A Review on the Mobile Applications Developed for COVID-19: An Exploratory Analysis

A Systematic Review of Cervical Cancer Mobile Applications and a Future Directions for Developers

OBJECTIVE

The objective of this study is to evaluate the quality of mobile health (mHealth) applications that promote cervical cancer awareness and provide screening assistance, with an emphasis on apps available on the Google Play Store and iOS.

METHODS

From December 2023 to February 2024, we assessed mobile applications focused on cervical cancer screening that are available on Google Play and Apple iTunes. The "Cervical Cancer," "Mobile Application," "Pap Test," "Cervical Cancer Guide," "Human Papillomavirus," plus "Cervical Screening are the keywords used to search the applications." Data collection includes features such as application name, pricing, download metrics, invention date, last update, affiliation, online access, login requirements, and notification functionality, which were gathered in Excel. Interrater reliability based on four reviewers' independent judgments, varied from 0.75 to 0.83.

RESULT

In our research, we found 25 apps (16 on the Google Play Store and 9 on iOS). After a thorough review, only 14 relevant apps were included. According to the MARS rating, Rise Against Cancer received the highest score (3.9), followed by FightHPV and Cervical Cancer Forum (3.8). Rise Against Cancer (29), HPV Vaccine (28), and CDC STI Tx Guidelines (28) scored highest in the APPLICATIONS rating system. Hope 4 All and OCI Cervibreast closely matched the statements, meeting seven of the thirteen requirements each.

CONCLUSION

Future app developers should produce user-friendly, often updated mHealth applications that include high-quality cervical cancer awareness and screening content. These apps should provide validated information and pleasant graphic effects.

The role of Contact-Tracing Mobile Apps in pandemic prevention: A multidisciplinary perspective on health beliefs, social, and technological factors

During the recent COVID-19 pandemic, governments implemented mobile applications for contact tracing as a rapid and effective solution to mitigate the spread of the virus. However, these seemingly straightforward solutions did not achieve their intended objectives. In line with previous research, this paper aims to investigate the factors that influence the acceptance and usage of contact-tracing mobile apps (CTMAs) in the context of disease control. The research model in this paper integrates the Unified Theory of Acceptance and Use of Technology and the Health Belief Model (HBM). The present study involved a diverse sample of 770 French participants of all genders, ages, occupations, and regions. Critical elements from the Health Belief Model, technological factors related to the app, and social factors, including the centrality of religiosity, were assessed using well-established measurement scales. The research's findings demonstrate that several factors, such as perceived benefits and perceived severity, social influence, health motivation, and centrality of religiosity, significantly impact the intention to use a CTMA. These findings suggest that CTMAs hold promise as valuable tools for managing future epidemics. However, addressing challenges, revising implementation strategies, and potentially collaborating with specialized industry partners under regulatory frameworks are crucial. This practical insight can guide policymakers and public health officials in their decision-making.

Artificial Intelligence-Based Facial Palsy Evaluation: A Survey

Facial palsy evaluation (FPE) aims to assess facial palsy severity of patients, which plays a vital role in facial functional treatment and rehabilitation. The traditional manners of FPE are based on subjective judgment by clinicians, which may ultimately depend on individual experience. Compared with subjective and manual evaluation, objective and automated evaluation using artificial intelligence (AI) has shown great promise in improving traditional manners and recently received significant attention. The motivation of this survey paper is mainly to provide a systemic review that would guide researchers in conducting their future research work and thus make automatic FPE applicable in real-life situations. In this survey, we comprehensively review the state-of-the-art development of AI-based FPE. First, we summarize the general pipeline of FPE systems with the related background introduction. Following this pipeline, we introduce the existing public databases and give the widely used objective evaluation metrics of FPE. In addition, the preprocessing methods in FPE are described. Then, we provide an overview of selected key publications from 2008 and summarize the state-of-the-art methods of FPE that are designed based on AI techniques. Finally, we extensively discuss the current research challenges faced by FPE and provide insights about potential future directions for advancing state-of-the-art research in this field.

A comprehensive survey on exploring and analyzing COVID-19 mobile apps: Meta and exploratory analysis

