Use of the NASA Giovanni Data System for Geospatial Public Health Research: Example of Weather-Influenza Connection

被引:16
作者
Acker, James [1 ]
Soebiyanto, Radina [2 ]
Kiang, Richard [3 ]
Kempler, Steve [4 ]
机构
[1] NASA, Adnet Inc, Goddard Space Flight Ctr, Goddard Earth Sci Data & Informat Serv Ctr, Greenbelt, MD 20771 USA
[2] Univ Space Res Assoc, Goddard Earth Sci Technol & Res GESTAR, Columbia, MD 21046 USA
[3] NASA, Goddard Space Flight Ctr, Greenbelt, MD 20771 USA
[4] NASA, Goddard Space Flight Ctr, Goddard Earth Sci Data & Informat Serv Ctr, Greenbelt, MD 20771 USA
关键词
remote sensing; climate; weather; public health; disease; environment; atmosphere; ocean; biosphere; precipitation; VISUALIZATION; TRANSMISSION; CHOLERA; CLIMATE;
D O I
10.3390/ijgi3041372
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The NASA Giovanni data analysis system has been recognized as a useful tool to access and analyze many different types of remote sensing data. The variety of environmental data types has allowed the use of Giovanni for different application areas, such as agriculture, hydrology, and air quality research. The use of Giovanni for researching connections between public health issues and Earth's environment and climate, potentially exacerbated by anthropogenic influence, has been increasingly demonstrated. In this communication, the pertinence of several different data parameters to public health will be described. This communication also provides a case study of the use of remote sensing data from Giovanni in assessing the associations between seasonal influenza and meteorological parameters. In this study, logistic regression was employed with precipitation, temperature and specific humidity as predictors. Specific humidity was found to be associated (p < 0.05) with influenza activity in both temperate and tropical climate. In the two temperate locations studied, specific humidity was negatively correlated with influenza; conversely, in the three tropical locations, specific humidity was positively correlated with influenza. Influenza prediction using the regression models showed good agreement with the observed data (correlation coefficient of 0.5-0.83).
引用
收藏
页码:1372 / 1386
页数:15
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