scholarly journals Features of COVID-19 applications and their impact on contact tracing: results of preliminary review

2021 ◽  
Vol 13 (4) ◽  
Author(s):  
Riikka Vuokko ◽  
Kaija Saranto ◽  
Sari Palojoki
Keyword(s):  
Data Storage ◽  
Data Privacy ◽  
Control Strategies ◽  
Contact Tracing ◽  
Preliminary Review ◽  
Application Development ◽  
Regulatory Frameworks ◽  
Real World Evidence ◽  
Pubmed Database ◽  
Comprehensive Health

Digital technologies and telehealth, specifically contact tracing applications can complement traditional approaches for contact tracing of COVID-19 and overall COVID-19 control strategies. Despite the potential benefits of these novel approaches, concerns regarding privacy and basic rights have challenged application development and adoption. We explore the features of tracing applications, focusing on the trade-off between technical possibilities and privacy concerns. Our main objective is to map out central features of applied technology solutions that may prove as drivers or constrains for future development. Our secondary aim was to review how the effectiveness of tracing applications was being apprehended in research. We conducted a literature review of COVID-19 tracing applications and related privacy issues using the PubMed database. For analysis, we conceptualized contact tracing and data privacy. Our review identified various technologies with potential for contact tracing, with Bluetooth and GPS based solutions being the most common. Effectiveness of the applications is dependent on how widely these are adopted. However, technological approaches of the applications vary markedly, affecting their effectiveness for pandemic control. Privacy and trust are key limitations affecting application adoption. Existing privacy solutions are based on voluntary use, user consent, cryptographic data storage, minimum data collection, limited data usage, and transparency of the contact tracing applications and frameworks. Although evidence of applications’ outcomes and benefits is yet tentative, the first evaluation frameworks for the applications are under development. In order to obtain maximum potential benefit from the applications, real-world evidence needs to be analyzed and evaluated carefully. However, along with contact tracing apps and comprehensive health programs, regulatory frameworks and safeguards are necessary to ensure that health information is not used for surveillance purposes and that app users’ privacy is maintained.

scholarly journals Security in Cloud Computing Using Hash Algorithm: A Neural Cloud Data Security Model

2018 ◽  
Vol 12 (6) ◽  
pp. 143 ◽  
Author(s):  
Osama Harfoushi ◽  
Ruba Obiedat
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Data Storage ◽  
Data Privacy ◽  
Security Model ◽  
Application Development ◽  
Cloud Data ◽  
Computing Services ◽  
Cloud Computing System ◽  
Cloud Computing Services

Cloud computing is the delivery of computing resources over the Internet. Examples include, among others, servers, storage, big data, databases, networking, software, and analytics. Institutes that provide cloud computing services are called providers. Cloud computing services were primarily developed to help IT professionals through application development, big data storage and recovery, website hosting, on-demand software delivery, and analysis of significant data patterns that could compromise a system’s security. Given the widespread availability of cloud computing, many companies have begun to implement the system because it is cost-efficient, reliable, scalable, and can be accessed from anywhere at any time. The most demanding feature of a cloud computing system is its security platform, which uses cryptographic algorithm levels to enhance protection of unauthorized access, modification, and denial of services. For the most part, cloud security uses algorithms to ensure the preservation of big data stored on remote servers. This study proposes a methodology to reduce concerns about data privacy by using cloud computing cryptography algorithms to improve the security of various platforms and to ensure customer satisfaction.

scholarly journals A Cloud Game-Based Educative Platform Architecture: The CyberScratch Project

2021 ◽  
Vol 11 (2) ◽  
pp. 807
Author(s):  
Llanos Tobarra ◽  
Alejandro Utrilla ◽  
Antonio Robles-Gómez ◽  
Rafael Pastor-Vargas ◽  
Roberto Hernández
Keyword(s):  
Data Storage ◽  
Data Privacy ◽  
Data Science ◽  
Critical Issue ◽  
Privacy Management ◽  
Instructional Process ◽  
Legal Context ◽  
Flexible Architecture ◽  
Efficient Data ◽  
Implementation Guidelines