During the current COVID-19 pandemic, many digital solutions around the world have been proposed to cope with the deadly virus but the role of mobile-based applications is dominant one. In Pakistan, during the current COVID-19 pandemic, an array of mobile health applications (apps) and platforms have been launched to grapple with the impacts of the COVID-19 situation. In this survey, our major focus is to explore and analyze the starring role of mobile apps based on the features and functionalities to tackle the COVID-19 disease, particularly in Pakistan. In this study, over fifty (50) mobile apps have been scrapped from the well-known three different sources i.e. Google Play Store, iOS Play Store, and web source. We developed our own data set after searching through the different play stores. We have designed two criteria such that the first criteria are known as eligibility criteria, while the second one is known as assessment criteria. The features and functions of each mobile app are pinpointed and discussed against the parameters of the assessment criteria. The major parameters of assessment criteria are: (i) Home monitoring; (ii) COVID-19 awareness; (iii) contact tracing; (iv) telemedicine; (v) health education; (vi) COVID-19 surveillance; (vii) self-assessment; (viii) security; and (ix) accessibility. This study conducted exploratory analysis and quantitative meta-data analysis by adopting PRISMA guidelines. This survey article is not only discussing the function and features of each COVID-19-centered app in Pakistan, but it also sheds light on the limitations of every mobile app as well. The results of this survey might be helpful for the mobile developers to review the current app products and enhance the existing mobile platforms targeted towards the COVID-19 pandemic. This is the first attempt of its kind to present a state-of-the-art survey of the COVID-19-centered mobile health apps in Pakistan.

A Systematic Review of Health Management Mobile Applications in COVID-19 Pandemic: Features, Advantages, and Disadvantages

Introduction

With the increasing accessibility of smartphones, their use has been considered in healthcare services. Mobile applications have played a pivotal role in providing health services during COVID-19. This study is aimed at identifying the features, advantages, and disadvantages of health management mobile applications during COVID-19.

Methods

This systematic review was conducted in PubMed, Scopus, and Web of Science using the related keywords up to November 2021. The original articles in English about the health management mobile applications in COVID-19 were selected. The study selection was done by two researchers independently according to inclusion and exclusion criteria. Data extraction was done using a data extraction form, and the results were summarized and reported in related tables and figures.

Results

Finally, 12 articles were included based on the criteria. The benefits of mobile health applications for health management during COVID-19 were in four themes and 19 subthemes, and the most advantages of the application were in disease management and the possibility of recording information by users, digital tracking of calls, and data confidentiality. Furthermore, the disadvantages of them have been presented in two themes and 14 subthemes. The most common disadvantages are reduced adherence to daily symptom reports, personal interpretation of questions, and result bias.

Conclusion

The study results showed that mobile applications have been effective in controlling the prevalence of COVID-19 by identifying virus-infested environments, identifying and monitoring infected people, controlling social distancing, and maintaining quarantine. It is suggested that usability, ethical and security considerations, protection of personal information, and privacy of users be considered in application design and development.

Mobile Apps for COVID-19: A Systematic Review of Reviews

BACKGROUND

One measure national governments took to react to the acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) pandemic was mobile applications (apps). This study aims to provide a high-level overview of published reviews of mobile apps used in association with coronavirus disease 19 (COVID-19), examine factors that contributed to the success of these apps, and provide data for further research into this topic.

METHODS

We conducted a systematic review of reviews (also referred to as an umbrella review) and searched two databases, Medline and Embase, for peer-reviewed reviews of COVID-19 mobile apps that were written in English and published between January 1st 2020 and April 25th 2022.

RESULTS

Out of the initial 17,611 studies, 24 studies were eligible for the analysis. Publication dates ranged from May 2020 to January 2022. In total, 54% (n = 13) of the studies were published in 2021, and 33% (n = 8) were published in 2020. Most reviews included in our review of reviews analyzed apps from the USA, the UK, and India. Apps from most of the African and Middle and South American countries were not analyzed in the reviews included in our study. Categorization resulted in four clusters (app overview, privacy and security, MARS rating, and miscellaneous).

CONCLUSIONS

Our study provides a high-level overview of 24 reviews of apps for COVID-19, identifies factors that contributed to the success of these apps, and identifies a gap in the current literature. The study provides data for further analyses and further research.

Investigating Individuals' Preferences in Determining the Functions of Smartphone Apps for Fighting Pandemics: Best-Worst Scaling Survey Study

BACKGROUND

Smartphone apps have been beneficial in controlling and preventing the COVID-19 pandemic. However, there is a gap in research surrounding the importance of smartphone app functions from a user's perspective. Although the insights and opinions of different stakeholders, such as policymakers and medical professionals, can influence the success of a public health policy, any strategy will face difficulty in achieving the expected effect if it is not based on a method that users can accept.

OBJECTIVE

This study aimed to assess the importance of a hypothetical smartphone app's functions for managing health during a pandemic based on the perspective of user preferences.

METHODS

A cross-sectional and web-based survey using the best-worst scaling (BWS) method was used to investigate the general population's preferences for important smartphone app functions. Participants were recruited from a professional surveying company's web-based surveying panel. The attributes of the BWS questionnaire were developed based on a robust process, including literature review, interviews, and expert discussion. A balanced incomplete block design was used to construct the choice task to ensure the effectiveness of the research design. Count analysis, conditional logit model analysis, and mixed logit analysis were used to estimate preference heterogeneity among respondents.

