Contact Tracing Apps Research Articles

A privacy calculus model for contact tracing apps: Analyzing the use behavior of the German Corona-Warn-App with a longitudinal user study

The SARS-CoV-2 pandemic is a pressing societal issue today. The German government promotes a contract tracing app named Corona-Warn-App (CWA), aiming to change citizens’ health behaviors during the pandemic by raising awareness about potential infections and enable infection chain tracking. Technical implementations, citizens’ perceptions, and public debates around apps differ between countries, e. g., in Germany there has been a huge discussion on potential privacy issues of the app.Thus, we analyze effects of privacy concerns regarding the CWA, perceived CWA benefits, and trust in the German healthcare system to answer why citizens use the CWA. In our initial conference publication at ICT Systems Security and Privacy Protection – 37th IFIP TC 11 International Conference, SEC 2022, we used a sample with 1752 actual users and non-users of the CWA and and support for the privacy calculus theory, i. e., individuals weigh privacy concerns and benefits in their use decision. Thus, citizens privacy perceptions about health technologies (e. g., shaped by public debates) are crucial as they can hinder adoption and negatively affect future fights against pandemics. In this special issue, we adapt our previous work by conducting a second survey 10 months after our initial study with the same pool of participants (830 participants from the first study participated in the second survey). The goal of this longitudinal study is to assess changes in the perceptions of users and non-users over time and to evaluate the influence of the significantly lower hospitalization and death rates on the use behavior which we could observe during the second survey. Our results show that the privacy calculus is relatively stable over time. The only relationship which significantly changes over time is the effect of privacy concerns on the use behavior which significantly decreases over time, i. e., privacy concerns have a lower negative effect one the CWA use indicating that it did not play such an important role in the use decision at a later point in time in the pandemic.We contribute to the literature by introducing one of the rare longitudinal analyses in the literature focusing on the privacy calculus and changes over time in the relevant constructs as well as the relationships between the calculus constructs and target variables (in our case use behavior of a contact tracing app). We can see that the explanatory power of the privacy calculus model is relatively stable over time even if strong externalities might affect individual perceptions related to the model.

The technology-behavioral compensation effect: Unintended consequences of health technology adoption

In their pursuit of public health goals, policymakers increasingly turn to innovative apps to complement existing health measures. However, findings from previous research in non-IT health contexts indicate that individuals may compensate for new interventions (e.g., start exercising) by reducing existing preventive health behaviors (e.g., eating fewer healthy foods). However, the findings are inconclusive, and it is unknown when people tend to engage in behavioral compensation. Building on this observation, we draw on rational choice theory to substantiate the subjective rationality of compensation behavior and develop a utility maximization model that suggests circumstances under which adoption of technological innovation may lead to users reducing existing preventive health behaviors. This research provides evidence from a multi-wave study on COVID-19 contact-tracing apps that confirms the existence of what we term the technology-behavioral compensation effect: Individuals who perceive the app to be highly useful or actively use it reduce other preventive health behaviors (e.g., social distancing) after app adoption. Ironically, this technology-behavioral compensation effect indicates a hitherto-overlooked tension between two established IS design goals (i.e., perceived usefulness and active use) and the successful exploitation of technology to support users’ health. We expand research on dark side effects of IS use by revealing a previously neglected type of unintended consequence and elaborate on its implications for research well beyond the health context. Our findings also will help policymakers make decisions on the design of societal technologies.

COVID-19 and the Data Governance Gap

The COVID-19 pandemic has highlighted many complexities involved in using data and advanced technologies to help resolve public health emergencies. These complexities highlight the need to embrace a broader framework of data governance with three foundational questions: ( a) who decides about data flows, ( b) on what basis, and ( c) with what accountability and oversight. These questions can accommodate the issues that have arisen in the literature regarding new types of data harms. However, these questions also foreground important issues of power, authority, and legitimacy. Data governance can provide an organizing normative framework to address emerging data themes including access to data, collective decision making, data intermediaries, data sovereignty, design and digital infrastructure, regulatory technologies, the rule of law, and social trust and license. The pandemic experience with contact tracing apps, in particular, showed the many unresolved governance challenges.

