Department of Emergency Medicine, School of Medicine, University of Washington, 4730 University Way NE, Suite 104, #2021, Seattle, 98105, WA, USA.
Department of Atmospheric Sciences, College of the Environment, University of Washington, 408 Atmospheric Sciences-Geophysics (ATG) Building, Box 351640, Seattle, WA, 98195-1640, USA.
Sci Rep. 2020 Jul 9;10(1):11334. doi: 10.1038/s41598-020-68095-y.
Tracking concentrations of regional airborne pollen is valuable for a variety of fields including plant and animal ecology as well as human health. However, current methods for directly measuring regional pollen concentrations are labor-intensive, requiring special equipment and manual counting by professionals leading to sparse data availability in select locations. Here, we use publicly available Google Trends data to evaluate whether searches for the term "pollen" can be used to approximate local observed early-season pollen concentrations as reported by the National Allergy Bureau across 25 U.S. regions from 2012-2017, in the context of site-specific characteristics. Our findings reveal that two major factors impact the ability of internet search data to approximate observed pollen: (1) volume/availability of internet search data, which is tied to local population size and media use; and (2) signal intensity of the seasonal peak in searches. Notably, in regions and years where internet search data was abundant, we found strong correlations between local search patterns and observed pollen, thus revealing a potential source of daily pollen data across the U.S. where observational pollen data are not reliably available.
追踪区域性空气花粉浓度对于包括植物和动物生态学以及人类健康在内的多个领域都具有重要价值。然而，目前直接测量区域性花粉浓度的方法劳动强度大，需要特殊设备和专业人员进行手动计数，导致在特定地点的数据可用性稀疏。在这里，我们利用公开的谷歌趋势数据来评估“花粉”一词的搜索量是否可以用于近似美国 25 个地区的国家过敏局在 2012-2017 年报告的当地早期季节性花粉浓度，同时考虑到特定地点的特征。我们的研究结果表明，有两个主要因素影响互联网搜索数据来近似观测到的花粉：（1）互联网搜索数据的数量/可用性，这与当地人口规模和媒体使用有关；（2）搜索季节性峰值的信号强度。值得注意的是，在互联网搜索数据丰富的地区和年份，我们发现当地搜索模式与观测到的花粉之间存在很强的相关性，从而揭示了美国各地日常花粉数据的潜在来源，在这些地区，观测花粉数据不可靠。
