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1. Exploiting a Contact Tracing App to Attack Neighboring Devices

   Fitzgerald, J. ( January 2023 , Proceedings of the 56th Hawaii International Conference on System Sciences)

   The recent pandemic fosters an increasing dependency on various forms of digital communications that support social distancing. To mitigate widespread exposure to COVID, the Louisiana Department of Health’s COVID Defense contact tracing application helps users learn about potential exposures to infected individuals. This research investigates the viability of using the Louisiana Department of Health’s COVID Defense application symptoms share feature as an attack vector. The primary contribution of this research is an initial assessment of the effective modification and distribution of a packaged JSON file that contains a malicious link. Secondly, it highlights the effectiveness of this attack through email, WIFI direct, and nearby share. 

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2. Contact Tracing: A Low Cost Reconstruction Framework for Surface Contact Interpolation

   Lakshmipathy, A. ; Bauer, D. ; Pollard, N. ( October 2021 , Proceedings of the IEEERSJ International Conference on Intelligent Robots and Systems)

   null (Ed.)

   We present a novel, low cost framework for reconstructing surface contact movements during in-hand manipulations. Unlike many existing methods focused on hand pose tracking, ours models the behavior of contact patches, and by doing so is the first to obtain detailed contact tracking estimates for multi-contact manipulations. Our framework is highly accessible, requiring only low cost, readily available paint materials, a single RGBD camera, and a simple, deterministic interpolation algorithm. Despite its simplicity, we demonstrate the framework’s effectiveness over the course of several manipulations on three common household items. Finally, we demonstrate the use of a generated contact time series in manipulation learning for a simulated robot hand. 

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3. COVIDFREE App: The User-Enabling Contact Prevention Application: A Review

   https://doi.org/10.25046/aj070215  

   Mimo, Edgard Musafiri ; McDaniel, Troy ; Ruvunangiza, Jeremie Biringanine ( April 2022 , Advances in Science, Technology and Engineering Systems Journal)
4. Use of an App With Embedded Video Modeling to Increase Eye Contact

   https://doi.org/10.1177/10883576221124805  

   Polychronis, Shamby C. ; Johnson, Andrea ; Thelin, Russell J. ; Eggett, Dennis L. ; Christensen, Jaime ( September 2022 , Focus on Autism and Other Developmental Disabilities)

   The use of mobile applications (apps) is popular among parents and teachers due to their cost-effectiveness and ease of implementation, and the number of apps with the specific aim to increase eye contact for children with autism is growing rapidly. However, research is limited to assess the efficiency of the majority of the apps available for educational purposes. This study was conducted to determine whether the addition of video modeling via an app to ongoing classroom instruction could increase eye contact with familiar and unfamiliar people in children with autism spectrum disorder (ASD). An experimental pretest–posttest control group design was applied with a full intervention group, a partial intervention group, and a control group. Forty-four U.S. students diagnosed with ASD, in kindergarten through third grade, engaged with social skill modules using an iPad app called We Are Friends. The frequency and duration of eye contact were measured. A 3-month follow-up test was given to determine maintenance. Results suggest the addition of the app was effective in increasing eye contact in children with ASD with both familiar and unfamiliar individuals.

    

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5. Contact tracing efficiency, transmission heterogeneity, and accelerating COVID-19 epidemics

   https://doi.org/10.1371/journal.pcbi.1009122  

   Gardner, Billy J. ; Kilpatrick, A. Marm ( June 2021 , PLOS Computational Biology)

   Funk, Sebastian (Ed.)

   Simultaneously controlling COVID-19 epidemics and limiting economic and societal impacts presents a difficult challenge, especially with limited public health budgets. Testing, contact tracing, and isolating/quarantining is a key strategy that has been used to reduce transmission of SARS-CoV-2, the virus that causes COVID-19 and other pathogens. However, manual contact tracing is a time-consuming process and as case numbers increase a smaller fraction of cases’ contacts can be traced, leading to additional virus spread. Delays between symptom onset and being tested (and receiving results), and a low fraction of symptomatic cases being tested and traced can also reduce the impact of contact tracing on transmission. We examined the relationship between increasing cases and delays and the pathogen reproductive number R t , and the implications for infection dynamics using deterministic and stochastic compartmental models of SARS-CoV-2. We found that R t increased sigmoidally with the number of cases due to decreasing contact tracing efficacy. This relationship results in accelerating epidemics because R t initially increases, rather than declines, as infections increase. Shifting contact tracers from locations with high and low case burdens relative to capacity to locations with intermediate case burdens maximizes their impact in reducing R t (but minimizing total infections may be more complicated). Contact tracing efficacy decreased sharply with increasing delays between symptom onset and tracing and with lower fraction of symptomatic infections being tested. Finally, testing and tracing reductions in R t can sometimes greatly delay epidemics due to the highly heterogeneous transmission dynamics of SARS-CoV-2. These results demonstrate the importance of having an expandable or mobile team of contact tracers that can be used to control surges in cases. They also highlight the synergistic value of high capacity, easy access testing and rapid turn-around of testing results, and outreach efforts to encourage symptomatic cases to be tested immediately after symptom onset. 

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