Contact Tracing Applications Research Articles

Acceptability and Effectiveness of COVID-19 Contact Tracing Applications: A Case Study in Saudi Arabia of the Tawakkalna Application.

Background Contact tracing applications were introduced during the COVID-19 pandemic to mitigate the spread of the infection in several countries. In Saudi Arabia, the Tawakkalna application was developed. The Tawakkalna application is a mobile health solution aimed to track infection cases, save lives, and reduce the burden on health facilities. This study aims to explore the public's attitude to and acceptance levels of the Tawakkalna application and to evaluate its effectiveness regarding privacy and security. The main objective of this study is to investigate the user acceptability of contact tracing applications and explore the safety and privacy effectiveness of the COVID-19 contact tracing application, the Tawakkalna application. In addition, the study analyzes factors associated with acceptance levels and compares the results obtained to similar studies in other countries using similar applications. Methodology This study used a valid and reliable online survey that was used in similar studies conducted in other countries to assess the acceptability of the application. The survey was conducted from September to November 2021, and the final dataset included 205 participants. To investigate the privacy and security performance of the Tawakkalna application, we followed the investigation method used by similar research that investigated 28 contact tracing applications across Europe. Results Out of the 205 participants, 84.87% were in favor of the opt-in voluntary installation of the Tawakkalna application, and 49.75% of the participants were in favor of the opt-out automatic installation. Individuals' trust in the government had a huge impact on acceptance, with 60.98% of the participants supporting the application because they believed that the Tawakkalna application would help them stay healthy during the COVID-19 pandemic. Overall, 49% of the participants supporting the application also agreed to the de-identification of their collected data and providing it for research. The Tawakkalna application ranked at the top compared to other contact tracing applications regarding privacy and security. Conclusions The Tawakkalna application developed by the Saudi Data and Artificial Intelligence Authority was a response to the COVID-19 pandemic, which is considered the biggest public health crisis in recent times. The Saudi Arabian government gained the population's acceptance through effective endorsement and the spread of educational content through media channels. By complying with privacy policies, the Tawakkalna application is an effective tool to combat public health infectious diseases.

Comparing Efficiency and Performance of IoT BLE and RFID-Based Systems for Achieving Contract Tracing to Monitor Infection Spread among Hospital and Office Staff.

COVID-19 is highly contagious and spreads rapidly; it can be transmitted through coughing or contact with virus-contaminated hands, surfaces, or objects. The virus spreads faster indoors and in crowded places; therefore, there is a huge demand for contact tracing applications in indoor environments, such as hospitals and offices, in order to measure personnel proximity while placing as little load on them as possible. Contact tracing is a vital step in controlling and restricting pandemic spread; however, traditional contact tracing is time-consuming, exhausting, and ineffective. As a result, more research and application of smart digital contact tracing is necessary. As the Internet of Things (IoT) and wearable sensor device studies have grown in popularity, this work has been based on the practicality and successful implementation of Bluetooth low energy (BLE) and radio frequency identification (RFID) IoT based wireless systems for achieving contact tracing. Our study presents autonomous, low-cost, long-battery-life wireless sensing systems for contact tracing applications in hospital/office environments; these systems are developed with off-the-shelf components and do not rely on end user participation in order to prevent any inconvenience. Performance evaluation of the two implemented systems is carried out under various real practical settings and scenarios; these two implemented centralised IoT contact tracing devices were tested and compared demonstrating their efficiency results.

Optimizing the order of actions in a model of contact tracing.

Contact tracing is a key tool for managing epidemic diseases like HIV, tuberculosis, COVID-19, and monkeypox. Manual investigations by human-contact tracers remain a dominant way in which this is carried out. This process is limited by the number of contact tracers available, who are often overburdened during an outbreak or epidemic. As a result, a crucial decision in any contact tracing strategy is, given a set of contacts, which person should a tracer trace next? In this work, we develop a formal model that articulates these questions and provides a framework for comparing contact tracing strategies. Through analyzing our model, we give provably optimal prioritization policies via a clean connection to a tool from operations research called a "branching bandit". Examining these policies gives qualitative insight into trade-offs in contact tracing applications.