The employment of modern technologies is widespread in our society, so the inclusion of practical activities for education has become essential and useful at the same time. These activities are more noticeable in Engineering, in areas such as cybersecurity, data science, artificial intelligence, etc. Additionally, these activities acquire even more relevance with a distance education methodology, as our case is. The inclusion of these practical activities has clear advantages, such as (1) promoting critical thinking and (2) improving students’ abilities and skills for their professional careers. There are several options, such as the use of remote and virtual laboratories, virtual reality and game-based platforms, among others. This work addresses the development of a new cloud game-based educational platform, which defines a modular and flexible architecture (using light containers). This architecture provides interactive and monitoring services and data storage in a transparent way. The platform uses gamification to integrate the game as part of the instructional process. The CyberScratch project is a particular implementation of this architecture focused on cybersecurity game-based activities. The data privacy management is a critical issue for these kinds of platforms, so the architecture is designed with this feature integrated in the platform components. To achieve this goal, we first focus on all the privacy aspects for the data generated by our cloud game-based platform, by considering the European legal context for data privacy following GDPR and ISO/IEC TR 20748-1:2016 recommendations for Learning Analytics (LA). Our second objective is to provide implementation guidelines for efficient data privacy management for our cloud game-based educative platform. All these contributions are not found in current related works. The CyberScratch project, which was approved by UNED for the year 2020, considers using the xAPI standard for data handling and services for the game editor, game engine and game monitor modules of CyberScratch. Therefore, apart from considering GDPR privacy and LA recommendations, our cloud game-based architecture covers all phases from game creation to the final users’ interactions with the game.

scholarly journals Moving Faster than the COVID-19 Pandemic: The Rapid, Digital Transformation of a Public Health System

2021 ◽  
Vol 12 (02) ◽  
pp. 229-236
Author(s):  
Clair Sullivan ◽  
Ides Wong ◽  
Emily Adams ◽  
Magid Fahim ◽  
Jon Fraser ◽  
...  
Keyword(s):  
Public Health ◽  
Health System ◽  
Public Health System ◽  
Digital Transformation ◽  
Contact Tracing ◽  
Programming Approach ◽  
Data Governance ◽  
Application Development ◽  
Containment Strategy

Abstract Background Queensland, Australia has been successful in containing the COVID-19 pandemic. Underpinning that response has been a highly effective virus containment strategy which relies on identification, isolation, and contact tracing of cases. The dramatic emergence of the COVID-19 pandemic rendered traditional paper-based systems for managing contact tracing no longer fit for purpose. A rapid digital transformation of the public health contact tracing system occurred to support this effort. Objectives The objectives of the digital transformation were to shift legacy systems (paper or standalone electronic systems) to a digitally enabled public health system, where data are centered around the consumer rather than isolated databases. The objective of this paper is to outline this case study and detail the lessons learnt to inform and give confidence to others contemplating digitization of public health systems in response to the COVID-19 pandemic. Methods This case study is set in Queensland, Australia. Universal health care is available. A multidisciplinary team was established consisting of clinical informaticians, developers, data strategists, and health information managers. An agile “pair-programming” approach was undertaken to application development and extensive change efforts were made to maximize adoption of the new digital workflows. Data governance and flows were changed to support rapid management of the pandemic. Results The digital coronavirus application (DCOVA) is a web-based application that securely captures information about people required to quarantine and creates a multiagency secure database to support a successful containment strategy. Conclusion Most of the literature surrounding digital transformation allows time for significant consultation, which was simply not possible under crisis conditions. Our observation is that staff was willing to adopt new digital systems because the reason for change (the COVID-19 pandemic) was clearly pressing. This case study highlights just how critical a unified purpose, is to successful, rapid digital transformation.

scholarly journals Do You Have COVID-19?: How to Increase the Use of Diagnostic and Contact-Tracing Apps

2021 ◽  
Author(s):  
Déborah Martínez ◽  
Cristina Parilli ◽  
Ana María Rojas ◽  
Carlos Scartascini ◽  
Alberto Simpser
Keyword(s):  
Data Privacy ◽  
Contact Tracing ◽  
Survey Experiment ◽  
Promotion Policy ◽  
Percentage Points ◽  
Willingness To Adopt ◽  
Mexican Adults

Diagnostic and contact tracing apps are an important weapon against contagion during a pandemic. We study how the content of the messages used to promote the apps influences adoption by conducting a survey experiment on approximately 23,000 Mexican adults. Respondents were randomly assigned to one of three different prompts, or a control condition, before stating their willingness to adopt a diagnostic app and contact-tracing app. The prompt emphasizing government efforts to ensure data privacy, which has been one of the most common strategies, reduced willingness to adopt the diagnostic app by about 4 percentage points and the contact tracing app by 3 percentage points. An effective app promotion policy must understand individuals' reservations and be wary of unintended reactions to naive reassurances.

scholarly journals Design of a Machine Learning-Based Intelligent Middleware Platform for a Heterogeneous Private Edge Cloud System