The Impact of Individuals' Social Environments on Contact Tracing App Use: Survey Study.

The German Corona-Warn-App (CWA) is a contact tracing app to mitigate the spread of SARS-CoV-2. As of today, it has been downloaded approximately 45 million times. This study aims to investigate the influence of (non)users' social environments on the usage of the CWA during 2 periods with relatively lower death rates and higher death rates caused by SARS-CoV-2. We conducted a longitudinal survey study in Germany with 833 participants in 2 waves to investigate how participants perceive their peer groups' opinion about making use of the German CWA to mitigate the risk of SARS-CoV-2. In addition, we asked whether this perceived opinion, in turn, influences the participants with respect to their own decision to use the CWA. We analyzed these questions with generalized estimating equations. Further, 2 related sample tests were performed to test for differences between users of the CWA and nonusers and between the 2 points in time (wave 1 with the highest death rates observable during the pandemic in Germany versus wave 2 with significantly lower death rates). Participants perceived that peer groups have a positive opinion toward using the CWA, with more positive opinions by the media, family doctors, politicians, and virologists/Robert Koch Institute and a lower, only slightly negative opinion originating from social media. Users of the CWA perceived their peer groups' opinions about using the app as more positive than nonusers do. Furthermore, the perceived positive opinion of the media (P=.001) and politicians (P<.001) was significantly lower in wave 2 compared with that in wave 1. The perceived opinion of friends and family (P<.001) as well as their perceived influence (P=.02) among nonusers toward using the CWA was significantly higher in the latter period compared with that in wave 1. The influence of virologists (in Germany primarily communicated via the Robert Koch Institute) had the highest positive effect on using the CWA (B=0.363, P<.001). We only found 1 decreasing effect of the influence of politicians (B=-0.098, P=.04). Opinions of peer groups play an important role when it comes to the adoption of the CWA. Our results show that the influence of virologists/Robert Koch Institute and family/friends exerts the strongest effect on participants' decisions to use the CWA while politicians had a slightly negative influence. Our results also indicate that it is crucial to accompany the introduction of such a contact tracing app with explanations and a media campaign to support its adoption that is backed up by political decision makers and subject matter experts.

How Mass surveillance Crowds Out Installations of COVID-19 Contact Tracing Applications

During the COVID-19 pandemic, many countries have developed contact tracing technologies to curb the spread of the disease by locating and isolating people who have been in contact with coronavirus carriers. Subsequently, understanding why people install and use contact tracing applications is becoming central to their effectiveness and impact. However, involuntary systems can crowd out the use of voluntary applications when several contact tracing initiatives are employed simultaneously. To investigate this hypothesis, we analyze the concurrent deployment of two contact tracing technologies in Israel: centralized mass surveillance technologies and a voluntary contact tracing mobile app. Based on a representative survey of Israelis (n=519), our findings show that positive attitudes toward mass surveillance were related to a reduced likelihood of installing contact tracing apps and an increased likelihood of uninstalling them. These results also hold when controlling for privacy concerns, attitudes toward the app, trust in authorities, and demographic properties. We conclude the paper by suggesting a broader framework for analyzing crowding out effects in ecosystems that combine involuntary surveillance and voluntary participation.

The Role and Mechanism of COVID-19 Apps in Fighting the Current Pandemic: A Novel Study

The Role and Mechanism of COVID-19 Apps in Fighting the Current Pandemic: A Novel Study

COVID-19 now and then: Reflections on mobile communication and the pandemic.

