Geospatial Analysis of COVID-19: A Scoping Review.
Geospatial Analysis of COVID-19: A Scoping Review.
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DOI：
10.3390/ijerph18052336
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发表时间：
2021-02-27
影响因子：
--
通讯作者：
Gruebner O
中科院分区：
文献类型：
--
作者：
Fatima M;O'Keefe KJ;Wei W;Arshad S;Gruebner O
2019年12月下旬在中国武汉爆发的SARS-CoV-2成为COVID-19大流行的先兆。在大流行期间，建模和绘图等地理空间技术有助于疾病模式的检测。在这里，我们提供了与COVID-19及其地理、环境和社会人口特征相关的技术和相关发现的综合，遵循系统性综述和范围界定综述荟萃分析扩展的首选报告项目（PRISMA-ScR）方法进行范围界定综述。我们检索了PubMed的相关文章，并分别讨论了三个类别的结果：疾病映射，暴露映射和空间流行病学建模。大多数研究是生态性质的，主要在中国、巴西和美国进行。最常用的空间方法有聚类分析、热点分析、时空扫描统计和回归建模。研究人员使用了广泛的空间和统计软件，将空间分析应用于疾病映射，暴露映射和流行病学建模。限制使用这些空间技术的因素是COVID-19数据的不可用性和偏见，以及精细的人口，环境和社会经济数据的稀缺性，这限制了大多数研究人员探索COVID-19潜在影响因素的因果关系。我们的审查确定了COVID-19研究中的地理空间分析，并强调了当前的趋势和研究差距。由于大多数研究都集中在亚洲和美洲，因此需要在世界其他地区使用地理上精细尺度的数据进行更具可比性的空间研究。
The outbreak of SARS-CoV-2 in Wuhan, China in late December 2019 became the harbinger of the COVID-19 pandemic. During the pandemic, geospatial techniques, such as modeling and mapping, have helped in disease pattern detection. Here we provide a synthesis of the techniques and associated findings in relation to COVID-19 and its geographic, environmental, and socio-demographic characteristics, following the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) methodology for scoping reviews. We searched PubMed for relevant articles and discussed the results separately for three categories: disease mapping, exposure mapping, and spatial epidemiological modeling. The majority of studies were ecological in nature and primarily carried out in China, Brazil, and the USA. The most common spatial methods used were clustering, hotspot analysis, space-time scan statistic, and regression modeling. Researchers used a wide range of spatial and statistical software to apply spatial analysis for the purpose of disease mapping, exposure mapping, and epidemiological modeling. Factors limiting the use of these spatial techniques were the unavailability and bias of COVID-19 data—along with scarcity of fine-scaled demographic, environmental, and socio-economic data—which restrained most of the researchers from exploring causal relationships of potential influencing factors of COVID-19. Our review identified geospatial analysis in COVID-19 research and highlighted current trends and research gaps. Since most of the studies found centered on Asia and the Americas, there is a need for more comparable spatial studies using geographically fine-scaled data in other areas of the world.
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影响因子：
2.9
作者：
Cao Y;Hiyoshi A;Montgomery S
通讯作者：
Montgomery S
影响因子：
3.4
作者：
Hohl, Alexander;Delmelle, Eric M.;Lan, Yu
通讯作者：
Lan, Yu
DOI：
10.5123/s1679-49742020000300007
发表时间：
2020-01-01
期刊：
Epidemiologia e Serviços de Saúde
影响因子：
--
作者：
Cavalcante, João Roberto;Abreu, Ariane de Jesus Lopes de
通讯作者：
Abreu, Ariane de Jesus Lopes de
影响因子：
5.5
作者：
Glass, GE
通讯作者：
Glass, GE
影响因子：
4.9
作者：
Azevedo, Leonardo;Pereira, Maria Joao;Soares, Amilcar
通讯作者：
Soares, Amilcar