COVID-19 Mobile Positioning Data Contact Tracing and Patient Privacy Regulations: Exploratory Search of Global Response Strategies and the Use of Digital Tools in Nigeria

Mobile Phone Network Data in the COVID-19 era: A systematic review of applications, socioeconomic factors affecting compliance to non-pharmaceutical interventions, privacy implications, and post-pandemic economic recovery strategies

BACKGROUND

The use of traditional mobility datasets, such as travel surveys and census data, has significantly impacted various disciplines, including transportation, urban sensing, criminology, and healthcare. However, because these datasets represent only discrete instances of measurement, they miss continuous temporal shifts in human activities, failing to record the majority of human mobility patterns in real-time. Bolstered by the rapid expansion of telecommunication networks and the ubiquitous use of smartphones, mobile phone network data (MPND) played a pivotal role in fighting and controlling the spread of COVID-19.

METHODS

We conduct an extensive review of the state-of-the-art and recent advancements in the application of MPND for analyzing the early and post-stages of the COVID-19 pandemic, following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Additionally, we evaluate and assess the included studies using the Mixed Methods Appraisal Tool (MMAT) and the Critical Appraisal Skills Programme (CASP). Furthermore, we apply bibliometric analysis to visualize publication structures, co-authorship networks, and keyword co-occurrence networks.

RESULTS

After the full-text screening process against the inclusion and exclusion criteria, our systematic literature review identified 55 studies that utilized MPND in the context of the COVID-19 pandemic: 46 (83.6%) were quantitative, and 9 (16.4%) were qualitative. These quantitative studies can be classified into five main groups: monitoring and tracking of human mobility patterns (n = 11), investigating the correlation between mobility patterns and the spread of COVID-19 (n = 7), analyzing the recovery of economic activities and travel patterns (n = 5), assessing factors associated with NPI compliance (n = 5), and investigating the impact of COVID-19 lockdowns and non-pharmaceutical interventions (NPI) measures on human behaviors, urban dynamics, and economic activity (n = 18). In addition, our findings indicate that NPI measures had a significant impact on reducing human movement and dynamics. However, demographics, political party affiliation, socioeconomic inequality, and racial inequality had a significant impact on population adherence to NPI measures, which could increase disease spread and delay social and economic recovery.

CONCLUSION

The usage of MPND for monitoring and tracking human activities and mobility patterns during the COVID-19 pandemic raises privacy implications and ethical concerns. Thus, striking a balance between meeting the ethical requirements and maintaining privacy risks should be further discovered and investigated in the future.

Development of a health-tracking tool for the Brazilian population: a pilot study with Brazilian women

BACKGROUND

Mobile apps can promote different behavioral interventions, thus decreasing preventable health problems. Challenges persist in ensuring the quality and reliability of these applications, as few have undergone rigorous scientific evaluation. Additionally, few scientifically validated questionnaires on well-being, adapted for the general public, are available in the literature. The objective of this study was to test and validate a general health assessment instrument based on questionnaires available in the literature, previously validated for the Brazilian population.

METHODS

The tracking tool was tested with healthy women, 18 to 50 years old. The instrument was constructed as a 29-question online form comprising 5 main clusters or "pillars" of individual health: general health, diet and nutrition, movement and activity, sleep, and mental health. The original and adapted versions of two sections (Sleep and Mental Health) were applied in a subsample of participants to compare intra-individual variability. Data from the "Mental Health" and "Sleep" sections were rigorously tested for normality and Pearson's correlation test was performed to compare the results of the original and adapted versions intra-individually. Chi-Square and McNemar tests were employed to pair categorical data and account for correspondence between the answers to the two forms of the questionnaires.

RESULTS

Seventy-one women answered the instrument with the proposed adapted versions of the questionnaires. The average completion time was between 12-20 min. The mean scores of the diet, movement, and general health questionnaires were similar to those of the original questionnaires from which questions were taken. The "Sleep" and "Mental Health" exhibited intra-individual divergences concerning the classification of results. The correlation between the original and adapted versions was improved after revising some of the questions (r = 0.9287; p < 0.0001).

CONCLUSION

The results of the present study demonstrate that this adapted instrument is valid and reliable for assessing the intended five pillars of health. Studies with larger sample sizes and other populations are encouraged.

