Contact Tracing Proximity Data Exchange and Consolidation with App Design

2020 ◽  
Author(s):  
Hari T.S. Narayanan
Keyword(s):  
Data Exchange ◽  
Contact Tracing ◽  
Proximity Data ◽  
App Design

scholarly journals Scheduling Proximity Data Exchange for Contact Tracing

2021 ◽  
Author(s):  
Hari T S Narayanan
Keyword(s):  
Analytical Model ◽  
Data Exchange ◽  
Contact Tracing ◽  
Proximity Data

The data is generated using analytical model for analysis

scholarly journals Scheduling Proximity Data Exchange for Contact Tracing

2021 ◽  
Author(s):  
Hari T S Narayanan
Keyword(s):  
Analytical Model ◽  
Data Exchange ◽  
Contact Tracing ◽  
Proximity Data

The data is generated using analytical model for analysis

scholarly journals Novel Distributed and Federated Contact Tracing Systems – A Global Solution

2021 ◽  
Author(s):  
Hari T S Narayanan
Keyword(s):  
Global Solution ◽  
Decentralized Control ◽  
Data Exchange ◽  
Low Risk ◽  
Contact Tracing ◽  
Distributed Design ◽  
Proximity Data ◽  
Global Mobility ◽  
User Groups

There are several contact tracing solutions, some are for closed user groups, some are for the residents of a country, and some are open solutions with no clear boundary defined. These independent solutions are not adequate to support pre-pandemic global mobility. Ideally, what is needed is a global solution that can support decentralized control over data and at the same time support proximity data exchange among Apps developed by different vendors and for different countries. This paper proposes a family of contact tracing designs with low-risk anonymity that includes a centralized design, a distributed design, and a federated design for global solution.

scholarly journals Novel Distributed and Federated Contact Tracing Systems – A Global Solution

2021 ◽  
Author(s):  
Hari T S Narayanan
Keyword(s):  
Global Solution ◽  
Decentralized Control ◽  
Data Exchange ◽  
Low Risk ◽  
Contact Tracing ◽  
Distributed Design ◽  
Proximity Data ◽  
Global Mobility ◽  
User Groups

There are several contact tracing solutions, some are for closed user groups, some are for the residents of a country, and some are open solutions with no clear boundary defined. These independent solutions are not adequate to support pre-pandemic global mobility. Ideally, what is needed is a global solution that can support decentralized control over data and at the same time support proximity data exchange among Apps developed by different vendors and for different countries. This paper proposes a family of contact tracing designs with low-risk anonymity that includes a centralized design, a distributed design, and a federated design for global solution.

scholarly journals A Novel Distributed and Federated Digital Contact Tracing Systems

2021 ◽  
Author(s):  
Hari T S Narayanan
Keyword(s):  
Global Solution ◽  
Decentralized Control ◽  
Data Exchange ◽  
Low Risk ◽  
Contact Tracing ◽  
Distributed Design ◽  
Proximity Data ◽  
Global Mobility ◽  
User Groups

There are several contact tracing solutions, some are for closed user groups, some are for the residents of a country, and some are open solutions with no clear boundary defined. These independent solutions are not adequate to support pre-pandemic global mobility. Ideally, what is needed is a global solution that can support decentralized control over data and at the same time support proximity data exchange among Apps developed by different vendors and for different countries. This paper proposes a family of contact tracing designs with low-risk anonymity that includes a centralized design, a distributed design, and a federated design for global solution.

scholarly journals Contact Tracing: a game of big numbers in the time of COVID-19

2020 ◽  
Author(s):  
Hyunju Kim ◽  
Ayan Paul
Keyword(s):  
Mobile Devices ◽  
Optimal Solution ◽  
Social Structures ◽  
Contact Tracing ◽  
Potential Danger ◽  
Crucial Importance ◽  
Minimum Threshold ◽  
Proximity Data ◽  
Slowing Down ◽  
Personal Mobile Devices

ABSTRACTOne of the more widely advocated solutions to slowing down the spread of COVID-19 has been automated contact tracing. Since proximity data can be collected by personal mobile devices, the natural proposal has been to use this for contact tracing as this provides a major gain over a manual implementation. In this work, we study the characteristics of automated contact tracing and its effectiveness for mapping the spread of a pandemic due to the spread of SARS-CoV-2. We highlight the infrastructure and social structures required for automated contact tracing to work for the current pandemic. We display the vulnerabilities of the strategy to inadequately sample the population, which results in the inability to sufficiently determine significant contact with infected individuals. Of crucial importance will be the participation of a significant fraction of the population for which we derive a minimum threshold. We conclude that a strong reliance on contact tracing to contain the spread of the SARS-CoV-2 pandemic can lead to the potential danger of allowing the pandemic to spread unchecked. A carefully thought out strategy for controlling the spread of the pandemic along with automated contact tracing can lead to an optimal solution.

