Smart technologies driven approaches to tackle COVID-19 pandemic: a review

Robotic versus manual disinfection of global priority pathogens at COVID-19-dedicated hospitals

BACKGROUND

Twelve bacterial families identified as global priority pathogens (GPPs) pose the greatest threat to human health due to declining antibiotic efficacy. Robotics, a swift and contactless tool for disinfecting hospital surfaces, was sought to compare with manual disinfection.

METHODS

The disinfection efficacy of a robot was compared with manual disinfection for multiple clinical surfaces and inanimate objects at two hospitals in Nepal using bleach (NaOCl). Surfaces were swabbed pre- and post-disinfection and total heterotrophic plate count evaluated, and bacterial pathogens identified using Gram's staining and biochemical characteristics. Disinfection outcomes were reported as log reduction (log10 CFU/inch2) of heterotrophic count and presence or absence of GPPs: Staphylococcus aureus, Escherichia coli, Acinetobacter spp., and Klebsiella pneumoniae, among others.

RESULTS

Both robotic and manual disinfection significantly reduced the microbial load (log 2.3 to log 5.8) on hospital surfaces. No pathogens were detected post-disinfection using the robot. Robotic disinfection was more effective, significantly reducing the bacterial load (log 5.8) compared to manual disinfection (log 3.95).

CONCLUSIONS

Our results showed better efficacy of robotic disinfection over manual disinfection of hospital surfaces, and thus contactless robotic disinfection is recommended for disinfecting surfaces in the hospital and clinical settings as it favors patient safety against GPPs.

The role of artificial intelligence in pandemic responses: from epidemiological modeling to vaccine development

Integrating Artificial Intelligence (AI) across numerous disciplines has transformed the worldwide landscape of pandemic response. This review investigates the multidimensional role of AI in the pandemic, which arises as a global health crisis, and its role in preparedness and responses, ranging from enhanced epidemiological modelling to the acceleration of vaccine development. The confluence of AI technologies has guided us in a new era of data-driven decision-making, revolutionizing our ability to anticipate, mitigate, and treat infectious illnesses. The review begins by discussing the impact of a pandemic on emerging countries worldwide, elaborating on the critical significance of AI in epidemiological modelling, bringing data-driven decision-making, and enabling forecasting, mitigation and response to the pandemic. In epidemiology, AI-driven epidemiological models like SIR (Susceptible-Infectious-Recovered) and SIS (Susceptible-Infectious-Susceptible) are applied to predict the spread of disease, preventing outbreaks and optimising vaccine distribution. The review also demonstrates how Machine Learning (ML) algorithms and predictive analytics improve our knowledge of disease propagation patterns. The collaborative aspect of AI in vaccine discovery and clinical trials of various vaccines is emphasised, focusing on constructing AI-powered surveillance networks. Conclusively, the review presents a comprehensive assessment of how AI impacts epidemiological modelling, builds AI-enabled dynamic models by collaborating ML and Deep Learning (DL) techniques, and develops and implements vaccines and clinical trials. The review also focuses on screening, forecasting, contact tracing and monitoring the virus-causing pandemic. It advocates for sustained research, real-world implications, ethical application and strategic integration of AI technologies to strengthen our collective ability to face and alleviate the effects of global health issues.

A review of the role of graphene-based nanomaterials in tackling challenges posed by the COVID-19 pandemic

