This study examined the temporal aspect of COVID-19-related health-seeking behavior in Metro Manila, National Capital Region, Philippines through a network density analysis of Google Trends data. A total of 15 keywords across five categories (English symptoms, Filipino symptoms, face wearing, quarantine, and new normal) were examined using both 15-day and 30-day rolling windows from March 2020 to March 2021. The methodology involved constructing network graphs using distance correlation coefficients at varying thresholds (0.4, 0.5, 0.6, and 0.8) and analyzing the time-series data of network density and clustering coefficients. Results revealed three key findings: (1) an inverse relationship between the threshold values and network metrics, indicating that higher thresholds provide more meaningful keyword relationships; (2) exceptionally high network connectivity during the initial pandemic months followed by gradual decline; and (3) distinct patterns in keyword relationships, transitioning from policy-focused searches to more symptom-specific queries as the pandemic temporally progressed. The 30-day window analysis showed more stable, but less search activities compared to the 15-day windows, suggesting stronger correlations in immediate search behaviors. These insights are helpful for health communication because it emphasizes the need of a strategic and conscientious information dissemination from the government or the private sector based on the networked search behavior (e.g. prioritizing to inform select symptoms rather than an overview of what the coronavirus is).

翻译：本研究通过网络密度分析，利用谷歌趋势数据考察了菲律宾国家首都区马尼拉大都会与COVID-19相关的健康寻求行为的时间特征。研究选取了五大类别（英文症状、菲律宾语症状、佩戴口罩、隔离措施及新常态）共15个关键词，采用15天和30天滚动窗口，分析了2020年3月至2021年3月的数据。方法包括基于不同阈值（0.4、0.5、0.6和0.8）的距离相关系数构建网络图，并分析网络密度与聚类系数的时间序列数据。结果揭示了三个主要发现：（1）阈值与网络指标呈负相关关系，表明较高阈值能提供更具意义的关键词关联；（2）疫情初期网络连通性异常高，随后逐渐下降；（3）关键词关联呈现明显模式转变，随着疫情发展，搜索重点从政策导向逐渐转向症状特异性查询。30天窗口分析显示出比15天窗口更稳定但搜索活动较少的特征，表明即时搜索行为中存在更强的相关性。这些发现对健康传播具有启示意义，强调政府或私营部门需基于网络化搜索行为（例如优先通报特定症状而非泛泛介绍冠状病毒概况），进行战略性和审慎的信息发布。