What motivates individuals to share information with governments when adopting health technologies during the COVID-19 pandemic?

BACKGROUND

While digital governance has been adopted by governments around the world to assist in the management of the COVID-19 pandemic, the effectiveness of its implementation relies on the collection and use of personal information. This study examines the willingness of individuals to engage in information-sharing with governments when adopting health technologies during the COVID-19 pandemic.

METHODS

Data were obtained from a cross-sectional survey of 4,800 individuals drawn from 16 cities in China in 2021. Tobit regression models were used to assess the impacts of an array of determinants on an individual's willingness to share information with governments when adopting health technologies.

RESULTS

Individuals who perceived a higher level of helpfulness, risk, expectations from others, weariness toward privacy issues, and were sensitive to positive outcomes were more willing to share information with governments when adopting health technologies during the COVID-19 pandemic. Across all the subgroups, self-efficacy only reduced the willingness to share information with governments for individuals who spent more than seven hours per day online. The negative impacts of being sensitive to negative outcomes on the willingness to share information were only found among females and the less educated group.

CONCLUSIONS

This study revealed the seemingly paradoxical behavior of individuals who perceived high risks of sharing information and a sense of fatigue toward privacy issues yet continued to be willing to share their information with their governments when adopting health technologies during the COVID-19 pandemic. This work highlighted significant differential motivations for sharing information with governments when using health technologies during a pandemic. Tailored policies that resonate with population sub-groups were suggested to be proposed to facilitate crisis management in future situations.

Governing public health emergencies during the coronavirus disease outbreak: Lessons from four Chinese cities in the first wave

The ongoing coronavirus disease (COVID-19) pandemic has had a far-reaching impact on urban living, prompting emergency preparedness and response from public health governance at multiple levels. The Chinese government has adopted a series of policy measures to control infectious disease, for which cities are the key spatial units. This research traces and reports analyses of those policy measures and their evolution in four Chinese cities: Zhengzhou, Hangzhou, Shanghai and Chengdu. The theoretical framework stems from conceptualisations of urban governance and its role in public health emergencies, wherein crisis management and emergency response are highlighted. In all four cities, the trend curves of cumulative diagnosed cases, critical policies launched in key time nodes and local governance approaches in the first wave were identified and compared. The findings suggest that capable local leadership is indispensable for controlling the coronavirus epidemic, yet local governments' approaches are varied, contributing to dissimilar local epidemic control policy pathways and positive outcomes in the fight against COVID-19. The effectiveness of disease control is determined by how local governments' measures have adapted to geospatial and socioeconomic heterogeneity. The coordinated actions from central to local governments also reveal an efficient, top-down command transmission and execution system for coping with the pandemic. This article argues that effective control of pandemics requires both a holistic package of governance strategies and locally adaptive governance measures/processes, and concludes with proposals for both a more effective response at the local level and identification of barriers to achieving these responses within diverse subnational institutional contexts.

Association of government effectiveness, logistics performance, IT systems and income with COVID-19 mortality

The COVID-19 pandemic has unprecedentedly shaken the public health system worldwide. It has been one of the greatest humanitarian crises faced by all countries, regardless of their economic prosperity. However, some countries have been able to minimize the deaths caused by the coronavirus even in the face of a large number of cases, while others have failed to control the death rate even in a comparatively small number of cases. This study explores possible causes of this disparity using cross-sectional data from 126 countries associated with demography, governance, income level, the extent of ICT maturity and the geographical divide. The results of this study suggest that while government effectiveness is negatively associated with the COVID-19 death rate, the logistics performance of governments is positively linked to the COVID-19 mortality rate. The ICT maturity proxied through online service delivery did not confirm its association with the COVID-19 mortality rate. This study informs that poverty and the location of countries do not necessarily influence COVID-19 deaths. Hence, it behoves governments to focus on improving government effectiveness and putting in place more effective and efficient mobility systems, healthcare supply chains and digital administration to address the global health crisis posed by the COVID-19 pandemic and mitigate its harsh effects, including mortality.