The COVID-19 pandemic may soon be coming to its end, but COVID-19 still kills thousands of people every single day (at time of writing). Even if COVID-19 now represents less of a health risk, and less disruption to our personal lives, we know this won't be the last pandemic. Preparing for the next pandemic includes understanding the past and planning for the future. It includes rethinking "normal" ways of interacting with others, our technologies, and the spaces in which we live. In this introduction, we show how the pandemic has challenged the role of mobile communication in our everyday lives, making us rethink the very meaning of mobile communication-from simply communicating while on the move, to a networked resource that supports emotional and personal connections. During the pandemic, mobile communication practices and the development of new mobile technologies, such as contact-tracing apps and mobile mapping, was strongly tied to the infrastructural politics that took place through government and private companies' interventions. In addition, mobile technologies became a primary source of support for those who became immobile, or were forced to move. However, mobile communication is not only enabled by end devices; it happens at the intersection of both end devices and the infrastructures that enable them to work. The articles in this special issue reflect some of these themes, and address how the pandemic has shaped and rearranged our mobile communication, sociability, and networked urban mobility practices around the world. Although each article engages with the challenges of the pandemic in its unique and original way, in this introduction we highlight some overlapping topics and methodologies that run across multiple articles, namely historical perspectives on the pandemic, urban and transnational networked mobilities, the use of mobile apps and interfaces for community and self-care, pandemic context in the Global South, and networks and infrastructures.

Modeling the acceptance and resistance to use mobile contact tracing apps: a developing nation perspective

PurposeThis study proposes and validates an integrated theoretical model involving the theory of planned behavior (TPB), health belief model (HBM), personal norms and information privacy to understand determinants of acceptance and resistance to the use of mobile contact tracing app (MCTA) in a pandemic situation.Design/methodology/approachThis study draws on online surveys of 194 research respondents and uses partial least squares structural equation modeling (PL-SEM) to test the proposed theoretical model.FindingsThe study establishes that a positive attitude towards MCTA is the most important predictor of individuals' willingness to use MCTA and resistance to use MCTA. Furthermore, barriers to taking action positively influence resistance to the use of MCTA. Personal norms negatively influence resistance to the use of MCTA. Information privacy showed a negative and positive influence on willingness to use MCTA and use the resistance of MCTA, respectively, but neither was statistically significant. The authors found no significant influence of perceived vulnerability, severity, subjective norms and perceived behavioral control on either acceptance or use resistance of MCTA.Originality/valueThe study has been one of the first in the literature to propose an integrated theoretical model in the investigation of the determinants of acceptance and resistance to the use of MCTA in a single study, thereby increasing the scientific understanding of the factors that can facilitate or inhibit individuals from engaging in the use of a protection technology during a pandemic situation.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-10-2021-0533

Elderly and Smartphone Apps: Case Study with Lightweight MySejahtera

The outbreak of Covid-19 in the past 2 years has made the usage of contact-tracing app almost mandatory in Malaysia. Though the usage is seeming to be simple, but one interesting phenomenon can be observed in Malaysia is that most of the senior citizen are found not using smartphones regularly. While check-in through MySejahtera (the primary contract-tracing app used in Malaysia) for business, premises, and transports has made compulsory, it does bring a lot of inconveniences to the elderly. Many elderlies start to learn how to use smartphone and government has also taking initiative by providing free or low-cost smartphone with data plan. However, it is important to note that many apps are not customized for elderly navigation. Thus, we would like to study how does an app can be strip down so that the essential functions can be remained and keep minimal for elderly usage. The interface design, color, and button sizes are also important to consider. In this study, MySejahtera has been used as an example to strip down and tested its lightweight version among a group of elderly.

Proactive Contact Tracing.

