The role of 5G for digital healthcare against COVID-19 pandemic: Opportunities and challenges

Digital health policy decoded: Mapping national strategies using Donabedian's model

National strategies are essential driving forces behind governments taking responsibility for setting the direction of digital health on a national level. This study employed a novel mixed-methods approach, integrating topic modeling, co-occurrence analysis, and qualitative content analysis, to comprehensively examine 22 national digital health strategies through the lens of Donabedian's structure-process-outcome model. The quantitative analysis identified 14 prevalent topics, while the qualitative analysis provided nuanced insights into the contexts underlying these topics. Leveraging Donabedian's framework, the topics were categorized into structure (training and digital health professionals, governance frameworks, computing infrastructure, public-private partnerships, regulatory frameworks), process (AI and big data, decision-support systems, shared digital health records, disease surveillance, information system interoperability), and outcome dimensions (improved health and social care, privacy and security, quality and efficiency of health services, universal coverage, sustainable development goals). This hybrid methodology offers a unique contribution by mapping the identified themes onto a widely accepted quality of care model, bridging the gap between policy analysis and healthcare quality assessment. The study unveils underaddressed themes, highlights the interrelationships between policy components, and provides a comprehensive understanding of the global digital health policy landscape. The findings inform future strategies, academic research directions, and potential policy considerations for governments formulating digital health regulations.

Exploring factors influencing farmers' health self-assessment in China based on the LASSO method

As the main force and practice subject of rural revitalisation, farmers' health is intricately linked to agricultural production and the rural economy. This study utilizes open data from the 2015 China Nutrition and Health Survey and employs the Least Absolute Shrinkage and Selection Operator (LASSO) method to explore the factors influencing farmers' self-assessment of health. The findings reveal that education level, proactive nutrition knowledge seeking, healthy dietary preferences and habits, and the use of clean cooking fuel positively impact farmers' health self-assessment. Conversely, age, history of illness or injury, and participation in medical insurance negatively affect their self-assessment. Furthermore, factors influencing farmers' health self-assessment exhibit heterogeneity across regions. Our findings suggest that promoting health education, disseminating nutritional dietary knowledge, and enhancing rural household infrastructure play an important role in improving farmers' self-evaluation of health. Therefore, policymakers should design more targeted health interventions and infrastructure improvement plans based on farmers' self-assessment of health and the level of regional economic development.

Barriers and Implications of 5G Technology Adoption for Hospitals in Western China: Integrated Interpretive Structural Modeling and Decision-Making Trial and Evaluation Laboratory Analysis

BACKGROUND

5G technology is gaining traction in Chinese hospitals for its potential to enhance patient care and internal management. However, various barriers hinder its implementation in clinical settings, and studies on their relevance and importance are scarce.

OBJECTIVE

This study aimed to identify critical barriers hampering the effective implementation of 5G in hospitals in Western China, to identify interaction relationships and priorities of the above-identified barriers, and to assess the intensity of the relationships and cause-and-effect relations between the adoption barriers.

METHODS

This paper uses the Delphi expert consultation method to determine key barriers to 5G adoption in Western China hospitals, the interpretive structural modeling to uncover interaction relationships and priorities, and the decision-making trial and evaluation laboratory method to reveal cause-and-effect relationships and their intensity levels.

RESULTS

In total, 14 barriers were determined by literature review and the Delphi method. Among these, "lack of policies on ethics, rights, and responsibilities in core health care scenarios" emerged as the fundamental influencing factor in the entire system, as it was the only factor at the bottom level of the interpretive structural model. Overall, 8 barriers were classified as the "cause group," and 6 as the "effect group" by the decision-making trial and evaluation laboratory method. "High expense" and "organizational barriers within hospitals" were determined as the most significant driving barrier (the highest R-C value of 1.361) and the most critical barrier (the highest R+C value of 4.317), respectively.

CONCLUSIONS

Promoting the integration of 5G in hospitals in Western China faces multiple complex and interrelated barriers. The study provides valuable quantitative evidence and a comprehensive approach for regulatory authorities, hospitals, and telecom operators, helping them develop strategic pathways for promoting widespread 5G adoption in health care. It is suggested that the stakeholders cooperate to explore and solve the problems in the 5G medical care era, aiming to achieve the coverage of 5G medical care across the country. To our best knowledge, this study is the first academic exploration systematically analyzing factors resisting 5G integration in Chinese hospitals, and it may give subsequent researchers a solid foundation for further studying the application and development of 5G in health care.

Realization of Green 5G Cellular Network Role in Medical Applications: Use of ChatGPT-AI

Wireless communication in medical applications improves patient monitoring, care coordination, early disease detection, and patient empowerment. It improves healthcare and patient outcomes. The design and configuration of a solar-powered emergency battery backup system for 5G telecommunication base stations, including medical applications, may vary depending on local climate, power requirements, and resources. In this connection, uninterrupted power supply to the base stations become crucial. The author utilizes the ChatGPT-AI features and prepared this comprehensive letter for realizing the role of sustainable practices towards climatic changes.

