Contact Tracing Applications Research Articles

Turkey’s Contact Tracing Infrastructure From Security and Privacy Perspective

Contact tracing applications may lead to security and privacy concerns. Turkey’s contact tracing application (Hayat Eve Sığar, abbreviated as HES), which is introduced during COVID-19 pandemic, have not been covered yet for its security and privacy features. Comparison of HES with the existing cutting-edge contact tracing approaches could be used to analyse and determine the features of HES. Comparison indicated the undocumented security and privacy features of HES and revealed a set of vulnerabilities that could cause serious attacks. Mitigation techniques against vulnerabilities are proposed but current HES application includes serious attacks that could be performed by an insider or an outsider. The analysis emphasized to be considered in the design of similar applications that will emerge in the future.

Developing a Model for Understanding the Factors that Affect Individuals' Intentions to Share Personal Information

With the outbreak of COVID-19, digital contact tracing (DCT) applications have been implemented to track the transmission of the highly contagious disease. However, there has been significant resistance to using these apps due to individuals' concerns about disclosing personal information. This study aimed to examine individuals' intentions to reveal their details on DCT applications. A conceptual framework was developed incorporating theories of dual calculus, Hofstede's cultural theory, information boundary theory, and individual factors. A quantitative approach was employed, using a random sampling methodology to gather data from 533 respondents. The proposed framework was validated through partial least squares path modeling. The findings revealed that COVID-19-related stress, lack of transparency, and uncertainty avoidance negatively predicted intentions to disclose personal information. Conversely, collectivism, expected community-related outcomes of sharing information, expected personal outcomes of sharing information, and information privacy concerns positively predicted intentions to disclose personal information. This research provides insights into the factors that influence the widespread acceptance of DCT applications and can assist related authorities in ensuring their successful implementation.

Practices on Aarogya Setu: Mapping Citizen Interaction with the Contact-Tracing App in the Time of COVID-19

The usage of contact-tracing applications has been synonymous with ensuring one's health security and safety during the COVID-19 pandemic. These contact-tracing apps have been scripted differently by each country, within design choices of centralized vs. decentralized architecture, closed vs. open-source protocol and collecting location vs. proximity data features. The distinct script of contact-tracing apps caters to the contextual background of each country with a presupposition about on-ground and consistent usage of the app. The article explores the ways in which citizens in India negotiate the usage of the Aarogya Setu digital contact-tracing app. It reveals citizens' on-ground practices of adopting or evading the app usage, besides reflecting on the broader institutional shortcomings that shape the scepticism towards technological solutionism in critical health exigencies. Three such practices are identified and thematically presented as resistance by early deletion, resistance by selective adoption and constrained adoption. The findings steer concerns regarding user-friendly designs and revisiting governance structures before deploying any technological solutionism by the state. Here, the paper attempts to reverse the gaze and explore how citizens'(in)effective adoption of the Aarogya Setu app not only responds but also challenges the norm of digital contact-tracing solutionism.

Clinical Impact of "Real World Data" and Blockchain on Public Health: A Scoping Review.

The digitisation of healthcare has allowed a significant rethinking of the previous clinical protocols, improving their interoperability through substantial standardisation. These technological advances have ensured that data are comparable, as they are obtained from 'reliable' and certified processes; however, there are billions of data that are neither structured nor quality-controlled. They are collectively referred to as 'Real World Data' (RWD). Blockchain (BC) is a procedure with specific characteristics and algorithms that ensure that the stored data cannot be tampered with. Nowadays, there is an increasing need to rethink blockchain in a one-health vision, making it more than just a 'repository' of data and information, but rather an active player in the process of data sharing. In this landscape, several scholars have analysed the potential benefits of BC in healthcare, focusing on the sharing and safety of clinical data and its contact tracing applications. There is limited research on this matter; moreover, there is a strategic interest in managing RWD in a reliable and comparable way, despite the lack of knowledge on this topic. Our work aims to analyse systematically the most impacting literature, highlighting the main aspects of BC within the context of the new digital healthcare, and speculating on the unexpressed potential of RWD.

