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Executive Summary
Contact tracing is becoming a joint intervention to control the spread of COVID-19, which is a highly infectious disease. This article investigates the Traffic Light QR Code mobile application and its use to impact the UK positively. The procedural fairness theory, dual calculus theory, protection motivation theory, theory of planned behavior, and Hofstede’s cultural dimension theory are all part of a conceptual framework developed for this article. The study takes a quantitative approach, using a random sampling technique to collect data from various respondents. Structural equation modeling is used to test the proposed model. The perceived effectiveness of privacy policies were found to harm privacy concerns, whereas perceived vulnerability positively impacted. Privacy concerns harmed DCT apps’ attitudes, whereas expected personal and community-related outcomes of sharing information positively impacted. Attitude, subjective norms, and privacy self-efficacy all influenced the intention to use the Traffic Light QR Code mobile app. This is the first study to empirically test the Traffic Light QR Code mobile app’s adoption, and it contributes both theoretically and practically to a better understanding of the factors that influence their widespread adoption.
Table of Contents TOC o “1-3” h z u Executive Summary PAGEREF _Toc67514794 h 2Chapter I. INTRODUCTION PAGEREF _Toc67514795 h 41.1Significance of the Problem PAGEREF _Toc67514796 h 51.2Theoretical Analysis PAGEREF _Toc67514797 h 51.3Problem Statement PAGEREF _Toc67514798 h 61.4 Hypothesis PAGEREF _Toc67514799 h 61.4.1 Hypothesis 1 PAGEREF _Toc67514800 h 61.4.2 Hypothesis 2 PAGEREF _Toc67514801 h 6Chapter II. LITERATURE REVIEW PAGEREF _Toc67514802 h 62.1 Historical Background PAGEREF _Toc67514803 h 92.2 The Relevant Theory Behind the Traffic Light QR Code Application PAGEREF _Toc67514804 h 112.3 Current Empirical Literature Relevant to the Traffic Light QR Code App PAGEREF _Toc67514805 h 15Chapter III. METHOD PAGEREF _Toc67514806 h 203.1 Participants PAGEREF _Toc67514807 h 223.2 Research Design PAGEREF _Toc67514808 h 263.3 Data Analysis PAGEREF _Toc67514809 h 27Chapter IV. RESULTS PAGEREF _Toc67514810 h 314.1 Statistical Analysis PAGEREF _Toc67514811 h 334.2 Tables and Figures PAGEREF _Toc67514812 h 36Chapter V. DISCUSSION PAGEREF _Toc67514813 h 395.1 Summary PAGEREF _Toc67514814 h 445.2 Conclusion PAGEREF _Toc67514815 h 475.3 Limitations PAGEREF _Toc67514816 h 475.4 Recommendations for Future Research PAGEREF _Toc67514817 h 48References PAGEREF _Toc67514818 h 50
Numerous governments are hurrying to adopt new known techniques that would have been unthinkable just a few months ago, from drones barking social distancing orders to tracking people’s movements through smartphones. A diverse and growing tech-based chorus, which is being relayed by the media and many governments worldwide, is calling for smartphone proximity technology to combat Covid-19. The logic is simple: because the coronavirus spreads with population movement, using the massive amounts of digital personal data generated by our smartphones can help us understand how the virus is spreading and even guide quarantine or lockdown decisions (Allam et al., 2020, 409). According to public health experts and tech giants, smartphones could provide a solution to an urgent need for widespread, rapid contact tracing applications, which would track and trace infected people and whom they came into contact with as they move around the world. According to proponents of this approach, many people already own smartphones, which are frequently used to track users’ movements and interactions in the physical world. Many different technical solutions are being proposed to put in place such tracing apps, all based on the belief that a digital solution exists to combat the pandemic’s spread. This paper provides an overview of the Traffic Light QR Code mobile application and examples of national deployments in the UK. It also raises concerns about the efficacy of such technologies for epidemiological purposes and their impact on personal privacy and liberties.