Opportunities and challenges of 5G network technology toward precision medicine

Moving away from traditional "one-size-fits-all" treatment to precision-based medicine has tremendously improved disease prognosis, accuracy of diagnosis, disease progression prediction, and targeted-treatment. The current cutting-edge of 5G network technology is enabling a growing trend in precision medicine to extend its utility and value to the smart healthcare system. The 5G network technology will bring together big data, artificial intelligence, and machine learning to provide essential levels of connectivity to enable a new health ecosystem toward precision medicine. In the 5G-enabled health ecosystem, its applications involve predictive and preventative measurements which enable advances in patient personalization. This review aims to discuss the opportunities, challenges, and prospects posed to 5G network technology in moving forward to deliver personalized treatments and patient-centric care via a precision medicine approach.

A Review of the Role of Artificial Intelligence in Healthcare

Artificial intelligence (AI) applications have transformed healthcare. This study is based on a general literature review uncovering the role of AI in healthcare and focuses on the following key aspects: (i) medical imaging and diagnostics, (ii) virtual patient care, (iii) medical research and drug discovery, (iv) patient engagement and compliance, (v) rehabilitation, and (vi) other administrative applications. The impact of AI is observed in detecting clinical conditions in medical imaging and diagnostic services, controlling the outbreak of coronavirus disease 2019 (COVID-19) with early diagnosis, providing virtual patient care using AI-powered tools, managing electronic health records, augmenting patient engagement and compliance with the treatment plan, reducing the administrative workload of healthcare professionals (HCPs), discovering new drugs and vaccines, spotting medical prescription errors, extensive data storage and analysis, and technology-assisted rehabilitation. Nevertheless, this science pitch meets several technical, ethical, and social challenges, including privacy, safety, the right to decide and try, costs, information and consent, access, and efficacy, while integrating AI into healthcare. The governance of AI applications is crucial for patient safety and accountability and for raising HCPs' belief in enhancing acceptance and boosting significant health consequences. Effective governance is a prerequisite to precisely address regulatory, ethical, and trust issues while advancing the acceptance and implementation of AI. Since COVID-19 hit the global health system, the concept of AI has created a revolution in healthcare, and such an uprising could be another step forward to meet future healthcare needs.

Investigating influencing factors for ICT adoption that changes travel behavior in response to the COVID-19 outbreak in Indonesia

Mobility and out-of-home activities restrictions from the COVID-19 pandemic have forced people to maximize their in-home activities. Considering the increase in Information and Communication Technology (ICT) adoption during the outbreak, this paper tries to shed light on the factors that influence changing travel behavior. For these purposes, the study uses data collected through an online questionnaire during the outbreak in Indonesia, which was then analyzed using cluster and discriminant analyses. The study found that online adaptation during the outbreak was affected by income level, whereby high-income individuals are associated with high online adaptation. Residential location also influences ICT adaptation during the outbreak. Cities with higher access to the internet and ICT platforms as well as higher income per capita tend to have higher ICT adoption. People with more experience with online platforms or services also record higher online in-home activity adoption during the outbreak. Furthermore, while the lower-income group tends to reduce their travel, the higher-income group still continues to travel to fulfil their household needs during the outbreak, such as in-store shopping. Since the lower-income group and less accessible areas tend to have difficulty in accessing ICT as a substitute for travel, this study recommends that the government and ICT stakeholders ensure equal access to ICT to support physical distancing and to limit mobility in order to flatten the peak of the pandemic.

ICT applications and the COVID-19 pandemic: Impacts on the individual's digital data, digital privacy, and data protection

A prominent move amid the COVID-19 pandemic is related to the wide use of ICT applications for various reasons. Such services are context-specific and sector-specific, but we see transformative directions leading to digital data collection, monitory, and management platforms. For now, these have been beneficial to evaluate trends and issues related to the pandemic. Some aggregated data could also help decision-making processes, which are helpful to contain such disruptive events. However, the main concern is the use of the individual's data and information, which means we may shift to micro-management and eventual controlling tools that could harm data protection processes. Undoubtedly, the use of ICTs during the COVID-19 pandemic has been primarily positive at multiple scales, but we have to evaluate the pros and cons before accepting all data collection processes. Such ICT-mediated platforms and/or applications must remain beneficial to all and avoid breaching the individual's data protection. This short communication paper first introduces ICT applications during the COVID-19 before providing an overview and further analysis of the situation of the ICT applications. Afterward, it discusses issues of data privacy, data collection, and data use, which are the backbone of ICT applications. The discussions highlight that future research in this area could look into associated issues related to digital privacy, data-driven approaches, and data protection regulations.

