背景:本系统评价的目的是在全球普通人群中确定结核病(TB)的高风险。审查是通过以下步骤进行的:阐述研究问题,搜索相关出版物,选择发现的研究,数据提取,分析,和证据综合。
方法:纳入的研究是以英文发表的,从原始研究中,发表了与全球结核病高风险相关的发现,发表于2017年至2023年之间,并基于结核病的地理空间分析。两名审稿人独立选择了文章,对彼此的评论视而不见。由此产生的分歧由第三位盲目的审阅者解决。对于书目搜索,使用了解决要调查的问题的受控和免费词汇。搜索是在PubMed上进行的,LILACS,EMBASE,Scopus,和WebofScience。谷歌学者。
结果:总共评估了79篇发表的文章,这些文章在1982年至2022年之间进行了40年的研究。根据79项研究,在所有进行结核病地理空间分析的国家中,超过40%来自亚洲,其次是南美洲,23%,非洲大约有15%,和其他人的2%和1%。各种研究中使用了各种地图,使用最多的是专题地图(32%),费率图(26%),时间趋势图(20%),和其他喜欢内核密度图(6%)。高风险的特征和影响热点的位置的因素是通过相关的研究很明显的不良社会经济条件构成(39%),其次是人口密度高(17%),与气候相关的聚类(15%),高风险蔓延到邻近城市(13%),不稳定和非随机聚类(11%)。
结论:结核病存在特定的高风险,这些高风险与低社会经济条件和壮观的天气条件有关,这些众所周知的领域将成为决策者干预的容易目标。我们建议更多利用空间的研究,temporal,进行时空分析,指出易感染结核病的地区和人群。
The objective of this systematic
review is to identify tuberculosis (TB) high-risk among the general population globally. The
review was conducted using the following steps: elaboration of the research question, search for relevant publications, selection of studies found, data extraction, analysis, and evidence synthesis.
The studies included were those published in English, from original research, presented findings relevant to tuberculosis high-risk across the globe, published between 2017 and 2023, and were based on geospatial analysis of TB. Two reviewers independently selected the articles and were blinded to each other`s comments. The resultant disagreement was resolved by a third blinded reviewer. For bibliographic search, controlled and free vocabularies that address the question to be investigated were used. The searches were carried out on PubMed, LILACS, EMBASE, Scopus, and Web of Science. and Google Scholar.
A total of 79 published articles with a 40-year study period between 1982 and 2022 were evaluated. Based on the 79 studies, more than 40% of all countries that have carried out geospatial analysis of TB were from Asia, followed by South America with 23%, Africa had about 15%, and others with 2% and 1%. Various maps were used in the various studies and the most used is the thematic map (32%), rate map (26%), map of temporal tendency (20%), and others like the kernel density map (6%). The characteristics of the high-risk and the factors that affect the hotspot\'s location are evident through studies related to poor socioeconomic conditions constituting (39%), followed by high population density (17%), climate-related clustering (15%), high-risk spread to neighbouring cities (13%), unstable and non-random cluster (11%).
There exist specific high-risk for TB which are areas that are related to low socioeconomic conditions and spectacular weather conditions, these areas when well-known will be easy targets for intervention by policymakers. We recommend that more studies making use of spatial, temporal, and spatiotemporal analysis be carried out to point out territories and populations that are vulnerable to TB.