RESULTS

The responses of 2153 participants were eligible for analysis. Nearly 55% (1192/2153) were female, and the mean age was 31.4 years. Most participants (1765/2153, 81.9%) had completed tertiary or higher education, and approximately 70% (1523/2153) were urban residents. The 3 most vital functions according to their selection were "surveillance and monitoring of infected cases," "quick self-screening," and "early detection of infected cases." The mixed logit regression model identified significant heterogeneity in preferences among respondents, and stratified analysis showed that some heterogeneities varied in respondents by demographics and COVID-19-related characteristics. Participants who preferred to use the app were more likely to assign a high weight to the preventive functions than those who did not prefer to use it. Conversely, participants who showed lower willingness to use the app tended to indicate a higher preference for supportive functions than those who preferred to use it.

CONCLUSIONS

This study ranks the importance of smartphone app features that provide health care services during a pandemic based on the general population's preferences in China. It provides empirical evidence for decision-makers to develop eHealth policies and strategies that address future public health crises from a person-centered care perspective. Continued use of apps and smart investment in digital health can help improve health outcomes and reduce the burden of disease on individuals and communities.

Exploring usability problems of mHealth applications developed for cervical cancer: An empirical study

Objectives

Nowadays, mobile health applications are developed to raise awareness and facilitate screening and treatment of cervical cancer, while a very few studies have been conducted focusing on the measurement and assurance of usability and exploring the acceptable user experience of such applications. Usability issues become a crucial concern for such cervical-cancer-related applications because users with diverse backgrounds in terms of education, information technology literacy, and geographic reasons are required to access those applications. The objective of this research is to evaluate the usability of mobile health applications developed for cervical cancer patients.

Methods

Two evaluation studies were conducted following the expert evaluation and a questionnaire-based user study. A total of four cervical-cancer-related applications that are focusing on the Awareness and Diagnosis theme were selected and each of the applications was evaluated by four usability experts. Then, a user study (n = 80) based on the Goal Question Metric was conducted to reveal the usability problems of four selected applications. Finally, findings of both evaluations were aggregated and analyzed.

Results

Both approaches showed that all applications suffer from several usability problems while "Cervical Cancer Guide" performs better and "Cervical Cancer Tracker" showed the least in performance from the usability perspective. Again, the Goal Question Metric performs noticeably better in assessing the learnability of the applications, while the analytical heuristic evaluation performs better in identifying the issues that cause user annoyance.

Conclusion

The methodology adopted and the usability problems revealed through this study can be well utilized by the information technology professionals or user interface designers for designing, evaluating, and developing the cervical-cancer-related applications with enhanced usability and user experience.

A Survey on harnessing the Applications of Mobile Computing in Healthcare during the COVID-19 Pandemic: Challenges and Solutions

The COVID-19 pandemic ravaged almost every walk of life but it triggered many challenges for the healthcare system, globally. Different cutting-edge technologies such as Internet of things (IoT), machine learning, Virtual Reality (VR), Big data, Blockchain etc. have been adopted to cope with this menace. In this regard, various surveys have been conducted to highlight the importance of these technologies. However, among these technologies, the role of mobile computing is of paramount importance which is not found in the existing literature. Hence, this survey in mainly targeted to highlight the significant role of mobile computing in alleviating the impacts of COVID-19 in healthcare sector. The major applications of mobile computing such as software-based solutions, hardware-based solutions and wireless communication-based support for diagnosis, prevention, self-symptom reporting, contact tracing, social distancing, telemedicine and treatment related to coronavirus are discussed in detailed and comprehensive fashion. A state-of-the-art work is presented to identify the challenges along with possible solutions in adoption of mobile computing with respect to COVID-19 pandemic. Hopefully, this research will help the researchers, policymakers and healthcare professionals to understand the current research gaps and future research directions in this domain. To the best level of our knowledge, this is the first survey of its type to address the COVID-19 pandemic by exploring the holistic contribution of mobile computing technologies in healthcare area.

Assessing the digital literacy levels of the community pharmacy workforce using a survey tool

OBJECTIVES

To investigate the digital literacy of staff in London, UK, community pharmacies and to explore their perceptions about the use of eHealth tools.

METHODS

The study population was community pharmacy staff (N = 21,346) in Greater London. A survey tool was divided into six sections: Use of the internet; Use of social media; Use of mobile health applications (MHAs); Perception of and practical use of digital health tools; Scenario-based questions and demographics. Responses were analysed in SPSS. Following data collection, Health Education England's (HEE's) Digital Capabilities Framework (DCF) was published. The authors mapped the survey tool retrospectively to the framework.

