Evidence map›Paper›PMID 29875082›Full record

ArticleJMIR mHealth and uHealth2018

A New Influenza-Tracking Smartphone App (Flu-Report) Based on a Self-Administered Questionnaire: Cross-Sectional Study.

Kazutoshi Fujibayashi, Hiromizu Takahashi, Mika Tanei, Yuki Uehara, Hirohide Yokokawa, Toshio Naito

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Mobile technology: A tool for healthcare and a boon in pandemic.Journal of family medicine and primary care · 2022
    Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. A scope of mobile health solutions in COVID-19 pandemics.Informatics in medicine unlocked · 2021
    Review
  10. Article
  11. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Kazutoshi Fujibayashi *Department of General Medicine, School of Medicine, Juntendo University, Tokyo, Japan.ORCID http://orcid.org/0000-0002-6580-5139
Hiromizu Takahashi *Department of General Medicine, School of Medicine, Juntendo University, Tokyo, Japan.ORCID http://orcid.org/0000-0002-5055-7937
Mika Tanei *Department of General Medicine, School of Medicine, Juntendo University, Tokyo, Japan.ORCID http://orcid.org/0000-0001-6009-1344
Yuki Uehara *Department of General Medicine, School of Medicine, Juntendo University, Tokyo, Japan.ORCID http://orcid.org/0000-0003-1014-8888
Hirohide YokokawaDepartment of General Medicine, School of Medicine, Juntendo University, Tokyo, Japan.ORCID http://orcid.org/0000-0001-9464-9828
Toshio NaitoDepartment of General Medicine, School of Medicine, Juntendo University, Tokyo, Japan.ORCID http://orcid.org/0000-0003-1646-9930

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

epidemiologyinfluenzainternetpandemicsparticipatory epidemiologyparticipatory surveillance

Identifiers

PMID29875082
PMCPMC6010834

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.