In search of ethical pandemic technology.

The duration of the pandemic over the last two years has witnessed the steering of multiple technological interventions by governments. These interventions - ranging from contact tracing applications to vaccine certificates - have been developed in the specific context of the pandemic, and were meant to address its unique requirements. This family of technological interventions may be termed "pandemic technology" - having diverse uses such as preventing the transmission of Covid-19, and aiding the relaxation of pandemic-induced restrictions. We propose a four-rung ethical paradigm for the deployment of such technology. We call it the STEP model and its four pillars consist of (i) sunset clauses, (ii) trust, (iii) equity, and (iv) privacy preservation.

A Framework for Infectious Disease Monitoring With Automated Contact Tracing—A Case Study of COVID-19

Throughout human history, deadly infectious diseases emerged occasionally. Even with the present-day advanced healthcare systems, the COVID-19 has caused more than six million deaths worldwide (as of 27 July 2022). Currently, researchers are working to develop tools for better and effective management of the pandemic. “Contact tracing” is one such tool to monitor and control the spread of the disease. However, manual contact tracing is labor-intensive and time-consuming. Therefore, manually tracking all potentially infected individuals is a great challenge, especially for an infectious disease like COVID-19. To date, many digital contact tracing applications were developed and used globally to restrain the spread of COVID-19. In this work, we perform a detailed review of the current digital contact tracing technologies. We mention some of their key limitations and propose a fully integrated system for contact tracing of infectious diseases using COVID-19 as a case study. Our system has four main modules—1) case maps; 2) exposure detection; 3) screening; and 4) health indicators that take multiple inputs like users’ self-reported information, measurement of physiological parameters, and information of the confirmed cases from the public health, and keeps a record of contact histories using Bluetooth technology. The system can potentially evaluate the users’ risk of getting infected and generate notifications to alert them about the exposure events, risk of infection, or abnormal health indicators. The system further integrates the Web-based information on confirmed COVID-19 cases and screening tools, which potentially increases the adoption rate of the system.

The 2020 İzmir earthquake and its effect on COVID-19 cases

On 30 October 2020, an earthquake measuring 6.9 moment magnitude occurred between Kusadasi and Samos, Türkiye, with a significant impact on buildings in the Bornova–Bayraklı district of İzmir. Immediately afterwards, a comprehensive study was commenced to investigate the relationship between the earthquake that occurred during the SARS-CoV-2 (COVID-19) pandemic and case numbers at the Ege University, Faculty of Medicine’s Hospital in Bornova, İzmir. This cross-sectional study was carried out based on the records of those admitted to the university hospital with suspicion of COVID-19 in the pre-earthquake and post-earthquake periods of the pandemic. The microbiology laboratory of the hospital used reverse transcription–polymerase chain reaction (RT-PCR) results as a dependent variable and compared with the time, age and gender as the independent variables, classified according to the timing of the earthquake. RT-PCR test results were positive in 11.60% of the whole study group; however, tests were 6.69% positive before the earthquake and increased to 23.42% afterwards (P < 0.001), which equated to an increase of 4.25 times (95% CI 4.04–4.47) when comparing pre- to post-earthquake RT-PCR positivity (P < 0.001). The positive COVID-19 RT-PCR detection rate among those aged 50 and over was greater by a factor of 1.15 (95% CI 1.06–1.23) compared to a younger age group (P < 0.001). There was no difference for the gender variable used in suspected case or contact tracing applications of COVID-19 PCR. However, when stratified by age and gender, in the female group, there was a 1.24-fold (95% CI 1.11–1.38) increase in the 50+ age group (26.2%) compared to the younger age group (22.2%) after the earthquake (P < 0.001). In the male group, the rate of laboratory diagnosis of COVID-19 before the earthquake was in the under-50 age group (7.6%) as compared to the >50 age group (5.2%; P < 0.001).

