论文标题
使用搜索引擎查询在英格兰的COVID19案例计数中提供区域异常的早期指示
Providing early indication of regional anomalies in COVID19 case counts in England using search engine queries
论文作者
论文摘要
Covid19于2020年1月底首次在英格兰报道，并于6月中旬报告了15万例。我们假设，与类似流感的疾病类似，患有Covid19的人可能会在进入医疗系统之前（或代替该疾病）来查询其症状。因此，我们分析了英格兰用户对BING的搜索，确定了在该国特定地区发生意外症状搜索中意外增加的情况。我们的分析表明，搜索“发烧”和“咳嗽”与未来的案例计数最相关，而案例计数之前的搜索为16-17天。搜索模式中意外的上升预测了未来的案例计数在一周内乘以2.5或更多，到达曲线下的区域（AUC）为0.64。预测死亡率的类似上升在3周的交货时间内约为0.61。因此，我们的指标提供了英格兰公共卫生的指示，可以用来计划对Covid19的反应，并可能被用来检测其他病原体的区域异常。
COVID19 was first reported in England at the end of January 2020, and by mid-June over 150,000 cases were reported. We assume that, similarly to influenza-like illnesses, people who suffer from COVID19 may query for their symptoms prior to accessing the medical system (or in lieu of it). Therefore, we analyzed searches to Bing from users in England, identifying cases where unexpected rises in relevant symptom searches occurred at specific areas of the country. Our analysis shows that searches for "fever" and "cough" were the most correlated with future case counts, with searches preceding case counts by 16-17 days. Unexpected rises in search patterns were predictive of future case counts multiplying by 2.5 or more within a week, reaching an Area Under Curve (AUC) of 0.64. Similar rises in mortality were predicted with an AUC of approximately 0.61 at a lead time of 3 weeks. Thus, our metric provided Public Health England with an indication which could be used to plan the response to COVID19 and could possibly be utilized to detect regional anomalies of other pathogens.
