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      Best Practice Guidance for Digital Contact Tracing Apps: A Cross-disciplinary Review of the Literature

      review-article
      , MB BCh BAO, MSc 1 , , BSc, MSc 1 , , PhD 1 , , PhD 1 , , PhD 1 , , PhD 1 , , MD 2 , , BEng, MEng, PhD 3 , , BSc, MB, MA, MD 4 , 5 , , BSc, MB BCh, PhD 4 , 5 , , PhD, MAE, MRIA 1 , 6 , , BM, BS, BEng, MSc 2 , , BA, BAI, MSc, PhD 1 , , PhD 1 , , BTech, MSc 1 , , BSc, MSc, PhD 1 , , PhD 7 , , PhD 1 , , PhD 1 , , PhD 8 , , PhD 1 , , BEng, MB BCh BAO, MEng, MD, PhD 1 , 4 , 5 ,
      (Reviewer), (Reviewer)
      JMIR mHealth and uHealth
      JMIR Publications
      digital contact tracing, automated contact tracing, COVID-19, SARS-CoV-2, mHealth, mobile app, app, tracing, monitoring, surveillance, review, best practice, design

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Digital contact tracing apps have the potential to augment contact tracing systems and disrupt COVID-19 transmission by rapidly identifying secondary cases prior to the onset of infectiousness and linking them into a system of quarantine, testing, and health care worker case management. The international experience of digital contact tracing apps during the COVID-19 pandemic demonstrates how challenging their design and deployment are.

          Objective

          This study aims to derive and summarize best practice guidance for the design of the ideal digital contact tracing app.

          Methods

          A collaborative cross-disciplinary approach was used to derive best practice guidance for designing the ideal digital contact tracing app. A search of the indexed and gray literature was conducted to identify articles describing or evaluating digital contact tracing apps. MEDLINE was searched using a combination of free-text terms and Medical Subject Headings search terms. Gray literature sources searched were the World Health Organization Institutional Repository for Information Sharing, the European Centre for Disease Prevention and Control publications library, and Google, including the websites of many health protection authorities. Articles that were acceptable for inclusion in this evidence synthesis were peer-reviewed publications, cohort studies, randomized trials, modeling studies, technical reports, white papers, and media reports related to digital contact tracing.

          Results

          Ethical, user experience, privacy and data protection, technical, clinical and societal, and evaluation considerations were identified from the literature. The ideal digital contact tracing app should be voluntary and should be equitably available and accessible. User engagement could be enhanced by small financial incentives, enabling users to tailor aspects of the app to their particular needs and integrating digital contact tracing apps into the wider public health information campaign. Adherence to the principles of good data protection and privacy by design is important to convince target populations to download and use digital contact tracing apps. Bluetooth Low Energy is recommended for a digital contact tracing app's contact event detection, but combining it with ultrasound technology may improve a digital contact tracing app's accuracy. A decentralized privacy-preserving protocol should be followed to enable digital contact tracing app users to exchange and record temporary contact numbers during contact events. The ideal digital contact tracing app should define and risk-stratify contact events according to proximity, duration of contact, and the infectiousness of the case at the time of contact. Evaluating digital contact tracing apps requires data to quantify app downloads, use among COVID-19 cases, successful contact alert generation, contact alert receivers, contact alert receivers that adhere to quarantine and testing recommendations, and the number of contact alert receivers who subsequently are tested positive for COVID-19. The outcomes of digital contact tracing apps' evaluations should be openly reported to allow for the wider public to review the evaluation of the app.

          Conclusions

          In conclusion, key considerations and best practice guidance for the design of the ideal digital contact tracing app were derived from the literature.

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          Most cited references192

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          A Novel Coronavirus from Patients with Pneumonia in China, 2019

          Summary In December 2019, a cluster of patients with pneumonia of unknown cause was linked to a seafood wholesale market in Wuhan, China. A previously unknown betacoronavirus was discovered through the use of unbiased sequencing in samples from patients with pneumonia. Human airway epithelial cells were used to isolate a novel coronavirus, named 2019-nCoV, which formed a clade within the subgenus sarbecovirus, Orthocoronavirinae subfamily. Different from both MERS-CoV and SARS-CoV, 2019-nCoV is the seventh member of the family of coronaviruses that infect humans. Enhanced surveillance and further investigation are ongoing. (Funded by the National Key Research and Development Program of China and the National Major Project for Control and Prevention of Infectious Disease in China.)
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            Temporal dynamics in viral shedding and transmissibility of COVID-19