Behavioral intention & use behavior of citizens in Iligan city towards the staysafe.ph application during the covid 19 pandemic

The Covid-19 pandemic has encouraged the use of digital solutions such as contact tracing applications to manage the spread of the virus infection. The use of Staysafe.ph app in particular is central to the management of public health emergencies in the country, however, it is important to understand the needs and tolerances of different users to address factors that may hinder the adoption of such strategy. Prior research in contact-tracing apps focuses solely on measuring people’s intentions to use the app. However, the effectiveness of contact-tracing apps is dependent on a significant percentage of the population installing and using the app. Hence, to investigate the intention to use and usage behavior of citizens towards the Staysafe.ph application during the pandemic, the UTAUT model is used, expanding it with three constructs: privacy concern and self-efficacy as direct determinants for behavioral intention; and fear of Covid-19 as a moderator. A survey experiment (N = 400) in Iligan City is used, in which a web-based version of the survey questionnaire was distributed through social networks. The measurement and structure model were appraised using structural equation modelling (SEM). The result shows that effort expectancy, social influence, facilitating conditions, and self-efficacy played an important role in behavioral intention and usage of the app, except for performance expectancy and privacy concerns. Moreover, respondents showing behavioral intention to use the application are more likely to use the app. The multiple regression analysis showed that fear of Covid-19 and age as moderating factors do not have a significant impact on behavioral intention and use behavior. These findings were interpreted in the light of current conceptualizations in the area of the study and their implications for the future were pointed out. You should leave 8 mm of space above the abstract and 10 mm after the abstract. The heading Abstract should be typed in bold 9-point Arial. The body of the abstract should be typed in normal 9-point Times in a single paragraph, immediately following the heading. The text should be set to 1 line spacing. The abstract should be centred across the page, indented 17 mm from the left and right page margins and justified. It should not normally exceed 200 words.

Understanding the impact of digital contact tracing during the COVID-19 pandemic.

Digital contact tracing (DCT) applications have been introduced in many countries to aid the containment of COVID-19 outbreaks. Initially, enthusiasm was high regarding their implementation as a non-pharmaceutical intervention (NPI). However, no country was able to prevent larger outbreaks without falling back to harsher NPIs. Here, we discuss results of a stochastic infectious-disease model that provide insights in how the progression of an outbreak and key parameters such as detection probability, app participation and its distribution, as well as engagement of users impact DCT efficacy informed by results of empirical studies. We further show how contact heterogeneity and local contact clustering impact the intervention's efficacy. We conclude that DCT apps might have prevented cases on the order of single-digit percentages during single outbreaks for empirically plausible ranges of parameters, ignoring that a substantial part of these contacts would have been identified by manual contact tracing. This result is generally robust against changes in network topology with exceptions for homogeneous-degree, locally-clustered contact networks, on which the intervention prevents more infections. An improvement of efficacy is similarly observed when app participation is highly clustered. We find that DCT typically averts more cases during the super-critical phase of an epidemic when case counts are rising and the measured efficacy therefore depends on the time of evaluation.

The insufficiency of the Malaysian contact tracing app from the perspective of Chinese tourists: preparing for international tourism in the post-COVID-19 world

Understanding tourists' feedback on using Mysejahtera is critical for tourism recovery in these destinations, and even more so for countries like Malaysia and China, where national Contact Tracing Applications (CTA) are mandatory. However, Previous surveys on CTA use have mainly focused on voluntary CTA users, using qualitative research methods. In this research, Chinese overseas students in Malaysia are included as the reference group, and Chinese tourists with experiences traveling overseas are put into the experimental group. A total of 890 questionnaires were collected and taken as the original data to carry out the Chi-squared and Mann-Whitney U tests. Meanwhile, the experiment implemented a multiple linear regression mechanism to explore the variables that may improve the app Mysejahtera, with further analysis being conducted. According to the results, language issues are the most significant barrier to Chinese visitors using MySejahtera; the inability to register with a Chinese mobile phone number and the need to register a permanent address in Malaysia have a significant negative impact on the use of MySejahtera; and visitors' trust in science positively related to MySejahtera use.