A systematic review on telenursing as a solution in improving the treatment compliance of tuberculosis patients in the COVID-19 pandemic

Introduction: The COVID-19 pandemic had made patients scared of coming to clinics or hospitals, and this could affect the treatment of TB. Therefore, one type of service that can be used by nurses to improve compliance to TB treatment is Telenursing. This article aims to ascertain whether telenursing could be a solution in improving the compliance of TB patients to treatments in the COVID-19 pandemic. Design and Method: This research was conducted using the Randomised Controlled Trial design as well as PRISMA. Furthermore, useful research articles were sourced from the database using the keywords, “Message Reminder and Tuberculosis OR Medication Adherence”. The databases used are Scopus, Science Direct, PubMed, and SAGE, all in English text and from 2015 to 2021, with inclusion criteria. 277 articles were obtained, and then filtered to select 3 articles by reading the main focus of the write-up, with regard to the topic of study. Result: Telenursing can be a solution to reduce the spread of COVID-19, and a substitute for remotely motivating individuals, as social support. Furthermore, it could be used as a reminder to patients to be obedient in carrying out treatments, and as a means of educating and improving good relationships with providers. Conclusions: Telenursing is a fairly effective solution in helping TB patients improve treatment compliance, reduce drug dropout rates and missed doses, as well as, raise awareness about the importance of health in the COVID-19 pandemic.  

Are digital services the right solution for empowering smallholder farmers? A perspective enlightened by COVID-19 experiences to inform smart IPM

The COVID-19 pandemic, surprised many through its impact on the food systems, resulting in collapses in the food production value chains and in the integrated pest disease management sector with fatal outcomes in many places. However, the impact of COVID-19 and the digital experience perspective on Integrating Pest Management (IPM) is still yet to be understood. In Africa, the impact was devastating, mostly for the vulnerable smallholder farm households, who were rendered unable to access markets to purchase inputs and sell their produce during the lockdown period. By using a holistic approach the paper reviews different Information and Communications Technologies (ICTs), digitalization, and how this enhanced the capacity of smallholder farmers resilient, and inform their smart-IPM practices in order to improve food systems' amidst climate change during and in the post-COVID-19 period. Different digital modalities were adopted to ensure continuous food production, access to inputs and finances, and selling surplus production among others. This was largely possible by using ICTs to deliver these needed services digitally. The study shares contributions and capacity perspectives of ICTs for empowering smallholder farmers to boost the resilience of their food systems based on COVID-19 successful experiences. Thus digital solutions must be embraced in the delivery of extension service on pest management and good agronomic practices, money transfers for purchasing inputs, receiving payment for sold farm produce, and markets information exchange. These are key avenues through which digital solutions strategically supported smallholder-based food systems through the pandemic.

Adopting 5G-Enabled E-Healthcare for Collaborative Pandemic Management

The spread of the COVID-19 pandemic had a huge impact on personal lives, society, and economies all over the world. Many countries are still struggling with the rising and falling numbers of COVID-19 cases. The drastic effects of the pandemic have brought sharp focus on healthcare and the need for rapid technology adoption and strong collaborative digital healthcare solutions for dealing with the health crisis. 5G networks can play a vital role in transforming the critical components of healthcare ecosystem by providing cost effective, high connectivity to the patients and healthcare workers. This research article investigates and highlights the technical aspects 5G technology, its effective utilization for collaborative e-health services, and the 5G-based solutions. It also presents a detailed discussion on challenges of 5G implementation and possible solutions. In the end, it discusses the future research directions for 5G-enabled e-collaboration in decreasing the health-based challenges and issues in future pandemic outbreaks.

A survey of COVID-19 detection and prediction approaches using mobile devices, AI, and telemedicine

Since 2019, the COVID-19 pandemic has had an extremely high impact on all facets of the society and will potentially have an everlasting impact for years to come. In response to this, over the past years, there have been a significant number of research efforts on exploring approaches to combat COVID-19. In this paper, we present a survey of the current research efforts on using mobile Internet of Thing (IoT) devices, Artificial Intelligence (AI), and telemedicine for COVID-19 detection and prediction. We first present the background and then present current research in this field. Specifically, we present the research on COVID-19 monitoring and detection, contact tracing, machine learning based approaches, telemedicine, and security. We finally discuss the challenges and the future work that lay ahead in this field before concluding this paper.

The technological intervention in e-health management: evidence from Thailand

Purpose

The e-health services came up as an effective tool to mitigate effects of COVID-19 and following social distance norms. This study highlighted an issue of contentious usage intentions of e-health services among Thai older citizens. This study aims to examine the relationship of social influence (SI), information quality (IQ) and the digital literacy (DL) to contentious usage intentions.

Design/methodology/approach

This study follows quantitative techniques, and the sample size is 140 to analyze, that is collected from the older Thai citizens. The convenient sampling technique was used to collect the data and the items were measured by using a five-point Likert scale.

Findings

The findings of this study are having mixed results. The effect of DL and satisfaction (SAT) on continuous usage intention (CUI) is significant. The effect of IQ and SI on CUI is non-significant. The effect of IQ and SI on SAT is significant. Further, the mediating effect of SAT between IQ and CUI is non-significant. However, the mediating effect of SAT between SI and CUI is significant.

