Dependence analysis of social contact behaviors under the impacts of COVID-19 based on a copula approach.

The spread of the SARS-CoV-2 virus during the COVID-19 pandemic was intricately linked with contact between people, but many of the policies designed to encourage safe contact behaviors were unsuccessful. One reason was that the determinants of social contact decisions have not been thoroughly investigated using scientifically sound methodologies. To fill this gap, a unique survey was designed which sought data on social contact behaviors and their determinants. Second, a copula-based behavior model was developed to jointly represent the choices of contact modes (including direct and indirect contact) and the number of contacted persons. The survey was conducted in six countries from March to May 2021 and collected valid responses from >7000 people. A comparison of five key copula functions found that the Frank function outperformed the others. The results of a Frank-based model showed that indirect contacts were significantly and positively associated with the number of contacted persons. Then the influence of various determinants, including activity attributes (e.g., frequency and travel distance), protective measures, safety level of activity settings, and psychological factors related to activity participation and risk perception, were extensively analyzed. In particular, the various heterogeneous influences in different social contact settings were examined. The findings provide scientific evidence for policymakers to promote safe social distancing, even for the post-pandemic era.

BECT: Beacon-based Contact Tracing for Detecting Direct & Indirect Contacts

Digital Contact tracing with smartphone apps may help control the spread of serious pathogens, such as COVID-19. Such apps typically use peer-to-peer Bluetooth data transfer to record a contact. However, they suffer from low adoption rates, high false alarm contact indications, battery drain, and user privacy concerns. This paper proposes BECT or BEacon-based Contact Tracing, a contact tracing framework using static Bluetooth beacon devices installed in public or private places that periodically broadcast packets to nearby users that are stored as coins. Users that are positively diagnosed submit their coin IDs to a third-party service (e.g., local health authority) which can mark these coins as infected and disseminate them to other users. A match between a user's stored coins and an infected coin implies that the user has come in direct or indirect contact with an infected person. The BECT framework does not expose users' private data and conserves the device battery. We use MATLAB simulations to compare the performance of the BECT framework to phone-phone apps in a restaurant scenario and show that BECT has superior contact tracing performance. We also provide general deployment guidelines. © 2022 IEEE.

Indirect contact tracing of a COVID-19 close contact a report from a COVID-19 nucleic acid testing site in Jinan

Background: April 11 , 2022, we learned from the public information platform that a COVID-19 close contact was tested nucleic acid in our hospital recently. This survey was performed to verify the infor-mation and timely identify high risk population of COVID 19. Methods: According to the National COVID-19 Control and Prevention Protocol ( 8th edition) , and the Emergency Response Plan for COVID-19 in our hospital, information verification, close contact investigation, indirect contact tracing, information report and close contact follow up were carried out by our team. Results: A total of 40 indirect contacts were identified. The basic information of those 40 indirect contacts was reported to the local Center for Diseases Control and Prevention. The close contact was followed up for 10 days, and the nucleic acid test results of COVID-19 of the contact were negative since then. No fever or other suspected symptoms of COVID-19 were appeared for the contact. Conclusion: Timely verify the COVID-19 related information, screening of high risk population and dynamically monitoring of the close contact will help to control the potential spread of COVID 19. 767. © 2022 Colegio Brasileiro de Patologia Animal. All rights reserved.

PCT-TEE: Trajectory-based Private Contact Tracing System with Trusted Execution Environment

