ArticleJMIR mHealth and uHealth2020
Evaluation of the Design and Implementation of a Peer-To-Peer COVID-19 Contact Tracing Mobile App (COCOA) in Japan.
Article in JMIR mHealth and uHealth, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 3 of them syntheses that pooled it.
What it found
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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.
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.
Who cites it
21 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- The role of digital tools and emerging devices in COVID-19 contact tracing during the first 18 months of the pandemic: a systematic review.European journal of public health · 2024Pooled it
- A Systematic Review of Health Management Mobile Applications in COVID-19 Pandemic: Features, Advantages, and Disadvantages.BioMed research international · 2024Pooled it
- Digital Contact Tracing Applications against COVID-19: A Systematic Review.Medical principles and practice : international journal of the Kuwait University, Health Science Centre · 2022Pooled it
- Participant Contributions to Person-Generated Health Data Research Using Mobile Devices: Scoping Review.Journal of medical Internet research · 2025Article
- Survey of Citizens' Preferences for Combined Contact Tracing App Features During a Pandemic: Conjoint Analysis.JMIR public health and surveillance · 2024Article
- [Comparative Analysis of International Coronavirus Disease 2019 Contact-Tracing, Isolation, and Quarantine (TIQ) Policies and Simulation of Policy Effects].Jugan geon-gang gwa jilbyeong · 2024Article
- Digital Public Health Solutions in Response to the COVID-19 Pandemic: Comparative Analysis of Contact Tracing Solutions Deployed in Japan and Germany.Journal of medical Internet research · 2023Article
- The Implications of Using Digital Technologies in the Management of COVID-19: Comparative Study of Japan and South Korea.Journal of medical Internet research · 2023Article
- Factors associated with acceptance of a digital contact tracing application for COVID-19 in the Japanese working-age population.Nagoya journal of medical science · 2023Article
- Modeling Adoption, Security, and Privacy of COVID-19 Apps: Findings and Recommendations From an Empirical Study Using the Unified Theory of Acceptance and Use of Technology.JMIR human factors · 2022Article
- Mobile health technology as a solution to self-control problems: The behavioral impact of COVID-19 contact tracing apps in Japan.Social science & medicine (1982) · 2022Article
- Public Attitudes Regarding Trade-offs Between the Functional Aspects of a Contact-Confirming App for COVID-19 Infection Control and the Benefits to Individuals and Public Health: Cross-sectional Survey.JMIR formative research · 2022Article
- The medical and societal impact of big data analytics and artificial intelligence applications in combating pandemics: A review focused on Covid-19.Social science & medicine (1982) · 2022Review
- Analytical mapping of information and communication technology in emerging infectious diseases using CiteSpace.Telematics and informatics · 2022Review
- QoS-Aware Smart Phone-Based User Tracking Application to Prevent Outbreak of COVID-19 in Saudi Arabia.Computational intelligence and neuroscience · 2022Article
- Effect of commuting on the risk of COVID-19 and COVID-19-induced anxiety in Japan, December 2020.Archives of public health = Archives belges de sante publique · 2021Article
- Industry and workplace characteristics associated with the downloading of a COVID-19 contact tracing app in Japan: a nation-wide cross-sectional study.Environmental health and preventive medicine · 2021Article
- Prosociality and the Uptake of COVID-19 Contact Tracing Apps: Survey Analysis of Intergenerational Differences in Japan.JMIR mHealth and uHealth · 2021Article
- Digital contact tracing, community uptake, and proximity awareness technology to fight COVID-19: a systematic review.Sustainable cities and society · 2021Article
- Best Practice Guidance for Digital Contact Tracing Apps: A Cross-disciplinary Review of the Literature.JMIR mHealth and uHealth · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We evaluate a Bluetooth-based mobile contact-confirming app, COVID-19 Contact-Confirming Application (COCOA), which is being used in Japan to contain the spread of COVID-19, the disease caused by the novel virus termed SARS-COV-2. The app prioritizes the protection of users' privacy from a variety of parties (eg, other users, potential attackers, and public authorities), enhances the capacity to balance the current load of excessive pressure on health care systems (eg, local triage of exposure risk and reduction of in-person hospital visits), increases the speed of responses to the pandemic (eg, automated recording of close contact based on proximity), and reduces operation errors and population mobility. The peer-to-peer framework of COCOA is intended to provide the public with dynamic and credible updates on the COVID-19 pandemic without sacrificing the privacy of their information. However, cautions must be exercised to address critical concerns, such as the rate of participation and delays in data sharing. The results of a simulation imply that the participation rate in Japan needs to be close 90% to effectively control the spread of COVID-19.
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Registered trials
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.