Originality/value

This study contributes to knowledge by empirical testing of DL and usage of the medicine. Furthermore, to the best of the authors’ knowledge, this study is one of the rare studies that incorporate technological intervention for drug usage intentions.

eHealth: A Survey of Architectures, Developments in mHealth, Security Concerns and Solutions

The ramifications of the COVID-19 pandemic have contributed in part to a recent upsurge in the study and development of eHealth systems. Although it is almost impossible to cover all aspects of eHealth in a single discussion, three critical areas have gained traction. These include the need for acceptable eHealth architectures, the development of mobile health (mHealth) technologies, and the need to address eHealth system security concerns. Existing survey articles lack a synthesis of the most recent advancements in the development of architectures, mHealth solutions, and innovative security measures, which are essential components of effective eHealth systems. Consequently, the present article aims at providing an encompassing survey of these three aspects towards the development of successful and efficient eHealth systems. Firstly, we discuss the most recent innovations in eHealth architectures, such as blockchain-, Internet of Things (IoT)-, and cloud-based architectures, focusing on their respective benefits and drawbacks while also providing an overview of how they might be implemented and used. Concerning mHealth and security, we focus on key developments in both areas while discussing other critical topics of importance for eHealth systems. We close with a discussion of the important research challenges and potential future directions as they pertain to architecture, mHealth, and security concerns. This survey gives a comprehensive overview, including the merits and limitations of several possible technologies for the development of eHealth systems. This endeavor offers researchers and developers a quick snapshot of the information necessary during the design and decision-making phases of the eHealth system development lifecycle. Furthermore, we conclude that building a unified architecture for eHealth systems would require combining several existing designs. It also points out that there are still a number of problems to be solved, so more research and investment are needed to develop and deploy functional eHealth systems.

Future of digital health and community care: Exploring intended positive impacts and unintended negative consequences of COVID-19

Response to COVID-19 has both intentionally and unintentionally progressed the digitization of health and community care, which can be viewed as a human rights issue considering that access to health and community care is a human right. In this article, we reviewed two cases of digitization of health and community care during the pandemic; one in Scotland, United Kingdom and another in British Columbia, Canada. An integrated analysis revealed that digitization of health and community care has intended positive and unintended negative consequences. Based on the analysis, we suggest five areas of improvement for equity in care: building on the momentum of technology advantages; education and digital literacy; information management and security; development of policy and regulatory frameworks; and the future of digital health and community care. This article sheds light on how health practitioners and leaders can work to enhance equity in care experiences amid the changing digital landscape.

Conceptual Design of the "Private Car" Self-Isolation Ecosystem for the 2019-nCoV Infection

Since the beginning of the COVID-19 outbreak, confirmed and suspected cases of the disease have been increasing rapidly. The isolation of cases is one of the most effective methods for the control and containment of COVID-19 and has been rapidly popularized. Problems with isolation have gradually emerged, such as the inadequate allocation of isolation resources and the failure to properly resettle many of the suspected cases of the 2019-nCoV infection. In this paper, a self-isolation ecosystem of a rapid-deploying negative-pressurized "private car" is proposed for housing patients with 2019-nCoV infection, which could be lightweight, moderately sized and transparent to enable group supervision and communication. This "private car" isolation method aims to achieve self-isolation of patients and essentially solves the problem of where and how to isolate suspected cases while saving isolation resources and preventing the large-scale transmission of COVID-19.

Data-Driven Analysis of Outdoor-to-Indoor Propagation for 5G Mid-Band Operational Networks

The successful rollout of fifth-generation (5G) networks requires a full understanding of the behavior of the propagation channel, taking into account the signal formats and the frequencies standardized by the Third Generation Partnership Project (3GPP). In the past, channel characterization for 5G has been addressed mainly based on the measurements performed on dedicated links in experimental setups. This paper presents a state-of-the-art contribution to the characterization of the outdoor-to-indoor radio channel in the 3.5 GHz band, based on experimental data for commercial, deployed 5G networks, collected during a large scale measurement campaign carried out in the city of Rome, Italy. The analysis presented in this work focuses on downlink, outdoor-to-indoor propagation for two operators adopting two different beamforming strategies, single wide-beam and multiple synchronization signal blocks (SSB) based beamforming; it is indeed the first contribution studying the impact of beamforming strategy in real 5G networks. The time and power-related channel characteristics, i.e., mean excess delay and Root Mean Square (RMS) delay spread, path loss, and K-factor are studied for the two operators in multiple measurement locations. The analysis of time and power-related parameters is supported and extended by a correlation analysis between each pair of parameters. The results show that beamforming strategy has a marked impact on propagation. A single wide-beam transmission leads, in fact, to lower RMS delay spread and lower mean excess delay compared to a multiple SSB-based transmission strategy. In addition, the single wide-beam transmission system is characterized by a smaller path loss and a higher K-factor, suggesting that the adoption of a multiple SSB-based transmission strategy may have a negative impact on downlink performance.

