Understanding temporal and spatial variations of viral disease in the US: The need for a one-health-based data collection and analysis approach
Understanding temporal and spatial variations of viral disease in the US: The need for a one-health-based data collection and analysis approach
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DOI：
10.1016/j.onehlt.2019.100105
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发表时间：
2019-12-01
期刊：
影响因子：
5
通讯作者：
Xagoraraki, Irene
中科院分区：
文献类型：
--
作者：
O'Brien, Evan;Xagoraraki, Irene
病毒性疾病具有时空差异，影响其发生的因素很多。确定这些因素对于预测和减轻病毒性疾病负担至关重要。由于病毒感染能够从环境、动物和其他人类传播给人类，因此可以使用“一个健康”框架来调查病毒运输和传播的关键途径。将人类、牲畜和野生动物疾病发生的公开临床数据与联邦和州数据库中报告的环境数据（如与土地使用、环境质量和天气有关的参数）结合起来，采用整体方法，可以加强对疾病模式变化的理解，从而设计和实施监测系统。本文以美国密歇根州为例，介绍了一种分析方法。密歇根州是一个拥有大型城市中心以及相当大的农村和农业人口的州。对2017年公开数据的分析表明，密歇根州胃肠（GI）和流感相关疾病与农业用地的关系可能高于当年已开发土地的关系。与此同时，甲型肝炎病毒似乎与人口密集地区的发达土地利用关系最为密切。胃肠道疾病可能与降水有关，这种关系在春季最为强烈，尽管胃肠道疾病在冬季最为常见。人类相关临床数据、动物疾病数据和环境数据的整合最终可用于确定城市和农村环境中病毒爆发的最关键地点和时间的优先顺序。
Viral diseases exhibit spatial and temporal variation, and there are many factors that can affect their occurrence. The identification of these factors is critical in the efforts to predict and lessen viral disease burden. Because viral infection is able to spread to humans from the environment, animals, and other humans, the One-Health framework can be used to investigate the critical pathways through which viruses are transported and transmitted. A holistic approach, incorporating publicly available clinical data for human, livestock, and wildlife disease occurrence, together with environmental data reported in federal and state databases such as parameters related to land use, environmental quality, and weather, can enhance the understanding of variations in disease patterns, leading to the design and implementation of surveillance systems. An example analysis approach is presented for Michigan, United States, which is a state with large urban centers as well as a sizeable rural and agricultural population. Analysis of publicly available data from 2017 indicates that gastrointestinal (GI) and influenza-associated illnesses in Michigan may have been related with agricultural land use to a higher extent than with developed land use during that year. Meanwhile, hepatitis A virus appears to be most closely related with developed land use in dense population areas. GI illnesses may be related to precipitation, and this relationship is strongest in the springtime, although GI illnesses are most common in the winter months. Integration of human-related clinical data, animal disease data, and environmental data can ultimately be used for prioritization of the most critical locations and times for viral outbreaks in both urban and rural environments.