Use of Bluetooth contact tracing technology to model COVID-19 quarantine policies in high-risk closed populations.

Containment measures in high-risk closed settings, like migrant worker (MW) dormitories, are critical for mitigating emerging infectious disease outbreaks and protecting potentially vulnerable populations in outbreaks such as coronavirus disease 2019 (COVID-19). The direct impact of social distancing measures can be assessed through wearable contact tracing devices. Here, we developed an individual-based model using data collected through a Bluetooth wearable device that collected 33.6M and 52.8M contact events in two dormitories in Singapore, one apartment style and the other a barrack style, to assess the impact of measures to reduce the social contact of cases and their contacts. The simulation of highly detailed contact networks accounts for different infrastructural levels, including room, floor, block, and dormitory, and intensity in terms of being regular or transient. Via a branching process model, we then simulated outbreaks that matched the prevalence during the COVID-19 outbreak in the two dormitories and explored alternative scenarios for control. We found that strict isolation of all cases and quarantine of all contacts would lead to very low prevalence but that quarantining only regular contacts would lead to only marginally higher prevalence but substantially fewer total man-hours lost in quarantine. Reducing the density of contacts by 30% through the construction of additional dormitories was modelled to reduce the prevalence by 14 and 9% under smaller and larger outbreaks, respectively. Wearable contact tracing devices may be used not just for contact tracing efforts but also to inform alternative containment measures in high-risk closed settings.

Views and Needs of Students, Parents, and Teachers on Closed-Circuit Television, Proximity Trackers, and Access Cards to Facilitate COVID-19 Contact Tracing in Schools: Thematic Analysis of Focus Groups and Interviews.

BACKGROUND: Contact tracing is considered a key measure in preventing the spread of infectious diseases. Governments around the world adopted contact tracing to limit the spread of COVID-19 in schools. Contact tracing tools utilizing digital technology (eg, GPS chips, Bluetooth radios) can increase efficiency compared to manual methods. However, these technologies can introduce certain privacy challenges in relation to retention, tracking, and the using and sharing of personal data, and little is known about their applicability in schools. OBJECTIVE: This is the second of two studies exploring the potential of digital tools and systems to help schools deal with the practical challenges of preventing and coping with an outbreak of COVID-19. The aim was to explore the views, needs, and concerns among secondary school stakeholders (parents, teachers, pupils) regarding the implementation of three digital tools for contact tracing: access cards, proximity tracking, and closed-circuit television (CCTV). METHODS: Focus groups and interviews were conducted with secondary school students, parents, and teachers. The topic guide was informed by the Unified Theory of Technology and Acceptance. Data-driven and theory-driven approaches were combined to identify themes and subthemes. RESULTS: We recruited 22 participants. Findings showed that there is no single solution that is suitable for all schools, with each technology option having advantages and limitations. Existing school infrastructure (eg, CCTV and smart/access cards technology) and the geography of each school would determine which tools would be optimal for a particular school. Concerns regarding the cost of installing and maintaining equipment were prominent among all groups. Parents and teachers worried about how the application of these solutions will affect students' right to privacy. Parents also appeared not to have adequate knowledge of the surveillance technologies already available in schools (eg, CCTV). Students, who were mostly aware of the presence of surveillance technologies, were less concerned about any potential threats to their privacy, while they wanted reassurances that any solutions would be used for their intended purposes. CONCLUSIONS: Findings revealed that there is not one tool that would be suitable for every school and the context will determine which tool would be appropriate. This study highlights important ethical issues such as privacy concerns, balancing invasions of privacy against potential benefits, transparency of communication around surveillance technology and data use, and processes of consent. These issues need to be carefully considered when implementing contact tracing technologies in school settings. Communication, transparency, and consent within the school community could lead to acceptance and engagement with the new tools.

Smart Transformative Services to Defuse Crises? The Meaning of Trust for the Usage of Digital Contact Tracing Apps

Smart transformative services such as digital contact tracing apps are a means to offer transformative and economic value by selfmonitoring contacts and improving the well-being of users, while also reducing concerns when using services during pandemics such as COVID-19. In this study, we identify significant factors as well as communication and promotion strategies to encourage digital contact tracing app nonusers to use such apps in order to benefit from their value-creating potential. This research contributes to transformative service literature by identifying digital contact tracing apps as a means to regain confidence in using services during a pandemic, thereby offering transformative and economic value. By integrating two trust dimensions as meaningful mediators, this research sheds light on the conditions under which social influence and Internet privacy concerns influence nonusers' usage intention. Moreover, the results not only identify significant factors influencing intended app usage but also reveal strategies for increasing actual app usage. © 2023 C.H.BECK oHG. All rights reserved.