In 2020, the World Health Organization (WHO) declared a pandemic due to the emergence of the coronavirus disease (COVID-19) which had resulted by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). At present, the emergence of many new variants and mutants were found to be more harmful compared to the previous strains. As a result, research scientists around the world had devoted significant efforts to understand the mechanism, causes and transmission due to COVID-19 along with the treatment to cure these diseases. However, despite achieving several findings, much more was unknown and yet to be explored. Hence, along with these developments, it is also extremely essential to design effective systems by incorporating smart materials to battle the COVID-19. Therefore, several approaches have been implemented to combat against COVID-19. Recently, the graphene-based materials have been explored for the current COVID-19 and future pandemics due to its superior physicochemical properties, providing efficient nanoplatforms for optical and electrochemical sensing and diagnostic applications with high sensitivity and selectivity. Moreover, based on the photothermal effects or reactive oxygen species formation, the carbon-based nanomaterials have shown its potentiality for targeted antiviral drug delivery and the inhibitory effects against pathogenic viruses. Therefore, this review article sheds light on the recent progress and the most promising strategies related to graphene and related materials and its applications for detection, decontamination, diagnosis, and protection against COVID-19. In addition, the key challenges and future directives are discussed in detail for fundamental design and development of technologies based on graphene-based materials along with the demand aspects of graphene-based products and lastly, our personal opinions on the appropriate approaches to improve these technologies respectively.

Linear and nonlinear regression modelling of industrial dye adsorption using nanocellulose@chitosan nanocomposite beads

Nanocellulose@chitosan (nc@ch) composite beads were prepared via coagulation technique for the elimination of malachite green dye from aqueous solution. As malachite green dye is highly used in textile industries for dyeing purpose which after usage shows fatal effects to the ecosystems and human beings also. In this study the formulated nanocellulose@chitosan composite beads were characterized by Particle size analysis (PSA), Field emission scanning electron microscopy (FESEM), Fourier-transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD) analysis were done to evaluate nanoparticles size distribution, morphological behaviour, functional group entities and degree of crystallinity of prepared beads. The nanocomposite beads adsorption performance was investigated for malachite green (MG) dye and BET analysis were also recorded to know about porous behaviour of the nanocomposite beads. Maximum removal of malachite green (MG) dye was found to be 72.0 mg/g for 100 ppm initial dye concentration. For accurate observations linear and non-linear modelling was done to know about the best-fitted adsorption model during the removal mechanism of dye molecules, on evaluating it has been observed that Langmuir isotherm and Freundlich isotherm show best-fitted observation in the case of linear and non-linear isotherm respectively (R2 = 0.96 & R2 = 0.957). In the case of kinetic linear models, the data was well fitted with pseudo-second-order showing chemosorption mechanism (R2 = 0.999), and in the case of non-linear kinetic model pseudo first order showed good fit showing physisorption mechanism during adsorption (R2 = 0.999). The thermodynamic study showed positive values for ΔH° and ΔS° throughout the adsorption process respectively, implying an endothermic behaviour. In view of cost effectiveness, desorption or regeneration study was done and it was showed that after the 5th cycle, the removal tendency had decreased from 48 to 38 % for 20-100 ppm dye solution accordingly. Thus, nanocomposite beads prepared by the coagulation method seem to be a suitable candidate for dye removal from synthetic wastewater and may have potential to be used in small scale textile industries for real wastewater treatment.

In vivo characterization of a luffa-based composite scaffold for subcutaneous implantation in rats

Recent advancements in tissue engineering have witnessed luffa-derived scaffolds, exhibiting their exceptional potential in cellular proliferation, biocompatibility, appropriate interconnectivity, and biomechanical strength. In vivo studies involved implanting fabricated scaffolds subcutaneously in Wistar rats to evaluate their impact on the heart, liver, and kidneys. This approach provided a safe and minimally invasive means to evaluate scaffold compatibility with surrounding tissues. Male Wistar rats were categorized into four distinct groups, Group A, B, C, and D are referred to as 3% LC implanted scaffolds, 5% LC implanted scaffolds, control (without luffa scaffolds), and Sham (without any scaffold implantation), respectively. Histological analysis in all the groups indicated that the animal models did not exhibit any signs of inflammation or toxicity, suggesting favorable tissue response to the implanted scaffolds. Initial observations revealed elevated levels of enzymes and biomarkers in the experimental groups after a 24 h interval, including aspartate aminotransferase (AST), alanine aminotransferase (ALT), alkaline phosphatase (ALP), bilirubin, creatine kinase-MB (CK-MB), and serum creatinine. However, these parameters normalized 3 weeks post-implantation, with no significant increase compared to the control groups, suggesting that the implanted luffa-based scaffolds did not induce adverse effects on the heart, liver, and kidneys. Furthermore, the scaffold's significant pore size and porosity enable it to release drugs, including antibacterial medications. This study demonstrates promising results, indicating excellent scaffold porosity, sustained drug release, affirming the in vivo biocompatibility, absence of inflammatory responses, and overall tissue compatibility highlighting the immense potential of these luffa-based scaffolds in various tissue engineering and regenerative medicine applications.