KEY FINDINGS

Almost all respondents (98.0%, n = 551/562) used eHealth tools at work, mainly to access medicine information (89.8%, n = 495/551). Almost one-third (31.7%, N = 178/562) used social media regularly, while many (79.4%, N = 446/562) were aware of MHAs. Self-perceived digital literacy indicated that 63.3% (n = 356/562) deemed themselves to be above average. Under 35s rated their digital literacy more highly than over 35s (P < 0.001). HEE's DCF indicated that actual digital literacy was lower than that of self-perceived. Despite the high use of eHealth tools, respondents were reluctant to recommend these to the public for health advice.

CONCLUSIONS

Community pharmacy staff self-report their digital literacy to be high yet do not use these skills for public health purposes. Furthermore, these self-reported skills appear to be over-estimated. Despite high levels of use of digital tools at work, staff do not use them for public health, therefore, further training to build confidence to better utilise them is recommended.

The impact of COVID-19 safety interventions on creating a controlled environment on campus

Objectives

During COVID-19 the re-opening of educational institutes was frequently debated, however with the decline in the number of COVID-19 cases, The Aga Khan University (AKU) in Karachi, Pakistan opened its campus for medical and nursing students after more than 6 months of closure. To ensure gradual resumption of activities on-campus, a combination of interventions was diligently deployed to minimize student infection rates. Scarce literature exists on students' perceptions regarding decisions implemented by university leadership. The aim of the study was to determine the efficacy of these interventions.

Methods

We conducted a convergent, parallel, mixed-methods observational study targeting medical and nursing students. An online questionnaire was disseminated to elicit students' degree of (dis)agreement on a four-point Likert scale. Focused group discussions (FGDs) were conducted to comprehend reasons for (dis)agreement.

Results

Total of 183 students responded to questionnaire (59.0% nursing, 67.8% female), 11 FGDs were conducted with 85 students. Interventions with highest agreement were mandatory face masks policy (94.54%), weekly mandated COVID-testing (92.35%) and students' Academic Bubble (91.26%); highest disagreement was for Sehat Check application (41.53%); and stay strong campaign (40.44%). Four themes emerged from FGDs: Effective safety interventions, Safety interventions with limited effectiveness, Utility of Sehat Check Application and Future recommendations for informing policy.

Conclusion

It is paramount to seek student-feedback at forefront of university re-opening strategy. Clear communication channels are as important as an administrative response system's robustness. Bidirectional communication channels are fundamental and requisite during ever-changing policies and regulations. Engaging student representatives in decision making or implementation processes (such as "pilot" before "roll-out") would allow any potential issues to be managed early on. Gather real-time anonymous feedback and identify key areas that need further promulgation and those that need to be replaced with more effective ones.

Development of a Mobile App for Self-Care Against COVID-19 Using the Analysis, Design, Development, Implementation, and Evaluation (ADDIE) Model: Methodological Study

Background

Mobile apps have been shown to play an important role in the management, care, and prevention of infectious diseases. Thus, skills for self-care—one of the most effective ways to prevent illness—can be improved through mobile health apps.

Objective

This study aimed to design, develop, and evaluate an educational mobile-based self-care app in order to help the self-prevention of COVID-19 in underdeveloped countries. We intended the app to be easy to use, quick, and inexpensive.

Methods

In 2020 and 2021, we conducted a methodological study. Using the ADDIE (analysis, design, development, implementation, and evaluation) educational model, we developed a self-care management mobile app. According to the ADDIE model, an effective training and performance support tool is built through the 5 phases that comprise its name. There were 27 participants who conducted 2 evaluations of the mobile app’s usability and impact using the mobile health app usability and self-care inventory scales. The study design included pre- and posttesting.

Results

An Android app called MyShield was developed. The results of pre- and posttests showed that on a scale from 0 to 5, MyShield scored a performance average of 4.17 in the physical health dimension and an average of 3.88 in the mental well-being dimension, thereby showing positive effects on self-care skills. MyShield scored highly on the “interface and satisfaction,” “ease of use,” and “usefulness” components.

Conclusions

MyShield facilitates learning self-care skills at home, even during quarantine, increasing acquisition of information. Given its low development cost and the ADDIE educational design on which it is based, the app can be helpful in underdeveloped countries. Thus, low-income countries—often lacking other tools—can use the app as an effective tool for fighting COVID-19, if it becomes a standard mobile app recommended by the government.