Inter-relationships among individual views of COVID-19 control measures across multi-cultural contexts

Individual-level georeferenced data have been widely used in COVID-19 control measures around the world. Recent research observed that there is a trade-off relationship between people's privacy concerns and their acceptance of these control measures. However, whether this trade-off relationship exists across different cultural contexts is still unaddressed. Using data we collected via an international survey (n = 4260) and network analysis, our study found a substantial trade-off inter-relationship among people's privacy concerns, perceived social benefits, and acceptance across different control measures and study areas. People's privacy concerns in culturally tight societies (e.g., Japan) have the smallest negative impacts on their acceptance of pandemic control measures. The results also identify people's key views of specific control measures that can influence their views of other control measures. The impacts of these key views are heightened among participants with a conservative political view, high levels of perceived social tightness, and vertical individualism. Our results indicate that cultural factors are a key mechanism that mediate people's privacy concerns and their acceptance of pandemic control measures. These close inter-relationships lead to a double-edged sword effect: the increased positive impacts of people's acceptance and perceived social benefits also lead to increased negative impacts of privacy concerns in different combinations of control strategies. The findings highlight the importance of cultural factors as key determinants that affect people's acceptance or rejection of specific pandemic control measures.

Development and Usability Evaluation of COVID-Iran: A Mobile Application for Mitigating COVID-19 Misinformation

OBJECTIVES

The spread of misinformation through the internet can lead to dangerous behavioral changes and erode trust in reliable sources, especially during public health crises like coronavirus disease 2019 (COVID-19). To combat this issue, innovative strategies that leverage information technology are essential. This study focused on developing and evaluating a mobile application (app), COVID-Iran, aimed at countering COVID-19 misinformation by delivering accurate, reliable, and credible information.

METHODS

The development of the app involved a multi-step, user-centered approach that integrated qualitative expert consultations with quantitative survey research to pinpoint and validate key features. The app was initially prototyped using Enterprise Architect software and subsequently developed using Android Studio and MySQL. We conducted a usability evaluation using the System Usability Scale (SUS), where participants engaged in various tasks related to information seeking, self-assessment, and health management. Data were analyzed using descriptive statistics in SPSS version 19.

RESULTS

The findings revealed a high usability level (SUS score of 81.35), with participants reporting ease of use and learnability. The app effectively countered misinformation by providing access to trusted sources and evidence-based counterarguments. User feedback emphasized the app's strengths in clarity, accuracy, trustworthiness, and its comprehensive approach. Plans for future improvements include the integration of artificial intelligence to deliver personalized content.

CONCLUSIONS

Despite limitations such as the small sample size and potential self-selection bias, this study highlights the significant potential of mHealth apps to provide reliable health information and combat misinformation.

Short- and Long-Term Predicted and Witnessed Consequences of Digital Surveillance During the COVID-19 Pandemic: Scoping Review

BACKGROUND

The COVID-19 pandemic has prompted the deployment of digital technologies for public health surveillance globally. The rapid development and use of these technologies have curtailed opportunities to fully consider their potential impacts (eg, for human rights, civil liberties, privacy, and marginalization of vulnerable groups).

OBJECTIVE

We conducted a scoping review of peer-reviewed and gray literature to identify the types and applications of digital technologies used for surveillance during the COVID-19 pandemic and the predicted and witnessed consequences of digital surveillance.

METHODS

Our methodology was informed by the 5-stage methodological framework to guide scoping reviews: identifying the research question; identifying relevant studies; study selection; charting the data; and collating, summarizing, and reporting the findings. We conducted a search of peer-reviewed and gray literature published between December 1, 2019, and December 31, 2020. We focused on the first year of the pandemic to provide a snapshot of the questions, concerns, findings, and discussions emerging from peer-reviewed and gray literature during this pivotal first year of the pandemic. Our review followed the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) reporting guidelines.

