Spatial Video and EpiExplorer: A Field Strategy to Contextualize Enteric Disease Risk in Slum Environments.
Spatial Video and EpiExplorer: A Field Strategy to Contextualize Enteric Disease Risk in Slum Environments.
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空间视频和EpiExplorer：在贫民窟环境中了解肠道疾病风险的现场策略。
DOI：
10.3390/ijerph19158902
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发表时间：
2022-07-22
影响因子：
--
通讯作者：
Morris, John Glenn, Jr.
中科院分区：
文献类型：
--
作者：
Ajayakumar, Jayakrishnan;Curtis, Andrew J.;Rouzier, Vanessa;Pape, Jean William;Bempah, Sandra;Alam, Meer Taifur;Alam, Md Mahbubul;Rashid, Mohammed H.;Ali, Afsar;Morris, John Glenn, Jr.
在非正规住区环境中，与受污染的水、恶劣的环境卫生和个人卫生有关的疾病风险在概念上得到了很好的理解。从分析的角度来看，收集数据在适当的细尺度空间和时间粒度是具有挑战性的。新的移动的方法，如空间视频（SV），可以补充更传统的流行病学现场工作，以解决这一差距。然而，这项工作随后在分析可视化方面提出了额外的挑战，这些分析可视化可用于理解子邻域的风险模式，甚至提供早期预警系统。在本文中，我们使用定制的空间规划，以创建一个灵活的，精细的规模探索性调查的非法收集的水质和环境调查在三个不同的非正式定居点的太子港，海地的框架。我们动态地挖掘这些时空流行病学和环境数据，以提供使用更传统的空间软件（如地理信息系统（GIS））不容易实现的见解。结果包括每月变化的局部风险的子邻域地图。最有趣的是，这些流行病学的变化可能是以前错误的解释，因为近似的环境因素和/或气象条件。
Disease risk associated with contaminated water, poor sanitation, and hygiene in informal settlement environments is conceptually well understood. From an analytical perspective, collecting data at a suitably fine scale spatial and temporal granularity is challenging. Novel mobile methodologies, such as spatial video (SV), can complement more traditional epidemiological field work to address this gap. However, this work then poses additional challenges in terms of analytical visualizations that can be used to both understand sub-neighborhood patterns of risk, and even provide an early warning system. In this paper, we use bespoke spatial programming to create a framework for flexible, fine-scale exploratory investigations of simultaneously-collected water quality and environmental surveys in three different informal settlements of Port-au-Prince, Haiti. We dynamically mine these spatio-temporal epidemiological and environmental data to provide insights not easily achievable using more traditional spatial software, such as Geographic Information System (GIS). The results include sub-neighborhood maps of localized risk that vary monthly. Most interestingly, some of these epidemiological variations might have previously been erroneously explained because of proximate environmental factors and/or meteorological conditions.
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影响因子：
4.9
作者：
Curtis A;Curtis JW;Shook E;Smith S;Jefferis E;Porter L;Schuch L;Felix C;Kerndt PR
通讯作者：
Kerndt PR
影响因子：
4.9
作者：
Ajayakumar J;Curtis AJ;Rouzier V;Pape JW;Bempah S;Alam MT;Alam MM;Rashid MH;Ali A;Morris JG
通讯作者：
Morris JG
影响因子：
0.8
作者：
Kulldorff, M
通讯作者：
Kulldorff, M
DOI：
10.1080/13658816.2020.1737700
发表时间：
2020-03-09
影响因子：
5.7
作者：
Jamonnak, Suphanut;Zhao, Ye;Yang, Jing
通讯作者：
Yang, Jing
影响因子：
3.4
作者：
Seo, Mijin;Lee, Haejin;Kim, Yongseok
通讯作者：
Kim, Yongseok