Smart Cities Mission in the Face of COVID: Scope and Scale of 'Smart' COVID Responses in India

COVID has expedited and expanded the already precarious smart city development in India with the multitude of 'smart' COVID responses-broadly known as CovTech-introduced since the early days of the global pandemic. This paper offers an analysis of the scope and scale of smart responses to COVID in the first 20 cities prioritized for smart city implementation-as part of the Smart Cities Mission in India. The analysis unravels the diversity within the smart COVID response, as 125 COVID applications, 14 COVID-War-Rooms, and numerous examples of smart public place initiatives are discussed. The findings include a typology of COVID applications and shed light on the operations of COVID-War-Rooms throughout the nation. The learnings point toward a mostly top-down approach to smart COVID response. Yet, early evidence indicates the existence of an alternative subaltern smart COVID response to provide bottom-up support to the most vulnerable groups, filling the gaps in the top-down approach. More research is required to thoroughly understand the scope and scale of the subaltern smart response to COVID.

Smartphone-based corona virus detection using saliva: A mini-review

During the ongoing worldwide epidemic, SARS-CoV-2 has infected millions of individuals and taken the lives of numerous victims. It is clear that early detection of infected individuals, especially asymptomatic carriers, is possible with the development of innovative analytical tools for rapid identification of COVID-19 present in nasopharyngeal swabs, serum, and saliva. The saliva, as a diagnostic sample, can be easily collected by the patient with almost no discomfort and needs specialized healthcare personnel to manage, which reduces the risks for the operator. Moreover, smartphone-based sensing systems are one of the most attractive techniques that can speed up the detection time of COVID-19 agents without the need for professional staff and clinical centers. In this review, recent advances in precise salivary-based SARS-CoV-2 diagnosis using smartphones via viral RNA detection, antibody identification, and viral antigen identification were summarized. Finally, the conclusion and future perspective of this field are described in brief.

A Study on the Structural Relationships between COVID-19 Coping Strategies, Positive Expectations, and the Behavioral Intentions of Various Tourism-Related Behaviors

The purpose of this study was to investigate the impact of coping strategies, attitudes, and positive anticipated emotions on the positive expectations and behavioral intentions of Korean tourists during the COVID-19 pandemic. An integrated model was proposed and tested, and the results indicate that effective coping strategies, attitudes, and positive anticipated emotions have a positive effect on the positive expectations of tourism during the pandemic, which in turn positively influences behavioral intentions. Practical suggestions were also provided based on the findings. This research has implications for understanding the ways in which individuals cope with and adapt to travel during times of crisis, and for identifying strategies that may facilitate positive expectations and behavioral intentions in the tourism industry.

Using drones to transport suspected COVID-19 samples; experiences from the second largest testing centre in Ghana, West Africa

BACKGROUND

The declaration of COVID-19 as a pandemic on March 11 2020, by the World Health Organisation prompted the need for a sustained and a rapid international response. In a swift response, the Government of Ghana, in partnership with Zipline company, launched the use of Unmanned Automated Vehicles (UAV) to transport suspected samples from selected districts to two foremost testing centres in the country. Here, we present the experiences of employing this technology and its impact on the transport time to the second largest testing centre, the Kumasi Centre for Collaborative Research in Tropical Medicine (KCCR) in Kumasi, Ghana.