Existing Bluetooth-based private contact tracing (PCT) systems can privately detect whether people have come into direct contact with patients with COVID-19. However, we find that the existing systems lack functionality and flexibility, which may hurt the success of contact tracing. Specifically, they cannot detect indirect contact (e.g., people may be exposed to COVID-19 by using a contaminated sheet at a restaurant without making direct contact with the infected individual);they also cannot flexibly change the rules of "risky contact,"such as the duration of exposure or the distance (both spatially and temporally) from a patient with COVID-19 that is considered to result in a risk of exposure, which may vary with the environmental situation.In this article, we propose an efficient and secure contact tracing system that enables us to trace both direct contact and indirect contact. To address the above problems, we need to utilize users' trajectory data for PCT, which we call trajectory-based PCT. We formalize this problem as a spatiotemporal private set intersection that satisfies both the security and efficiency requirements. By analyzing different approaches such as homomorphic encryption, which could be extended to solve this problem, we identify the trusted execution environment (TEE) as a candidate method to achieve our requirements. The major challenge is how to design algorithms for a spatiotemporal private set intersection under the limited secure memory of the TEE. To this end, we design a TEE-based system with flexible trajectory data encoding algorithms. Our experiments on real-world data show that the proposed system can process hundreds of queries on tens of millions of records of trajectory data within a few seconds. © 2021 Copyright held by the owner/author(s). Publication rights licensed to ACM.

Uses of Drones in Fighting COVID-19 Pandemic

COVID-19 outbreak has been faced by every country across the globe. Its affects transmit through direct or indirect contact of infected person with a healthy person. So, isolation is one of the mechanism for prevention from it. Now a day's advancement in technology is playing a great role in fighting against COVID-19. Uses of drone is one of them. Drones can offer a large number of services in this era. Drone or UAV's not only minimizes the risk of contact, they had been used for aerial monitoring of containment or curfews areas, for evaluation of post-massive epidemic contagious diseases, for reaching inaccessible areas and many mores. This study, presents the utilization of drones in various areas in fighting against COVID-19 pandemic and various technologies that assists these drones. Various challenges in the implementation of contactless deliveries using drones have been presented. © 2021 IEEE.

Phi 6 recovery from inoculated fingerpads based on elution buffer and methodology.

Phi 6 (Φ6) bacteriophage is a proposed surrogate to study pathogenic enveloped viruses including SARS-CoV-2-the causative agent of COVID-19-based on structural similarities, BSL-1 status, and ease of use. To determine the role of virus-contaminated hands in disease transmission, an enhanced understanding of buffer and method performance for Φ6 recovery needs to be determined. Four buffer types and three methodologies were investigated for the recovery of Φ6 from human fingerpads over a 30 min duration. Phosphate buffered saline (PBS), PBS + 0.1 % Tween, 0.1 M glycine + 3% beef extract, and viral transport medium were evaluated as buffers for recovery of Φ6 via a dish, modified glove juice, and vigorous swabbing method. Φ6 concentrations on fingerpads were determined at 0-, 5-, 10-, and 30-min post-inoculation. While there were observed differences in virus recovery across buffer and method types depending on the time point, log PFU recovery based on buffer type or methodology was not significantly different at any time point (P > 0.05). The results presented in this study will allow for future work on Φ6 persistence, transfer between hands and surfaces, and efficacy of hand hygiene methods to be performed using a well-characterized and validated recovery method.

Comparing approaches for modelling indirect contact transmission of infectious diseases.

Mathematical models describing indirect contact transmission are an important component of infectious disease mitigation and risk assessment. A model that tracks microorganisms between compartments by coupled ordinary differential equations or a Markov chain is benchmarked against a mechanistic interpretation of the physical transfer of microorganisms from surfaces to fingers and subsequently to a susceptible person's facial mucosal membranes. The primary objective was to compare these models in their estimates of doses and changes in microorganism concentrations on hands and fomites over time. The abilities of the models to capture the impact of episodic events, such as hand hygiene, and of contact patterns were also explored. For both models, greater doses were estimated for the asymmetrical scenarios in which a more contaminated fomite was touched more often. Differing representations of hand hygiene in the Markov model did not notably impact estimated doses but affected pathogen concentration dynamics on hands. When using the Markov model, losses due to hand hygiene should be handled as separate events as opposed to time-averaging expected losses. The discrete event model demonstrated the effect of hand-to-mouth contact timing on the dose. Understanding how model design influences estimated doses is important for advancing models as reliable risk assessment tools.