Identifying the Superspreader in Proactive Backward Contact Tracing by Deep Learning

The goal of proactive contact tracing is to diminish the spread of an epidemic by means of contact tracing mobile apps and big data analysis. Finding superspreaders as has been used in Japan and Australia during the early days of the COVID-19 pandemic has proven effective as backward contact tracing can pick up infections that might otherwise be missed. In this paper, we formulate a proactive contact tracing problem to identify the superspreaders using maximum-likelihood estimation, graph traversal and deep learning algorithms. This problem is challenging due to its sheer combinatorial complexity, problem scale and the fact that the underlying infection network topology is rarely known. We propose a deep learning-based framework using Graph Neural Networks to iteratively refine the supervised learning of proactive contact tracing networks using smaller infection networks and to identify the superspreader. By optimizing the graph traversal and topological features for deep learning, proactive contact tracing strategies can be developed to contain superspreading in an epidemic outbreak.

Attitudes Towards COVID-19 Contact Tracing Apps: A Cross-National Survey

To help prevent the spread of COVID-19, countries around the world have implemented a range of measures and virus containment strategies, including digital contact-tracing (DCT) in the form of smartphone apps. While early studies showed a high level of acceptability of such technologies, the adoption rates varied greatly between countries after contact-tracing apps became available to download. This cross-national user survey (n=871) aims to explore public attitudes and factors that affect user acceptability and adoption of contact-tracing apps in the USA, UK, and the Republic of Ireland, which employ similar underlying technology, but have uneven adoption rates. The results indicate interactions between installation decisions and public trust in actors and institutions communicating COVID-related information, and releasing such technologies. Beyond the immediate case of contact tracing, our findings hold implications for the deployment and communicative framing of technology for public health and the public good, and inform the design of crisis response public health information systems.

Implementation of a Hardware-Assisted Bluetooth-Based COVID-19 Tracking Device in a High School: Mixed Methods Study.

BACKGROUND: Contact tracing is a vital public health tool used to prevent the spread of infectious diseases. However, traditional interview-format contact tracing (TCT) is labor-intensive and time-consuming and may be unsustainable for large-scale pandemics such as COVID-19. OBJECTIVE: In this study, we aimed to address the limitations of TCT. The Yale School of Engineering developed a Hardware-Assisted Bluetooth-based Infection Tracking (HABIT) device. Following the successful implementation of HABIT in a university setting, this study sought to evaluate the performance and implementation of HABIT in a high school setting using an embedded mixed methods design. METHODS: In this pilot implementation study, we first assessed the performance of HABIT using mock case simulations in which we compared contact tracing data collected from mock case interviews (TCT) versus Bluetooth devices (HABIT). For each method, we compared the number of close contacts identified and identification of unique contacts. We then conducted an embedded mixed methods evaluation of the implementation outcomes of HABIT devices using pre- and postimplementation quantitative surveys and qualitative focus group discussions with users and implementers according to the Reach, Effectiveness, Adoption, Implementation, and Maintenance framework. RESULTS: In total, 17 students and staff completed mock case simulations in which 161 close contact interactions were detected by interview or Bluetooth devices. We detected significant differences in the number of close contacts detected by interview versus Bluetooth devices (P<.001), with most (127/161, 78.9%) contacts being reported by interview only. However, a significant number (26/161, 16.1%; P<.001) of contacts were uniquely identified by Bluetooth devices. The interface, ease of use, coherence, and appropriateness were highly rated by both faculty and students. HABIT provided emotional security to users. However, the prototype design and technical difficulties presented barriers to the uptake and sustained use of HABIT. CONCLUSIONS: Implementation of HABIT in a high school was impeded by technical difficulties leading to decreased engagement and adherence. Nonetheless, HABIT identified a significant number of unique contacts not reported by interview, indicating that electronic technologies may augment traditional contact tracing once user preferences are accommodated and technical glitches are overcome. Participants indicated a high degree of acceptance, citing emotional reassurance and a sense of security with the device.