METHODS

Swab samples collected from suspected COVID-19 patients were transported to the Zipline office by health workers. Information on the samples were sent to laboratory personnel located at KCCR through a WhatsApp platform to get them ready to receive the suspected COVID-19 samples while Zipline repackaged samples and transported them via drone. Time of take-off was reported as well as time of drop-off.

RESULTS

A total of 2537 COVID-19 suspected samples were received via drone transport from 10 districts between April 2020 to June 2021 in 440 deliveries. Ejura-Sekyedumase District Health Directorate delivered the highest number of samples (765; 30%). The farthest district to use the drone was Pru East, located 270 km away from KCCR in Kumasi and 173 km to the Zipline office in Mampong. Here, significantly, it took on the average 39 minutes for drones to deliver samples compared to 117 minutes spent in transporting samples by road (p<0.001).

CONCLUSION

The use of drones for sample transport during the COVID-19 pandemic significantly reduced the travel time taken for samples to be transported by road to the testing site. This has enhanced innovative measures to fight the pandemic using technology.

Integrating drones in response to public health emergencies: A combined framework to explore technology acceptance

The aim of the study was to propose and test an integrated model combining the technology acceptance model (TAM), task-technology fit (TTF), social motivation, and drone-related perceived risks to explore the intention to use drones in public health emergencies (PHEs). We conducted a survey among the Israeli population, yielding a sample of 568 participants. Structural equation modeling was implemented to test the research hypotheses. The results showed that our integrated model provided a robust and comprehensive framework to perform an in-depth investigation of the factors and mechanisms affecting drone acceptance in PHEs. First, ease of use, attitudes, individual-technology fit, task-technology fit, and social influence significantly and directly influenced users' behavioral intention to utilize drone technology. Second, attitudes were significant mediators of the effects of social influence and perceived risks on the intention to use drones. Finally, significant relationships between TAM, TTF, social motivation, and perceived risks were also observed. Theoretical aspects and practical implications-which can serve as the basis for shaping a positive development in drone public acceptance in PHEs and in general-are discussed.

Role of Drone Technology Helping in Alleviating the COVID-19 Pandemic

The COVID-19 pandemic, caused by a new coronavirus, has affected economic and social standards as governments and healthcare regulatory agencies throughout the world expressed worry and explored harsh preventative measures to counteract the disease's spread and intensity. Several academics and experts are primarily concerned with halting the continuous spread of the unique virus. Social separation, the closing of borders, the avoidance of big gatherings, contactless transit, and quarantine are important methods. Multiple nations employ autonomous, digital, wireless, and other promising technologies to tackle this coronary pneumonia. This research examines a number of potential technologies, including unmanned aerial vehicles (UAVs), artificial intelligence (AI), blockchain, deep learning (DL), the Internet of Things (IoT), edge computing, and virtual reality (VR), in an effort to mitigate the danger of COVID-19. Due to their ability to transport food and medical supplies to a specific location, UAVs are currently being utilized as an innovative method to combat this illness. This research intends to examine the possibilities of UAVs in the context of the COVID-19 pandemic from several angles. UAVs offer intriguing options for delivering medical supplies, spraying disinfectants, broadcasting communications, conducting surveillance, inspecting, and screening patients for infection. This article examines the use of drones in healthcare as well as the advantages and disadvantages of strict adoption. Finally, challenges, opportunities, and future work are discussed to assist in adopting drone technology to tackle COVID-19-like diseases.