Sensors ◽  
2021 ◽  
Vol 21 (22) ◽  
pp. 7701
Author(s):  
Sayed-Chhattan Shah
Keyword(s):  
Machine Learning ◽  
Data Storage ◽  
Smart City ◽  
Data Privacy ◽  
Mobile Technologies ◽  
Cloud System ◽  
Multilayer Network ◽  
Network Applications ◽  
Data Rates ◽  
5G Network

Recent advances in mobile technologies have facilitated the development of a new class of smart city and fifth-generation (5G) network applications. These applications have diverse requirements, such as low latencies, high data rates, significant amounts of computing and storage resources, and access to sensors and actuators. A heterogeneous private edge cloud system was proposed to address the requirements of these applications. The proposed heterogeneous private edge cloud system is characterized by a complex and dynamic multilayer network and computing infrastructure. Efficient management and utilization of this infrastructure may increase data rates and reduce data latency, data privacy risks, and traffic to the core Internet network. A novel intelligent middleware platform is proposed in the current study to manage and utilize heterogeneous private edge cloud infrastructure efficiently. The proposed platform aims to provide computing, data collection, and data storage services to support emerging resource-intensive and non-resource-intensive smart city and 5G network applications. It aims to leverage regression analysis and reinforcement learning methods to solve the problem of efficiently allocating heterogeneous resources to application tasks. This platform adopts parallel transmission techniques, dynamic interface allocation techniques, and machine learning-based algorithms in a dynamic multilayer network infrastructure to improve network and application performance. Moreover, it uses container and device virtualization technologies to address problems related to heterogeneous hardware and execution environments.

scholarly journals COVID-19 control strategies and intervention effects in resource limited settings: A modeling study

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0252570
Author(s):  
Kiran Raj Pandey ◽  
Anup Subedee ◽  
Bishesh Khanal ◽  
Bhagawan Koirala
Keyword(s):  
Control Strategies ◽  
Case Finding ◽  
Contact Tracing ◽  
Active Case Finding ◽  
Resource Limited Settings ◽  
Peak Demand ◽  
Active Case ◽  
Resource Limited ◽  
Base Scenario ◽  
Annual Mortality

Introduction Many countries with weaker health systems are struggling to put together a coherent strategy against the COVID-19 epidemic. We explored COVID-19 control strategies that could offer the greatest benefit in resource limited settings. Methods Using an age-structured SEIR model, we explored the effects of COVID-19 control interventions–a lockdown, physical distancing measures, and active case finding (testing and isolation, contact tracing and quarantine)–implemented individually and in combination to control a hypothetical COVID-19 epidemic in Kathmandu (population 2.6 million), Nepal. Results A month-long lockdown will delay peak demand for hospital beds by 36 days, as compared to a base scenario of no intervention (peak demand at 108 days (IQR 97-119); a 2 month long lockdown will delay it by 74 days, without any difference in annual mortality, or healthcare demand volume. Year-long physical distancing measures will reduce peak demand to 36% (IQR 23%-46%) and annual morality to 67% (IQR 48%-77%) of base scenario. Following a month long lockdown with ongoing physical distancing measures and an active case finding intervention that detects 5% of the daily infection burden could reduce projected morality and peak demand by more than 99%. Conclusion Limited resource settings are best served by a combination of early and aggressive case finding with ongoing physical distancing measures to control the COVID-19 epidemic. A lockdown may be helpful until combination interventions can be put in place but is unlikely to reduce annual mortality or healthcare demand.

scholarly journals Enhanced Integrity Checking for Preserve Data Owner and User Level Privacy Using Dual Cryptography Approach

2019 ◽  
pp. 138-146
Author(s):  
Poovizhi. M ◽  
Raja. G
Keyword(s):  
Data Storage ◽  
Data Privacy ◽  
Capital Expenditure ◽  
Data Access ◽  
Third Party ◽  
Configurable Computing ◽  
Local Data ◽  
Cloud Data ◽  
On Demand ◽  
Integrity Checking