Beyond legislation and technological design: The importance and implications of institutional trust for privacy issues of digital contact tracing.

For proper implementation of digital contact tracing technologies for fighting against SARS-CoV-2, participants' privacy vulnerability and the uncertainty from the relevant institutions' side could be seen as two core elements that should be dealt with, among others. In this paper, we propose to understand the current approaches for preserving privacy, referred to as privacy by legislation and privacy by technological design, as distrusting strategies that primarily work to reduce participants' vulnerability by specifying and implementing privacy standards related to this digital solution. We point out that mere distrusting strategies are insufficient for the ethically appropriate development of this digital solution, nor can they eliminate the need for institutional trust that plays an essential role in fostering voluntary support for this solution. To reach well-grounded trust in both an ethical and epistemological sense, we argue that trust in institutions concerning personal data protection in the case of digital contact tracing ought to be built on the relevant institutions' and individuals' goodwill towards the public and their competence in improving the actual effectiveness of this solution. We conclude by clarifying three dimensions, including the purpose, procedure, and outcome, where the relevant trustees can work to signal and justify their intentions and increase their trustworthiness via an effective communication strategy. Given the complementary qualities shown by the distrusting and trusting strategies, a combined strategy including both sorts seems closer to what we expect from the responsible implementation of this digital solution, which could also improve the effectiveness of this institutional response.

Multi-view POI-level Cellular Trajectory Reconstruction for Digital Contact Tracing of Infectious Diseases

Digital contact tracing is an effective solution to prevent such a pandemic, but the low adoption rate of a required mobile app hinders its effectiveness. A large collection of cellular trajectories from mobile subscribers can be an out-of-the-box solution that is free from the low adoption issue, but has been overlooked due to its low spatial resolution. In this paper, to increase the resolution of this cellular trajectory, we present a new problem that estimates the user's visited places at the point-of-interest(POI) level, which we call POI-level cellular trajectory reconstruction. We propose a novel algorithm, Pincette, that accomplishes more accurate POI reconstruction by leveraging various external data such as road networks and POI contexts. Specifically, Pincette comprises multi-view feature extraction and GCN-LSTM-based POI estimation. In the multi-view feature extraction, Pincette extracts three complementary features from three views: efficiency, periodicity, and popularity. In the GCN-LSTM-based POI estimation, these three views are seamlessly integrated, where spatio-temporal periodic patterns are captured by graph convolutional networks (GCNs) and an LSTM. With extensive experiments on two real data collections of two cities, we show that Pincette outperforms four POI estimation baselines by up to 21.20%. We believe that our work sheds light on the use of cellular trajectories for digital contact tracing. We release the source code at https://github.com/kaist-dmlab/Pincette. © 2022 IEEE.

Tell me who your contacts are, or what can we learn from standard setting in the context of COVID-19 tracing apps

At the beginning of the pandemic, digital contact tracing was a much-hoped-for initiative that spurred a myriad of apps. Despite a great theoretical promise, however, the tool fell short of significant impact and, essentially, came to nothing. The technological development effort has attracted much scholarly and media attention and coverage. This article seeks to contribute to this growing body of knowledge by approaching the topic from a largely unexplored perspective. It examines the emergence of digital contact tracing as a standard setting exercise, focusing on key actors, processes of technical specification development and data protection assessment of technological choices. It also explores the governance attributes of standard settings from the perspective of data protection law. Given a potential of a technical standard to act as a regulatory means, it is proposed that the governance and legitimacy issues should receive much more consideration. It is believed that for a technical solution to stand the competition for a regulatory share and succeed in the future, the values of inclusiveness, transparency, accountability and openness should be meaningfully internalised in the very process of its development. © 2023

On the voluntariness of public health apps: a European case study on digital contact tracing

As evidenced during the COVID-19 pandemic, there is a growing reliance on smartphone apps such as digital contact tracing apps and vaccination passports to respond to and mitigate public health threats. In light of the European Commission's guidance, Member States typically offer such apps on a voluntary, ‘opt-in' basis. In this paper, we question the extent to which the individual choice to use these apps–and similar future technologies–is indeed a voluntary one. By explicating ethical and legal considerations governing the choice situations surrounding the use of smartphone apps, specifically those related to the negative consequences that declining the use of these apps may have (e.g. loss of opportunities, social exclusion, stigma), we argue that the projected downsides of refusal may in effect limit the liberty to decline for certain subpopulations. To mitigate these concerns, we recommend three categories of approaches that may be employed by governments to safeguard voluntariness. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

Assessing the Governance of Digital Contact Tracing in Response to COVID-19: Results of a Multi-National Study.