Comparing Rapid Ag Test and PCR in SARS-CoV-2 Management in Rural Egypt

Like elsewhere around the globe, SARS-CoV-2 infection is spreading in rural Egypt. Due to high sensitivity and specificity, the gold standard of diagnostics is reverse transcription polymerase chain reaction PCR (RT-PCR). Rural areas without access to certified laboratories cannot take advantage of RT-PCR testing, and thus are dependent upon rapid antigen testing, a point-of-care test that requires less training and can produce results within 15 minutes. Rapid antigen testing can give an advantage to medical teams in rural settings by affording effective and early control of SARS-CoV-2 infection spread. We sought to assess the contribution of different COVID-19 testing procedures in rural Egypt. We conducted a prospective cohort study in a rural lab in Giza, Egypt. Approximately 223 individuals with potential SARS-CoV-2 infection were involved in the study during the pandemic peak in Giza, Egypt, from March 4 – May 30, 2021. Subjects were subjected to RT-PCR and rapid antigen testing, and the performance of each testing procedure was compared. Between March 4 – May 30, 2021, approximately 223 symptomatic individuals were included in this study. 190 patients (85.2%) were indicated as PCR positive for SARS-CoV-2, while 33 (14.8%) were PCR negative. In comparison, a rapid antigen test showed 178 out of 223 patients (79.8%) were indicated as positive, or 94% of the PCR-positive individuals. In Giza, a rural area of Egypt, RT-PCR had an optimal balance of sensitivity and specificity, however, the turnaround time was a limiting factor. Antigen testing, performed as a rapid point-of-care test, can play an effective role in rural outbreak control due to its ease of use and rapid results.

A Deep Learning Approach for Sentiment Analysis of COVID-19 Reviews

User-generated multi-media content, such as images, text, videos, and speech, has recently become more popular on social media sites as a means for people to share their ideas and opinions. One of the most popular social media sites for providing public sentiment towards events that occurred during the COVID-19 period is Twitter. This is because Twitter posts are short and constantly being generated. This paper presents a deep learning approach for sentiment analysis of Twitter data related to COVID-19 reviews. The proposed algorithm is based on an LSTM-RNN-based network and enhanced featured weighting by attention layers. This algorithm uses an enhanced feature transformation framework via the attention mechanism. A total of four class labels (sad, joy, fear, and anger) from publicly available Twitter data posted in the Kaggle database were used in this study. Based on the use of attention layers with the existing LSTM-RNN approach, the proposed deep learning approach significantly improved the performance metrics, with an increase of 20% in accuracy and 10% to 12% in precision but only 12–13% in recall as compared with the current approaches. Out of a total of 179,108 COVID-19-related tweets, tweets with positive, neutral, and negative sentiments were found to account for 45%, 30%, and 25%, respectively. This shows that the proposed deep learning approach is efficient and practical and can be easily implemented for sentiment classification of COVID-19 reviews.

Digital technologies, healthcare and Covid-19: insights from developing and emerging nations

COVID-19 pandemic created a global health crisis affecting every nation. The essential smart medical devices/accessories, quarantine facilities, surveillance systems, and related digital technologies are in huge demand. Healthcare, manufacturing industries, and educational institutions need technologies that allow working from a safe location. Digital technologies and Industry 4.0 tools have the potential to fulfil these customized requirements during and post COVID-19 crisis. The purpose of this research is to provide understanding to healthcare professionals, government policymakers, researchers, industry professionals, academics, and students/learners of the paradigm of different Digital technologies, Industry 4.0 tools, and their applications during the COVID-19 pandemic. Digital technologies, Industry 4.0 tools and their current and potential applications have been reviewed. The use of different Digital technologies and Industry 4.0 tools is identified. Digital technologies and Industry 4.0 tools (3D Printing, Artificial Intelligence, Cloud Computing, Autonomous Robot, Biosensor, Telemedicine service, Internet of Things (IoT), Virtual reality, and holography) offer opportunities for effective delivery of healthcare service(s), online education, and Work from Home (WFH) environment. The article emphasises the usefulness, most recent development, and implementation of Digital technologies, Industry 4.0 techniques, and tools in fighting the COVID-19 pandemic worldwide.

