@文章{info:doi/ 10.21960 /32364，作者=“Cai, Owen和Sousa-Pinto, Bernardo”，标题=“COVID-19出现以来的美国流感搜索模式:信息流行病学研究”，期刊=“JMIR公共卫生监测”，年=“2022”，月=“3”，日=“3”，卷=“8”，数=“3”，页=“e32364”，关键词=“COVID-19;流感;监测;媒体报道;谷歌趋势;infodemiology;监控;趋势;美国;寻求信息; online health information", abstract="Background: The emergence and media coverage of COVID-19 may have affected influenza search patterns, possibly affecting influenza surveillance results using Google Trends. Objective: We aimed to investigate if the emergence of COVID-19 was associated with modifications in influenza search patterns in the United States. Methods: We retrieved US Google Trends data (relative number of searches for specified terms) for the topics influenza, Coronavirus disease 2019, and symptoms shared between influenza and COVID-19. We calculated the correlations between influenza and COVID-19 search data for a 1-year period after the first COVID-19 diagnosis in the United States (January 21, 2020 to January 20, 2021). We constructed a seasonal autoregressive integrated moving average model and compared predicted search volumes, using the 4 previous years, with Google Trends relative search volume data. We built a similar model for shared symptoms data. We also assessed correlations for the past 5 years between Google Trends influenza data, US Centers for Diseases Control and Prevention influenza-like illness data, and influenza media coverage data. Results: We observed a nonsignificant weak correlation ($\rho$= --0.171; P=0.23) between COVID-19 and influenza Google Trends data. Influenza search volumes for 2020-2021 distinctly deviated from values predicted by seasonal autoregressive integrated moving average models---for 6 weeks within the first 13 weeks after the first COVID-19 infection was confirmed in the United States, the observed volume of searches was higher than the upper bound of 95{\%} confidence intervals for predicted values. Similar results were observed for shared symptoms with influenza and COVID-19 data. The correlation between Google Trends influenza data and CDC influenza-like-illness data decreased after the emergence of COVID-19 (2020-2021: $\rho$=0.643; 2019-2020: $\rho$=0.902), while the correlation between Google Trends influenza data and influenza media coverage volume remained stable (2020-2021: $\rho$=0.746; 2019-2020: $\rho$=0.707). Conclusions: Relevant differences were observed between predicted and observed influenza Google Trends data the year after the onset of the COVID-19 pandemic in the United States. Such differences are possibly due to media coverage, suggesting limitations to the use of Google Trends as a flu surveillance tool. ", issn="2369-2960", doi="10.2196/32364", url="https://publichealth.www.mybigtv.com/2022/3/e32364", url="https://doi.org/10.2196/32364", url="http://www.ncbi.nlm.nih.gov/pubmed/34878996" }