Emerging Technologies of Three-Dimensional Printing and Mobile Health in COVID-19 Immunity and Regenerative Dentistry

The ongoing coronavirus disease 2019 (COVID-19) pandemic highlights the importance of developing point-of-care (POC) antibody tests for monitoring the COVID-19 immune response upon viral infection or following vaccination, which requires three key aspects to achieve optimal monitoring, including three-dimensional (3D)-printed POC devices, mobile health (mHealth), and noninvasive sampling. As a critical tissue engineering concept, additive manufacturing (AM, also known as 3D printing) enables accurate control over the dimensional and architectural features of the devices. mHealth refers to the use of portable digital devices, such as smartphones, tablet computers, and fitness and medical wearables, to support health, which facilitates contact tracing, and telehealth consultations during the pandemic. Compared with invasive biosample (blood), saliva is of great importance in the spread and surveillance of COVID-19 as a noninvasive diagnostic method for virus detection and immune status monitoring. However, investigations into 3D-printed POC antibody test and mHealth using noninvasive saliva are relatively limited. Further exploration of 3D-printed antibody POC tests and mHealth applications to monitor antibody production for either disease onset or immune response following vaccination is warranted. This review briefly describes the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus and immune response after infection and vaccination, then discusses current widely used binding antibody tests using blood samples and enzyme-linked immunosorbent assays on two-dimensional microplates before focusing upon emerging POC technological platforms, such as field-effect transistor biosensors, lateral flow assay, microfluidics, and AM for fabricating immunoassays, and the possibility of their combination with mHealth. This review proposes that noninvasive biofluid sampling combined with 3D POC antibody tests and mHealth technologies is a promising and novel approach for POC detection and surveillance of SARS-CoV-2 immune response. Furthermore, as key concepts in dentistry, the application of 3D printing and mHealth was also included to facilitate the appreciation of cutting edge techniques in regenerative dentistry. This review highlights the potential of 3D printing and mHealth in both COVID-19 immunity monitoring and regenerative dentistry.

A tale of two applications: lessons learned from national LMIC COVID applications

Mobile health (mHealth) technologies in low- and middle-income countries (LMICs) have received increased attention for the significant potential benefits they can bring to underserved populations. As smartphones are becoming increasingly accessible, many stakeholders in the mHealth space have begun exploring smartphone applications as a means to impact individuals living within LMICs. With the COVID-19 pandemic straining healthcare systems around the world, many governments in LMICs turned to use smartphone applications to help support and manage their pandemic responses. By analyzing national COVID-19 applications created and launched by the Indian and Vietnamese governments, we highlight effective application functions and strategies, summarizing best practices for future LMIC application development.

Governing digital health for infectious disease outbreaks

ABSTRACTHow can governing digital health for infectious disease outbreaks be enhanced? In many ways, the COVID-19 pandemic has simultaneously represented both the potential and marked limitations of digital health practices for infectious disease outbreaks. During the pandemic's initial stages, states along with Big Data and Big Tech actors unleashed a scope of both established and experimental digital technologies for tracking infections, hospitalisations, and deaths from COVID-19 - and sometimes exposure to the virus SARS-CoV-2. Despite the proliferation of these technologies at the global level, transnational and cross-border integration, and cooperation within digital health responses to COVID-19 often faltered, while digital health regulations were fragmented, contested, and uncoordinated. This article presents a critiquing reflection of approaches to conceptualising, understanding, and implementing digital health for infectious disease outbreaks, observed from COVID-19 and previous examples. In assessing the strengths and limitations of existing practices of governing digital health for infectious disease outbreaks, this article particularly examines 'informal' digital health to build upon and consider how digitised responses to addressing and governing infectious disease outbreaks may be reconceptualised, revisited, or revised.

In the shadow of privacy: Overlooked ethical concerns in COVID-19 digital epidemiology

The COVID-19 pandemic witnessed a surge in the use of health data to combat the public health threat. As a result, the use of digital technologies for epidemic surveillance showed great potential to collect vast volumes of data, and thereby respond more effectively to the healthcare challenges. However, the deployment of these technologies raised legitimate concerns over risks to individual privacy. While the ethical and governance debate focused primarily on these concerns, other relevant issues remained in the shadows. Leveraging examples from the COVID-19 pandemic, this perspective article aims to investigate these overlooked issues and their ethical implications. Accordingly, we explore the problem of the digital divide, the role played by tech companies in the public health domain and their power dynamics with the government and public research sector, and the re-use of personal data, especially in the absence of adequate public involvement. Even if individual privacy is ensured, failure to properly engage with these other issues will result in digital epidemiology tools that undermine equity, fairness, public trust, just distribution of benefits, autonomy, and minimization of group harm. On the contrary, a better understanding of these issues, a broader ethical and data governance approach, and meaningful public engagement will encourage adoption of these technologies and the use of personal data for public health research, thus increasing their power to tackle epidemics.