How the 5G Enabled the COVID-19 Pandemic Prevention and Control: Materiality, Affordance, and (De-)Spatialization

5G, the most disruptive innovation, had played a significant role in the COVID-19 pandemic prevention and control. However, as a novel technology and context, we have little knowledge about how 5G enabled pandemic prevention and control. This study collected 212 cases and conducted qualitative research to explore how the 5G worked in prevention and control. Based on the concepts of materiality and affordance, we grounded two affordances of spatialization and de-spatialization from the data. Spatialization provides non-contact ways to complete the tasks which are supposed to be completed in contact, and de-spatialization provides remote operations to complete the tasks which are supposed to be completed on-site. Spatialization and de-spatialization enabled the diagnosis and treatment of the infectors to relieve the unbalance of medical staff, cutting the infectious route to contain the viral spread, and logistic supply to support the prevention and control. Our study offers theoretical contributions to digital pandemic prevention and control, and the literature on 5G also offers practical implications.

Antenna Systems in Medical Masks: Applications for 5G FR1 and Wi-Fi 7 Wireless Systems

This paper proposes a small antenna system (47 mm × 8 mm × 0.2 mm) to be used in a medical mask. The medical mask is composed of a frame and shield. The frame is made of polycarbonate (PC), and the shield is made of polyethylene terephthalate (PET). The author sets two groups of antennas on the upper side of the frame and sets two other groups of antennas on the sides facing away from the face of the shield. The substrates of the four antennas are all FR4 (εr = 4.4, tanδ = 0.02), so the first antenna type is a combination of PC and FR4, and the second antenna type is a combination of PET and FR4. The antenna system has three working frequency bands, in which the reflection coefficient is lower than −10 dB after actual measurement, and its working frequency bandwidth is 2.38–2.62 GHz, 3.38–3.74 GHz, and 5.14–8 GHz, respectively. It can be effectively used in 5G FR1 and Wi-Fi 7 frequency bands and can easily be combined with medical masks of different materials. This antenna system can use Wi-Fi 7 for wireless transmission indoors and use the 5G FR1 frequency band for wireless transmission outdoors, achieving seamless transmission capabilities.

Foresight study on online health community: The perspective of knowledge empowerment for patients with chronic diseases

Patient empowerment is an indispensable precondition for patients to self-manage their disease. The article takes the position that patients are empowered for disease self-management through patient knowledge empowerment when sharing knowledge. One of the most important instruments to successfully empower a patient to manage a chronic disease and maintain social relations, which are also a precondition for the prevention of chronic illnesses, is the possibility to access online health communities (OHCs) and participate in them. The aim of the article is to model possible development scenarios of OHCs as enablers of patient knowledge in relation to other digital health technologies (DHTs). A foresight methodology was used to achieve the goal, employing a technology scanning approach after selecting 10 foresight studies, which resulted in four future scenario models for the empowerment of patients wcith chronic diseases through digital health communities. They reveal options for the future interoperability of OHCs with other DHTs and highlight their importance and significance for the healthcare system as a technology for balancing patient self-efficacy and social relations as well as the need to maintain and develop them.

Digital health care services in post COVID-19 scenario: modeling the enabling factors

Purpose

The recent pandemic of COVID-19 has posed challenges for delivering essential and desirable health-care services for the masses. Digital health-care services initiated by several hospitals and health practitioners promise efficient and safe health care in the new normal post-COVID era but need a supportive enabling ecosystem. Therefore, this study aims toward identifying and modeling the key enabling factors for digital health-care services.

Design/methodology/approach

A total of nine factors were identified from the literature review and verified by the domain experts which can enable the wider acceptance of digital health-care services. The identified factors were then modeled with the help of the total interpretive structural modeling (TISM) approach and fuzzy Matrices d’Impacts Croises Multiplication Appliquée à un Classement (MICMAC) and a meaningful contextual relationship were developed for the factors.

Findings

This study reflects that the trust of patients is required for the acceptance of digital health care. Quality of patient care and affordability cum accessibility of online services will define mass engagement. Hospital staff resilience, hospital care service capacity, strategic partnerships and collaborations supported by technology and regulatory structure are the major factors defining the enabling ecosystem.

Originality/value

This study has its uniqueness in the way the TISM approach and fuzzy MICMAC are used for modeling the enabling factors toward growth and acceptance of digital health-care services in the days to come in developing nations. The focus of this study can be considered as relevant for the study interested in investigating the role of cognitive dimensions in influencing actors’ behaviors and decisions.