Evaluating the sustainability of smart technology applications in healthcare after the COVID-19 pandemic: A hybridising subjective and objective fuzzy group decision-making approach with explainable artificial intelligence

During the COVID-19 pandemic, some smart technology applications were more effective than had been expected, whereas some others did not achieve satisfactory performance. Consequently, whether smart technology applications in healthcare are sustainable is a question that warrants investigation. To address this question, a hybridising subjective and objective fuzzy group decision-making approach with explainable artificial intelligence was proposed in this study and then used to evaluate the sustainability of smart technology applications in healthcare. The contribution of this research is its subjective evaluation of the sustainability of smart technology applications followed by correction of the evaluation outcome on the basis of the applications' objective performance during the COVID-19 pandemic. To this end, a fuzzy nonlinear programming model was formulated and optimised. In addition, the impact of several major global events that occurred during the pandemic on the sustainability of smart technology applications was considered. The proposed methodology was applied to evaluate the sustainability levels of eight smart technology applications in healthcare. According to the experimental results, three applications-namely healthcare apps, smartwatches, and remote temperature scanners-are expected to be highly sustainable in healthcare, whereas one application, namely smart clothing, is not.

A Scoping Review of Supply Chain Management Systems for Point of Care Diagnostic Services: Optimising COVID-19 Testing Capacity in Resource-Limited Settings

BACKGROUND

Point of care (POC) testing has enabled rapid coronavirus disease 2019 (COVID-19) diagnosis in resource-limited settings with limited laboratory infrastructure and high disease burden. However, the accessibility of the tests is not optimal in these settings. This scoping review mapped evidence on supply chain management (SCM) systems for POC diagnostic services to reveal evidence that can help guide future research and inform the improved implementation of SARS-CoV-2 POC diagnostics in resource-limited settings.

METHODOLOGY

This scoping review was guided by an adapted version of the Arksey and O'Malley methodological framework. We searched the following electronic databases: Medline Ovid, Medline EBSCO, Scopus, PubMed, PsychInfo, Web of Science and EBSCOHost. We also searched grey literature in the form of dissertations/theses, conference proceedings, websites of international organisations such as the World Health Organisation and government reports. A search summary table was used to test the efficacy of the search strategy. The quality of the included studies was appraised using the mixed method appraisal tool (MMAT) version 2018.

RESULTS

We retrieved 1206 articles (databases n = 1192, grey literature n = 14). Of these, 31 articles were included following abstract and full-text screening. Fifteen were primary studies conducted in LMICs, and 16 were reviews. The following themes emerged from the included articles: availability and accessibility of POC diagnostic services; reasons for stockouts of POC diagnostic tests (procurement, storage, distribution, inventory management and quality assurance) and human resources capacity in POC diagnostic services. Of the 31 eligible articles, 15 underwent methodological quality appraisal with scores between 90% and 100%.

CONCLUSIONS

Our findings revealed limited published research on SCM systems for POC diagnostic services globally. We recommend primary studies aimed at investigating the barriers and enablers of SCM systems for POC diagnostic services for highly infectious pathogens such SARS-CoV-2 in high disease-burdened settings with limited laboratory infrastructures.

Methodology for integrating artificial intelligence in healthcare systems: learning from COVID-19 to prepare for Disease X

Artificial intelligence and edge devices have been used at an increased rate in managing the COVID-19 pandemic. In this article we review the lessons learned from COVID-19 to postulate possible solutions for a Disease X event. The overall purpose of the study and the research problems investigated is the integration of artificial intelligence function in digital healthcare systems. The basic design of the study includes a systematic state-of-the-art review, followed by an evaluation of different approaches to managing global pandemics. The study design then engages with constructing a new methodology for integrating algorithms in healthcare systems, followed by analysis of the new methodology and a discussion. Action research is applied to review existing state of the art, and a qualitative case study method is used to analyse the knowledge acquired from the COVID-19 pandemic. Major trends found as a result of the study derive from the synthesis of COVID-19 knowledge, presenting new insights in the form of a conceptual methodology-that includes six phases for managing a future Disease X event, resulting with a summary map of various problems, solutions and expected results from integrating functional AI in healthcare systems.