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.

Where horizontal and vertical surveillances meet: Sense-making of US COVID-19 contact-tracing apps during a health crisis

Analyzing user reviews of seven US digital contact-tracing apps for COVID-19, this article unpacks how the new form of surveillance technology is understood and experienced by individuals during a global health crisis. The findings suggest that the app users felt empowered via self-tracking capacity and expressed community-level care and concerns, including those regarding the marginalized. At the same time, the users were raising doubts over technical effectiveness, navigating varying levels of voluntary choice available, and negotiating privacy concerns depending on the (dis)trust they held of institutional entities behind the governance of the apps. We argue that it is critical to investigate how surveillance technologies are situated across horizontal and vertical relationships in people's everyday lives to fully understand the individual and societal acceptance and/or refusal of the very systems during crises.

Delineating privacy aspects of COVID tracing applications embedded with proximity measurement technologies & digital technologies

As the COVID-19 pandemic expanded over the globe, governments implemented a series of technological measures to prevent the disease's spread. The development of the COVID Tracing Application (CTA) was one of these measures. In this study, we employed bibliometric and topic-based content analysis to determine the most significant entities and research topics. Additionally, we identified significant privacy concerns posed by CTAs, which gather, store, and analyze data in partnership with large technology corporations using proximity measurement technologies, artificial intelligence, and blockchain. We examined a series of key privacy threats identified in our study. These privacy risks include anti-democratic and discriminatory behaviors, politicization of care, derogation of human rights, techno governance, citizen distrust and refusal to adopt, citizen surveillance, and mandatory legislation of the apps' installation. Finally, sixteen research gaps were identified. Then, based on the identified theoretical gaps, we recommended fourteen prospective study strands. Theoretically, this study contributes to the growing body of knowledge about the privacy of mobile health applications that are embedded with cutting-edge technologies and are employed during global pandemics.

Can Digital Transformation Promote the Rapid Recovery of Cities from the COVID-19 Epidemic? An Empirical Analysis from Chinese Cities

Background: Digital transformation has become a key intervention strategy for the global response to the COVID-19 epidemic, and digital technology is helping cities recover from the COVID-19 epidemic. However, the effects of urban digital transformation on the recovery from the COVID-19 epidemic still lack mechanism analyses and empirical testing. This study aimed to explain the theoretical mechanism of urban digital transformation on the recovery from the COVID-19 epidemic and to test its effectiveness using an empirical analysis. Methods: This study, using a theoretical and literature-based analysis, summarizes the impact mechanisms of urban digital transformation on the recovery of cities from the COVID-19 epidemic. A total of 83 large- and medium-sized cities from China are included in the empirical research sample, covering most major cities in China. The ordinary least squares (OLS) method is adopted to estimate the effect of China’s urban digitalization level on population attraction in the second quarter of 2020. Results: The theoretical analysis found that urban digital transformation improves the ability of cities to recover from the COVID-19 epidemic by promoting social communication, collaborative governance, and resilience. The main findings of the empirical analysis show that the digital level of a city has a significant positive effect on urban population attraction (p < 0.001). Conclusions: A positive relationship was found between urban digital transformation and the rapid recovery of cities from the COVID-19 epidemic. Digital inventions for social communication, collaborative governance, and urban resilience are an effective way of fighting the COVID-19 emergency.

Challenges for modelling interventions for future pandemics

Mathematical modelling and statistical inference provide a framework to evaluate different non-pharmaceutical and pharmaceutical interventions for the control of epidemics that has been widely used during the COVID-19 pandemic. In this paper, lessons learned from this and previous epidemics are used to highlight the challenges for future pandemic control. We consider the availability and use of data, as well as the need for correct parameterisation and calibration for different model frameworks. We discuss challenges that arise in describing and distinguishing between different interventions, within different modelling structures, and allowing both within and between host dynamics. We also highlight challenges in modelling the health economic and political aspects of interventions. Given the diversity of these challenges, a broad variety of interdisciplinary expertise is needed to address them, combining mathematical knowledge with biological and social insights, and including health economics and communication skills. Addressing these challenges for the future requires strong cross-disciplinary collaboration together with close communication between scientists and policy makers.