Ultrawideband Ranging in Dynamic Dense Human Networks

Non-line-of-sight (NLoS) conditions are a known performance limiting factor in ultrawideband (UWB) ranging accuracy, particularly in environments with densely packed dynamically moving humans, i.e., crowds. As UWB technology is recently seeing wide deployment in consumer devices, the effects of NLoS conditions due to human body shadowing will greatly degrade the performance of related ranging and localization applications. We thus propose the round-robin ranging protocol, an extension of alternative double-sided two-way ranging, which scales well for high rate sampling of dense networks and further propose a cooperative statistical approach based on multidimensional scaling (MDS) to mitigate NLoS conditions. Experimental validation was performed in a densely packed dynamically moving human environment. Nine subjects walked naturally within a 16-m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> motion capture area while wearing UWB sensors at the foot, wrist, torso, and head and reflective optical motion capture markers. UWB accuracy of the 36 intersubject ranges was computed as the difference in range estimates between the UWB sensors and the optical motion capture system. Results showed that the proposed MDS approach reduced ranging accuracy errors by 11%, 13%, 16%, and 32% at the foot, wrist, torso, and head, respectively. Body placement had a significant effect on the ranging performance in that transceivers placed on the head and foot reduced ranging errors by 84% and 63% compared with the traditional torso placement. These results suggest that the proposed approaches could significantly improve the performance in UWB ranging applications involving human bodies such as human movement monitoring, athletics, logistics, and social contact tracing applications.

Governing digital crisis responses: platform standards and the dilemma of COVID-19 contact tracing

In response to the impact of the SARS-CoV-2 (COVID-19) pandemic, various developers turned to smartphone-based contact tracing to address the challenges of manual tracing. Due to the presence of network effects, i.e., the effectiveness of contact tracing applications increases with the number of users, information technology standards were critical to the technology’s success. The standardization efforts in Europe led to a variety of trade-offs concerning the choice of an appropriate technological architecture due to the contradictory tensions resulting from the dualism between the need for contact tracing data to contain the pandemic and the need for data minimization to preserve user privacy. Drawing predominantly on the software platform and standards literature, we conduct an interpretive case study to examine the emergence and consequences of this multi-layered decision situation. Our findings reveal how Google and Apple were able to limit the individual leeway of external developers, thereby effectively resolving the European standards war. Furthermore, we identify and discuss the various short-term and long-term trade-offs associated with the standardization of contact tracing applications and translate our findings into recommendations for policy makers with respect to future crisis situations. Specifically, we propose a strategy grounded in our data that enables responsible actors to make goal-oriented and rapid decisions under time constraints.

Analysis of Factor in User Intention to Use the Covid-19 Tracking Application

Science and technology can be collaborated to create an application that can help to track the contacts of COVID-19 patients. Smartphone-based contact tracing applications have been adopted by more than 50 countries. One of which is in Indonesia. In March 2020, Indonesia launched a mobile application to track the contact of COVID-19 patients namely PeduliLindungi. During its usage, users find some issues about PeduliLindungi, such as potential data leaks, data misuse, and data inaccuracies. This research is aimed to develop a conceptual model to analyze factors that affect user intentions in using the PeduliLindungi application. The proposed conceptual model is the integration of EUCS, DeLone and McLean that is equipped by the system security variables. There were 288 respondents. The data is processed using SmartPLS 3.0. According to the results of the analysis, the proposed conceptual model has 83.1 percent for its accuracy. User satisfaction and system security give a positive and significant impact on user intentions. The variables of content, accuracy, format, ease of use, and timeliness give a positive and significant impact on user satisfaction. On the other hand, the system security has no positive and significant impact on user satisfaction. Meanwhile, user satisfaction and system security itself affects the user's intentions in using the PeduliLindungi application.

The impact of source credibility and risk perception attitudes on Americans’ willingness to participate in contact tracing applications

ABSTRACT Contact tracing has emerged as one tool to communicate infection risks with the public during the COVID-19 pandemic. This study uses source credibility and the risk perception attitude framework to interpret how Americans responded to contact tracing messages from a technology company, employer, physician, or state government. Survey participants (n = 245) were generally positive towards a contact tracing message regardless of source. Participants with high risk perceptions and low efficacy beliefs responded more strongly to appeals from their company and their physician while the low risk-low efficacy group found the state government appeal more compelling. The results suggest that several sources delivering the same health message could engage people with different risk perceptions and efficacy beliefs.