Thematic Analysis of User Experience of Contact Tracing Applications for COVID-19 Using Twitter Data

This paper aims to explore Kuwaiti users' perspectives and experiences with Shlonik, the mandatory contact tracing application that was used during the COVID-19 pandemic. A sample of 2,450 tweets about users' experiences was collected and thematically analyzed. The analysis used DeLone and McLean's information system success model to explore aspects of the degree to which this app can be judged a “success,” using parameters of system quality and service quality. A novel finding identified by this qualitative study was the significance of themes identified in the analysis such as social privacy (timing, privacy, and female privacy, which are related to the cultural and religious norms of Kuwait) and technical privacy (related to data protection). The research identified significant conflict with cultural and social norms in users' experience of the Shlonik app – factors not normally identified or discussed in existing literature. This research supports a need for improved strategies and designs in future m-government applications in developing countries.

Epidemic exposure risk assessment in digital contact tracing: A fuzzy logic approach.

Bluetooth low energy (BLE)-based contact-tracing applications were widely used during the COVID-19 pandemic. However, the use of only the received signal strength feature for proximity calculations may not be adaptable to different virus variants or scalable for other potential epidemic diseases. This study presents a novel framework in regard to evaluating and classifying personal exposure risk that considers both contact features, which include distance and length of contact, and environment features, which include crowd size and the number of recently infected cases in the environment. The framework utilizes a fuzzy expert system that is adaptable to different virus variants. The proposed method was tested on two viruses with different close contact features, which used four membership functions and 256 fuzzy rule sets. The proposed framework classified personal exposure risks into four classes, which include low, medium, high, and too high risk. The empirical results showed that the fuzzy logic-based approach reduced the number of false positive cases and demonstrated better accuracy and precision than the current BLE-only approaches. The proposed framework provides a more practical and adaptable method in regard to assessing exposure risks in real-world scenarios. It has the potential to be scalable and adaptable to different virus variants and other potential epidemic diseases by considering both contact and environment features. These findings may be useful in order to develop more effective digital contact-tracing applications and policies.

DP-ACT: Decentralized Privacy-Preserving Asymmetric Digital Contact Tracing

Digital contact tracing substantially improves the identification of high-risk contacts during pandemics. Despite several attempts to encourage people to use digital contact-tracing applications by developing and rolling out decentralized privacy-preserving protocols (broadcasting pseudo-random IDs over Bluetooth Low Energy---BLE), the adoption of digital contact tracing mobile applications has been limited, with privacy being one of the main concerns. In this paper, we propose a decentralized privacy-preserving contact tracing protocol, called DP-ACT, with both active and passive participants. Active participants broadcast BLE beacons with pseudo-random IDs, while passive participants model conservative users who do not broadcast BLE beacons but still listen to the broadcasted BLE beacons. We analyze the proposed protocol and discuss a set of interesting properties. The proposed protocol is evaluated using both a face-to-face individual interaction dataset and five real-world BLE datasets. Our simulation results demonstrate that the proposed DP-ACT protocol outperforms the state-of-the-art protocols in the presence of passive users.

Characterizing the role of human behavior in the effectiveness of contact-tracing applications.

Although numerous countries relied on contact-tracing (CT) applications as an epidemic control measure against the COVID-19 pandemic, the debate around their effectiveness is still open. Most studies indicate that very high levels of adoption are required to stop disease progression, placing the main interest of policymakers in promoting app adherence. However, other factors of human behavior, like delays in adherence or heterogeneous compliance, are often disregarded. To characterize the impact of human behavior on the effectiveness of CT apps we propose a multilayer network model reflecting the co-evolution of an epidemic outbreak and the app adoption dynamics over a synthetic population generated from survey data. The model was initialized to produce epidemic outbreaks resembling the first wave of the COVID-19 pandemic and was used to explore the impact of different changes in behavioral features in peak incidence and maximal prevalence. The results corroborate the relevance of the number of users for the effectiveness of CT apps but also highlight the need for early adoption and, at least, moderate levels of compliance, which are factors often not considered by most policymakers. The insight obtained was used to identify a bottleneck in the implementation of several apps, such as the Spanish CT app, where we hypothesize that a simplification of the reporting system could result in increased effectiveness through a rise in the levels of compliance.