Nowcasting (Short-Term Forecasting) of COVID-19 Hospitalizations Using Syndromic Healthcare Data, Sweden, 2020

We report on local nowcasting (short-term forecasting) of coronavirus disease (COVID-19) hospitalizations based on syndromic (symptom) data recorded in regular healthcare routines in Östergötland County (population ≈465,000), Sweden, early in the pandemic, when broad laboratory testing was unavailable. Daily nowcasts were supplied to the local healthcare management based on analyses of the time lag between telenursing calls with the chief complaints (cough by adult or fever by adult) and COVID-19 hospitalization. The complaint cough by adult showed satisfactory performance (Pearson correlation coefficient r>0.80; mean absolute percentage error <20%) in nowcasting the incidence of daily COVID-19 hospitalizations 14 days in advance until the incidence decreased to <1.5/100,000 population, whereas the corresponding performance for fever by adult was unsatisfactory. Our results support local nowcasting of hospitalizations on the basis of symptom data recorded in routine healthcare during the initial stage of a pandemic.

Evidence-based guiding principles to build public trust in personal data use in health systems

Objective

Public trust in health systems is pivotal for their effective and efficient functioning. In particular, public trust is essential for personal data use, as demonstrated in debates in many countries, for example, about whether data from COVID-19 contact tracing apps should be pooled or remain on individuals' smartphones. Low levels of public trust pose a risk not only to health system legitimacy but can also harm population health.

Methods

Synthesising our previous qualitative and theoretical research in the English National Health Service which enabled us to conceptualise the nature of public trust in health systems, we present guiding principles designed to rebuild public trust, if lost, and to maintain high levels of public trust in personal data use within the health system, if not.

Results

To build public trust, health system actors need to not rush trust building; engage with the public; keep the public safe; offer autonomy to the public; plan for diverse trust relationships; recognise that trust is shaped by both emotion and rational thought; represent the public interest; and work towards realising a net benefit for the health system and the public.

Conclusions

Beyond policymakers and government officials, the guiding principles address a wide range of actors within health systems so that they can work collectively to build public trust. The guiding principles can be used to inform policymaking in health and health care and to analyse the performance of different governments to see if those governments that operate in greater conformity with the guiding principles perform better.

Rigorous Policy-Making Amid COVID-19 and Beyond: Literature Review and Critical Insights

Policies shape society. Public health policies are of particular importance, as they often dictate matters in life and death. Accumulating evidence indicates that good-intentioned COVID-19 policies, such as shelter-in-place measures, can often result in unintended consequences among vulnerable populations such as nursing home residents and domestic violence victims. Thus, to shed light on the issue, this study aimed to identify policy-making processes that have the potential of developing policies that could induce optimal desirable outcomes with limited to no unintended consequences amid the pandemic and beyond. Methods: A literature review was conducted in PubMed, PsycINFO, and Scopus to answer the research question. To better structure the review and the subsequent analysis, theoretical frameworks such as the social ecological model were adopted to guide the process. Results: The findings suggested that: (1) people-centered; (2) artificial intelligence (AI)-powered; (3) data-driven, and (4) supervision-enhanced policy-making processes could help society develop policies that have the potential to yield desirable outcomes with limited unintended consequences. To leverage these strategies' interconnectedness, the people-centered, AI-powered, data-driven, and supervision-enhanced (PADS) model of policy making was subsequently developed. Conclusions: The PADS model can develop policies that have the potential to induce optimal outcomes and limit or eliminate unintended consequences amid COVID-19 and beyond. Rather than serving as a definitive answer to problematic COVID-19 policy-making practices, the PADS model could be best understood as one of many promising frameworks that could bring the pandemic policy-making process more in line with the interests of societies at large; in other words, more cost-effectively, and consistently anti-COVID and pro-human.