scholarly journals Heuristic Scheduler for Proximity Data Exchange

2021 ◽  
Author(s):  
Hari T S Narayanan
Keyword(s):  
Analytical Model ◽  
Data Exchange ◽  
Proximity Data

The data is generated using analytical model for analysis

scholarly journals Social network heterogeneity is essential for contact tracing

2020 ◽  
Author(s):  
Bjarke Frost Nielsen ◽  
Kim Sneppen ◽  
Lone Simonsen ◽  
Joachim Mathiesen
Keyword(s):  
Social Network ◽  
Social Structure ◽  
Mitigation Strategy ◽  
Mitigation Strategies ◽  
Contact Tracing ◽  
Activity Levels ◽  
Proximity Data ◽  
Personal Mobility ◽  
Network Heterogeneity ◽  
The Social

Contact tracing is suggested as an effective strategy for controlling an epidemic without severely limiting personal mobility. Here, we explore how social structure affects contact tracing of COVID-19. Using smartphone proximity data, we simulate the spread of COVID-19 and find that heterogeneity in the social network and activity levels of individuals decreases the severity of an epidemic and improves the effectiveness of contact tracing. As a mitigation strategy, contact tracing depends strongly on social structure and can be remarkably effective, even if only frequent contacts are traced. In perspective, this highlights the necessity of incorporating social heterogeneity into models of mitigation strategies.

scholarly journals Corona Contact Tracing Apps: Empirical Study on Self-Focused and Other-Focused Health Concerns as Predictors of App-Uptake (Preprint)

2021 ◽  
Author(s):  
Fenne große Deters ◽  
Tabea Meier ◽  
Anne Milek ◽  
Andrea B. Horn
Keyword(s):  
Odds Ratio ◽  
Demographic Variables ◽  
Contact Tracing ◽  
Curvilinear Relationship ◽  
Economic Activities ◽  
German Speaking ◽  
The Government ◽  
App Design ◽  
And Control

BACKGROUND Corona contact tracing apps are a novel and promising measure to reduce the spread of COVID-19. They can help to balance the need to maintain normal life and economic activities as much as possible while still avoiding exponentially growing case numbers. However, a majority of citizens needs to be willing to install such an app for it to be effective. Hence, knowledge about drivers for app-uptake is crucial. OBJECTIVE The present study aims to add to our understanding of underlying psychological factors motivating app-uptake. More specifically, we investigated the role of concern for one’s own health and concern to unknowingly infect others. METHODS A two-wave survey with N = 346 German-speaking participants from Switzerland and Germany was conducted. We measured the uptake of two decentralized contact tracing apps officially launched by governments (“Corona-Warn-App”, Germany; “SwissCovid”, Switzerland) as well as concerns regarding COVID-19 and control variables. RESULTS While controlling for demographic variables as well as general attitudes towards the government and the pandemic, logistic regression analysis showed a significant effect of self-focused concerns (Odds Ratio = 1.64, P <.01). Meanwhile, concern to unknowingly infect others did not contribute significantly to the prediction of app-uptake over and above concern for one’s own health (Odds Ratio = 1.01, P = .92). Longitudinal analyses replicated this pattern and showed no support for the possibility that app-uptake provokes changes in levels of concern. Testing for a curvilinear relationship, no evidence was found that “too much” concern leads to defensive reactions and reduces app-uptake. CONCLUSIONS As one of the first studies to assess the installation of already launched corona tracing apps, our study extends our knowledge of the motivational landscape of app-uptake. Based on that, practical implications for communication strategies and app design are discussed. CLINICALTRIAL

scholarly journals Automated contact tracing: a game of big numbers in the time of COVID-19

2021 ◽  
Vol 18 (175) ◽  
pp. 20200954
Author(s):  
Hyunju Kim ◽  
Ayan Paul
Keyword(s):  
Optimal Solution ◽  
Social Structures ◽  
Contact Tracing ◽  
Crucial Importance ◽  
Minimum Threshold ◽  
Proximity Data ◽  
Slowing Down ◽  
Personal Mobile Devices ◽  
Mitigation Methods ◽  
Simultaneous Implementation

One of the more widely advocated solutions for slowing down the spread of COVID-19 has been automated contact tracing. Since proximity data can be collected by personal mobile devices, the natural proposal has been to use this for automated contact tracing providing a major gain over a manual implementation. In this work, we study the characteristics of voluntary and automated contact tracing and its effectiveness for mapping the spread of a pandemic due to the spread of SARS-CoV-2. We highlight the infrastructure and social structures required for automated contact tracing to work. We display the vulnerabilities of the strategy to inadequate sampling of the population, which results in the inability to sufficiently determine significant contact with infected individuals. Of crucial importance will be the participation of a significant fraction of the population for which we derive a minimum threshold. We conclude that relying largely on automated contact tracing without population-wide participation to contain the spread of the SARS-CoV-2 pandemic can be counterproductive and allow the pandemic to spread unchecked. The simultaneous implementation of various mitigation methods along with automated contact tracing is necessary for reaching an optimal solution to contain the pandemic.

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