Towards a Unified Pandemic Management Architecture: Survey, Challenges, and Future Directions

The pandemic caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has impacted the economy, health, and society. Emerging strains are making pandemic management challenging. There is an urge to collect epidemiological, clinical, and physiological data to make an informed decision on mitigation. Advances in the Internet of Things (IoT) and edge computing provide solutions for pandemic management through data collection and intelligent computation. While existing data-driven architectures operate on specific application domains and attempt to automate decision-making, they do not capture the multifaceted interaction among computational models, communication infrastructure, and data. In this article, we survey the existing approaches for pandemic management, including data repositories and contact-tracing applications. We envision a unified pandemic management architecture that leverages the IoT and edge computing paradigms to automate recommendations on vaccine distribution, dynamic lockdown, mobility scheduling, and pandemic trend prediction. We elucidate the data flow among the layers, namely, cloud, edge, and end device layers. Moreover, we address the privacy implications, threats, regulations, and solutions that may be adapted to optimize the utility of health data with security guarantees. The article ends with a discussion of the limitations of the architecture and research directions to enhance its practicality.

Privacy Aspects of Contact Tracing Applications in Europe and Recommendations for Their Future Use

The first global pandemic in the age of digitalism indicated that there might be new types of privacy risks stemming from the processing activities taking place within the scope of digital contact tracing activities. While the right to life of all individuals living in the community should be primarily protected, their right to privacy should also be considered. Therefore, a balance between privacy and public health should be struck by both regulators and data controllers. The purpose of this review is to analyze the compliance efforts of data controllers in Europe with the existing EU data protection regulations, and guidance, and draw lessons for the use of contact tracing applications within the scope of potential disaster scenarios that may arise in the future by reviewing the existing literature and the privacy policies of the applications.

COVID-19 Contact Tracing Mobile Apps: A Comparative Perspective using the “Cascade of Deference”

This article frames the action imperative as an ethical dilemma for governance actors. It situates the debate in the context of the design and implementation of digital contact tracing applications to mitigate the spread of the COVID-19 pandemic. Using a normative case study approach, it seeks to answer the question—how can the ethical dilemma of an action imperative in the face of scientific and normative uncertainty, be resolved by governance actors in ways that can minimize harms? Drawing insights from the field of Science and Technology Studies, this article makes the case that when scientific evidence claims are weak, the action imperative should follow a cascade of deference with objectivity, consensus, precaution, and subsidiarity as stopping points. It concludes by making a broader case to promote moral reasoning concerning the substantive goals of digitalization.

Portuguese Validation of the Unified Theory of Acceptance and Use of Technology Scale (UTAUT) to a COVID-19 Mobile Application: A Pilot Study.

The use of technology has proven to be a powerful tool in the fight against COVID-19 and its variants of concern (Gamma, Beta, Alpha, Delta, and Omicron). The urgency of responding to this worldwide pandemic has accelerated the development of monitoring systems and contact tracing applications. Without technology's contribution, the adverse effects on humanity economically, socially, and psychologically would be even more devastating. This study aimed to translate, adapt, and validate the Unified Theory of Acceptance and Use of Technology (UTAUT) model in a Portuguese university population, to evaluate adherence to a mobile application for tracking COVID-19. An observational cross-sectional study was developed using a sample with 1081 participants (71% female, 59.2% with ages between 16 and 24, and 78.2% of the respondent's university students). The Portuguese version model showed a good reliability (Cronbach's α = 0.82) and an acceptable overall adjustment to the sample under study (χ2/df = 3.732, CFI = 0.955, TLI = 0.944, RMSEA = 0.05, SRMR = 0.06); however, this model could be improved, as we proved. Since this is a pilot study, more studies are needed. The results indicated that the P-UTAUT can be improved for evaluating adherence to a COVID-19 mobile application.