Designing evaluation framework for the empirical assessment of COVID-19 mobile apps in Pakistan

The significant proliferation in the mobile health applications (Apps) amidst Coronaviruses disease 2019 (COVID-19) resulted in decision making problems for healthcare professionals, decision makers and mobile users in Pakistan. This decision making process is also hampered by mobile app trade-offs, multiple features support, evolving healthcare needs and varying vendors. In this regard, evaluation model for mobile apps is presented which completes in three different phases. In first phase, features-based criteria is designed by leveraging Delphi method, and twenty (20) mobile apps are selected from app stores. In second stage, empirical evaluation is performed by using hybrid multi criteria decision approaches like CRiteria Importance Through Inter-criteria Correlation (CRITIC) method has been used for assigning weights to criteria features; and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method has been used for assessment of mobile app alternatives. In last step, decision making is performed to select the best mobile app for COVID-19 situations. The results suggest that proposed model can be adopted as a guideline by mobile app subscribers, patients and healthcare professionals.

COVID-19 Mobile Health Apps: An Overview of Mobile Applications in Indonesia

Background

Mobile health applications (mHealth apps) have been widely used for various purposes for mitigating the COVID-19 pandemic, such as self-assessment, contact tracing, disseminating information, minimizing exposure, and reducing face-to-face health consultation. The objective of this study is to systematically review COVID-19 related mHealth apps and highlight gaps to inform the development of future mHealth initiatives in Indonesia.

Methods

A systematic search strategy using a PRISMA flowchart was used to identify mHealth apps available in Google Play and Apple Play stores. We searched mHealth apps using certain specific terms related to COVID-19 outbreaks. The inclusion criteria were apps-based smartphone users related to COVID-19 using local language, free of cost, available in the Google Play and Apple Play Stores, and supported by the Indonesian government. We excluded games, apps on infectious diseases unrelated to COVID-19 specifically, and apps with non-Bahasa Indonesia (Indonesian language). The selected mHealth apps were assessed based on two measures: (1) the WHO guidelines on digital health intervention and (2) the four dimensions of the mHealth technology fit framework. In addition, user feedback from experienced and non-experienced users was conducted to evaluate four dimensions of the apps.

Results

A total of 339 mHealth apps were generated from the initial search, remaining seven selected apps that met inclusion criteria. The results highlighted that mHealth apps reviewed had still not been widely used by the general public. The applications were purposed to disseminate information, conduct a self-risk assessment, provide an online community forum, and telemedicine or teleconsultation regarding COVID-19. Data services, including data storage, aggregation, and data exchange, are available in most apps. The rarest function found was contact tracing and assisting health management and health workers, such as the availability of testing facilities, reporting test results, and prescribing medication. The main issues reported were the lack of data security and data privacy protection, integration and infrastructures, usability, and usefulness.

Conclusion

Our study highlighted the necessity to improve mHealth apps' functions related to assisting health workers and the function of digital contact tracing. An effort to increase public awareness regarding the use of mHealth is also necessary to streamline the function of this innovation. Policymakers must consider usefulness, usability, integration, and infrastructure issues to improve their mHealth function.

A Comprehensive Review of Artificial Intelligence in Prevention and Treatment of COVID-19 Pandemic

The unprecedented outbreak of the Corona Virus Disease 2019 (COVID-19) pandemic has seriously affected numerous countries in the world from various aspects such as education, economy, social security, public health, etc. Most governments have made great efforts to control the spread of COVID-19, e.g., locking down hard-hit cities and advocating masks for the population. However, some countries and regions have relatively poor medical conditions in terms of insufficient medical equipment, hospital capacity overload, personnel shortage, and other problems, resulting in the large-scale spread of the epidemic. With the unique advantages of Artificial Intelligence (AI), it plays an extremely important role in medical imaging, clinical data, drug development, epidemic prediction, and telemedicine. Therefore, AI is a powerful tool that can help humans solve complex problems, especially in the fight against COVID-19. This study aims to analyze past research results and interpret the role of Artificial Intelligence in the prevention and treatment of COVID-19 from five aspects. In this paper, we also discuss the future development directions in different fields and prove the validity of the models through experiments, which will help researchers develop more efficient models to control the spread of COVID-19.

Factors Influencing the Perceived Effectiveness of COVID-19 Risk Assessment Mobile Application "MorChana" in Thailand: UTAUT2 Approach

COVID-19 contact-tracing mobile applications have been some of the most important tools during the COVID-19 pandemic. One preventive measure that has been incorporated to help reduce the virus spread is the strict implementation of utilizing a COVID-19 tracing application, such as the MorChana mobile application of Thailand. This study aimed to evaluate the factors affecting the actual usage of the MorChana mobile application. Through the integration of Protection Motivation Theory (PMT) and Unified Theory of Acceptance and Use of Technology (UTAUT2), latent variables such as performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating conditions (FC), hedonic motivation (HM), habit (HB), perceived risk (PCR), self-efficacy (SEF), privacy (PR), trust (TR), and understanding COVID-19 (U) were considered to measure the intention to use MorChana (IU) and the actual usage (AU) of the mobile application. This study considered 907 anonymous participants who voluntarily answered an online self-administered survey collected via convenience sampling. The results show that IU presented the highest significant effect on AU, followed by HB, HM, PR, FC, U, SEF, PE, EE, TR, and SI. This is evident due to the strict implementation of using mobile applications upon entering any area of the vicinity. Moreover, PCR was not seen to be a significant latent factor affecting AU. This study is the first to have evaluated mobile contact tracing in Thailand. The integrated framework can be applied and extended to determine factors affecting COVID-19 tracing applications in other countries. Moreover, the findings of this study could be applied to other health-related mobile applications worldwide.