Psychological distance towards COVID-19: Geographical and hypothetical distance predict attitudes and mediate knowledge

While different antecedents have been examined to explain peoples’ reactions towards COVID-19, there is only scarce understanding about the role of the subjective closeness and distance to the pandemic. Within the current study, we applied the concept of psychological distance to understand the distance towards COVID-19 and investigated its (1) connection with preventive attitudes and proactive behaviors, (2) context-specific antecedents, and its (3) mediating effect of knowledge on attitudes. Using an online sample from a German quantitative cross-sectional study (N = 395, M = 32.2 years, SD = 13.9 years, 64.3% female) in July 2020, a time with a general low incidence of people infected with Sars-CoV2, we measured relevant socio-psychological constructs addressing COVID-19 and included further information from external sources. Based on a path model, we found geographical distance as a significant predictor of cognitive attitudes towards COVID-19. Furthermore, hypothetical distance (i.e., feeling to be likely affected by COVID-19) predicted not only participants’ affective, cognitive, and behavioral attitudes, but also the installation of a corona warning-app. While several variables affected the different dimensions of psychological distance, hypothetical and geographical distance mediated the effect of knowledge on attitudes. These results underline the role of geographical and hypothetical distance for health-related behaviors and education. For example, people will only comply with preventive measures if they feel geographically concerned by the disease, which is particularly challenging for fast-spreading global diseases such as COVID-19. Therefore, there is a need to clearly communicate the personal risks of diseases and address peoples’ hypothetical distance.

What makes people install a COVID-19 contact-tracing app? Understanding the influence of app design and individual difference on contact-tracing app adoption intention

Smartphone-based contact-tracing apps are a promising solution to help scale up the conventional contact-tracing process. However, low adoption rates have become a major issue that prevents these apps from achieving their full potential. In this paper, we present a national-scale survey experiment ( N = 1963 ) in the U.S. to investigate the effects of app design choices and individual differences on COVID-19 contact-tracing app adoption intentions. We found that individual differences such as prosocialness, COVID-19 risk perceptions, general privacy concerns, technology readiness, and demographic factors played a more important role than app design choices such as decentralized design vs. centralized design, location use, app providers, and the presentation of security risks. Certain app designs could exacerbate the different preferences in different sub-populations which may lead to an inequality of acceptance to certain app design choices (e.g., developed by state health authorities vs. a large tech company) among different groups of people (e.g., people living in rural areas vs. people living in urban areas). Our mediation analysis showed that one's perception of the public health benefits offered by the app and the adoption willingness of other people had a larger effect in explaining the observed effects of app design choices and individual differences than one's perception of the app's security and privacy risks. With these findings, we discuss practical implications on the design, marketing, and deployment of COVID-19 contact-tracing apps in the U.S.

Do you have COVID-19? How to increase the use of diagnostic and contact tracing apps

Diagnostic and contact tracing apps are a needed weapon to contain contagion during a pandemic. We study how the content of the messages used to promote the apps influence adoption by running a survey experiment on approximately 23,000 Mexican adults. Respondents were randomly assigned to one of three different prompts, or a control condition, before stating their willingness to adopt a diagnostic app and contact tracing app. The prompt emphasizing government efforts to ensure data privacy, which has been one of the most common strategies, reduced willingness to adopt the apps by about 4 pp and 3 pp, respectively. An effective app promotion policy must understand individuals’ reservations and be wary of unintended reactions to naïve reassurances.

Digital Contact Tracing Against COVID-19 in Europe: Current Features and Ongoing Developments

The SARS-CoV-2 pandemic is a public health challenge of unprecedented scale. In the midst of the first wave of the pandemic, governments worldwide introduced digital contact tracing systems as part of a strategy to contain the spread of the virus. In Europe, after intense discussion about privacy-related risks involving policymakers, technology experts, information technology companies, and—albeit to a limited extent—the public at large, technical protocols were created to support the development of privacy-compatible proximity tracing apps. However, as the second wave of SARS-CoV-2 sweeps the continent, digital contact tracing in Europe is evolving in terms of both technological and governance features. To enable policymakers to harness the full potential of digital health tools against SARS-CoV-2, this paper examines the evolution of digital contact tracing in eight European countries. Our study highlights that while privacy and data protection are at the core of contact tracing apps in Europe, countries differ in their technical protocols, and in their capacity to utilize collected data beyond proximity tracing alone. In particular, the most recently released apps tend to offer users more granular information about risk in specific locations, and to collect data about user whereabouts, in order to enhance retrospective contact tracing capacity. These developments signal a shift from a strict interpretation of data minimization and purpose limitation toward a more expansive approach to digital contact tracing in Europe, calling for careful scrutiny and appropriate oversight.