This paper describes the results of a multi-country survey of governance approaches for the use of digital contact tracing (DCT) in response to the COVID-19 pandemic. We argue that the countries in our survey represent two distinct models of DCT governance, both of which are flawed. The "data protection model" emphasizes privacy protections at the expense of public health benefit, while the "emergency response model" sacrifices transparency and accountability, prompting concerns about excessive governance surveillance. The ethical and effective use of DCT in the future requires a new governance approach that is better suited to this novel use of mobile phone data to promote public health."

Why Govern Broken Tools?

In Assessing the Governance of Digital Contact Tracing in Response to COVID-19: Results of a Multi-National Study, Brian Hutler et al. ably compare two approaches to the governance of digital contract tracing (DCT).1 In this brief essay, I want to examine to what extent governance actually played a meaningful role in the failure of DCT. If DCT failed primarily for other reasons, then the authors' normative suggestion to pursue "a new governance approach … for designing and implementing DCT technology going forward" may be misplaced.

Systematic scoping review of the implementation, adoption, use, and effectiveness of digital contact tracing interventions for COVID-19 in the Western Pacific Region.

A systematic scoping review of digital contact tracing (DCT) interventions for COVID-19 was conducted to describe the implementation, adoption, use and effectiveness of DCT interventions implemented as part of the COVID-19 response in the Western Pacific Region (WPR). A systematic search identified 341 studies and 128 grey literature sources, of which 18 studies and 41 grey literature sources were included. 17 (46%) WPR countries and areas implemented DCT interventions. Adoption ranged from 14.6% to 92.7% in different adult populations and epidemiological contexts. Trust in authorities, and privacy concerns and beliefs, were the most frequent determinants of adoption and use. Only two studies analysed DCT effectiveness, which showed limited to no effectiveness of DCT interventions in low transmission settings. Overall, there is limited evidence available to evaluate the contribution of DCT to mitigating COVID-19 in the WPR. Preparedness for future health emergencies should include developing robust frameworks for DCT effectiveness evaluations.

Feasibility of digital contact tracing in low-income settings - pilot trial for a location-based DCT app.

BACKGROUND: Data about the effectiveness of digital contact tracing are based on studies conducted in countries with predominantly high- or middle-income settings. Up to now, little research is done to identify specific problems for the implementation of such technique in low-income countries. METHODS: A Bluetooth-assisted GPS location-based digital contact tracing (DCT) app was tested by 141 participants during 14 days in a hospital in Monrovia, Liberia in February 2020. The DCT app was compared to a paper-based reference system. Hits between participants and 10 designated infected participants were recorded simultaneously by both methods. Additional data about GPS and Bluetooth adherence were gathered and surveys to estimate battery consumption and app adherence were conducted. DCT apps accuracy was evaluated in different settings. RESULTS: GPS coordinates from 101/141 (71.6%) participants were received. The number of hours recorded by the participants during the study period, true Hours Recorded (tHR), was 496.3 h (1.1% of maximum Hours recordable) during the study period. With the paper-based method 1075 hits and with the DCT app five hits of designated infected participants with other participants have been listed. Differences between true and maximum recording times were due to failed permission settings (45%), data transmission issues (11.3%), of the participants 10.1% switched off GPS and 32.5% experienced other technical or compliance problems. In buildings, use of Bluetooth increased the accuracy of the DCT app (GPS + BT 22.9 m ± 21.6 SD vs. GPS 60.9 m ± 34.7 SD; p = 0.004). GPS accuracy in public transportation was 10.3 m ± 10.05 SD with a significant (p = 0.007) correlation between precision and phone brand. GPS resolution outdoors was 10.4 m ± 4.2 SD. CONCLUSION: In our study several limitations of the DCT together with the impairment of GPS accuracy in urban settings impede the solely use of a DCT app. It could be feasible as a supplement to traditional manual contact tracing. DKRS, DRKS00029327 . Registered 20 June 2020 - Retrospectively registered.