The medical and societal impact of big data analytics and artificial intelligence applications in combating pandemics: A review focused on Covid-19

With Covid-19 impacting communities in different ways, research has increasingly turned to big data analytics (BDA) and artificial intelligence (AI) tools to track and monitor the virus's spread and its effect on humanity and the global economy. The purpose of this study is to conduct an in-depth literature review to identify how BDA and AI were involved in the management of Covid-19 (while considering diversity, equity, and inclusion (DEI)). The rigorous search resulted in a portfolio of 607 articles, retrieved from the Web of Science database, where content analysis has been conducted. This study identifies the BDA and AI applications developed to deal with the initial Covid-19 outbreak and the containment of the pandemic, along with their benefits for the social good. Moreover, this study reveals the DEI challenges related to these applications, ways to mitigate the concerns, and how to develop viable techniques to deal with similar crises in the future. The article pool recognized the high presence of machine learning (ML) and the role of mobile technology, social media and telemedicine in the use of BDA and AI during Covid-19. This study offers a collective insight into many of the key issues and underlying complexities affecting public health and society from Covid-19, and the solutions offered from information systems and technological perspectives.

COVID-19 Mobile Apps in Saudi Arabia: Systematic Identification, Evaluation, and Features Assessment

Background

The coronavirus disease 2019 (COVID-19) pandemic is the greatest global health threat in our century at the moment, and the use of mobile health apps has been one digital healthcare strategy adopted for coping with this outbreak.

Objective

This study aims to identify and explore the mobile applications that are currently being utilized for dealing with COVID-19 in Saudi Arabia.

Methods

The applications were selected based on the (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) PRISMA guidelines, then the functionalities were extracted based on the COVID-19 application mind map. Finally, the quality of the apps was assessed using the Mobile Application Rating Scale (MARS) for overall quality, satisfaction, engagement, functionality, aesthetics, and information.

Results

The search identified six applications that were currently being used for COVID-19 which provided the following functionalities: self-assessment, self-isolation, permit for car mobility, prevention guidelines, COVID-19 lab results, call support, identifying nearby facilities, reporting suspected cases, and booking clinic appointments and the COVID-19 test. The findings showed that while most of these features were provided by multiple apps, on the MARS, the overall scores ranged from 3.26 to 3.69 with the apps scoring lower in the areas of satisfaction and engagement and higher in functionalities.

Conclusion

Further steps are needed to unify all these functions in one health app to enhance the users' experience.

A framework for information technology-based management against COVID-19 in Iran

BACKGROUND

The COVID-19 pandemic has become a global concern. Iran is one of the countries affected most by the SARS-CoV-2 outbreak. As a result, the use of information technology (IT) has a variety of applications for pandemic management. The purpose of this study was to develop a conceptual framework for responding to the COVID-19 pandemic via IT management, based on extensive literature review and expert knowledge.

METHODS

The conceptual framework is developed in three stages: (1) a literature review to gather practical experience with IT applications for managing the COVID-19 pandemic, (2) a study of Iranian documents and papers that present Iran's practical experience with COVID-19, and (3) developing a conceptual framework based on the previous steps and validating it through a Delphi approach in two rounds, and by 13 experts.

RESULTS

The proposed conceptual framework demonstrates that during pandemics, 22 different types of technologies were used for various purposes, including virtual education, early warning, rapid screening and diagnosis of infected individuals, and data management. These objectives were classified into six categories, with the following applications highlighted: (1) Prevention (M-health, Internet search queries, telehealth, robotics, Internet of things (IoT), Artificial Intelligence (AI), big data, Virtual Reality (VR), social media); (2) Diagnosis (M-health, drones, telehealth, IoT, Robotics, AI, Decision Support System (DSS), Electronic Health Record (EHR)); (3) Treatment (Telehealth, M-health, AI, Robotic, VR, IoT); (4) Follow-up (Telehealth, M-health, VR), (5) Management & planning (Geographic information system, M-health, IoT, blockchain), and (6) Protection (IoT, AI, Robotic and automatic vehicles, Augmented Reality (AR)). In Iran, the use of IT for prevention has been emphasized through M-health, internet search queries, social media, video conferencing, management and planning objectives using databases, health information systems, dashboards, surveillance systems, and vaccine coverage.