Covid-19 and organisational development: important signs of a new pillar for sustainability

Purpose

The global pandemic has had a considerable effect on organisations’ performance and development and on the daily lives of the general population. This study aims to analyse the recent literature on the topics of Covid-19 and sustainability and proposes to rethink and redefine sustainability with the intersection of human health as a fourth sustainable pillar.

Design/methodology/approach

Using the Scopus and ISI Web of Science databases, 119 articles were analysed in detail and classified according to concepts and principles for achieving sustainable development, based on the Brundtland Report, 1987.

Findings

The results indicate a high number of publications in the social dimension, with a relevant proportion of studies in the health sector. This study allows us to conclude that all sectors of society are being affected by the pandemic. However, the enormous tension and the immediate impact felt by the health sector during the pandemic reflect directly on the population, and there are clear signs that in the medium and long term, instability and uncertainty in the environmental, economic and social dimensions will remain. In national health systems, monitoring, innovating in human resource management and investing in information technology can ensure organizations’ reliability and sustainability. The conclusion involves the suggestion of introducing health as a new pillar for sustainability to consolidate the basis and structure of the United Nations’ Sustainable Development Objectives. The use of fundamental concepts is necessary and must be aligned to reassess the results obtained in studies, in comparison with observational data.

Practical implications

The implications arising from the inclusion of health as a fourth pillar of sustainability are diverse. The need to build a new theoretical and conceptual framework for sustainability derives from the fact that health reflects the concern of many postulants in this field of practices. The determining or conditioning conditions of the observed effects of the pandemic by COVID-19, whether situated simply as factors and/or economic, environmental or social reflexes that precede them, requires a conceptual development that allows its approach, as a complex object, whose determinations are subject to variable degrees of uncertainty and diversity.

Originality/value

This study aims to redefine the concept of sustainability, considering that health has become a public health emergency of international interest. Health affects the supply chain, cash flow, interferes with the educational format and interrupts the workforce’s routine, among other aspects, showing the true nature of its importance and its impact in all spheres (economic, environmental and social).

How to Improve Information Technology to Support Healthcare to Address the COVID-19 Pandemic: an International Survey with Health Informatics Experts

OBJECTIVES

To identify the ways in which healthcare information and communication technologies can be improved to address the challenges raised by the COVID-19 pandemic.

METHODS

The study population included health informatics experts who had been involved with the planning, development and deployment of healthcare information and communication technologies in healthcare settings in response to the challenges presented by the COVID-19 pandemic. Data were collected via an online survey. A non-probability convenience sampling strategy was employed. Data were analyzed with content analysis.

RESULTS

A total of 65 participants from 16 countries responded to the conducted survey. The four major themes regarding recommended improvements identified from the content analysis included: improved technology availability, improved interoperability, intuitive user interfaces and adoption of standards of care. Respondents also identified several key healthcare information and communication technologies that can help to provide better healthcare to patients during the COVID-19 pandemic, including telehealth, advanced software, electronic health records, remote work technologies (e.g., remote desktop computer access), and clinical decision support tools.

CONCLUSIONS

Our results help to identify several important healthcare information and communication technologies, recommended by health informatics experts, which can help to provide better care to patients during the COVID-19 pandemic. The results also highlight the need for improved interoperability, intuitive user interfaces and advocating the adoption of standards of care.

