How to Return to Normalcy: Fast and Comprehensive Contact Tracing of COVID-19 through Proximity Sensing Using Mobile Devices

• URL: http://arxiv.org/abs/2004.12576v1
• Date: Mon, 27 Apr 2020 04:17:51 GMT
• Title: How to Return to Normalcy: Fast and Comprehensive Contact Tracing of COVID-19 through Proximity Sensing Using Mobile Devices
• Authors: Ye Xia and Gwendolyn Lee
• Abstract summary: We outline a contact-tracing strategy based on proximity sensing using mobile devices. We show that, when adopted sufficiently broadly, such a contact-tracing strategy can bring COVID-19 under complete control.
• Score: 0.8756822885568589
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We outline a contact-tracing strategy based on proximity sensing using mobile devices. We discuss what an ideal system should look like and what it can do. We show that, when adopted sufficiently broadly, such a contact-tracing strategy can bring COVID-19 under complete control, end the need of social distancing, and return the society to full normalcy. We also review some of the challenges faced by the current generation of proximity-sensing technologies, including Bluetooth Low Energy used by phones, and consider both interim and longer-term solutions. Our main contribution is that we reason through why such a contact-tracing strategy is likely to achieve the stated goal of returning to full normalcy. Using probabilistic models, we show that universal adoption is not necessary to achieve the stated goal, thus there is some room for exceptions; however, the adoption rate needs to be very high, e.g., above $95\%$ depending on the disease parameters. With more vigilance in disease surveillance to detect mild cases earlier, the number may be brought down to about $90\%$. The results call for deployment effort to be led by public authorities at the state or federal level so that the required adoption rate can be reached and the tracing coverage is wide enough to be relevant for disease control.

Related papers

• Artificial Intelligence Empowered Multiple Access for Ultra Reliable and Low Latency THz Wireless Networks [76.89730672544216]
  Terahertz (THz) wireless networks are expected to catalyze the beyond fifth generation (B5G) era. To satisfy the ultra-reliability and low-latency demands of several B5G applications, novel mobility management approaches are required. This article presents a holistic MAC layer approach that enables intelligent user association and resource allocation, as well as flexible and adaptive mobility management.
  arXiv  Detail & Related papers  (2022-08-17T03:00:24Z)
• An Empirical Evaluation of Bluetooth-based Decentralized Contact Tracing in Crowds [7.469941131704084]
  This study empirically investigates the effectiveness of Bluetooth-based contact tracing in crowd environments with a total of 80 participants. Results confirm that Bluetooth RSSI is unreliable for detecting proximity, and that this inaccuracy worsens in environments that are especially crowded. We recommend that existing contact-tracing apps can be re-purposed to focus on coarse-grained proximity detection.
  arXiv  Detail & Related papers  (2020-11-09T10:44:03Z)
• Predicting Infectiousness for Proactive Contact Tracing [75.62186539860787]
  Large-scale digital contact tracing is a potential solution to resume economic and social activity while minimizing spread of the virus. Various DCT methods have been proposed, each making trade-offs between privacy, mobility restrictions, and public health. This paper develops and test methods that can be deployed to a smartphone to proactively predict an individual's infectiousness.
  arXiv  Detail & Related papers  (2020-10-23T17:06:07Z)
• Epidemic mitigation by statistical inference from contact tracing data [61.04165571425021]
  We develop Bayesian inference methods to estimate the risk that an individual is infected. We propose to use probabilistic risk estimation in order to optimize testing and quarantining strategies for the control of an epidemic. Our approaches translate into fully distributed algorithms that only require communication between individuals who have recently been in contact.
  arXiv  Detail & Related papers  (2020-09-20T12:24:45Z)
• Exploring the effectiveness of a COVID-19 contact tracing app using an agent-based model [0.0]
  A contact-tracing strategy has been deemed necessary to contain the spread of COVID-19 following the relaxation of lockdown measures. We explore one of the technology-based strategies proposed, a contact-tracing smartphone app. The model simulates the spread of COVID-19 in a population of agents on an urban scale.
  arXiv  Detail & Related papers  (2020-07-27T16:58:17Z)
• The Fallibility of Contact-Tracing Apps [0.42970700836450487]
  We show that there are not enough smartphones worldwide to reach required adoption thresholds. We report that the contact tracing apps that are already deployed on an opt-in basis show disappointing adoption levels. We warn about the potential consequences of over-extending the existing state and corporate surveillance powers.
  arXiv  Detail & Related papers  (2020-05-22T17:46:16Z)
• COVI White Paper [67.04578448931741]
  Contact tracing is an essential tool to change the course of the Covid-19 pandemic. We present an overview of the rationale, design, ethical considerations and privacy strategy of COVI,' a Covid-19 public peer-to-peer contact tracing and risk awareness mobile application developed in Canada.
  arXiv  Detail & Related papers  (2020-05-18T07:40:49Z)
• Bluetooth Smartphone Apps: Are they the most private and effective solution for COVID-19 contact tracing? [0.21108097398435333]
  Many digital solutions are being proposed for Contact Tracing Apps (CTA) to reduce the spread of COVID-19. Concerns have been raised regarding privacy, consent, uptake required in a given population, and the degree to which use of CTAs can impact individual behaviours. We propose to build on some of the digital solutions already under development that, with addition to a Bayesian model that predicts likelihood for infection, can enable us to reach 90% of a population.
  arXiv  Detail & Related papers  (2020-05-08T07:07:00Z)
• Digital Ariadne: Citizen Empowerment for Epidemic Control [55.41644538483948]
  The COVID-19 crisis represents the most dangerous threat to public health since the H1N1 pandemic of 1918. Technology-assisted location and contact tracing, if broadly adopted, may help limit the spread of infectious diseases. We present a tool, called 'diAry' or 'digital Ariadne', based on voluntary location and Bluetooth tracking on personal devices.
  arXiv  Detail & Related papers  (2020-04-16T15:53:42Z)
• Give more data, awareness and control to individual citizens, and they will help COVID-19 containment [74.10257867142049]
  Contact-tracing apps are being proposed for large scale adoption by many countries. A centralized approach raises concerns about citizens' privacy and needlessly strong digital surveillance. We advocate a decentralized approach, where both contact and location data are collected exclusively in individual citizens' "personal data stores"
  arXiv  Detail & Related papers  (2020-04-10T20:30:37Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.