A Close Contact Tracing Method Based on Bluetooth Signals Applicable to Ship Environments

There are still outbreaks of COVID-19 across the world. Ships increase the risk of worldwide transmission of the virus. Close contact tracing remains as an effective method of reducing the risk of virus transmission. Therefore, close contact tracing in ship environments becomes a research topic. Exposure Notifications API (Application Programming Interface) can be used to determine the encountered location points of close contacts on ships. Location points of close contact are estimated by the encountered location points. Risky areas in ships can be calculated based on the encountered location points. The tracking of close contacts is possible with Bluetooth technology without the Internet. The Bluetooth signal can be used to judge the proximity among detecting devices by using the feature that Bluetooth has a strong signal at close range. This Bluetooth feature makes it possible to trace close contacts in ship environments. In this paper, we propose a method for close contact tracing and showing the risky area in a ship environment by combining beacon and Exposure Notification API using Bluetooth technology. This method does not require an Internet connection for tracing close contacts and can protect the personal information of close contacts. Copyright © 2023 KSII.

Quarantine in Motion: A Graph Learning Framework to Reduce Disease Transmission Without Lockdown

Exposure notification applications are developed to increase the scale and speed of disease contact tracing. Indeed, by taking advantage of Bluetooth technology, they track the infected population's mobility and then inform close contacts to get tested. In this paper, we ask whether these applications can extend from reactive to preemptive risk management tools? To this end, we propose a new framework that utilizes graph neural networks (GNN) and real-world Foursquare mobility data to predict high risk locations on an hourly basis. As a proof of concept, we then simulate a risk-informed Foursquare population of over 36,000 people in Austin TX after the peak of an outbreak. We find that even after 50% of the population has been infected with COVID-19, they can still maintain their mobility, while reducing the new infections by 13%. Consequently, these results are a first step towards achieving what we call Quarantine in Motion. © 2022 IEEE.

Quantifying SARS-CoV-2 Infection Risk Within the Google/Apple Exposure Notification Framework to Inform Quarantine Recommendations.

Most early Bluetooth-based exposure notification apps use three binary classifications to recommend quarantine following SARS-CoV-2 exposure: a window of infectiousness in the transmitter, ≥15 minutes duration, and Bluetooth attenuation below a threshold. However, Bluetooth attenuation is not a reliable measure of distance, and infection risk is not a binary function of distance, nor duration, nor timing. We model uncertainty in the shape and orientation of an exhaled virus-containing plume and in inhalation parameters, and measure uncertainty in distance as a function of Bluetooth attenuation. We calculate expected dose by combining this with estimated infectiousness based on timing relative to symptom onset. We calibrate an exponential dose-response curve based on infection probabilities of household contacts. The probability of current or future infectiousness, conditioned on how long postexposure an exposed individual has been symptom-free, decreases during quarantine, with shape determined by incubation periods, proportion of asymptomatic cases, and asymptomatic shedding durations. It can be adjusted for negative test results using Bayes' theorem. We capture a 10-fold range of risk using six infectiousness values, 11-fold range using three Bluetooth attenuation bins, ∼sixfold range from exposure duration given the 30 minute duration cap imposed by the Google/Apple v1.1, and ∼11-fold between the beginning and end of 14 day quarantine. Public health authorities can either set a threshold on initial infection risk to determine 14-day quarantine onset, or on the conditional probability of current and future infectiousness conditions to determine both quarantine and duration.

New digital public health tools: privacy by design in contact tracing mobile apps for COVID-19

The technology adoption cycle in the public sector is usually much longer than in the private sector. The COVID-19 pandemic caused an acceleration in the adoption of various digital tools which serve as a bridge between the public and private sector. These digital tools include instantaneous contact tracing mobile applications (apps) used to alert individuals who have recently been in contact with an infected person and used by governments to manage public health policies. From the perspective of individuals' data storage there are two general possible approaches, namely centralised and decentralised. Each approach has some legal and ethical considerations, mostly related to finding the right balance between the individual's privacy and public health. In this paper we will outline how privacy according to the design principle should be applied as a minimum standard when developing government approved contact tracking apps. Copyright © 2022 Inderscience Enterprises Ltd.

Reliability Investigation of Contact Tracing using Resource-Constrained Mobile Devices

During this pandemic time while finding the (SARS-CoV-2) infected person many of the applications got active where various nations participated actively. The main device involved in the whole process is Smartphone. The existing applications are focusing on the use of Bluetooth technology. Bluetooth is limited with the area it can cover and noise it produces to broadcast the messages to the neighbors. Also, while searching the position of the infected person one concern could be that is Position of the smartphone accurate? or for how long the tracing will happen? While tracing the position of the person whether infected or not infected, the compromise cannot be done. At the pandemic situation, the little mistake of the position will cost the life of a person and the growing number of infected persons will yield to an exponential cost. Also, the life of the smartphone to keep working needs energy through battery. Continuous localization will need continuous flow of the energy for that device. Thus, the smartphone needs to be charged after a period of time. So, when a person is in a public place, he will need his smartphone to be active. Our main concern with the whole paper is to find the solution through the simulation for the position accuracy of the smartphone as well as to manage the energy consumption. © 2022 IEEE.

Mobile technologies for contact tracing and prevention of COVID-19 positive cases: a cross- sectional study

PurposeThe purpose of this paper is to review the techniques for versatile advancements in contact tracing for the coronavirus disease 2019 (COVID-19) positive cases in this pandemic and to introduce the way of using the mobile location information collected within the country India. As the method, an exploratory review of current measures was conducted for confirmed COVID-19 contact tracing after understanding the current situation of the world. This paper has examined the way of using free locational information in an innovative way to reduce the spread of COVID-19 spread.Design/methodology/approachCOVID-19 pandemic is the utmost global economic and health challenge of the century. One powerful and consistent procedure to slow down the spread and decrease the effect of COVID-19 is to track the essential and auxiliary contacts of confirmed COVID-19 positive cases by using contact-tracing innovation.FindingsAlthough it takes the information from various clients, there are numerous odds in the information. The sincere measures were taken by the authors to avoid the abuse of information by any kind. A portion of the tips for keeping information from getting abused is on the whole, the information ought to be with just higher specialists, and they ought not to have the authorization to impart information to anybody.Originality/valueThis paper helps to track the COVID-19 positive cases as of now by using the field information assortment and outbreak examination stages. At the same time, mobile location information used inside the current guideline, rules for information handlers must incorporate measures to reduce the abusing of information.

A Bluetooth-Based Contact-Tracing Mobile App for Airborne-Based Epidemic Control

In the situation of an epidemic outbreak, a contact tracing tool is preferred to alert the infection status of daily encountered people. Since we are in the era that smartphone is carried everywhere and embedded with Bluetooth technology, a Bluetooth-based mobile app is proposed in this paper for advanced contact tracing. The proposed app can not only trace the infectious people contacted with the user but also label the danger level by scanning the proximity and lingering time for each case. It is simple yet efficient to apply as it does not employ any new Bluetooth protocol but only requires basic inputs that are acquirable from any smartphone with Bluetooth 2.0 and above. This application is built using service-oriented architecture which helps mobile devices to communicate with a data collection server as well as each other. The collected data will be shown in a web application and used to further study the propagation characteristics of new infectious viruses. It also comprises a daily survey that users answer, and which will be used by health officials for early prognosis. The app is currently tested campus-wide and showed salient features in terms of scalability, mobility, and sensing inaccuracy-proof, which has the potential to be applied in larger populations with more complicated scenarios. © 2021 IEEE.