Emerging Digital Technologies to Combat Future Crises: Learnings From COVID-19 to be Prepared for the Future

In 2020, the world has witnessed an unprecedented global pandemic with COVID-19. It has led nations to take measures that have an enormous impact on individuals, society, and the economy. Researchers and practitioners responded rapidly, evaluating the opportunities to capitalize on technology for tackling the associated challenges. We investigate the innovative potentials of three emerging digital technologies — namely, the Internet of Things, artificial intelligence, and distributed ledgers — to tackle pandemic-related challenges. We present our findings on the most effective means of leveraging each technology’s potential, the implications for use in crises, and the convergence of the three technologies.

Quality and Adoption of COVID-19 Tracing Apps and Recommendations for Development: Systematic Interdisciplinary Review of European Apps

BACKGROUND

Simulation study results suggest that COVID-19 contact tracing apps have the potential to achieve pandemic control. Concordantly, high app adoption rates were a stipulated prerequisite for success. Early studies on potential adoption were encouraging. Several factors predicting adoption rates were investigated, especially pertaining to user characteristics. Since then, several countries have released COVID-19 contact tracing apps.

OBJECTIVE

This study's primary aim is to investigate the quality characteristics of national European COVID-19 contact tracing apps, thereby shifting attention from user to app characteristics. The secondary aim is to investigate associations between app quality and adoption. Finally, app features contributing to higher app quality were identified.

METHODS

Eligible COVID-19 contact tracing apps were those released by national health authorities of European Union member states, former member states, and countries of the European Free Trade Association, all countries with comparable legal standards concerning personal data protection and app use voluntariness. The Mobile App Rating Scale was used to assess app quality. An interdisciplinary team, consisting of two health and two human-computer interaction scientists, independently conducted Mobile App Rating Scale ratings. To investigate associations between app quality and adoption rates and infection rates, Bayesian linear regression analyses were conducted.

RESULTS

We discovered 21 national COVID-19 contact tracing apps, all demonstrating high quality overall and high-level functionality, aesthetics, and information quality. However, the average app adoption rate of 22.9% (SD 12.5%) was below the level recommended by simulation studies. Lower levels of engagement-oriented app design were detected, with substantial variations between apps. By regression analyses, the best-case adoption rate was calculated by assuming apps achieve the highest ratings. The mean best-case adoption rates for engagement and overall app quality were 39.5% and 43.6%, respectively. Higher adoption rates were associated with lower cumulative infection rates. Overall, we identified 5 feature categories (symptom assessment and monitoring, regularly updated information, individualization, tracing, and communication) and 14 individual features that contributed to higher app quality. These 14 features were a symptom checker, a symptom diary, statistics on COVID-19, app use, public health instructions and restrictions, information of burden on health care system, assigning personal data, regional updates, control over tracing activity, contact diary, venue check-in, chats, helplines, and app-sharing capacity.

CONCLUSIONS

European national health authorities have generally released high quality COVID-19 contact tracing apps, with regard to functionality, aesthetics, and information quality. However, the app's engagement-oriented design generally was of lower quality, even though regression analyses results identify engagement as a promising optimization target to increase adoption rates. Associations between higher app adoption and lower infection rates are consistent with simulation study results, albeit acknowledging that app use might be part of a broader set of protective attitudes and behaviors for self and others. Various features were identified that could guide further engagement-enhancing app development.