The COVID-19 pandemic has spurred an unprecedented demand for interventions that can reduce disease spread without excessively restricting daily activity, given negative impacts on mental health and economic outcomes. Digital contact tracing (DCT) apps have emerged as a component of the epidemic management toolkit. Existing DCT apps typically recommend quarantine to all digitally-recorded contacts of test-confirmed cases. Over-reliance on testing may, however, impede the effectiveness of such apps, since by the time cases are confirmed through testing, onward transmissions are likely to have occurred. Furthermore, most cases are infectious over a short period; only a subset of their contacts are likely to become infected. These apps do not fully utilize data sources to base their predictions of transmission risk during an encounter, leading to recommendations of quarantine to many uninfected people and associated slowdowns in economic activity. This phenomenon, commonly termed as "pingdemic," may additionally contribute to reduced compliance to public health measures. In this work, we propose a novel DCT framework, Proactive Contact Tracing (PCT), which uses multiple sources of information (e.g. self-reported symptoms, received messages from contacts) to estimate app users' infectiousness histories and provide behavioral recommendations. PCT methods are by design proactive, predicting spread before it occurs. We present an interpretable instance of this framework, the Rule-based PCT algorithm, designed via a multi-disciplinary collaboration among epidemiologists, computer scientists, and behavior experts. Finally, we develop an agent-based model that allows us to compare different DCT methods and evaluate their performance in negotiating the trade-off between epidemic control and restricting population mobility. Performing extensive sensitivity analysis across user behavior, public health policy, and virological parameters, we compare Rule-based PCT to i) binary contact tracing (BCT), which exclusively relies on test results and recommends a fixed-duration quarantine, and ii) household quarantine (HQ). Our results suggest that both BCT and Rule-based PCT improve upon HQ, however, Rule-based PCT is more efficient at controlling spread of disease than BCT across a range of scenarios. In terms of cost-effectiveness, we show that Rule-based PCT pareto-dominates BCT, as demonstrated by a decrease in Disability Adjusted Life Years, as well as Temporary Productivity Loss. Overall, we find that Rule-based PCT outperforms existing approaches across a varying range of parameters. By leveraging anonymized infectiousness estimates received from digitally-recorded contacts, PCT is able to notify potentially infected users earlier than BCT methods and prevent onward transmissions. Our results suggest that PCT-based applications could be a useful tool in managing future epidemics.

National approaches for citizen data management in response to COVID-19: An overview and implications of contact tracing apps in 21 countries

The COVID-19 pandemic brings the topic of citizen data management (CDAMA) into the public eye. This study is one of the first attempts to analyze the national approaches for CDAMA applied by governments of different countries and continents in public sectors. The study first conducts a systematic overview of the representative contact tracing apps in 21 countries of four continents, collecting information of the four aspects of the CDAMA system. It then summarizes and analyzes the various governments’ approaches to the CDAMA system applied by different countries and continents based on the app overview. We found that governments’ priority between national safety (i.e., public health in this study) and citizen privacy is different in terms of their national approaches for CDAMA. For example, governments of Asian countries are more intrusive and hold a stricter attitude in their national CDAMA approach than countries elsewhere. Our study has contributions both theoretically and practically. Theoretically, it fills the literature gap about data management by discussing the data management in governments; practically, the study provides the background information as well as implications for future debates and discussions on governments’ data management system and citizen data use.

When Privacy, Distrust, and Misinformation Cause Worry About Using COVID-19 Contact-Tracing Apps

Public health authorities worldwide are advocating for contact-tracing apps to help track COVID-19 infections during the pandemic and interrupt virus transmission. However, app users have to share their personally identifiable information, whereabouts, and in some cases, their vaccination records with authorities via mobile Internet. This situation creates grave concerns about how such personal information is transmitted, stored, archived, and disposed. In addition, the apps’ technical design would also impact the adoption, such as whether the apps would drain the battery. Further, citizens’ high distrust of governments also reduces app adoption. This article reviews recent research on contact-tracing apps and examines how privacy concerns, distrust in governments, and misinformation affect people's perceptions of contact-tracing apps. We recommend possible solutions for promoting these apps by analyzing what we learn from recent literature.