RESULTS

We reviewed a total of 147 peer-reviewed and 79 gray literature publications. Based on our analysis of these publications, we identified a total of 90 countries and regions where digital technologies were used for public health surveillance during the COVID-19 pandemic. Some of the most frequently used technologies included mobile phone apps, location-tracking technologies, drones, temperature-scanning technologies, and wearable devices. We also found that the literature raised concerns regarding the implications of digital surveillance in relation to data security and privacy, function creep and mission creep, private sector involvement in surveillance, human rights, civil liberties, and impacts on marginalized groups. Finally, we identified recommendations for ethical digital technology design and use, including proportionality, transparency, purpose limitation, protecting privacy and security, and accountability.

CONCLUSIONS

A wide range of digital technologies was used worldwide to support public health surveillance during the COVID-19 pandemic. The findings of our analysis highlight the importance of considering short- and long-term consequences of digital surveillance not only during the COVID-19 pandemic but also for future public health crises. These findings also demonstrate the ways in which digital surveillance has rendered visible the shifting and blurred boundaries between public health surveillance and other forms of surveillance, particularly given the ubiquitous nature of digital surveillance.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-https://doi.org/10.1136/bmjopen-2021-053962.

Effectiveness and intention to use a COVID-19 self-management app for epidemiological investigation: a web-based survey study

Introduction

Numerous COVID-19-related apps were widely used during the COVID-19 pandemic. Among them, those supporting epidemiological investigations were particularly useful. This study explored the effectiveness of apps that support epidemiological investigations, factors influencing users' intention to use them, and ways to encourage their use.

Methods

We developed and evaluated the KODARI app to demonstrate its importance in epidemiological investigations. After adapting a questionnaire based on an existing evaluation framework for COVID-19-related apps, we collected data from 276 participants through an online survey conducted between April 28 and May 25, 2023. We conducted two independent sample t-tests to determine the differences between each variable according to demographic characteristics and a multiple regression analysis to identify factors affecting intention to use.

Results

Users were generally satisfied with the KODARI. We observed differences in sex, age, marital status, occupational characteristics, and experience with epidemiological investigation. Females rated the app's information accuracy higher than males. Males had a higher intention to use than females. Participants aged under 35 years rated information accuracy and transparency highly, whereas single participants rated information accuracy higher than married participants. Occupational groups with frequent interactions with others evaluated their self-determination regarding the application. The app's self-determination was highly valued among participants with experience in epidemiological investigations. By investigating the factors affecting the intention to use the app, we confirmed that effectiveness, self-determination, and usability significantly affected the intention to use.

Discussion

This study demonstrated the effectiveness of app supporting epidemiological investigations, identified meaningful factors that influence intention to use, and confirmed the applicability of our new framework by considering the specificity of infectious disease situations such as COVID-19. This study provides a new basis for future epidemiological studies.

People's political views, perceived social norms, and individualism shape their privacy concerns for and acceptance of pandemic control measures that use individual-level georeferenced data

BACKGROUND

As the COVID-19 pandemic became a major global health crisis, many COVID-19 control measures that use individual-level georeferenced data (e.g., the locations of people's residences and activities) have been used in different countries around the world. Because these measures involve some disclosure risk and have the potential for privacy violations, people's concerns for geoprivacy (locational privacy) have recently heightened as a result, leading to an urgent need to understand and address the geoprivacy issues associated with COVID-19 control measures that use data on people's private locations.

METHODS

We conducted an international cross-sectional survey in six study areas (n = 4260) to examine how people's political views, perceived social norms, and individualism shape their privacy concerns, perceived social benefits, and acceptance of ten COVID-19 control measures that use individual-level georeferenced data. Multilevel linear regression models were used to examine these effects. We also applied multilevel structure equation models (SEMs) to explore the direct, indirect, and mediating effects among the variables.

RESULTS

We observed a tradeoff relationship between people's privacy concerns and the acceptance (and perceived social benefits) of the control measures. People's perceived social tightness and vertical individualism are positively associated with their acceptance and perceived social benefits of the control measures, while horizontal individualism has a negative association. Further, people with conservative political views and high levels of individualism (both vertical and horizontal) have high levels of privacy concerns.

CONCLUSIONS

Our results first suggest that people's privacy concerns significantly affect their perceived social benefits and acceptance of the COVID-19 control measures. Besides, our results also imply that strengthening social norms may increase people's acceptance and perceived social benefits of the control measures but may not reduce people's privacy concerns, which could be an obstacle to the implementation of similar control measures during future pandemics. Lastly, people's privacy concerns tend to increase with their conservatism and individualism.