1 Significance of the Problem
As public health officials worldwide prepare vaccination campaigns against COVID-19, a new SARS-CoV-2 variant has emerged in the United Kingdom, prompting scientists to wonder if it has any implications for the virus’s transmissibility, the severity of infection, or vaccine success. However, experts say it is unlikely to stymie vaccination efforts. According to Public Health England, 1,108 COVID-19 cases with the new variant were identified as of December 13, primarily in England’s south and east (December 14). According to the statement, “high numbers of cases of the variant virus have been observed in some areas where there is also a high incidence of COVID-19.” “At this time, it’s unclear whether the variant is to blame for the increased number of cases.” In this case, this mobile application will be groundbreaking and play a significant role in controlling the spread of the virus in the UK (Bayram et al., 2020, 460).
2 Theoretical Analysis
Practitioners and researchers were becoming increasingly interested in the topic of privacy. The process of weighing the costs and benefits of privacy was discovered to be a rational one. However, studies on privacy and information disclosure have produced contradictory results. The decision-making process was irrational, with people giving little to no thought to privacy risk factors. This emphasizes the contextual nature of privacy decision-making and suggests the need for more research in various settings (Allam et al., 2020, 409). Studies have revealed significant differences in people’s perceptions across countries when weighing privacy costs and benefits. According to the researchers, personality traits and culture influence people in the United States to be more attracted to rewards. In Europe, however, intrusiveness is a critical consideration when it comes to privacy and information disclosure. In both China and the United States, it was discovered that technological infrastructure and the environmental impact technology adoption rates (Bayram et al., 2020, 460). The United States is currently lagging in terms of contact tracing application deployment. Because each state was left to develop its applications, Alabama, North Carolina, North Dakota, South Dakota, and Utah have released them. The United States’ patchwork approach makes effective application deployment particularly difficult.
3 Problem Statement
The Traffic Light QR Code mobile app will play a significant role in curbing the spread of Covid-19 in the UK. As such, there will be clear avenues and platforms for notifications to facilitate quicker decision-making concerning this.
1.4 Hypothesis
1.4.1 Hypothesis 1
Individuals who will readily accept the Traffic Light QR Code mobile app will play an essential role in curbing the spread of COVID-19 as compared to those who reject this mobile application.
1.4.2 Hypothesis 2
Individuals who reject the Traffic Light QR Code mobile app will fasten the virus’s pace since there is no control measure in place.
Data on people’s movements and locations can be gathered using various technologies, the most common of cell sites, GPS, and Bluetooth. Cell phones work by connecting to a network of radio antennas known as “cell sites.” Cell site records are frequently only capable of locating a phone within a range of 800 meters to three kilometers. Phones with GPS sensors built-in can do a lot better. Under the open sky, GPS-enabled smartphones are usually accurate within a 4.9 m (16 ft.) radius.
On the other hand, GPS radio signals are weak; the technology does not work indoors and performs poorly near large buildings, in large cities, and inclement weather. For Covid19 tracing solutions, more precise technologies were required to identify close contacts. As a result, developers quickly developed workarounds for apps that used Bluetooth signal strength to determine whether two smartphones were close enough together for their users to spread the virus (Allam et al., 2020, 409).
When two users of the Traffic Light QR Code mobile app come close to each other, the Bluetooth technology allows both apps to estimate the distance between them based on Bluetooth signal strength. The apps exchange identifiers if they estimate they are less than two meters apart for a long enough period. Each app records an encounter with the identifier of the other. The application does not require the users’ location because it only needs to know if they are close enough together to pose a risk of infection (Bayram et al., 2020, 462). However, none of these technologies, even when combined for greater precision, can guarantee that a phone can be located with less than 2 meters of precision at any given time, which is one of the central promises of these technological solutions.
Nonetheless, Apple and Google announced a joint app based on these principles that will be released in May for iOS and Android, and a growing number of other apps with similar designs are now available and being used across the globe in many countries. At least 19 countries are using phone apps to identify corona-positive people and figure out whom they may have interacted with. Because China is the subject of another article, we ch…