CoAvoid: Secure, Privacy-Preserved Tracing of Contacts for Infectious Diseases

To fight against infectious diseases (e.g., SARS, COVID-19, Ebola, etc.), government agencies, technology companies and health institutes have launched various contact tracing approaches to identify and notify the people exposed to infection sources. However, existing tracing approaches can lead to severe privacy and security concerns, thereby preventing their secure and widespread use among communities. To tackle these problems, this paper proposes CoAvoid, a decentralized, privacy-preserved contact tracing system that features good dependability and usability. CoAvoid leverages the Google/Apple Exposure Notification (GAEN) API to achieve decent device compatibility and operating efficiency. It utilizes GPS along with Bluetooth Low Energy (BLE) to dependably verify user information. In addition, to enhance privacy protection, CoAvoid applies fuzzification and obfuscation measures to shelter sensitive data, making both servers and users agnostic to information of both low and high-risk populations. The evaluation demonstrates good efficacy and security of CoAvoid. Compared with four state-of-art contact tracing applications, CoAvoid can reduce upload data by at least 90% and simultaneously resist wormhole and replay attacks in various scenarios.

Investigating the Use of COVID-19 Contact Tracing Applications in South Korea and China: An Agency Theory Perspective

Contact tracing applications are one of the most promising tools to slow the spread of coronavirus. Since being first documented in China, the coronavirus disease 2019 (COVID-19) has affected all aspects of society in serious and long-term ways. Tragically, the COVID-19 pandemic has caused more than six million deaths and even set back the progress of world economy by decades. In this study, we investigated the uptake of COVID-19 contact tracing applications in South Korea and China. In particular, drawing on agency theory, we examined the determinants of application use and compared the differences between these two countries. We also identified the moderating effects of privacy concerns and the mediating effects of implementation intention. We conducted a survey-based cross-country field study, and recruited undergraduate and graduate students from South Korea and China, separately. Results showed a large gap regarding the uptake of COVID-19 contact tracing applications between the two countries. In South Korea, self-regulation was the primary determinant, whereas government regulation was the primary factor in China. Our study contributes to the literature on both public health and information privacy, and more significantly, suggests how we can motivate more people to use such applications to prevent the spread of COVID-19.

Innovative methods for health monitoring in Europe: results of a cross-sectional study

Abstract Background Innovative solutions are used to monitor the spread of COVID-19, to research and develop vaccines, and to ensure online privacy and security. The aim of the study is to investigate which innovative methods, including algorithms and digital tools (e.g., social media, artificial intelligence, contact tracing applications) are used to monitor health issues related to COVID-19 in Europe, and who is using them. Methods A questionnaire was developed and administered online to European countries’ representatives and stakeholders of the project Population Health Information Research Infrastructure (PHIRI). The survey investigated the use of innovative solutions and digital tools in Europe to monitor COVID-19 and vaccination programs, to research and develop diagnostics and teleconsultations, and to fight online disinformation. Legislative and ethical aspects were also considered. A descriptive data analysis was performed. Results 19 responses were collected from 14 countries. Digital tools are used to monitor COVID-19 (13/14 countries), vaccination programs (12/14), for telemedicine (7/14), and to fight disinformation (10/14). Specific algorithms to detect the patterns of the pandemic spread are available in five countries. The main target groups of the tools are the general population, healthcare providers, patients and epidemiologists. The uptake rate of the tools ranged 5-100% across countries. Measures to evaluate the impact of digital tools (e.g., user surveys, reviews, evaluation teams) have been adopted in seven countries. Information on legislative and ethical aspects related to the use of digital solutions are available in 10 countries. Conclusions The development and use of innovative methods for population health monitoring and research purposes have been the key to mitigate the COVID-19 pandemic. Improving the uptake rate, impact assessment of digital tools and fight against disinformation could enhance countries’ preparedness for future pandemics. Key messages • Given that digital solutions are deployed in population health monitoring, research, and for online privacy and security, they have a key role in mitigating the COVID-19 pandemic. • Enhancement of the uptake rate and assessment of digital tools, and fight against disinformation could strengthen countries’ preparedness for future pandemics.

