SARiSsa -- A Mobile Application for the Proactive Control of SARS-CoV-2
Spread
- URL: http://arxiv.org/abs/2106.14567v2
- Date: Tue, 29 Jun 2021 10:40:03 GMT
- Title: SARiSsa -- A Mobile Application for the Proactive Control of SARS-CoV-2
Spread
- Authors: Christos Chondros, Christos Georgiou-Mousses, Stavros D. Nikolopoulos,
Iosif Polenakis and Vasileios Vouronikos
- Abstract summary: We propose the design principles behind the development of a smart application utilized by mobile devices in order to control the spread of SARS-CoV-2 coronavirus disease.
We propose an open architecture for the development of such applications, that incorporates a more elaborated graph-theoretic and algorithmic background regarding the contact tracing.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: In this work we propose the design principles behind the development of a
smart application utilized by mobile devices in order to control the spread of
SARS-CoV-2 coronavirus disease that caused the COVID-19 pandemic. Through the
deployment of this application utilizing their Bluetooth enabled devices,
individuals may keep track of their close contacts, and if nearby contacts
using the same application are reported later as infected the proximate
individual is informed in order to be quarantined for a short of time,
preventing hence the spread of the virus. Through the latest year, there have
been developed several applications in the Google Play Store that can be
deployed by smart devices utilizing their Bluetooth connectivity for the nearby
device tracking. However, in this work we propose an open architecture for the
development of such applications, that also incorporates a more elaborated
graph-theoretic and algorithmic background regarding the contact tracing. The
proposed contact tracing algorithm, that can be embedded in the deployment of
the application, provides a more immediate tracking of the contacts of an
infected individuals, providing a wider extent in the tracing of the contacts,
leading hence to a more immediate mitigation of the epidemic.
Related papers
- Protect Your Score: Contact Tracing With Differential Privacy Guarantees [68.53998103087508]
We argue that privacy concerns currently hold deployment back.
We propose a contact tracing algorithm with differential privacy guarantees against this attack.
Especially for realistic test scenarios, we achieve a two to ten-fold reduction in the infection rate of the virus.
arXiv Detail & Related papers (2023-12-18T11:16:33Z) - Epidemic Management and Control Through Risk-Dependent Individual
Contact Interventions [1.1439420412899566]
Testing, contact tracing, and isolation (TTI) is an epidemic management and control approach that is difficult to implement at scale.
Here we demonstrate a scalable improvement to TTI and exposure notification apps that uses data assimilation (DA) on a contact network.
arXiv Detail & Related papers (2021-09-22T18:39:10Z) - Explainable Link Prediction for Privacy-Preserving Contact Tracing [5.866574931696403]
Contact tracing has been used to identify people who were in close proximity to those infected with SARS-Cov2 coronavirus.
A number of digital contract tracing applications have been introduced to facilitate or complement physical contact tracing.
We present ideas from Graph Neural Networks and explainability, that could improve trust in these applications, and encourage adoption by people.
arXiv Detail & Related papers (2020-12-10T08:58:24Z) - Contact Tracing Made Un-relay-able [18.841230080121118]
SARS-CoV-2 pandemic put a heavy strain on the healthcare system of many countries.
Governments chose different approaches to face the spread of the virus.
Mobile apps allow to achieve a privacy-preserving contact tracing of citizens.
arXiv Detail & Related papers (2020-10-23T20:03:31Z) - 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) - An Automated Contact Tracing Approach for Controlling Covid-19 Spread
Based on Geolocation Data from Mobile Cellular Networks [5.409709616786615]
We propose a new method for COVID-19 contact tracing based on mobile phone users' geolocation data.
The proposed method will help the authorities to identify the number of probable infected persons without using smartphone based mobile applications.
arXiv Detail & Related papers (2020-07-06T11:40:23Z) - Trust and Transparency in Contact Tracing Applications [81.07729301514182]
The global outbreak of COVID-19 has led to efforts to manage and mitigate the continued spread of the disease.
One of these efforts include the use of contact tracing to identify people who are at-risk of developing the disease through exposure to an infected person.
There has been significant interest in the development and use of digital contact tracing solutions to supplement the work of human contact tracers.
The collection and use of sensitive personal details by these applications has led to a number of concerns by the stakeholder groups with a vested interest in these solutions.
arXiv Detail & Related papers (2020-06-19T20:29:24Z) - Mind the GAP: Security & Privacy Risks of Contact Tracing Apps [75.7995398006171]
Google and Apple have jointly provided an API for exposure notification in order to implement decentralized contract tracing apps using Bluetooth Low Energy.
We demonstrate that in real-world scenarios the GAP design is vulnerable to (i) profiling and possibly de-anonymizing persons, and (ii) relay-based wormhole attacks that basically can generate fake contacts.
arXiv Detail & Related papers (2020-06-10T16:05:05Z) - Decentralized Privacy-Preserving Proximity Tracing [50.27258414960402]
DP3T provides a technological foundation to help slow the spread of SARS-CoV-2.
System aims to minimise privacy and security risks for individuals and communities.
arXiv Detail & Related papers (2020-05-25T12:32:02Z) - 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) - Proximity: a recipe to break the outbreak [0.0]
This smartphone application will work offline and will be able to detect other devices in close proximity and list all the interactions in an anonymous and encrypted way.
If an app user is tested positive and so is certified as infected, the application notifies immediately the potential contagion to the devices in the list and suggests to start a voluntary quarantine and undergo a medical test.
arXiv Detail & Related papers (2020-03-23T12:33:28Z)
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.