Contact tracing apps, nationalism, and users with disability in the Global South: The faith in state and collective objective

Contact tracing apps have magnified the potential usefulness of mobile media and communication technologies for responding to disruptive events such as the COVID-19 pandemic. Their efficacy and ethical debates have become the focus of recent studies in the Global North. Reasons for using contact tracing apps among users with disability living in the Global South, however, seem to be understudied. Through cases from Indonesia and Vietnam, this study found that nationalistic values were among the reasons for using contact tracing apps as reflected in the users’ faith in the state and inclination to support its collective objective to control the pandemic. The users believed the state would be accountable in managing the personal and mobility data the contact tracing apps collected. Using contact tracing apps represented the users’ sense of capabilities to individually partake in the existing efforts to control the pandemic.

COVID-19 Tracking Applications Acceptance among General Populace: An Overview in Malaysia

The COVID-19 pandemic forced governments to implement strategies for contact tracing due to the disease’s ease of spread. The Malaysian government has sought to develop and implement a digital contact-tracking application to make it easier and faster to detect the spread; the system has become an integral part of the exit strategy from mandated lockdowns. These applications keep track of the user’s proximity with others who are in the system to inform them early on if they are at a risk of infection. The effectiveness of these applications depends on the willingness of users to install and allow the application to track their location at all times. Therefore, this research aims to identify the factors that would stimulate or slow down the adoption of contact-tracing apps.

Why Individuals Do (Not) Use Contact Tracing Apps: A Health Belief Model Perspective on the German Corona-Warn-App

The World Health Organization declared the emergence of the novel coronavirus (SARS-CoV-2) in January 2020. To trace infection chains, Germany launched its smartphone contact tracing app, the "Corona-Warn-App" (CWA), in June 2020. In order to be successful as a tool for fighting the pandemic, a high adoption rate is required in the population. We analyse the respective factors influencing app adoption based on the health belief model (HBM) with a cross-sectional online study including 1752 participants from Germany. The study was conducted with a certified panel provider from the end of December 2020 to January 2021. This model is primarily known from evaluations of medical treatments, such as breast cancer screenings, but it was rarely applied in prior work for a health-related information system such as the CWA. Our results indicate that intrinsic and extrinsic motivation to use the CWA are the strongest drivers of app use. In contrast, technical barriers, privacy concerns and lower income are the main inhibitors. Our findings contribute to the literature on the adoption of contact tracing apps by questioning actual users and non-users of the CWA, and we provide valuable insights for policymakers regarding influences of adoption and potential user groups of disease prevention technologies in times of pandemics.

Breaking the chain with individual gain? Investigating the moral intensity of COVID-19 digital contact tracing

During the COVID-19 pandemic, contact tracing apps such as the German Corona-Warning-App (CWA) were introduced to facilitate contact tracing of infected individuals with the aim of breaking chains of infection. Therefore, using a contact tracing app is beneficial to society as a whole. Even though this is a good cause, the rather reluctant use of the CWA in the beginning indicated that the pains (e.g., privacy concerns) obviously outweighed the gains (helping others) at the level of the individual user. Thus, in order to identify what lies behind the gain of this app and how it can be promoted, we were interested in the individual's moral perspective (helping others) on the app. We expected a positive relation between CWA download and moral intensity derived from (i) the magnitude or seriousness of consequences, (ii) social norms about app use, (iii) the individual proximity to COVID-19 cases, and (iv) the probability of the app's positive effect. Using a heterogeneous German sample of N = 1,454, we found a strong influence of moral intensity on app download. Furthermore, a manipulation of moral intensity among non-users led to a higher number of downloads in a follow-up study (N = 662) as compared to the population. Our results show possibilities to enhance the adoption of contact tracing apps and potentially other apps for the common good in the population.