The role of disinfectants and sanitizers during COVID-19 pandemic: advantages and deleterious effects on humans and the environment

Disinfectants and sanitizers are essential preventive agents against the coronavirus disease 2019 (COVID-19) pandemic; however, the pandemic crisis was marred by undue hype, which led to the indiscriminate use of disinfectants and sanitizers. Despite demonstrating a beneficial role in the control and prevention of COVID-19, there are crucial concerns regarding the large-scale use of disinfectants and sanitizers, including the side effects on human and animal health along with harmful impacts exerted on the environment and ecological balance. This article discusses the roles of disinfectants and sanitizers in the control and prevention of the current pandemic and highlights updated disinfection techniques against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This article provides evidence of the deleterious effects of disinfectants and sanitizers exerted on humans, animals, and the environment as well as suggests mitigation strategies to reduce these effects. Additionally, potential technologies and approaches for the reduction of these effects and the development of safe, affordable, and effective disinfectants are discussed, particularly, eco-friendly technologies using nanotechnology and nanomedicine.

Smart city projects against COVID-19: Quantitative evidence from China

The outbreak of COVID-19 pandemic worldwide has brought huge challenges to urban governance. Whether the smart city projects play a significant role in the COVID-19 prevention and control process is a question worthy of attention. Based on the data of COVID-19 confirmed cases and the smart cities projects investment in China cities, our empirical results show that smart city projects have significantly reduced the number of COVID-19 confirmed cases. Specifically, for every 1 million yuan increase in smart city investment per 10,000 people, the number of COVID-19 confirmed cases per 10,000 people would decrease by 0.342. The heterogeneity analysis results show that the effect of the smart city projects on COVID-19 in the spread phase inside a city is stronger than that in the input phase. In addition, the effect differs for cities with different population sizes. This study provides quantitative evidence of the impact of smart city projects on COVID-19 prevention and control.

IoT MEMS: IoT-Based Paradigm for Medical Equipment Management Systems of ICUs in Light of COVID-19 Outbreak

Recently, COVID-19 has infected a lot of people around the world. The healthcare systems are overwhelmed because of this virus. The intensive care unit (ICU) as a part of the healthcare sector has faced several challenges due to the poor information quality provided by current ICUs' medical equipment management. IoT has raised the ability for vital data transfer in the healthcare sector of the new century. However, most of the existing paradigms have adopted IoT technology to track patients' health statuses. Therefore, there is a lack of understanding on how to utilize such technology for ICUs' medical equipment management. This paper proposes a novel IoT-based paradigm called IoT Based Paradigm for Medical Equipment Management Systems (IoT MEMS) to manage medical equipment of ICUs efficiently. It employs IoT technology to enhance the information flow between medical equipment management systems (THIS) and ICUs during the COVID-19 outbreak to ensure the highest level of transparency and fairness in reallocating medical equipment. We described in detail the theoretical and practical aspects of IoT MEMS. Adopting IoT MEMS will enhance hospital capacity and capability in mitigating COVID-19 efficiently. It will also positively influence the information quality of (THIS) and strengthen trust and transparency among the stakeholders.

Nanobiotechnology as a platform for the diagnosis of COVID-19: a review

A sensitive method for diagnosing co ronavi rus d isease 2019 (COVID-19) is highly required to fight the current and future global health threats due to s evere a cute r espiratory s yndrome c oronavirus 2 (SARS-CoV 2). However, most of the current methods exhibited high false‐negative rates, resulting in patient misdiagnosis and impeding early treatment. Nanoparticles show promising performance and great potential to serve as a platform for diagnosing viral infection in a short time and with high sensitivity. This review highlighted the potential of nanoparticles as platforms for the diagnosis of COVID-19. Nanoparticles such as gold nanoparticles, magnetic nanoparticles, and graphene (G) were applied to detect SARS-CoV 2. They have been used for molecular-based diagnosis methods and serological methods. Nanoparticles improved specificity and shorten the time required for the diagnosis. They may be implemented into small devices that facilitate the self-diagnosis at home or in places such as airports and shops. Nanoparticles-based methods can be used for the analysis of virus-contaminated samples from a patient, surface, and air. The advantages and challenges were discussed to introduce useful information for designing a sensitive, fast, and low-cost diagnostic method. This review aims to present a helpful survey for the lesson learned from handling this outbreak to prepare ourself for future  pandemic.