Anthropomorphic Robotic Eyes: Structural Design and Non-Verbal Communication Effectiveness

This paper shows the structure of a mechanical system with 9 DOFs for driving robot eyes, as well as the system's ability to produce facial expressions. It consists of three subsystems which enable the motion of the eyeballs, eyelids, and eyebrows independently to the rest of the face. Due to its structure, the mechanical system of the eyeballs is able to reproduce all of the motions human eyes are capable of, which is an important condition for the realization of binocular function of the artificial robot eyes, as well as stereovision. From a kinematic standpoint, the mechanical systems of the eyeballs, eyelids, and eyebrows are highly capable of generating the movements of the human eye. The structure of a control system is proposed with the goal of realizing the desired motion of the output links of the mechanical systems. The success of the mechanical system is also rated on how well it enables the robot to generate non-verbal emotional content, which is why an experiment was conducted. Due to this, the face of the human-like robot MARKO was used, covered with a face mask to aid in focusing the participants on the eye region. The participants evaluated the efficiency of the robot's non-verbal communication, with certain emotions achieving a high rate of recognition.

Large-Scale Dataset for the Analysis of Outdoor-to-Indoor Propagation for 5G Mid-Band Operational Networks

Understanding radio propagation characteristics and developing channel models is fundamental to building and operating wireless communication systems. Among others uses, channel characterization and modeling can be used for coverage and performance analysis and prediction. Within this context, this paper describes a comprehensive dataset of channel measurements performed to analyze outdoor-to-indoor propagation characteristics in the mid-band spectrum identified for the operation of 5th Generation (5G) cellular systems. Previous efforts to analyze outdoor-to-indoor propagation characteristics in this band were made by using measurements collected on dedicated, mostly single-link setups. Hence, measurements performed on deployed and operational 5G networks still lack in the literature. To fill this gap, this paper presents a dataset of measurements performed over commercial 5G networks. In particular, the dataset includes measurements of channel power delay profiles from two 5G networks in Band n78, i.e., 3.3–3.8 GHz. Such measurements were collected at multiple locations in a large office building in the city of Rome, Italy by using the Rohde & Schwarz (R&S) TSMA6 network scanner during several weeks in 2020 and 2021. A primary goal of the dataset is to provide an opportunity for researchers to investigate a large set of 5G channel measurements, aiming at analyzing the corresponding propagation characteristics toward the definition and refinement of empirical channel propagation models.

The Impact of COVID-19 Epidemic on the Development of the Digital Economy of China—Based on the Data of 31 Provinces in China

This study investigates the impact of coronavirus disease 2019 (COVID-19) on economic development of China by measuring the HP financial index as an alternative variable of the digital economy. This study shows that economy of China developed further with the dissemination of COVID-19. Furthermore, the digital economy increased the level of economic development more prominently at the onset of COVID-19 pandemic. Moreover, an analysis of regional heterogeneity reveals that the eastern region maintained economic stability through its digital economy during COVID-19, while the central region improved its digital economy during COVID-19 pandemic. Although the economically underdeveloped western region has not suffered too seriously from COVID-19 pandemic, considering the sustained impact of disease and the uncertainty of its transmission speed, the region should vigorously develop its digital economy to manage public risk.

Non-Pharmaceutical Interventions against COVID-19 Pandemic: Review of Contact Tracing and Social Distancing Technologies, Protocols, Apps, Security and Open Research Directions

The COVID-19 Pandemic has punched a devastating blow on the majority of the world's population. Millions of people have been infected while hundreds of thousands have died of the disease throwing many families into mourning and other psychological torments. It has also crippled the economy of many countries of the world leading to job losses, high inflation, and dwindling Gross Domestic Product (GDP). The duo of social distancing and contact tracing are the major technological-based non-pharmaceutical public health intervention strategies adopted for combating the dreaded disease. These technologies have been deployed by different countries around the world to achieve effective and efficient means of maintaining appropriate distance and tracking the transmission pattern of the diseases or identifying those at high risk of infecting others. This paper aims to synthesize the research efforts on contact tracing and social distancing to minimize the spread of COVID-19. The paper critically and comprehensively reviews contact tracing technologies, protocols, and mobile applications (apps) that were recently developed and deployed against the coronavirus disease. Furthermore, the paper discusses social distancing technologies, appropriate methods to maintain distances, regulations, isolation/quarantine, and interaction strategies. In addition, the paper highlights different security/privacy vulnerabilities identified in contact tracing and social distancing technologies and solutions against these vulnerabilities. We also x-rayed the strengths and weaknesses of the various technologies concerning their application in contact tracing and social distancing. Finally, the paper proposed insightful recommendations and open research directions in contact tracing and social distancing that could assist researchers, developers, and governments in implementing new technological methods to combat the menace of COVID-19.