Facilitators and barriers of mHealth interventions during the Covid-19 pandemic: systematic review

BACKGROUND

With the spread of Covid-19 disease, health interventions related to the control, prevention, and treatment of this disease and other diseases were given real attention. The purpose of this systematic review is to express facilitators and barriers of using mobile health (mHealth) interventions during the Covid-19 pandemic.

METHODS

In this systematic review, original studies were searched using keywords in the electronic database of PubMed until August 2022. The objectives and outcomes of these studies were extracted. Finally, to identify the facilitators and barriers of mHealth interventions, a qualitative content analysis was conducted based on the strengths, weaknesses, opportunities, and threats (SWOT) analysis method with Atlas.ti 8 software. We evaluated the studies using the Mixed Methods Appraisal Tool (MMAT).

RESULTS

In total, 1598 articles were identified and 55 articles were included in this study. Most of the studies used mobile applications to provide and receive health services during the Covid-19 pandemic (96.4%). The purpose of the applications was to help prevention (17), follow-up (15), treatment (12), and diagnosis (8). Using SWOT analysis, 13 facilitators and 18 barriers to patients' use of mHealth services were identified.

CONCLUSION

Mobile applications are very flexible technologies that can be customized for each person, patient, and population. During the Covid-19 pandemic, the applications designed due to lack of interaction, lack of time, lack of attention to privacy, and non-academic nature have not met their expectations of them.

Enhancing Data Protection in Dynamic Consent Management Systems: Formalizing Privacy and Security Definitions with Differential Privacy, Decentralization, and Zero-Knowledge Proofs

Dynamic consent management allows a data subject to dynamically govern her consent to access her data. Clearly, security and privacy guarantees are vital for the adoption of dynamic consent management systems. In particular, specific data protection guarantees can be required to comply with rules and laws (e.g., the General Data Protection Regulation (GDPR)). Since the primary instantiation of the dynamic consent management systems in the existing literature is towards developing sustainable e-healthcare services, in this paper, we study data protection issues in dynamic consent management systems, identifying crucial security and privacy properties and discussing severe limitations of systems described in the state of the art. We have presented the precise definitions of security and privacy properties that are essential to confirm the robustness of the dynamic consent management systems against diverse adversaries. Finally, under those precise formal definitions of security and privacy, we have proposed the implications of state-of-the-art tools and technologies such as differential privacy, blockchain technologies, zero-knowledge proofs, and cryptographic procedures that can be used to build dynamic consent management systems that are secure and private by design.

A New eHealth Investment Appraisal Framework for Africa: Validation

(1) Background: Decisions to use eHealth are complex and involve addressing a large opportunity cost. Sound choices are essential. Weighing up investment options is challenging in resource-constrained settings where there are frequently insufficient economics data and expertise to conduct adequate appraisals. To address this, a new eHealth Investment Appraisal Framework (eHIAF) for Africa has been designed and developed. The aim of this paper was to validate the new framework to consider whether it is fit for purpose and to refine it as needed. (2) Methods: An online survey of purposively selected eHealth experts was used to conduct a desktop validation of the proposed eHIAF for Africa. The survey covered the framework development process, structure, content, completeness, and utility. Expert opinions were charted, and a reflective and iterative process used to assess the tool and extract recommendations for refinement. (3) Results: Eleven eHealth experts who completed the survey had experience in African countries and elsewhere. The majority agreed with the eHIAF for Africa development approach and output. They provided valuable suggestions for minor refinements and felt that with these amendments, the eHIAF for Africa would be 'fit for purpose'. (4) Conclusions: The eHIAF for Africa is considered appropriate for use by policy- and decision-makers working in resource-constrained settings who face the task of selecting optimal eHealth investments. It has the potential for applicability beyond Africa and the framework should now be tested in African countries.

