ArticleJMIR mHealth and uHealth2018
A New Influenza-Tracking Smartphone App (Flu-Report) Based on a Self-Administered Questionnaire: Cross-Sectional Study.
Article in JMIR mHealth and uHealth, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 2 of them syntheses that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
11 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Facilitators and barriers of mHealth interventions during the Covid-19 pandemic: systematic review.BMC health services research · 2023Pooled it
- What are the characteristics of participatory surveillance systems for influenza-like-illness?Journal of global health · 2023Pooled it
- A multi-method analytical approach to predicting young adults' intention to invest in mHealth during the COVID-19 pandemic.Telematics and informatics · 2022Article
- Mobile technology: A tool for healthcare and a boon in pandemic.Journal of family medicine and primary care · 2022Review
- Association between influenza and the incidence rate of new-onset type 1 diabetes in Japan.Journal of diabetes investigation · 2021Article
- Using Mobile Phone Data to Estimate the Relationship between Population Flow and Influenza Infection Pathways.International journal of environmental research and public health · 2021Article
- Evaluating an app-guided self-test for influenza: lessons learned for improving the feasibility of study designs to evaluate self-tests for respiratory viruses.BMC infectious diseases · 2021Article
- An Overview of Commercially Available Apps in the Initial Months of the COVID-19 Pandemic.Frontiers in psychiatry · 2021Article
- A scope of mobile health solutions in COVID-19 pandemics.Informatics in medicine unlocked · 2021Review
- Participatory Surveillance Based on Crowdsourcing During the Rio 2016 Olympic Games Using the Guardians of Health Platform: Descriptive Study.JMIR public health and surveillance · 2020Article
- The Fever Coach Mobile App for Participatory Influenza Surveillance in Children: Usability Study.JMIR mHealth and uHealth · 2019Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundInfluenza 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.
objectiveThis 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.
methodsFlu-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).
resultsInformation 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.
conclusionsFlu-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.
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