The potential and challenges of Health 4.0 to face COVID-19 pandemic: a rapid review

The COVID-19 pandemic has generated the need to evolve health services to reduce the risk of contagion and promote a collaborative environment even remotely. Advances in Industry 4.0, including the internet of things, mobile networks, cloud computing, and artificial intelligence make Health 4.0 possible to connect patients with healthcare professionals. Hence, the focus of this work is analyzing the potentiality, and challenges of state-of-the-art Health 4.0 applications to face the COVID-19 pandemic including augmented environments, diagnosis of the virus, forecasts, medical robotics, and remote clinical services. It is concluded that Health 4.0 can be applied in the prevention of contagion, improve diagnosis, promote virtual learning environments, and offer remote services. However, there are still ethical, technical, security, and legal challenges to be addressed. Additionally, more imaging datasets for COVID-19 detection need to be made available to the scientific community. Working in the areas of opportunity will help to address the new normal. Likewise, Health 4.0 can be applied not only in the COVID-19 pandemic, but also in future global viruses and natural disasters.

Towards Smart Healthcare: UAV-Based Optimized Path Planning for Delivering COVID-19 Self-Testing Kits Using Cutting Edge Technologies

Coronavirus Disease 2019 (COVID-19) has emerged as a global pandemic since late 2019 and has affected all forms of human life and economic developments. Various techniques are used to collect the infected patients’ sample, which carries risks of transferring the infection to others. The current study proposes an AI-powered UAV-based sample collection procedure through self-collection kits delivery to the potential patients and bringing the samples back for testing. Using a hypothetical case study of Islamabad, Pakistan, various test cases are run where the UAVs paths are optimized using four key algorithms, greedy, intra-route, inter-route, and tabu, to save time and reduce carbon emissions associated with alternate transportation methods. Four cases with 30, 50, 100, and 500 patients are investigated for delivering the self-testing kits to the patients. The results show that the Tabu algorithm provides the best-optimized paths covering 31.85, 51.35, 85, and 349.15 km distance for different numbers of patients. In addition, the algorithms optimize the number of UAVs to be used in each case and address the studied cases patients with 5, 8, 14, and 71 UAVs, respectively. The current study provides the first step towards the practical handling of COVID-19 and other pandemics in developing countries, where the risks of spreading the infections can be minimized by reducing person-to-person contact. Furthermore, the reduced carbon footprints of these UAVs are an added advantage for developing countries that struggle to control such emissions. The proposed system is equally applicable to both developed and developing countries and can help reduce the spread of COVID-19 through minimizing the person-to-person contact, thus helping the transformation of healthcare to smart healthcare.

Applications of Artificial Intelligence, Machine Learning, Big Data and the Internet of Things to the COVID-19 Pandemic: A Scientometric Review Using Text Mining

The COVID-19 pandemic has wreaked havoc in every country in the world, with serious health-related, economic, and social consequences. Since its outbreak in March 2020, many researchers from different fields have joined forces to provide a wide range of solutions, and the support for this work from artificial intelligence (AI) and other emerging concepts linked to intelligent data analysis has been decisive. The enormous amount of research and the high number of publications during this period makes it difficult to obtain an overall view of the different applications of AI to the management of COVID-19 and an understanding of how research in this field has been evolving. Therefore, in this paper, we carry out a scientometric analysis of this area supported by text mining, including a review of 18,955 publications related to AI and COVID-19 from the Scopus database from March 2020 to June 2021 inclusive. For this purpose, we used VOSviewer software, which was developed by researchers at Leiden University in the Netherlands. This allowed us to examine the exponential growth in research on this issue and its distribution by country, and to highlight the clear hegemony of the United States (USA) and China in this respect. We used an automatic process to extract topics of research interest and observed that the most important current lines of research focused on patient-based solutions. We also identified the most relevant journals in terms of the COVID-19 pandemic, demonstrated the growing value of open-access publication, and highlighted the most influential authors by means of an analysis of citations and co-citations. This study provides an overview of the current status of research on the application of AI to the pandemic.

Ethics for integrating emerging technologies to contain COVID-19 in Zimbabwe

Zimbabwe is among the countries affected with the coronavirus disease (COVID-19) and implemented several infection control and measures such as social distancing, contact tracing, regular temperature checking in strategic entry and exit points, face masking among others. The country also implemented recursive national lockdowns and curfews to reduce the virus transmission rate and its catastrophic impact. These large-scale measures are not easy to implement, adhere to and subsequently difficult to practice and maintain which lead to imperfect public compliance, especially if there is a significant impact on social and political norms, economy, and psychological wellbeing of the affected population. Also, emerging COVID-19 variants, porous borders, regular movement of informal traders and sale of fake vaccination certificates continue to threaten impressive progress made towards virus containment. Therefore, several emerging technologies have been adopted to strengthen the health system and health services delivery, improve compliance, adherence and maintain social distancing. These technologies use health data, symptoms monitoring, mobility, location and proximity data for contact tracing, self-isolation, and quarantine compliance. However, the use of emerging technologies has been debatable and contentious because of the potential violation of ethical values such as security and privacy, data format and management, synchronization, over-tracking, over-surveillance and lack of proper development and implementation guidelines which impact their efficacy, adoption and ultimately influence public trust. Therefore, the study proposes ethical framework for using emerging technologies to contain the COVID-19 pandemic. The framework is centered on ethical practices such as security, privacy, justice, human dignity, autonomy, solidarity, beneficence, and non-maleficence.