Positioning digital tracing applications in France's COVID-19 pandemic management

To combat the COVID-19 pandemic, many European countries have developed a public health strategy involving the use of digital contact tracing (DCT) applications to improve timely tracking and contact tracing of COVID-19 cases. France’s independent COVID-19 Control and Society Connection Council (CCL) was established by law in May 2020 to issue advice and recommendations on the national epidemic digital systems. In this paper, we present the recommendations by the CCL, with the objective to increase the uptake and utility of French DCT applications. As the country's most vulnerable population has been subjected to greater virus exposure, a stronger impact of the lockdown, and less access to preventive and health care services, the CCL is particularly aware of health inequalities. The French DCT app TousAntiCovid had been downloaded by 13.6 million users (ie, 20% of the French population) in March 2021. To promote the use of DCT apps, the CCL has recommended that communication about the app’s individual and collective objectives be increased. The CCL has also recommended the introduction of clear, simple, accessible, incentivizing, noncoercive information within the digital tools. In addition, the CCL has recommended improving public health policies to address the needs of the underprivileged. The CCL calls for promoting population empowerment with the use of digital tools, improving public health culture for decision-makers dealing with health determinants, taking social considerations into account, and incorporating community participation.

Challenges for Nontechnical Implementation of Digital Proximity Tracing During the COVID-19 Pandemic: Media Analysis of the SwissCovid App

BACKGROUND

Several countries have released digital proximity tracing (DPT) apps to complement manual contact tracing for combatting the SARS-CoV-2 pandemic. DPT aims to notify app users about proximity exposures to persons infected with SARS-CoV-2 so that they can self-quarantine. The success of DPT apps depends on user acceptance and the embedding of DPT into the pandemic mitigation strategy.

OBJECTIVE

By searching for media articles published during the first 3 months after DPT launch, the implementation of DPT in Switzerland was evaluated to inform similar undertakings in other countries. The second aim of the study was to create a link between reported DPT implementation challenges and normalization process theory for planning and optimizing complex digital health interventions, which can provide useful guidance for decision-making in DPT design and implementation.

METHODS

A Swiss media database was searched for articles on the Swiss DPT app (SwissCovid) published in German or French between July 4 and October 3, 2020. In a structured process, topics were extracted and clustered manually from articles that were deemed pertinent. Extracted topics were mapped to four NPT constructs, which reflected the flow of intervention development from planning, stakeholder onboarding, and execution to critical appraisal. Coherence constructs describe sense-making by stakeholders, cognitive participation constructs reflect participants' efforts to create engagement with the intervention, collective actions refer to intervention execution and joint stakeholder efforts to make the intervention work, and reflexive monitoring refers to collective risk-benefit appraisals to create improvements.

RESULTS

Out of 94 articles deemed pertinent and selected for closer inspection, 38 provided unique information on implementation challenges. Five challenge areas were identified: communication challenges, challenges for DPT to interface with other processes, fear of resource competition with established pandemic mitigation measures, unclear DPT effectiveness, and obstacles to greater user coverage and compliance. Specifically, several articles mentioned unclear DPT benefits to affect commitment and to raise fears among different health system actors regarding resource competition. Moreover, media reports indicated process interface challenges such as delays or unclear responsibilities in the notification cascade, as well as misunderstandings and unmet communication needs from health system actors. Finally, reports suggested misaligned incentives, not only for app usage by the public but also for process engagement by other actors in the app notification cascade. NPT provided a well-fitting framework to contextualize the different DPT implementation challenges and to highlight improvement strategies, namely a better alignment of stakeholder incentives, or stakeholder-specific communication to address their concerns about DPT.

CONCLUSIONS

Early experiences from one of the first adopters of DPT indicate that nontechnical implementation challenges may affect the effectiveness of DPT. The NPT analysis provides a novel perspective on DPT implementation and stresses the need for stakeholder inclusion in development and operationalization.

Profiling adopters (and non-adopters) of a contact tracing mobile application: Insights from Australia

OBJECTIVE

Many governments are using contact tracing mobile applications (CTMAs) yet public adoption of such systems has been relatively low. The main objective of this paper is to profile adopters (and non-adopters) of Australia's COVIDSafe CTMA.

MATERIALS AND METHODS

We use latent profile analysis to examine predictors of CTMA download behaviour. Specifically, we draw on a representative Australian sample (N = 2575) to examine the interplay between age, education, income, dispositional desire for privacy and political ideology on download behaviour. We examine trust in government as a mediating mechanism between profiles and download behaviour.

RESULTS

Our analysis produces seven profiles. Trust in government mediates the relationship between most profiles and download behaviour. A combination of wealth and education appear to be key explanatory factors of CTMA download behaviour. Two profiles -- comprising individuals with high income and education -- had the highest rates of download behaviour. Profiles with low download percentages comprised politically left-leaning participants with average to low income and education.