CONCLUSIONS

IT capabilities were critical during the COVID-19 outbreak. Practical experience demonstrates that various aspects of information technologies were overlooked. To combat this pandemic, the government and decision-makers of this country should consider strategic planning that incorporates successful experiences against COVID-19 and the most advanced IT capabilities.

Data privacy during pandemics: a systematic literature review of COVID-19 smartphone applications

BACKGROUND

On January 8, 2020, the Centers for Disease Control and Prevention officially announced a new virus in Wuhan, China. The first novel coronavirus (COVID-19) case was discovered on December 1, 2019, implying that the disease was spreading quietly and quickly in the community before reaching the rest of the world. To deal with the virus' wide spread, countries have deployed contact tracing mobile applications to control viral transmission. Such applications collect users' information and inform them if they were in contact with an individual diagnosed with COVID-19. However, these applications might have affected human rights by breaching users' privacy.

METHODOLOGY

This systematic literature review followed a comprehensive methodology to highlight current research discussing such privacy issues. First, it used a search strategy to obtain 808 relevant papers published in 2020 from well-established digital libraries. Second, inclusion/exclusion criteria and the snowballing technique were applied to produce more comprehensive results. Finally, by the application of a quality assessment procedure, 40 studies were chosen.

RESULTS

This review highlights privacy issues, discusses centralized and decentralized models and the different technologies affecting users' privacy, and identifies solutions to improve data privacy from three perspectives: public, law, and health considerations.

CONCLUSIONS

Governments need to address the privacy issues related to contact tracing apps. This can be done through enforcing special policies to guarantee users privacy. Additionally, it is important to be transparent and let users know what data is being collected and how it is being used.

Understanding the Impact of Digital Health Strategies During the COVID-19 Outbreak in Saudi Arabia

BACKGROUND

The impact of COVID-19 has been analyzed from various aspects on the health care services management, accessibility and delivery of health care services. However, the COVID-19 pandemic has led to disruptions in health care services, which led to the increase in adoption of digital health technologies, mostly arising out of need and necessity.

OBJECTIVE

Focusing on the prevailing situations (increasing reliance on digital health services), this study investigates the impact of digital health technologies from the perspectives of policymakers and citizens.

METHODS

A mixed-methods approach was adopted. Twenty-seven semi-structured online interviews were conducted with experts and policymakers for assessing the impact from policymakers' perspectives. An online survey questionnaire instrument was used to collect the responses from 1698 Saudi Arabian citizens in relation to the various aspects of digital health applications.

RESULTS

Health care expenditures increased during the COVID-19 outbreak, resulting in launch of various digital health applications. While policymakers defended their stand in improving health care services and accessibility; citizens reflected inability to book medicines/personal medical equipment online (Mean=2.4) and suffered a lack of personalized care (Mean=2.9) through digital health applications. Moreover, disparities exist between the population groups with respect to the accessibility, utilization, and perceptions of digital health technologies.

CONCLUSION

Policymakers have to consider and address these differences in formulating digital health policies and implementing them.

Identifying data elements and key features of a mobile-based self-care application for patients with COVID-19 in Iran

Mobile Health applications have shown different usages in the COVID-19 pandemic, which consisted of empowering patient's awareness, promoting patient's self-care, and self-monitor behaviors. The purpose of this study is to identify key features and capabilities of a mobile-based application for self-care and self-management of people with COVID-19 disease. This study was a descriptive-analytical study that was conducted in two main phases in 2020. In the first phase, a literature review study was performed. In the second phase, using the information obtained from the review of similar articles, a questionnaire was designed to validate identified requirements. Based on the results of the first phase, 53 data elements and technical key features for mobile-based self-care application for people with COVID-19 were identified. According to the statistical population, 11 data elements for demographic requirements, 11 data elements for clinical requirements, 15 data elements for self-care specifications, and 16 features for the technical capability of this app were determined. Most of the items were selected by infectious and internal medicine specialists (94%). This study supports that the use of mobile-based applications can play an important role in the management of this disease. Software design and development could help manage and improve patients' health status.

