Willson Thomas J, Lospinoso Joshua, Weitzel Erik K, McMains Kevin C
Department of Otolaryngology-Head and Neck Surgery, San Antonio Military Medical Center, San Antonio, Texas.
Portia Statistical Consulting, San Antonio, Texas.
Laryngoscope. 2015 Nov;125(11):2447-50. doi: 10.1002/lary.25420. Epub 2015 Jun 24.
OBJECTIVES/HYPOTHESIS: Sinusitis significantly affects the population of the United States, exacting direct cost and lost productivity. Patients are likely to search the Internet for information related to their health before seeking care by a healthcare professional. Utilizing data generated from these searches may serve as an epidemiologic surrogate.
A retrospective time series analysis was performed.
Google search trend data from the Dallas-Fort Worth metro region for the years 2012 and 2013 were collected from www.google.com/trends for terms related to sinusitis based on literature outlining the most important symptoms for diagnosis. Additional terms were selected based on common English language terms used to describe the disease. Twelve months of data from the same time period and location for common pollutants (nitrogen dioxide, ozone, sulfur dioxide, and particulates), pollen and mold counts, and influenza-like illness were also collected. Statistical analysis was performed using Pearson correlation coefficients, and potential search activity predictors were assessed using autoregressive integrated moving average.
Pearson correlation was strongest between the terms congestion and influenza-like illness (r=0.615), and sinus and influenza-like illness (r=0.534) and nitrogen dioxide (r=0.487). Autoregressive integrated moving average analysis revealed ozone, influenza-like illness, and nitrogen dioxide levels to be potential predictors for sinus pressure searches, with estimates of 0.118, 0.349, and 0.438, respectively. Nitrogen dioxide was also a potential predictor for the terms congestion and sinus, with estimates of 0.191 and 0.272, respectively.
Google search activity for related terms follow the pattern of seasonal influenza-like illness and nitrogen dioxide. These data highlight the epidemiologic potential of this novel surveillance method.
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目的/假设：鼻窦炎对美国民众有显著影响，造成直接成本和生产力损失。患者在寻求医疗专业人员诊治之前，可能会在互联网上搜索与其健康相关的信息。利用这些搜索产生的数据可作为一种流行病学替代指标。
进行了一项回顾性时间序列分析。
根据概述诊断最重要症状的文献，从www.google.com/trends收集2012年和2013年达拉斯 - 沃思堡都会区与鼻窦炎相关术语的谷歌搜索趋势数据。根据用于描述该疾病的常用英语术语选择了其他术语。还收集了同一时期和地点12个月的常见污染物（二氧化氮、臭氧、二氧化硫和颗粒物）、花粉和霉菌计数以及流感样疾病的数据。使用Pearson相关系数进行统计分析，并使用自回归积分移动平均评估潜在的搜索活动预测因素。
“鼻塞”与“流感样疾病”（r = 0.615）、“鼻窦”与“流感样疾病”（r = 0.534）以及“鼻窦”与“二氧化氮”（r = 0.487）之间的Pearson相关性最强。自回归积分移动平均分析显示，臭氧、流感样疾病和二氧化氮水平是鼻窦压力搜索的潜在预测因素，估计值分别为0.118、0.349和0.438。二氧化氮也是“鼻塞”和“鼻窦”术语的潜在预测因素，估计值分别为0.191和0.272。
谷歌对相关术语的搜索活动遵循季节性流感样疾病和二氧化氮的模式。这些数据突出了这种新型监测方法的流行病学潜力。
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