A New Influenza-Tracking Smartphone App (Flu-Report) Based on a Self-Administered Questionnaire: Cross-Sectional Study.
A New Influenza-Tracking Smartphone App (Flu-Report) Based on a Self-Administered Questionnaire: Cross-Sectional Study.
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DOI：
10.2196/mhealth.9834
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发表时间：
2018-06-06
影响因子：
5
通讯作者：
Naito T
中科院分区：
文献类型：
--
作者：
Fujibayashi K;Takahashi H;Tanei M;Uehara Y;Yokokawa H;Naito T
流感感染可以迅速传播，流感爆发是全球主要的公共卫生问题。早期发现流感大流行的迹象对防止全球爆发非常重要。用于流感监测的信息和通信技术，包括有非专业用户参与的监测系统的开发最近有所增加。这些系统中的许多系统可以比传统的流感监测系统更快地估计流感活动。不幸的是，日本几乎没有这种流感追踪系统。本研究旨在评估流感报告的流感跟踪能力，流感报告是一种新的流感跟踪移动的手机应用程序，使用自填问卷进行流感活动的早期检测。流感报告用于收集2016年11月至2017年3月期间的流感相关信息（即，诊断流感感染的日期）。参与者是来自日本各地的成年志愿者，他们还提供了有关同居家庭成员的信息。通过与传统流感监测信息和现有大规模流感跟踪系统（基于处方药购买电子记录的自动监测系统）的基本信息进行比较，评估了Flu-Report的实用性。通过流感报告获得了约10，094名志愿者的信息。共有2134名参与者年龄<20岁，6958名年龄在20-59岁之间，1002名年龄≥60岁。在2016年11月至2017年3月期间，有347名参与者报告他们在2016年流感季节患有流感或流感样疾病。流感报告衍生的流感感染时间序列数据显示与从现有流感监测系统获得的基本信息具有良好的相关性（rho，ρ=.65，P=.001）。然而，我们参与者的流感发病率约为日本人群平均流感发病率的25%。<20岁人群流感报告发病率为5.06%（108/2134），20-59岁人群为3.16%（220/6958），≥60岁人群为0.59%（6/1002）。相比之下，日本年龄<20岁、20-59岁和≥60岁人群的流感发病率最近估计分别为31.97%至37.90%、8.16%至9.07%和2.71%至4.39%。Flu-Report支持通过收集自填问卷，轻松获取有关流感活动的近实时信息。然而，流感报告用户可能会受到选择偏差的影响，这是一个与使用信息和通信技术进行监测相关的常见问题。尽管如此，流感报告有可能提供有助于检测流感爆发的基本数据。
Influenza infections can spread rapidly, and influenza outbreaks are a major public health concern worldwide. Early detection of signs of an influenza pandemic is important to prevent global outbreaks. Development of information and communications technologies for influenza surveillance, including participatory surveillance systems involving lay users, has recently increased. Many of these systems can estimate influenza activity faster than the conventional influenza surveillance systems. Unfortunately, few of these influenza-tracking systems are available in Japan. This study aimed to evaluate the flu-tracking ability of Flu-Report, a new influenza-tracking mobile phone app that uses a self-administered questionnaire for the early detection of influenza activity. Flu-Report was used to collect influenza-related information (ie, dates on which influenza infections were diagnosed) from November 2016 to March 2017. Participants were adult volunteers from throughout Japan, who also provided information about their cohabiting family members. The utility of Flu-Report was evaluated by comparison with the conventional influenza surveillance information and basic information from an existing large-scale influenza-tracking system (an automatic surveillance system based on electronic records of prescription drug purchases). Information was obtained through Flu-Report for approximately 10,094 volunteers. In total, 2134 participants were aged <20 years, 6958 were aged 20-59 years, and 1002 were aged ≥60 years. Between November 2016 and March 2017, 347 participants reported they had influenza or an influenza-like illness in the 2016 season. Flu-Report-derived influenza infection time series data displayed a good correlation with basic information obtained from the existing influenza surveillance system (rho, ρ=.65, P=.001). However, the influenza morbidity ratio for our participants was approximately 25% of the mean influenza morbidity ratio for the Japanese population. The Flu-Report influenza morbidity ratio was 5.06% (108/2134) among those aged <20 years, 3.16% (220/6958) among those aged 20-59 years, and 0.59% (6/1002) among those aged ≥60 years. In contrast, influenza morbidity ratios for Japanese individuals aged <20 years, 20-59 years, and ≥60 years were recently estimated at 31.97% to 37.90%, 8.16% to 9.07%, and 2.71% to 4.39%, respectively. Flu-Report supports easy access to near real-time information about influenza activity via the accumulation of self-administered questionnaires. However, Flu-Report users may be influenced by selection bias, which is a common issue associated with surveillance using information and communications technologies. Despite this, Flu-Report has the potential to provide basic data that could help detect influenza outbreaks.