Digital Literacy and Awareness of User Location Privacy: What People in Turkey Know About Google COVID-19 Community Mobility Reports?

At the outbreak of the COVID-19, governments, health organizations and large technology companies were not prepared for the measures to be taken against the disease. Contact tracking was widely carried out using location data to prevent the spread of COVID-19 with the use of technological tools, especially smartphones. In this epidemic, economic difficulties also emerged due to the lockdown imposed by the governments. For this reason, social distancing and contact tracing applications have become widespread in order to prevent the disease as soon as possible. Such strategies negatively affected individuals’ perceptions of privacy, because authorities gave priority to collecting data from individuals in order to prevent the epidemic. On the other hand, non-governmental organizations suggested that “privacy-first” and “decentralized” approaches should be preferred instead of “data-first” and “centralized” approaches. In this direction, Google and Apple companies have developed a decentralized common API to help fight the virus, which also complies with the European Union’s General Data Protection Regulation. And in particular, Google has regularly shared Google Community Mobility Reports (GCMR) publicly by anonymizing the data it collects from Google Maps. Using these reports people and authorities can get movement data about different categories of places such as retail and recreation, supermarkets and pharmacies, parks, public transport, workplaces and residential.Our aim is to find out whether individuals in Turkey are aware that their location and movement data are being tracked by Google Maps and contact tracing apps for preventing the spread of COVID-19. We also examined their motivations for downloading location tracing apps and whether they have been taking necessary steps to protect their privacy. We investigated whether they had concerns about the possible future use of contact tracing data collected by the health authorities in Turkey and other institutions like Google. The scope of the study covers smartphone users. We collected data through an online survey using Google Forms. Our survey consists mostly of narrative questions, where we asked respondents to imagine various scenarios where app manufacturers, mobile phone operators/manufacturers, or the government were using some of their data to study or mitigate the spread of COVID-19. Then, between 12.15.2020/01.02.2021 we distributed the survey link to the participants through various social media networks. We reported the results of the data of 444 people collected anonymously by quantitative analysis methods. As a result of the study, it was determined that the digital literacy levels of the individuals are high due to their high education level. Despite this, it has been revealed that the participants do not read the terms and conditions offered in apps. Individuals who care about privacy expressed their willingness to share their data for the sake of public health. As an answer to the main question of our study, it was concluded that the participants’ knowledge of GCMR was insufficient. As a matter of fact, it was understood that individuals were indecisive and worried about the use of their data by the authorities in the future due to the uncertainty experienced during the pandemic period.

A Lesson for the Future: Will You Let Me Violate Your Privacy to Save Your Life?

COVID-19 was an unprecedented pandemic that changed the lives of everyone. To handle the virus’s rapid spread, governments and big tech companies, such as Google and Apple, implemented Contact Tracing Applications (CTAs). However, the response by the public was different in each country. While some countries mandated downloading the application for their citizens, others made it optional, revealing contrasting patterns to the spread of COVID-19. In this study, in addition to investigating the privacy and security of the Canadian CTA, COVID Alert, we aim to disclose the public’s perception of these varying patterns. Additionally, if known of the results of other nations, would Canadians sacrifice their freedoms to prevent the spread of a future pandemic? Hence, a survey was conducted, gathering responses from 154 participants across Canada. Next, we questioned the participants regarding the COVID-19 pandemic and their knowledge and opinion of CTAs before presenting our findings regarding other countries. After showing our results, we then asked the participants their views of CTAs again. The arrangement of the preceding questions, the findings, and succeeding questions to identify whether Canadians’ opinions on CTAs would change, after presenting the proper evidence, were performed. Among all of our findings, there is a clear difference between before and after the findings regarding whether CTAs should be mandatory, with 34% of participants agreeing before and 56% agreeing afterward. This hints that all the public needed was information to decide whether or not to participate. In addition, this exposes the value of transparency and communication when persuading the public to collaborate. Finally, we offer three recommendations on how governments and health authorities can respond effectively in a future pandemic and increase the adoption rate for CTAs to save more lives.