Using Cloud Storage, users can tenuously store their data and enjoy the on-demand great quality applications and facilities from a shared pool of configurable computing resources, without the problem of local data storage and maintenance. However, the fact that users no longer have physical possession of the outsourced data makes the data integrity protection in Cloud Computing a formidable task, especially for users with constrained dividing resources. From users’ perspective, including both individuals and IT systems, storing data remotely into the cloud in a flexible on-demand manner brings tempting benefits: relief of the burden for storage management, universal data access with independent geographical locations, and avoidance of capital expenditure on hardware, software, and personnel maintenances, etc. To securely introduce an effective Sanitizer and third party auditor (TPA), the following two fundamental requirements have to be met: 1) TPA should be able to capably audit the cloud data storage without demanding the local copy of data, and introduce no additional on-line burden to the cloud user; 2) The third party auditing process should take in no new vulnerabilities towards user data privacy. In this project, utilize and uniquely combine the public auditing protocols with double encryption approach to achieve the privacy-preserving public cloud data auditing system, which meets all integrity checking without any leakage of data. To support efficient handling of multiple auditing tasks, we further explore the technique of online signature to extend our main result into a multi-user setting, where TPA can perform multiple auditing tasks simultaneously. We can implement double encryption algorithm to encrypt the data twice and stored cloud server in Electronic Health Record applications.

Staffing Electronic Commerce Projects

2011 ◽  
pp. 1807-1818
Author(s):  
Fred Niederman ◽  
Xiaorui Hu
Keyword(s):  
Project Management ◽  
Resource Management ◽  
Human Resource Management ◽  
Electronic Commerce ◽  
Conceptual Framework ◽  
Human Resource ◽  
Data Storage ◽  
Application Development ◽  
Dot Com ◽  
Number Of Firms

Electronic commerce (e-commerce) personnel are instrumental in developing and maintaining electronic commerce programs and projects within firms. In spite of the dot-com bust, the number of firms developing and using e-commerce for interactions with customers and suppliers is growing. Personnel competence as individuals and as a group can be a decisive force in determining the level of success of e-commerce projects. In this chapter, we present a conceptual framework as an extension and reformulation of several of the currently active fit theories of human resource management and industrial psychology. We propose consideration of five categories of skills that should be present in organizational e-commerce workforce (human computer interface, data storage and analysis, transaction/application development, infrastructure, and project management). Finally, based on the adjusted concepts of fit, we present a set of propositions showing expected relationships between organizational and fit related variables on workforce outcomes.

Hardware and Software Implementation of an Artificial Pancreas System on a Mobile Device

2017 ◽  
Vol 8 (1) ◽  
pp. 14-28
Author(s):  
Caterina Lazaro ◽  
Erdal Oruklu ◽  
Mert Sevil ◽  
Kamuran Turksoy ◽  
Ali Cinar
Keyword(s):  
Data Storage ◽  
Mobile Device ◽  
Closed Loop ◽  
Insulin Pump ◽  
Artificial Pancreas ◽  
Vital Signs ◽  
Application Development ◽  
Loop Control ◽  
Remote Server ◽  
Fusion Data

In this work, an artificial pancreas (AP) system, implemented on a mobile device is described. The proposed AP platform integrates hardware (insulin pump, glucose monitor, various sensors for vital signs and physical activities) and software (closed-loop control algorithm, sensor fusion, data storage and remote server access) components via smartphone that is running a dedicated Operating System designed for AP systems. Interfacing with this OS and custom application development steps are presented. Closed loop operation is demonstrated with case studies.

scholarly journals Modelling and Simulating the Novel Coronavirus with Implications of Asymptomatic Carriers

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Ghassane Benrhmach ◽  
Khalil Namir ◽  
Jamal Bouyaghroumni
Keyword(s):  
Control Strategies ◽  
World Health ◽  
Contact Tracing ◽  
Effective Control ◽  
Public Authorities ◽  
Asymptomatic Carriers ◽  
Social Distancing ◽  
Infected People ◽  
Novel Coronavirus ◽  
Health Organization

The World Health Organization declared that the total number of confirmed cases tested positive for SARS‐CoV‐2, affecting 210 countries, exceeded 3 million on 29 April 2020, with more than 207,973 deaths. In order to end the global COVID‐19 pandemic, public authorities have put in place multiple strategies like testing, contact tracing, and social distancing. Predictive mathematical models for epidemics are fundamental to understand the development of the epidemic and to plan effective control strategies. Some hosts may carry SARS‐CoV‐2 and transmit it to others, yet display no symptoms themselves. We propose applying a model (SELIAHRD) taking in consideration the number of asymptomatic infected people. The SELIAHRD model consists of eight stages: Susceptible, Exposed, Latent, Symptomatic Infected, Asymptomatic Infected, Hospitalized, Recovered, and Dead. The asymptomatic carriers contribute to the spread of disease, but go largely undetected and can therefore undermine efforts to control transmission. The simulation of possible scenarios of the implementation of social distancing shows that if we rigorously follow the social distancing rule then the healthcare system will not be overloaded.

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