BECT: Beacon-based Contact Tracing for Detecting Direct & Indirect Contacts

Digital Contact tracing with smartphone apps may help control the spread of serious pathogens, such as COVID-19. Such apps typically use peer-to-peer Bluetooth data transfer to record a contact. However, they suffer from low adoption rates, high false alarm contact indications, battery drain, and user privacy concerns. This paper proposes BECT or BEacon-based Contact Tracing, a contact tracing framework using static Bluetooth beacon devices installed in public or private places that periodically broadcast packets to nearby users that are stored as coins. Users that are positively diagnosed submit their coin IDs to a third-party service (e.g., local health authority) which can mark these coins as infected and disseminate them to other users. A match between a user's stored coins and an infected coin implies that the user has come in direct or indirect contact with an infected person. The BECT framework does not expose users' private data and conserves the device battery. We use MATLAB simulations to compare the performance of the BECT framework to phone-phone apps in a restaurant scenario and show that BECT has superior contact tracing performance. We also provide general deployment guidelines. © 2022 IEEE.

Impact of Privacy Messaging on COVID-19 Exposure Notification App Downloads: Evidence From a Randomized Experiment.

Introduction: Digital contact-tracing smartphone apps have the potential to slow the spread of disease but are not widely used. We tested whether messages describing how a COVID-19 digital contact-tracing app protects users' privacy led to increased or decreased intentions to download the app by either calming privacy concerns or increasing their saliency. Design: Randomized controlled trial. Setting/participants: We recruited adult smartphone owners in the U.S. (oversampled for younger adults aged 18-34 years) in November 2020 through an online panel. Intervention: Survey software randomly assigned 860 participants to 1 of 2 parallel messaging conditions (n=430 privacy assured, n=430 no privacy described). Main outcome measures: 4-point scale of intention to use the app "if public health officials released a COVID Exposure Notification app in their state" that averaged likelihood to (1) download and install the app on their phone; (2) keep the app active on their phone; and (3) keep Bluetooth active on their phone (needed for the app to work). Results: After removing incompletes, those who failed the manipulation checks, or those who had already downloaded a COVID-19 digital contact-tracing app, we analyzed 671 participants (n=330 privacy, n=341 no privacy) in 2021. There was no relationship between privacy condition and download intention (meanprivacy=2.69, meannoprivacy=2.69, b=0.01, 95% CI= -0.13, 0.15, p=0.922) but also no evidence that describing the app's security increased context-dependent privacy concerns (measured 3 ways). Instead, we found increased endorsement of data security in the privacy condition using a scale of beliefs about the app keeping privacy secure (meanprivacy=2.74, meannoprivacy=2.58, b=0.16, 95% CI=0.04, 0.28, p=0.009, small effect ω2=0.009). Conclusions: This study provides some evidence that people developing contact-tracing messaging campaigns do not need to worry that describing a digital contact-tracing app's privacy protections will backfire. Future mixed methods testing of messages about who has access to information-and for how long-may uncover new communication strategies to increase public trust in contact-tracing apps. Trial registration: This study is registered with AsPredicted#51826.

SwissCovid in the Perspective of Its Goals

SwissCovid is the Swiss digital contact tracing app, which was deployed to help fighting against the COVID-19 pandemic. After a year of activity, it is high time to evaluate how effective it has been in its mission. At the highest peak, about 22% of the Swiss population was actively using SwissCovid. The activity of SwissCovid follows the curve on the number of COVID-19 cases. However, performances are rather poor. About 1% of the cases may have been discovered by SwissCovid and much less than 2% of SwissCovid alerts may have been useful, while SwissCovid generates 5% of the quarantines. The measure of the proximity of each encounter and its duration are also imprecise. It further comes with security and privacy issues: adversaries can inject false alerts for SwissCovid users and users can be tracked. On top of that, SwissCovid contributes to strengthen the monopoly of Apple and Google and to make users and their data captive of these giants. It also digs the digital divide. Contrarily to the original plan, the implementation is not open source and the law was twisted to fit the constraints by Apple and Google. Therefore, SwissCovid did not meet its goals. © 2022 Association for Computing Machinery.

