Periodic trends in Internet Searches for Ocular Symptoms in the US

To identify periodic trends in internet searches for ocular symptoms and to determine the seasonal peaks and troughs. This cross-sectional study examined publicly available Google Trends data from the United States (01/01/2015 to 12/31/2019). A list of common ocular symptoms was compiled from the American Academy of Ophthalmology Eye Health website and Wills Eye Manual. Ocular symptoms were stratified into categories involving vision change, eye pain, or eye redness. The search volume over time for each term was modeled using periodic regression functions and the goodness-of-fit was reported. Fisher’s exact tests were used to compare the characteristics of periodic vs. non-periodic query terms. Seasonal trends were demonstrated by 45% (48/106) of the ocular symptoms included in this investigation. Search terms with best fit to the periodic model included stye (r2 = 0.89), pink eye (r2 = 0.82), dry eye (r2 = 0.76), blurry vision (r2 = 0.72), and swollen eye (r2 = 0.71). Periodic search terms were more likely to involve eye redness (21% vs. 11%, p = .014) and less likely to involve vision change (11% vs. 36%; p < .001). Periodic queries involving eye redness most often peaked in the spring and those involving eye pain peaked in the summer. Ocular symptom queries directly reflect seasonal trends for allergic eye disease and ocular trauma. Search query analyses can serve as accurate epidemiological tools with research and real-world clinical applications.

本研究旨在明确眼部症状网络搜索的周期性趋势，并确定其季节性高峰与低谷。本横断面研究分析了2015年1月1日至2019年12月31日期间美国公开的谷歌趋势（Google Trends）数据。研究团队从美国眼科学会（American Academy of Ophthalmology）眼部健康官网及《威尔斯眼科手册》（Wills Eye Manual）中整理出常见眼部症状清单。将眼部症状划分为视力变化、眼部疼痛或眼部红肿三类。采用周期性回归函数对各关键词的随时间变化的搜索量进行建模，并报告其拟合优度。采用费希尔精确检验（Fisher’s exact test）比较周期性与非周期性搜索关键词的特征差异。本研究纳入的106种眼部症状中，有45%（48/106）呈现出季节性趋势。与周期性模型拟合度最高的搜索关键词包括麦粒肿（stye，r²=0.89）、红眼病（pink eye，r²=0.82）、干眼症（dry eye，r²=0.76）、视力模糊（blurry vision，r²=0.72）及眼肿（swollen eye，r²=0.71）。周期性搜索关键词更常涉及眼部红肿（21% vs. 11%，p=0.014），而涉及视力变化的比例更低（11% vs. 36%，p<0.001）。涉及眼部红肿的周期性搜索关键词峰值多出现于春季，而涉及眼部疼痛的峰值则多出现于夏季。眼部症状搜索量可直接反映过敏性眼病及眼外伤的季节性变化趋势。搜索关键词分析可作为精准的流行病学工具，兼具科研与真实世界临床应用价值。