Causal Relationships Among Pollen Counts, Tweet Numbers, and Patient Numbers for Seasonal Allergic Rhinitis Surveillance: Retrospective Analysis
Causal Relationships Among Pollen Counts, Tweet Numbers, and Patient Numbers for Seasonal Allergic Rhinitis Surveillance: Retrospective Analysis
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DOI：
10.2196/10450
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发表时间：
2019-02-20
影响因子：
7.4
通讯作者：
Aramaki, Eiji
中科院分区：
文献类型：
--
作者：
Wakamiya, Shoko;Matsune, Shoji;Aramaki, Eiji
背景资料：与健康相关的社交媒体数据越来越多地用于疾病监测研究，这些研究表明社交媒体帖子数量与患者数量之间存在适度的高度相关性。然而，有必要了解社交媒体用户的行为和实际患者数量之间的因果关系，以增加基于社交媒体数据的疾病监测的可信度。目的：本研究旨在阐明花粉计数、社交媒体用户的发帖行为和真实的世界中季节性变应性鼻炎患者数量之间的因果关系。该分析使用花粉计数、鸣叫次数和日本神奈川县季节性过敏性鼻炎患者人数的数据集进行。我们从2017年2月1日至5月31日检查了日本雪松（日本季节性过敏性鼻炎的主要原因）和扁柏（通常使季节性过敏性鼻炎复杂化）的每日花粉计数。包括关键字“kafunsho”（或季节性过敏性鼻炎）的每日推文数量是在2017年1月1日至5月31日期间计算的。2017年1月1日至5月31日期间，从参与研究的三家医疗机构获得了季节性过敏性鼻炎患者的每日人数。使用格兰杰因果关系检验来检查2017年2月至5月期间花粉计数、推文数量和季节性过敏性鼻炎患者数量之间的因果关系。为了确定是否随时间变化的因素影响这些因果关系，我们分析了主要的季节性过敏性鼻炎阶段（2月至4月）时，日本杉树积极生产和释放pollones.Results：花粉计数的增加被发现增加的鸣叫的数量在整个研究期间（P= 0.04），但不是主要的季节性过敏性鼻炎阶段（P= 0.05）。相比之下，研究期间（P= 0.04）和主要季节性过敏性鼻炎阶段（P= 0.01）的花粉计数增加会增加患者数量。在主要的季节性过敏性鼻炎阶段，推特数量的增加增加了患者数量（P= 0.02），但在整个研究期间没有增加（P= 0.89）。患者数量并没有影响在整个研究期间（P=.24）和主要季节性过敏性鼻炎阶段（P=.47）的鸣叫数量。结论：了解花粉计数，鸣叫数量和季节性过敏性鼻炎患者数量之间的因果关系是增加使用社交媒体数据的监测系统的可信度的重要一步。需要进一步深入研究，以确定本探索性分析中描述的社交媒体帖子的决定因素。
Background: Health-related social media data are increasingly used in disease-surveillance studies, which have demonstrated moderately high correlations between the number of social media posts and the number of patients. However, there is a need to understand the causal relationship between the behavior of social media users and the actual number of patients in order to increase the credibility of disease surveillance based on social media data.Objective: This study aimed to clarify the causal relationships among pollen count, the posting behavior of social media users, and the number of patients with seasonal allergic rhinitis in the real world.Methods: This analysis was conducted using datasets of pollen counts, tweet numbers, and numbers of patients with seasonal allergic rhinitis from Kanagawa Prefecture, Japan. We examined daily pollen counts for Japanese cedar (the major cause of seasonal allergic rhinitis in Japan) and hinoki cypress (which commonly complicates seasonal allergic rhinitis) from February 1 to May 31, 2017. The daily numbers of tweets that included the keyword "kafunsho" (or seasonal allergic rhinitis) were calculated between January 1 and May 31, 2017. Daily numbers of patients with seasonal allergic rhinitis from January 1 to May 31, 2017, were obtained from three healthcare institutes that participated in the study. The Granger causality test was used to examine the causal relationships among pollen count, tweet numbers, and the number of patients with seasonal allergic rhinitis from February to May 2017. To determine if time-variant factors affect these causal relationships, we analyzed the main seasonal allergic rhinitis phase (February to April) when Japanese cedar trees actively produce and release pollen.Results: Increases in pollen count were found to increase the number of tweets during the overall study period (P=.04), but not the main seasonal allergic rhinitis phase (P=.05). In contrast, increases in pollen count were found to increase patient numbers in both the study period (P=.04) and the main seasonal allergic rhinitis phase (P=.01). Increases in the number of tweets increased the patient numbers during the main seasonal allergic rhinitis phase (P=.02), but not the overall study period (P=.89). Patient numbers did not affect the number of tweets in both the overall study period (P=.24) and the main seasonal allergic rhinitis phase (P=.47).Conclusions: Understanding the causal relationships among pollen counts, tweet numbers, and numbers of patients with seasonal allergic rhinitis is an important step to increasing the credibility of surveillance systems that use social media data. Further in-depth studies are needed to identify the determinants of social media posts described in this exploratory analysis.