通过谷歌搜索的透视来看COVID-19大流行病的演变
Robert Marty1, Manuel Ramos-Maqueda2, Nausheen Khan2
1World Bank, Washington, DC, USA. rmarty@worldbank.org.
Scientific reports
|November 14, 2023
概括
谷歌搜索数据可以预测COVID-19病例并揭示政策影响. 搜索趋势预测了报告的病例,而制政策与对失业和心理健康术语的兴趣增加有关.
科学领域:
- 流行病学 流行病学
- 公共卫生 公共卫生
- 数字流行病学数字流行病学
背景情况:
- 实时数据对于在COVID-19流行病等快速发展的健康危机期间制定有效政策至关重要.
- 了解公共卫生干预措施的社会经济影响对于全面的政策制定至关重要.
研究的目的:
- 评估谷歌搜索数据在预测COVID-19病例数量的有用性.
- 调查国家制政策与搜索趋势中反映的社会经济指标之间的关联.
主要方法:
- 分析了来自221个国家和地区的谷歌搜索数据,以及报告的COVID-19病例数据.
- 相关性分析以确定对症状的搜索兴趣和报告的病例之间的关系.
- 检查与制政策的严格性相关的社会经济术语 (例如,失业,心理健康) 的搜索趋势.
主要成果:
- 对一般"COVID症状"的搜索兴趣始终与报告的病例相关,而特定症状的搜索显示随着时间的推移相关性正在减少.
- 与COVID-19相关术语的搜索趋势在报告病例增加之前出现,特别是在大流行病的第一年.
- 更严格的制政策与对失业和心理健康的搜索兴趣增加有关,这表明了社会经济后果. 高收入国家显示,与失业有关的搜索数量增加,计划生育搜索数量减少.
结论:
- 谷歌搜索数据为监测和理解COVID-19流行病等公共卫生情况提供了有价值的实时资源.
- 搜索趋势可以作为疾病传播的早期预警系统,并代表公共卫生政策的社会经济影响.
- 这些研究结果突出显示了数字数据在传染病的各个阶段和不同社会经济背景下为政策决策提供信息的潜力.
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