COVICT: an IoT based architecture for COVID-19 detection and contact tracing.

The world we live in has been taken quite surprisingly by the outbreak of a novel virus namely SARS-CoV-2. COVID-19 i.e. the disease associated with the virus, has not only shaken the world economy due to enforced lockdown but has also saturated the public health care systems of even most advanced countries due to its exponential spread. The fight against COVID-19 pandemic will continue until majority of world’s population get vaccinated or herd immunity is achieved. Many researchers have exploited the Artificial intelligence (AI) knacks based IoT architecture for early detection and monitoring of potential COVID-19 cases to control the transmission of the virus. However, the main cause of the spread is that people infected with COVID-19 do not show any symptoms and are asymptomatic but can still transmit virus to the masses. Researcher have introduced contact tracing applications to automatically detect contacts that can be infected by the index case. However, these fully automated contact tracing apps have not been accepted due to issues like privacy and cross-app compatibility. In the current study, an IoT based COVID-19 detection and monitoring system with semi-automated and improved contact tracing capability namely COVICT has been presented with application of real-time data of symptoms collected from individuals and contact tracing. The deployment of COVICT, the prediction of infected persons can be made more effective and contaminated areas can be identified to mitigate the further propagation of the virus by imposing Smart Lockdown. The proposed IoT based architecture can be quite helpful for regulatory authorities for policy making to fight COVID-19.

AI-powered public surveillance systems: why we (might) need them and how we want them

In this article, we address the introduction of AI-powered surveillance systems in our society by looking at the deployment of real-time facial recognition technologies (FRT) in public spaces and public health surveillance technologies, in particular contact tracing applications. Both cases of surveillance technologies assist public authorities in the enforcement of the law by allowing the tracking of individual movements and extrapolating results towards monitoring and predicting social behavior. Therefore, they are considered as potentially useful tools in response to societal crises, such as those generated by crime and health related pandemics. To approach the assessment of the potentials and threats of such tools, we offer a framework with three dimensions. A function dimension, examines the type, quality and quantity of data the system needs to employ to work effectively.The consent dimension considers the user's right to be informed about and reject the use of surveillance, questioning whether consent is achievable and whether the user can decide fully autonomously/independently. Finally, a societal dimension that frames vulnerabilities and the impacts of the increased empowerment of established political regimes through new means to control populations based on data surveillance. Our analysis framework can assist public authorities in their decisions on how to design and deploy public surveillance tools in a way that enables compliance with the law while highlighting individual and societal tradeoffs.

Effectiveness of Covid-19 contact tracing solutions

COVID 19 has become a global pandemic requiring public health officials to take many measures to contain its spread. Amongst the measures is tracing those who have been in contact with infected people i.e. contact tracing. This paper examines some digital contact tracing applications that were developed soon after the outbreak (in the year 2020) and how effective they have been. The paper highlights a study done on these applications which shows that there are some issues around the use of the applications which hinders their wider adoption by the public (adoption of these applications by the public is one of the surest ways of containing the spread of the pandemic). The paper goes on to examine an instance where one of the issues raised (security of Personally Identifiable Information, PII) is addressed in a proposed design solution. The paper concludes by suggesting what should be done by contact tracing application developers to ensure their products are more acceptable to consumers thereby leading to their wider adoption.

A Review of COVID-19 Mobile Contact Tracing Applications and Their Impact on Privacy

Contact tracing is a well-established process that has been utilized for years to assist in the effort to control the spread of contagious diseases. The rapid onset and spread of COVID-19 brought about the need for digital solutions which would help to speed up the collection and analysis of relevant health information. With the proliferation of mobile devices, the development of mobile device-based digital contact tracing applications appeared to be the solution. As countries around the globe created digital contact tracing applications for use by their respective populations, a variety of factors allowed for success for some and resulted in failure for others. This review highlights example countries with respect to their unique COVID-19 digital contact tracing solutions, the success or failure of the applications employed on mobile platforms, and the factors which have contributed to the success or failure of these solutions. Additionally, a review of research around data privacy and security in digital contact tracing apps is included.