Digital Landscape of COVID-19 Testing: Challenges and Opportunities

• URL: http://arxiv.org/abs/2012.01772v1
• Date: Thu, 3 Dec 2020 09:01:51 GMT
• Title: Digital Landscape of COVID-19 Testing: Challenges and Opportunities
• Authors: Darshan Gandhi, Rohan Sukumaran, Priyanshi Katiyar, Alex Radunsky, Sunaina Anand, Shailesh Advani, Jil Kothari, Kasia Jakimowicz, Sheshank Shankar, Sethuraman T. V., Krutika Misra, Aishwarya Saxena, Sanskruti Landage, Richa Sonker, Parth Patwa, Aryan Mahindra, Mikhail Dmitrienko, Kanishka Vaish, Ashley Mehra, Srinidhi Murali, Rohan Iyer, Joseph Bae, Vivek Sharma, Abhishek Singh, Rachel Barbar and Ramesh Raskar
• Abstract summary: Digital technology, currently being used for COVID-19 testing include certain mobile apps, web dashboards, and online self-assessment tools. We summarize the challenges experienced using these tools in terms of quality of information, privacy, and user-centric issues.
• Score: 8.445546861208243
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The COVID-19 Pandemic has left a devastating trail all over the world, in terms of loss of lives, economic decline, travel restrictions, trade deficit, and collapsing economy including real-estate, job loss, loss of health benefits, the decline in quality of access to care and services and overall quality of life. Immunization from the anticipated vaccines will not be the stand-alone guideline that will help surpass the pandemic and return to normalcy. Four pillars of effective public health intervention include diagnostic testing for both asymptomatic and symptomatic individuals, contact tracing, quarantine of individuals with symptoms or who are exposed to COVID-19, and maintaining strict hygiene standards at the individual and community level. Digital technology, currently being used for COVID-19 testing include certain mobile apps, web dashboards, and online self-assessment tools. Herein, we look into various digital solutions adapted by communities across universities, businesses, and other organizations. We summarize the challenges experienced using these tools in terms of quality of information, privacy, and user-centric issues. Despite numerous digital solutions available and being developed, many vary in terms of information being shared in terms of both quality and quantity, which can be overwhelming to the users. Understanding the testing landscape through a digital lens will give a clear insight into the multiple challenges that we face including data privacy, cost, and miscommunication. It is the destiny of digitalization to navigate testing for COVID-19. Block-chain based systems can be used for privacy preservation and ensuring ownership of the data to remain with the user. Another solution involves having digital health passports with relevant and correct information. In this early draft, we summarize the challenges and propose possible solutions to address the same.

Related papers

• A Comprehensive Picture of Factors Affecting User Willingness to Use Mobile Health Applications [62.60524178293434]
  The aim of this paper is to investigate the factors that influence user acceptance of mHealth apps. Users' digital literacy has the strongest impact on their willingness to use them, followed by their online habit of sharing personal information. Users' demographic background, such as their country of residence, age, ethnicity, and education, has a significant moderating effect.
  arXiv  Detail & Related papers  (2023-05-10T08:11:21Z)
• Challenges of Blockchain Applications in Digital Health: A Systematic Review [0.0]
  This systematic literature review aims to explore the challenges of blockchain applications in digital health. Key issues identified include regulatory compliance, energy consumption, network effects, data standards, and the accessibility of the technology to stakeholders.
  arXiv  Detail & Related papers  (2023-04-08T20:50:20Z)
• A Survey on Computer Vision based Human Analysis in the COVID-19 Era [58.79053747159797]
  The emergence of COVID-19 has had a global and profound impact, not only on society as a whole, but also on the lives of individuals. Various prevention measures were introduced around the world to limit the transmission of the disease, including face masks, mandates for social distancing and regular disinfection in public spaces, and the use of screening applications. These developments triggered the need for novel and improved computer vision techniques capable of (i) providing support to the prevention measures through an automated analysis of visual data, on the one hand, and (ii) facilitating normal operation of existing vision-based services, such as biometric authentication
  arXiv  Detail & Related papers  (2022-11-07T17:20:39Z)
• Mental Illness Classification on Social Media Texts using Deep Learning and Transfer Learning [55.653944436488786]
  According to the World health organization (WHO), approximately 450 million people are affected. Mental illnesses, such as depression, anxiety, bipolar disorder, ADHD, and PTSD. This study analyzes unstructured user data on Reddit platform and classifies five common mental illnesses: depression, anxiety, bipolar disorder, ADHD, and PTSD.
  arXiv  Detail & Related papers  (2022-07-03T11:33:52Z)
• When Accuracy Meets Privacy: Two-Stage Federated Transfer Learning Framework in Classification of Medical Images on Limited Data: A COVID-19 Case Study [77.34726150561087]
  COVID-19 pandemic has spread rapidly and caused a shortage of global medical resources. CNN has been widely utilized and verified in analyzing medical images.
  arXiv  Detail & Related papers  (2022-03-24T02:09:41Z)
• COVID-19 Digital Contact Tracing Applications and Techniques: A Review Post Initial Deployments [2.05040847923906]
  coronavirus disease 2019 (COVID-19) is a severe global pandemic that has claimed millions of lives and continues to overwhelm public health systems. To increase the effectiveness of contact tracing, countries across the globe are leveraging advancements in mobile technology and Internet of Things.
  arXiv  Detail & Related papers  (2021-02-25T10:18:40Z)
• COVID-19 Tests Gone Rogue: Privacy, Efficacy, Mismanagement and Misunderstandings [8.154109462429988]
  We review the current landscape of COVID-19 testing, identify four key challenges, and discuss the consequences of the failure to address these challenges. The current infrastructure around testing and information propagation is highly privacy-invasive and does not leverage scalable digital components.
  arXiv  Detail & Related papers  (2021-01-05T18:37:26Z)
• Assessing the Severity of Health States based on Social Media Posts [62.52087340582502]
  We propose a multiview learning framework that models both the textual content as well as contextual-information to assess the severity of the user's health state. The diverse NLU views demonstrate its effectiveness on both the tasks and as well as on the individual disease to assess a user's health.
  arXiv  Detail & Related papers  (2020-09-21T03:45:14Z)
• A Partially Observable MDP Approach for Sequential Testing for Infectious Diseases such as COVID-19 [29.84897273754802]
  We show that the testing problem can be cast as a sequential learning-based resource allocation problem with constraints. We then develop efficient learning strategies that minimize the number of infected individuals.
  arXiv  Detail & Related papers  (2020-07-25T22:13:37Z)
• 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)
• Digital tools against COVID-19: Framing the ethical challenges and how to address them [3.1498833540989413]
  We present a typology of the primary digital public health applications currently in use. For each, we discuss context-specific risks, cross-sectional issues, and ethical concerns. We propose a navigation aid for policymakers made up of ten steps for the ethical use of digital public health tools.
  arXiv  Detail & Related papers  (2020-04-21T18:39:08Z)

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.