%0期刊文章%@ 2369-2960 %I JMIR出版物%V 7% 卡塔尔世界杯8强波胆分析N 12% P e31961 %T分析芬兰公民和卫生保健专业人员在COVID-19大流行期间对嗅觉/味觉障碍和冠状病毒的搜索:使用数据库日志的信息流行病学方法%A Mukka,Milla %A Pesälä，Samuli %A Hammer,Charlotte %A Mustonen,Pekka %A Jormanainen,Vesa %A Pelttari,Hanna %A Kaila,Minna %A Helve,Otto %+赫尔辛基大学Temppelikatu 17 A 5，赫尔辛基，00100，芬兰，358 0504397177，milla.mukka@helsinki.fi %K COVID-19 %K SARS-CoV-2 %K嗅觉障碍%K味觉障碍%K信息寻求行为%K卫生人员%K统计模型%K医学信息学%D 2021 %7 7.12.2021 %9原始论文%J JMIR公共卫生监测%G英语%X背景:COVID-19大流行已经流行了一年多，已经利用冠状病毒的日志和登记数据建立了大流行检测模型。然而，许多来源包含关于COVID-19及其症状的不可靠健康信息，平台无法描述执行搜索的用户的特征。先前的研究评估了来自通用搜索引擎的症状搜索(谷歌/谷歌趋势)。目前尚不清楚公民和卫生保健专业人员(HCPs)使用的专用互联网数据库中关于嗅觉/味觉障碍和冠状病毒的建模日志数据如何加强疾病监测。我们的材料和方法提供了一种新的方法来分析基于网络的信息，以检测传染病的爆发。目的:本研究的目的是(1)评估公民和专业人员对嗅觉/味觉障碍和冠状病毒的搜索是否与COVID-19病例的流行病学数据相关，以及(2)测试我们的负二项回归模型(即，纳入病例计数是否可以改善模型)。方法:我们收集了2019年12月30日至2020年11月30日(49周)期间与COVID-19(嗅觉/味觉障碍，冠状病毒)相关的每周搜索日志数据。在芬兰使用了两个主要的医疗互联网数据库:健康图书馆(HL)，一个面向公民的免费门户网站，以及医生数据库(PD)，一个广泛用于卫生保健中心的数据库。 Log data from databases were combined with register data on the numbers of COVID-19 cases reported in the Finnish National Infectious Diseases Register. We used negative binomial regression modeling to assess whether the case numbers could explain some of the dynamics of searches when plotting database logs. Results: We found that coronavirus searches drastically increased in HL (0 to 744,113) and PD (4 to 5375) prior to the first wave of COVID-19 cases between December 2019 and March 2020. Searches for smell disorders in HL doubled from the end of December 2019 to the end of March 2020 (2148 to 4195), and searches for taste disorders in HL increased from mid-May to the end of November (0 to 1980). Case numbers were significantly associated with smell disorders (P<.001) and taste disorders (P<.001) in HL, and with coronavirus searches (P<.001) in PD. We could not identify any other associations between case numbers and searches in either database. Conclusions: Novel infodemiological approaches could be used in analyzing database logs. Modeling log data from web-based sources was seen to improve the model only occasionally. However, search behaviors among citizens and professionals could be used as a supplementary source of information for infectious disease surveillance. Further research is needed to apply statistical models to log data of the dedicated medical databases. %M 34727525 %R 10.2196/31961 %U https://publichealth.www.mybigtv.com/2021/12/e31961 %U https://doi.org/10.2196/31961 %U http://www.ncbi.nlm.nih.gov/pubmed/34727525