CONCLUSION

Our findings clearly indicate the profiles of people who are (not) likely to download a CTMA. Practical ways to improve widespread adoption include providing structural support to the more vulnerable members of society, making clear the societal benefits of downloading CTMAs, and engaging in bipartisan promotion of such apps.

The meaning of Freedom after Covid-19

Many governments have seen digital health technologies as promising tools to tackle the current COVID-19 pandemic. A much-talked example in this context involves the recent deluge of digital contact tracing apps (DCT) aimed at detecting Covid-19 exposure. In this short contribution we look at the bio-political justification of this phenomenon and reflect on whether DCT apps constitute, as it is often argued, a serious potential breach of our right to privacy. Despite praising efforts attempting to develop legal and ethical frameworks for DCT apps' usage; we argue that such endeavours are not sufficient to tackle the more fundamental problem of mass surveillance, which will remain largely unaddressed unless we deal with the biopolitical arguments presented and resort to a technical and structural defence.

Drivers of Acceptance of COVID-19 Proximity Tracing Apps in Switzerland: Panel Survey Analysis

BACKGROUND

Digital proximity tracing apps have been released to mitigate the transmission of SARS-CoV-2, the virus known to cause COVID-19. However, it remains unclear how the acceptance and uptake of these apps can be improved.

OBJECTIVE

This study aimed to investigate the coverage of the SwissCovid app and the reasons for its nonuse in Switzerland during a period of increasing incidence of COVID-19 cases.

METHODS

We collected data between September 28 and October 8, 2020, via a nationwide online panel survey (COVID-19 Social Monitor, N=1511). We examined sociodemographic and behavioral factors associated with app use by using multivariable logistic regression, whereas reasons for app nonuse were analyzed descriptively.

RESULTS

Overall, 46.5% (703/1511) of the survey participants reported they used the SwissCovid app, which was an increase from 43.9% (662/1508) reported in the previous study wave conducted in July 2020. A higher monthly household income (ie, income >CHF 10,000 or >US $11,000 vs income ≤CHF 6000 or

CONCLUSIONS

Eliminating technical hurdles and communicating the benefits of digital proximity tracing apps are crucial to promote further uptake and adherence of such apps and, ultimately, enhance their effectiveness to aid pandemic mitigation strategies.

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Key Words

• COVID-19
• SARS-CoV-2
• acceptance
• communication
• compliance
• digital contact tracing
• digital proximity tracing
• mHealth
• tracing
• uptake
• usability

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MESH Headings

• Adult
• Aged
• COVID-19/complications
• COVID-19/psychology
• COVID-19/transmission
• Contact Tracing/instrumentation
• Contact Tracing/trends
• Female
• Humans
• Male
• Middle Aged
• Mobile Applications/standards
• Mobile Applications/statistics & numerical data
• Physical Distancing
• Surveys and Questionnaires
• Switzerland

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Affiliation(s)

Viktor von Wyl Epdemiology, Biostatistics & Prevention Institute, University of Zurich, Zürich, Switzerland Institute for Implementation Science in Health Care, University of Zurich, Zürich, Switzerland
Marc Höglinger Winterthur Institute of Health Economics, Zurich University of Applied Sciences, Winterthur, Switzerland
Chloé Sieber Epdemiology, Biostatistics & Prevention Institute, University of Zurich, Zürich, Switzerland
Marco Kaufmann Epdemiology, Biostatistics & Prevention Institute, University of Zurich, Zürich, Switzerland
André Moser Epdemiology, Biostatistics & Prevention Institute, University of Zurich, Zürich, Switzerland
Miquel Serra-Burriel Epdemiology, Biostatistics & Prevention Institute, University of Zurich, Zürich, Switzerland
Tala Ballouz Epdemiology, Biostatistics & Prevention Institute, University of Zurich, Zürich, Switzerland
Dominik Menges Epdemiology, Biostatistics & Prevention Institute, University of Zurich, Zürich, Switzerland
Anja Frei Epdemiology, Biostatistics & Prevention Institute, University of Zurich, Zürich, Switzerland
Milo Alan Puhan Epdemiology, Biostatistics & Prevention Institute, University of Zurich, Zürich, Switzerland

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