Digital Contact Tracing Solutions: Promises, Pitfalls and Challenges

The COVID-19 pandemic has caused many countries to deploy novel digital contact tracing (DCT) systems to boost the efficiency of manual tracing of infection chains. In this paper, we systematically analyze DCT solutions and categorize them based on their design approaches and architectures. We analyze them with regard to effectiveness, security, privacy and ethical aspects and compare prominent solutions based on these requirements. In particular, we discuss shortcomings of the Google and Apple Exposure Notification API (GAEN) that is currently widely adopted all over the world. We find that the security and privacy of GAEN has considerable deficiencies as it can be compromised by severe large-scale attacks. We also discuss other proposed approaches for contact tracing, including our proposal <sc>TraceCORONA</sc>, that are based on Diffie-Hellman (DH) key exchange and aim at tackling shortcomings of existing solutions. Our extensive analysis shows that <sc>TraceCORONA</sc> fulfills the above security requirements better than deployed state-of-the-art approaches. We have implemented <sc>TraceCORONA</sc> and its beta test version has been used by more than 2000 users without any major functional problems<uri>https://tracecorona.net/download-tracecorona/</uri>, demonstrating that there are no technical reasons requiring to make compromises with regard to the requirements of DCT approaches. IEEE

Contact Tracing Applications During The Pandemic Era: A Systematic Literature Review

Covid 19 has become a global pandemic since 2019, which brings not only health problems, but also brings problems to all aspects of human life. There have been many efforts that have been carried out by countries around the world to overcome the pandemic. One of the efforts taken in almost all countries is the use of digital contact tracing applications whose main goal is to reduce the rate of transmission of the disease. But in reality, the use of these applications also brings a negative impact, especially related to the use of personal information. There are many articles that review the use of this application and its side effects. In this paper, we attempt to conduct a systematic literature review on various similar applications issued by various state institutions from previous publications researching the topic, and also discuss various issues related to these applications. It is hoped that the results can be used as a reference for the government to make improvements to similar applications and can also be used as a basis for researchers to be able to carry out further research. Especially by examining the antecedents for worldwide adoption of similar applications. © 2022 IEEE.

The Dutch COVID-19 Notification App: Lessons Learned From a Mixed Methods Evaluation Among End Users and Contact-Tracing Employees.

BACKGROUND: The Dutch CoronaMelder (CM) app is the official Dutch contact-tracing app (CTA). It has been used to contain the spread of the SARS-CoV-2 in the Netherlands. It allows its users and those of connected apps to anonymously exchange warnings about potentially high-risk contacts with individuals infected with the SARS-CoV-2. OBJECTIVE: The goal of this mixed methods study is to understand the use of CTA in the pandemic and its integration into the Municipal Health Services (MHS) efforts of containment through contact tracing. Moreover, the study aims to investigate both the motivations and user experience-related factors concerning adherence to quarantine and isolation measures. METHODS: A topic analysis of 56 emails and a web-based survey of 1937 adults from the Netherlands, combined with a series of 48 in-depth interviews with end users of the app and 14 employees of the Dutch MHS involved in contact tracing, were conducted. Mirroring sessions were held (n=2) with representatives from the development (n=2) and communication teams (n=2) responsible for the creation and implementation of the CM app. RESULTS: Topic analysis and interviews identified procedural and technical issues in the use of the CTA. Procedural issues included the lack of training of MHS employees in the use of CTAs. Technical issues identified for the end users included the inability to send notifications without phone contact with the MHS, unwarranted notifications, and nightly notifications. Together, these issues undermined confidence in and satisfaction with the app's use. The interviews offered a deeper understanding of the various factors at play and their effects on users; for example, the mixed experiences of the app's users, the end user's own fears, and uncertainties concerning the SARS-CoV-2; problematic infrastructure at the time of the app's implementation on the side of the health services; the effects of the society-wide efforts in containment of the SARS-CoV-2 on the CM app's perception, resulting in further doubts concerning the app's effectiveness among MHS workers and citizens; and problems with adherence to behavioral measures propagated by the app because of the lack of confidence in the app and uncertainty concerning the execution of the behavioral measures. All findings were evaluated with the app's creators and have since contributed to improvements. CONCLUSIONS: Although most participants perceived the app positively, procedural and technical issues identified in this study limited satisfaction and confidence in the CM app and affected its adoption and long-term use. Moreover, these same issues negatively affected the CM app's effectiveness in improving compliance with behavioral measures aimed at reducing the spread of the SARS-CoV-2. This study offers lessons learned for future eHealth interventions in pandemics. Lessons that can aid in more effective design, implementation, and communication for more effective and readily adoptable eHealth applications.