Can technological advancements help to alleviate COVID-19 pandemic? a review

The COVID-19 pandemic is continuing, and the innovative and efficient contributions of the emerging modern technologies to the pandemic responses are too early and cannot be completely quantified at this moment. Digital technologies are not a final solution but are the tools that facilitate a quick and effective pandemic response. In accordance, mobile applications, robots and drones, social media platforms (such as search engines, Twitter, and Facebook), television, and associated technologies deployed in tackling the COVID-19 (SARS-CoV-2) outbreak are discussed adequately, emphasizing the current-state-of-art. A collective discussion on reported literature, press releases, and organizational claims are reviewed. This review addresses and highlights how these effective modern technological solutions can aid in healthcare (involving contact tracing, real-time isolation monitoring/screening, disinfection, quarantine enforcement, syndromic surveillance, and mental health), communication (involving remote assistance, information sharing, and communication support), logistics, tourism, and hospitality. The study discusses the benefits of these digital technologies in curtailing the pandemic and 'how' the different sectors adapted to these in a shorter period. Social media and television's role in ensuring global connectivity and serving as a common platform to share authentic information among the general public were summarized. The World Health Organization and Governments' role globally in-line with the prevention of propagation of false news, spreading awareness, and diminishing the severity of the COVID-19 was discussed. Furthermore, this collective review is helpful to investigators, health departments, Government organizations, and policymakers alike to facilitate a quick and effective pandemic response.

A Systematic Review on the Use of AI and ML for Fighting the COVID-19 Pandemic

Artificial intelligence (AI) and machine learning (ML) have caused a paradigm shift in healthcare that can be used for decision support and forecasting by exploring medical data. Recent studies have shown that AI and ML can be used to fight COVID-19. The objective of this article is to summarize the recent AI- and ML-based studies that have addressed the pandemic. From an initial set of 634 articles, a total of 49 articles were finally selected through an inclusion-exclusion process. In this article, we have explored the objectives of the existing studies (i.e., the role of AI/ML in fighting the COVID-19 pandemic); the context of the studies (i.e., whether it was focused on a specific country-context or with a global perspective; the type and volume of the dataset; and the methodology, algorithms, and techniques adopted in the prediction or diagnosis processes). We have mapped the algorithms and techniques with the data type by highlighting their prediction/classification accuracy. From our analysis, we categorized the objectives of the studies into four groups: disease detection, epidemic forecasting, sustainable development, and disease diagnosis. We observed that most of these studies used deep learning algorithms on image-data, more specifically on chest X-rays and CT scans. We have identified six future research opportunities that we have summarized in this paper. Impact Statement: Artificial intelligence (AI) and machine learning(ML) methods have been widely used to assist in the fight against COVID-19 pandemic. A very few in-depth literature reviews have been conducted to synthesize the knowledge and identify future research agenda including a previously published review on data science for COVID-19 in this article. In this article, we synthesized reviewed recent literature that focuses on the usages and applications of AI and ML to fight against COVID-19. We have identified seven future research directions that would guide researchers to conduct future research. The most significant of these are: develop new treatment options, explore the contextual effect and variation in research outcomes, support the health care workforce, and explore the effect and variation in research outcomes based on different types of data.

Machine Learning for Mortality Analysis in Patients with COVID-19

This paper analyzes a sample of patients hospitalized with COVID-19 in the region of Madrid (Spain). Survival analysis, logistic regression, and machine learning techniques (both supervised and unsupervised) are applied to carry out the analysis where the endpoint variable is the reason for hospital discharge (home or deceased). The different methods applied show the importance of variables such as age, O2 saturation at Emergency Rooms (ER), and whether the patient comes from a nursing home. In addition, biclustering is used to globally analyze the patient-drug dataset, extracting segments of patients. We highlight the validity of the classifiers developed to predict the mortality, reaching an appreciable accuracy. Finally, interpretable decision rules for estimating the risk of mortality of patients can be obtained from the decision tree, which can be crucial in the prioritization of medical care and resources.

Novel Coronavirus Cough Database: NoCoCoDa

The current pandemic associated with the novel coronavirus (COVID-19) presents a new area of research with its own set of challenges. Creating unobtrusive remote monitoring tools for medical professionals that may aid in diagnosis, monitoring and contact tracing could lead to more efficient and accurate treatments, especially in this time of physical distancing. Audio based sensing methods can address this by measuring the frequency, severity and characteristics of the COVID-19 cough. However, the feasibility of accumulating coughs directly from patients is low in the short term. This article introduces a novel database (NoCoCoDa), which contains COVID-19 cough events obtained through public media interviews with COVID-19 patients, as an interim solution. After manual segmentation of the interviews, a total of 73 individual cough events were extracted and cough phase annotation was performed. Furthermore, the COVID-19 cough is typically dry but can present as a more productive cough in severe cases. Therefore, an investigation of cough sub-type (productive vs. dry) of the NoCoCoDa was performed using methods previously published by our research group. Most of the NoCoCoDa cough events were recorded either during or after a severe period of the disease, which is supported by the fact that 77% of the COVID-19 coughs were classified as productive based on our previous work. The NoCoCoDa is designed to be used for rapid exploration and algorithm development, which can then be applied to more extensive datasets and potentially real time applications. The NoCoCoDa is available for free to the research community upon request.