            We report temporal patterns of viral shedding in 94 patients with laboratory-confirmed COVID-19 and modeled COVID-19 infectiousness profiles from a separate sample of 77 infector-infectee transmission pairs. We observed the highest viral load in throat swabs at the time of symptom onset, and inferred that infectiousness peaked on or before symptom onset. We estimated that 44% (95% confidence interval, 25-69%) of secondary cases were infected during the index cases' presymptomatic stage, in settings with substantial household clustering, active case finding and quarantine outside the home. Disease control measures should be adjusted to account for probable substantial presymptomatic transmission.
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              Quantifying SARS-CoV-2 transmission suggests epidemic control with digital contact tracing

              The newly emergent human virus SARS-CoV-2 is resulting in high fatality rates and incapacitated health systems. Preventing further transmission is a priority. We analyzed key parameters of epidemic spread to estimate the contribution of different transmission routes and determine requirements for case isolation and contact-tracing needed to stop the epidemic. We conclude that viral spread is too fast to be contained by manual contact tracing, but could be controlled if this process was faster, more efficient and happened at scale. A contact-tracing App which builds a memory of proximity contacts and immediately notifies contacts of positive cases can achieve epidemic control if used by enough people. By targeting recommendations to only those at risk, epidemics could be contained without need for mass quarantines (‘lock-downs’) that are harmful to society. We discuss the ethical requirements for an intervention of this kind.
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                Author and article information

                Contributors
                Journal
                JMIR Mhealth Uhealth
                JMIR Mhealth Uhealth
                JMU
                JMIR mHealth and uHealth
                JMIR Publications (Toronto, Canada )
                2291-5222
                June 2021
                7 June 2021
                7 June 2021
                : 9
                : 6
                : e27753
                Affiliations
                [1 ] Lero, Science Foundation Ireland Research Centre for Software University of Limerick Limerick Ireland
                [2 ] School of Medicine University of Limerick Limerick Ireland
                [3 ] Department of Nursing and Midwifery University of Limerick Limerick Ireland
                [4 ] School of Medicine National University of Ireland Galway Galway Ireland
                [5 ] University Hospital Galway, Saolta, Health Services Executive Galway Ireland
                [6 ] School of Computing and Communications The Open University Milton Keynes United Kingdom
                [7 ] School of Mathematics, Statistics and Applied Mathematics National University of Ireland Galway Galway Ireland
                [8 ] School of Psychology National University of Ireland Galway Galway Ireland
                Author notes
                Corresponding Author: Derek O'Keeffe derek.okeeffe@ 123456nuigalway.ie
                Author information
                https://orcid.org/0000-0003-1553-4489
                https://orcid.org/0000-0003-0645-9253
                https://orcid.org/0000-0003-1584-5447
                https://orcid.org/0000-0001-6928-6746
                https://orcid.org/0000-0002-6580-0311
                https://orcid.org/0000-0001-9193-2863
                https://orcid.org/0000-0002-6153-9363
                https://orcid.org/0000-0002-2116-8078
                https://orcid.org/0000-0002-1246-9573
                https://orcid.org/0000-0001-9524-4021
                https://orcid.org/0000-0002-3476-053X
                https://orcid.org/0000-0002-8450-186X
                https://orcid.org/0000-0001-7329-0617
                https://orcid.org/0000-0003-4351-1487
                https://orcid.org/0000-0002-5766-6650
                https://orcid.org/0000-0002-5493-2837
                https://orcid.org/0000-0002-4975-444X
                https://orcid.org/0000-0003-1601-0900
                https://orcid.org/0000-0002-1686-7413
                https://orcid.org/0000-0001-5476-1348
                https://orcid.org/0000-0003-3134-5469
                https://orcid.org/0000-0001-8501-2382
                Article
                v9i6e27753
                10.2196/27753
                8189288
                34003764
                85b3e16b-2e0e-4680-9fb4-6fb9669ddafb
                ©James O'Connell, Manzar Abbas, Sarah Beecham, Jim Buckley, Muslim Chochlov, Brian Fitzgerald, Liam Glynn, Kevin Johnson, John Laffey, Bairbre McNicholas, Bashar Nuseibeh, Michael O'Callaghan, Ian O'Keeffe, Abdul Razzaq, Kaavya Rekanar, Ita Richardson, Andrew Simpkin, Cristiano Storni, Damyanka Tsvyatkova, Jane Walsh, Thomas Welsh, Derek O'Keeffe. Originally published in JMIR mHealth and uHealth (https://mhealth.jmir.org), 07.06.2021.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mHealth and uHealth, is properly cited. The complete bibliographic information, a link to the original publication on https://mhealth.jmir.org/, as well as this copyright and license information must be included.

                History
                : 4 February 2021
                : 26 February 2021
                : 17 March 2021
                : 5 April 2021
                Categories
                Review
                Review

                digital contact tracing,automated contact tracing,covid-19,sars-cov-2,mhealth,mobile app,app,tracing,monitoring,surveillance,review,best practice,design

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