Contributions of Smart City Solutions and Technologies to Resilience against the COVID-19 Pandemic: A Literature Review

Since its emergence in late 2019, the COVID-19 pandemic has swept through many cities around the world, claiming millions of lives and causing major socio-economic impacts. The pandemic occurred at an important historical juncture when smart solutions and technologies have become ubiquitous in many cities. Against this background, in this review, we examine how smart city solutions and technologies have contributed to resilience by enhancing planning, absorption, recovery, and adaptation abilities. For this purpose, we reviewed 147 studies that have discussed issues related to the use of smart solutions and technologies during the pandemic. The results were synthesized under four themes, namely, planning and preparation, absorption, recovery, and adaptation. This review shows that investment in smart city initiatives can enhance the planning and preparation ability. In addition, the adoption of smart solutions and technologies can, among other things, enhance the capacity of cities to predict pandemic patterns, facilitate an integrated and timely response, minimize or postpone transmission of the virus, provide support to overstretched sectors, minimize supply chain disruption, ensure continuity of basic services, and offer solutions for optimizing city operations. These are promising results that demonstrate the utility of smart solutions for enhancing resilience. However, it should be noted that realizing this potential hinges on careful attention to important issues and challenges related to privacy and security, access to open-source data, technological affordance, legal barriers, technological feasibility, and citizen engagement. Despite this, this review shows that further development of smart city initiatives can provide unprecedented opportunities for enhancing resilience to the pandemic and similar future events.

Integrating Digital Technologies and Public Health to Fight Covid-19 Pandemic: Key Technologies, Applications, Challenges and Outlook of Digital Healthcare

Integration of digital technologies and public health (or digital healthcare) helps us to fight the Coronavirus Disease 2019 (COVID-19) pandemic, which is the biggest public health crisis humanity has faced since the 1918 Influenza Pandemic. In order to better understand the digital healthcare, this work conducted a systematic and comprehensive review of digital healthcare, with the purpose of helping us combat the COVID-19 pandemic. This paper covers the background information and research overview of digital healthcare, summarizes its applications and challenges in the COVID-19 pandemic, and finally puts forward the prospects of digital healthcare. First, main concepts, key development processes, and common application scenarios of integrating digital technologies and digital healthcare were offered in the part of background information. Second, the bibliometric techniques were used to analyze the research output, geographic distribution, discipline distribution, collaboration network, and hot topics of digital healthcare before and after COVID-19 pandemic. We found that the COVID-19 pandemic has greatly accelerated research on the integration of digital technologies and healthcare. Third, application cases of China, EU and U.S using digital technologies to fight the COVID-19 pandemic were collected and analyzed. Among these digital technologies, big data, artificial intelligence, cloud computing, 5G are most effective weapons to combat the COVID-19 pandemic. Applications cases show that these technologies play an irreplaceable role in controlling the spread of the COVID-19. By comparing the application cases in these three regions, we contend that the key to China's success in avoiding the second wave of COVID-19 pandemic is to integrate digital technologies and public health on a large scale without hesitation. Fourth, the application challenges of digital technologies in the public health field are summarized. These challenges mainly come from four aspects: data delays, data fragmentation, privacy security, and data security vulnerabilities. Finally, this study provides the future application prospects of digital healthcare. In addition, we also provide policy recommendations for other countries that use digital technology to combat COVID-19.

Framework for ethical and acceptable use of social distancing tools and smart devices during COVID-19 pandemic in Zimbabwe

Despite the successful development of vaccines, coronavirus disease (COVID-19) continues to present unprecedented challenges. Besides the ongoing vaccination activities, many countries still rely on measures including social distancing, contact tracing, mandatory face masking among others. Several digital technologies such as smart devices, social distancing tools, smart applications have been adopted to enhance public adherence to reduce secondary transmission. Such technologies use health data, symptoms monitoring, mobility, location and proximity data for contact tracing, self-isolation and quarantine compliance. The use of digital technologies has been debatable and contentious because of the potential violation of ethical values such as security and privacy, data format and management, synchronization, over-tracking, over-surveillance and lack of proper development and implementation guidelines which subsequently impact their efficacy and adoption. Also, the aggressive and mandatory use of large-scale digital technologies is not easy to implement, adhere to and subsequently difficult to practice which ultimately lead to imperfect public compliance. To alleviate these impediments, we analysed the available literature and propose an ethical framework for the use of digital technologies centred on ethical practices. The proposed framework highlights the trade-offs, potential roles and coordination of different stakeholders involved in the development and implementation of digital technologies, from various social and political contexts in Zimbabwe. We suggest that transparency, regular engagement and participation of potential users are likely to boost public trust. However, the potential violation of ethical values, poor communication, hasty implementation of digital technologies will likely undermine public trust, and as such, risk their adoption and efficacy.