The role of ethics in technology acceptance: analysing resistance to new health technologies on the example of a COVID-19 contact-tracing app

ABSTRACT New health technologies promise enormous benefits for human wellbeing, yet their diffusion is often inhibited by potential users’ uncertainty about their consequences. Since ethics help individuals to cope with uncertainty, this study investigates the potential of ethics to promote technology acceptance. To this end, we test the influence of typical acceptance predictors (perceived health threat, privacy attitudes, and technology readiness) and two new ethics-related variables (‘ethical optimism’ and ‘perceived governmental responsibility’) on resistance to a government-issued COVID-19 contact-tracing app. Using structural equation modelling, we find significant effects of the typical acceptance predictors, and that ethical optimism and perceived governmental responsibility interact in determining the resistance to the tracing app. The paper highlights the relevance of ethics for the acceptance of new (health) technologies and suggests that the role of ethics is not confined to being a ‘moral watchdog’ but can serve as a powerful lever to promote their acceptance.

On the Performance and Effectiveness of Digital Contact Tracing in the Second Wave of COVID-19 in Italy

Contact-tracing smartphone applications have been developed and used as a complement to manual contact tracing in the COVID-19 pandemic. The goal of these apps is to trace contacts between people and notify the mobile phone owners when one of their contacts tested positive. People who receive a notification should behave as exposed people, take a test, and possibly isolate themselves until they receive the result. Unfortunately, identifying contacts based on distance is technically a daunting task: apps can be configured conservatively (a very small number of people are notified, limiting the effectiveness of the app) or they may be more tolerant and produce a high number of notifications but also of false positives. We review the data available from Immuni, the Italian app, which provides detailed figures on the notifications sent and the positive users, and we show that Immuni was configured to generate a very large amount of notifications. We estimate the testing resources that the health system would have needed if the app was downloaded by 100% of the adult population, and every notified person would require a test. In such conditions, Immuni would have generated a number of tests orders of magnitude higher than what was available. We compare the performance of Immuni with the currently available literature on other apps and observe that contact-tracing apps had a limited impact on the second wave of the COVID-19 pandemic. As contact tracing exposes citizens to privacy risks, we discuss some ways to reshape the goal of the apps to achieve a better tradeoff between social benefit and risk.

Factors associated with acceptance of a digital contact tracing application for COVID-19 in the Japanese working-age population.

The working-age population is at the epicenter of coronavirus disease 2019 (COVID-19) infections. Therefore, it is important to increase the acceptance of digital contact tracing apps in this population. Contact-Confirming Application (COCOA) is the only digital contact tracing app in Japan. This study aimed to determine factors associated with acceptance of the COCOA for COVID-19 in the Japanese working-age population. A cross-sectional study was performed for 27,036 full-time workers registered with an internet survey company during December 2020 in Japan. Factors associated with COCOA adoption were evaluated by multivariate logistic regression analysis. The rate of downloading the COCOA was 25.1%. The COCOA was more likely to be accepted by people with married status, university graduation or above, higher income, and occupations involving desk work. Fear of COVID-19 transmission, wearing a mask, using hand disinfection, willingness to be vaccinated against COVID-19, and presence of an acquaintance infected with COVID-19 were also associated with a greater likelihood of adopting the app. The rate of downloading the COCOA in Japan was not very high. The present findings have important implications for widespread adoption of digital contact tracing apps in working-age populations in Japan and elsewhere.

Critical reflections on three popular computational linguistic approaches to examine Twitter discourses.

Although computational linguistic methods-such as topic modelling, sentiment analysis and emotion detection-can provide social media researchers with insights into online public discourses, it is not inherent as to how these methods should be used, with a lack of transparent instructions on how to apply them in a critical way. There is a growing body of work focusing on the strengths and shortcomings of these methods. Through applying best practices for using these methods within the literature, we focus on setting expectations, presenting trajectories, examining with context and critically reflecting on the diachronic Twitter discourse of two case studies: the longitudinal discourse of the NHS Covid-19 digital contact-tracing app and the snapshot discourse of the Ofqual A Level grade calculation algorithm, both related to the UK. We identified difficulties in interpretation and potential application in all three of the approaches. Other shortcomings, such the detection of negation and sarcasm, were also found. We discuss the need for further transparency of these methods for diachronic social media researchers, including the potential for combining these approaches with qualitative ones-such as corpus linguistics and critical discourse analysis-in a more formal framework.