Digital Contact Tracing for COVID-19

The spread of the COVID-19 virus across the globe has permanently changed life for billions of people. Manual contact tracing has been utilized to assist in limiting the spread of contagious diseases for many years. The ubiquitous use of smartphones and similar wireless devices has allowed this process to become digital in nature through contact tracing applications installed on these devices. Various countries, and even various regional units within those countries, developed contact tracing applications. Such applications relied on location and short-range communication technologies associated with wireless devices and found varying degrees of success. This work reviews research conducted by universities, governmental organizations, and other entities with respect to the adoption, use, and ultimate success of, digital contact tracing applications across various countries and points to their rather limited success in fighting the spread of the disease. The authors also briefly discuss some implications regarding privacy and security that affected their use in certain countries.

The Adoption of Contact-Tracing Applications and the Integration of a Health Pass

Contact tracing applications (CTAs) have been presented as important tools in the fight against the Covid-19 pandemic. In France, the government developed the ‘StopCovid' CTA which later became ‘TousAntiCovid.' This research aims at understanding the determinants of the use of this CTA and of the intention to integrate the health pass. To do that, this study focuses on the perceived value of its use based on the privacy calculus theory. A quantitative study was conducted using a sample of 779 French people. The results show that the use of the CTA and the intention to integrate the health pass are influenced, as hypothesized, by perceived value, distrust towards the government, and personal innovativeness. Perceived value is positively influenced by social and individual benefits, as well as social influence, and, to a lesser extent, negatively influenced by social risks but not by individual risks.

Design of a Reminder and Recall System in a Contact Tracing Application to Support Coronavirus Booster Vaccination.

The rate of coronavirus disease 2019 (COVID-19) booster vaccination in Indonesia remains relatively low, representing 15.33% of the overall vaccination target as of April 2022. The implementation of a reminder and recall system has been shown to be effective in increasing vaccination rates. In prior research, reminders and recalls were sent through traditional media, such as mail, and had not yet been integrated into modern media, such as smartphone applications and (in particular) contact tracing applications. Therefore, the present study was conducted to design a reminder and recall system for the PeduliLindungi contact tracing application. We used the design science research (DSR) methodology with three iterations. The first iteration produced a low-fidelity prototype (or wireframe), and the next yielded a high-fidelity (clickable) prototype. The final prototype included three main features: a reminder and recall mechanism, online registration for COVID-19 booster vaccination, and educational articles. The evaluation consisted of interviews in the first iteration, interviews and the System Usability Scale (SUS) questionnaire in the second, and the Post-Study System Usability Questionnaire (PSSUQ) in the third. The SUS value obtained in the second iteration was 71.6, indicating good (acceptable) results, while in the third iteration, the system usefulness, information quality, interface quality, and overall PSSUQ values were 2.456, 2.473, 2.230, and 2.397, respectively, indicating good quality of the resulting design. This research contributes to two areas: implementation of a reminder and recall system in the PeduliLindungi contact tracing application and enhancement of contact tracing applications using DSR methodology.

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.

Kepastian Hukum Pemilik Data Pribadi Dalam Aplikasi Satu Sehat

PeduliLindung is a contact tracing application initiated by the Government of Indonesia with the aim of tracking the Covid-19 Virus. However, in its implementation, there have been many criticisms and protests from the public regarding the insecurity of personal data protection in the PeduliLindung application. Moreover, until now Indonesia does not yet have a Personal Data Protection Law. This journal discusses how legal protection is for people who use the PeduliLindung application, as well as a comparison of Indonesian laws with other countries that have previously used contact tracing applications and have regulations regarding personal data. The research method used is literature study by studying journals and related laws.

How Are Security, Privacy and Trust Affecting Continuance Intention of Contact Tracing Applications?

How Are Security, Privacy and Trust Affecting Continuance Intention of Contact Tracing Applications?