3.3466","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
摘要
本研究考察了津巴布韦艾滋病发病率与贫困严重程度指数、长期就业女性和男性、失业女性、贫困家庭百分比、贫困发生率、夜间照明指数、识字率、家庭粮食安全以及基尼系数等社会经济因素之间的空间异质性关系。采用基于原始对数似然比(LLR)的泊松模型、全局Moran’s I、局部空间关联指标LISA等空间分析方法确定HIV热点。利用地理加权泊松回归(GWPR)和半参数泊松回归(s-GWPR)确定HIV发病率与社会经济因素之间的空间关联关系。艾滋病毒发病率(每1000例病例数)从0.6例(布赫拉县)到13.30例(芒格韦县)不等。HIV发病率呈空间聚类(Global Moran’s I = - 0.150;Z分数3.038;假定值0.002)。在地区一级观察到显著的艾滋病毒聚集。艾滋病毒发病率及其与社会经济因素的关系在各地区有所不同,但女性失业百分比除外。减少艾滋病毒发病率的干预方案应在地区一级处理已查明的社会经济因素。
Spatial Heterogeneity Association of HIV Incidence with Socio-economic Factors in Zimbabwe
This study examined the spatial heterogeneity association of HIV incidence and socio-economic factors including poverty severity index,permanently employed females and males, unemployed females, percentage of poor households i.e., poverty prevalence, night lights index, literacy rate,household food security, and Gini index at district level in Zimbabwe.A mix of spatial analysis methods including Poisson model based on original log likelihood ratios (LLR), global Moran’s I, local indicator of spatial association - LISA were employed to determine the HIV hotspots.Geographically Weighted Poisson Regression (GWPR) and semi-parametric GWPR (s-GWPR) were used to determine the spatial association between HIV incidence and socio-economic factors. HIV incidence (number of cases per 1000) ranged from 0.6 (Buhera district) to 13.30 (Mangwe district). Spatial clustering of HIV incidence was observed (Global Moran’s I = - 0.150; Z score 3.038; p-value 0.002). Significant clusters of HIV were observed at district level. HIV incidence and its association with socioeconomic factors varied across the districts except percentage of females unemployed. Intervention programmes to reduce HIV incidence should address the identified socio-economic factors at district level.