REAL TIME COVID-19 CONTACT TRACING USING MOBILE APPLICATION


REAL TIME COVID-19 CONTACT TRACING USING MOBILE APPLICATION  

ABSTRACT 

This study is on Real Time COVID-19 Contact Tracing using Mobile Application.. The Automated digital contact tracing is effective and efficient, and one of the non-pharmaceutical complementary approaches to mitigate and manage epidemics like Coronavirus disease 2019 (COVID-19). Despite the advantages of digital contact tracing, it is not widely used in the western world, including the US and Europe, due to strict privacy regulations and patient rights. We categorized the current approaches for contact tracing, namely: mobile service-provider-application, mobile network operators’ call detail, citizen- application, and IoT-based. Current measures for infection control and tracing do not include animals and moving objects like cars despite evidence that these moving objects can be infection carriers. In this article, we designed and presented a novel privacy anonymous IoT model. We presented an RFID proof-of-concept for this model. Our model leverages blockchain’s trust-oriented decentralization for on-chain data logging and retrieval. Our model solution will allow moving objects to receive or send notifications when they are close to a flagged, probable, or confirmed diseased case, or flagged place or object. We implemented and presented three prototype blockchain smart contracts for our model. We then simulated contract deployments and execution of functions. We presented the cost differentials. Our simulation results show less than one- second deployment and call time for smart contracts, though, in real life, it can be up to 25 seconds on Ethereum public blockchain. Our simulation results also show that it costs an average of $1.95 to deploy our prototype smart contracts, and an average of $0.34 to call our functions. Our model will make it easy to identify clusters of infection contacts and help deliver a notification for mass isolation while preserving individual privacy. Furthermore, it can be used to understand better human connectivity, model similar other infection spread network, and develop public policies to control the spread of COVID-19 while preparing for future epidemics.

CHAPTER ONE

INTRODUCTION

Background to the study

Non-pharmacetical measures taken to contain outbreaks require the cooperation of data subjects. Transparency in how consents are obtained and how individual data is used continue to fuel mistrust amongst citizens [1]. The conflict between the right to know, censorship, and data privacy con- tinues to grow. Traditional approaches to sharing information amongst healthcare stakeholders have been with the help of central intermediaries who facilitate care coordination [2].

Blockchain promises the trusted and secure decentralization of these intermediaries [3].The fear of massive surveillance and data misused has hampered voluntary and rapid containment of outbreaks like the Coronavirus disease 2019 (COVID-19) pandemic. The number of infected persons and deaths continue to grow, with wide disparity between jurisdictions with less-stringent privacy rules like China, Africa, Singapore, and South Korea, when compared with infections and deaths per population from the USA, Europe, and, the UK with stricter privacy con- trol measures. Though other factors like the number of tests conducted, the accuracy of data, weather conditions and many

Image

FIGURE 1. COVID-19 infections and deaths per million (June 2nd, 2020) [6].

more may have contributed. The rapidly evolving statistics from the pandemic as of June 2nd, 2020, in Figure 1 shows the number of infections and the number of deaths per million population [4], [5].

COVID-19 spreads mainly through person-to-person transmission and often through respiratory droplets and con- tact with surfaces or items contaminated [7]. Researchers believe that COVID-19 originated from animals [8]. Human to animal transmission is also possible [9].

ASSUMPTION OF THE STUDY

Countries are set to reopen due to economic pressures, and concerns are high on how to sustain pandemic containment gains. We investigated how digital contact tracing is used as one of the many countermeasures against COVID-19. Based on our survey, initiatives around the world and current contact tracing solutions are centrally managed with attendant pri- vacy concerns [10]. There are proposals to decentralize con- tact tracing data storage championed by Apple and Google, the leading mobile phone application providers [11]. These efforts have not enjoyed widespread public and political sup- port. Moreover, these efforts replace one form of central- ization with another. We hypothesize that citizen trust and privacy-concern may affect the voluntary adoption of poten- tially scalable solutions. Also, to our knowledge, there is no contact tracing solution targeted at moving objects or ani- mals. One example of privacy fueled resistance to adoption is India’s Aarogy Setu application. It is now at the centre of a privacy controversy after initial launch successes [12].

Blockchain technology promises trust-oriented intermedi- ation in healthcare [3]. This intermediation capability can help address citizen privacy concerns [3]. Therefore, we are proposing extending the current digital contact tracing solu- tions by updating anonymized contact proximity informa- tion to a blockchain as against traditional centralized gov- ernment servers. In addition, we also propose the use of RFID transceiver to help track moving objects while logging anonymity preserving information on a blockchain.

ORGANIZATION OF THE STUDY

The remaining sections of this article are organized as follows: Section II presents the definition of a case, and then contacts of a case. Section III presents brief literature on how the contact tracing concept is used for the current COVID19 response. Section IV explains the details of the proposed model, including system architecture, networks, and prototype. Section V discusses and interprets technical considerations and tradeoffs of our model while presenting its limitations. Finally, Section VI summarizes and concludes the paper and lay a foundation for future research.

RESEARCH QUESTIONS (RQ)

The research questions answered by this study are:

• RQ-1 What are the current digital contact tracing strate- gies?

• RQ-2 Which contact tracing approach or combination thereof can be used for moving objects?

• RQ-3 What model can both scale and preserve privacy?

CHAPTER TWO

REVIEW OF RELATED LITERATURE

CONTACT TRACING AND WARNING MEASURE

Non-pharmaceutical systematic contact tracing and enforcement of precautionary self-isolation is a key component of the global response [13]. A recent mathematical stochastic model shows that contact tracing can be useful if done within the first three months of COVID-19 or any outbreak [14]. The process often involves contact mapping, identification, isolation, confirmation, and treatment depicted in Figure 2. Contact tracing is the process presented by the dark shades in white print in the block diagram [15].

A. CONTACT DEFINITION

Contact tracing commences when a COVID-19 case is confirmed positive through a laboratory test. In traditional approaches, interviews will then be conducted with the case to ascertain their contacts up to 14 days following symptoms. The next step will be the identification of these contacts  and initiating the contact tracing process [16]. The next two sections will define a COVID-19 case and their contacts following Figure 2 [15].

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