Embracing e-health systems in managing the COVID 19 pandemic in Sub-Saharan Africa

The COVID-19 pandemic and the policy responses adopted to curtail it have drastically altered how health services are delivered around the globe. To enable the public to continue accessing health care, e-health innovations have become the most viable tool to provide convenient, timely, effective and safe care, while reducing the spread of the virus. This paper utilized data from existing literature to explore the benefits and challenges of implementing e-health technologies in Sub Saharan Africa (SSA) amid this pandemic. Evidence suggests that these technologies have the potential to strengthen public health systems in SSA as they have in First World countries. However, there are a number of challenges that need to be addressed first in order to realize the full promises of e-health on the continent. The paper proposes that African governments should come together and implement similar e-health policies, share software, expertise and other critical ICT infrastructure as it can result in the successful implementation of e-health innovations, while reducing the financial burden associated with their set up.

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.

Protection Motivation Perspective Regarding the Use of COVID-19 Mobile Tracing Apps Among Public Users: Empirical Study

BACKGROUND

Access to data is crucial for decision-making; this fact has become more evident during the pandemic. Data collected using mobile apps can positively influence diagnosis and treatment, the supply chain, and the staffing resources of health care facilities. Developers and health care professionals have worked to create apps that can track a person's COVID-19 status. For example, these apps can monitor positive COVID-19 test results and vaccination status. Regrettably, people may be concerned about sharing their data with government or private sector organizations that are developing apps. Understanding user perceptions is essential; without substantial user adoption and the use of mobile tracing apps, benefits cannot be achieved.

OBJECTIVE

This study aimed to assess the factors that positively and negatively affect the use of COVID-19 tracing apps by examining individuals' perceptions about sharing data on mobile apps, such as testing regularity, infection, and immunization status.

METHODS

The hypothesized research model was tested using a cross-sectional survey instrument. The survey contained 5 reflective constructs and 4 control variables selected after reviewing the literature and interviewing health care professionals. A digital copy of the survey was created using Qualtrics. After receiving approval, data were collected from 367 participants through Amazon Mechanical Turk (MTurk). Participants of any gender who were 18 years or older were considered for inclusion to complete the anonymized survey. We then analyzed the theoretical model using structural equation modeling.

RESULTS

After analyzing the quality of responses, 325 participants were included. Of these 325 participants, 216 (66.5%) were male and 109 (33.5%) were female. Among the participants in the final data set, 72.6% (236/325) were employed. The results of structural equation modeling showed that perceived vulnerability (β=0.688; P<.001), self-efficacy (β=0.292; P<.001), and an individual's prior infection with COVID-19 (β=0.194; P=.002) had statistically significant positive impacts on the intention to use mobile tracing apps. Privacy concerns (β=-0.360; P<.001), risk aversion (β=-0.150; P=.09), and a family member's prior infection with COVID-19 (β=-0.139; P=.02) had statistically significant negative influences on a person's intention to use mobile tracing apps.

CONCLUSIONS

This study illustrates that various user perceptions affect whether individuals use COVID-19 tracing apps. By working collaboratively on legislation and the messaging provided to potential users before releasing an app, developers, health care professionals, and policymakers can improve the use of tracking apps. Health care professionals need to emphasize disease vulnerability to motivate people to use mobile tracing apps, which can help reduce the spread of viruses and diseases. In addition, more work is needed at the policy-making level to protect the privacy of users, which in return can increase user engagement.

Comparing Efficiency and Performance of IoT BLE and RFID-Based Systems for Achieving Contract Tracing to Monitor Infection Spread among Hospital and Office Staff

COVID-19 is highly contagious and spreads rapidly; it can be transmitted through coughing or contact with virus-contaminated hands, surfaces, or objects. The virus spreads faster indoors and in crowded places; therefore, there is a huge demand for contact tracing applications in indoor environments, such as hospitals and offices, in order to measure personnel proximity while placing as little load on them as possible. Contact tracing is a vital step in controlling and restricting pandemic spread; however, traditional contact tracing is time-consuming, exhausting, and ineffective. As a result, more research and application of smart digital contact tracing is necessary. As the Internet of Things (IoT) and wearable sensor device studies have grown in popularity, this work has been based on the practicality and successful implementation of Bluetooth low energy (BLE) and radio frequency identification (RFID) IoT based wireless systems for achieving contact tracing. Our study presents autonomous, low-cost, long-battery-life wireless sensing systems for contact tracing applications in hospital/office environments; these systems are developed with off-the-shelf components and do not rely on end user participation in order to prevent any inconvenience. Performance evaluation of the two implemented systems is carried out under various real practical settings and scenarios; these two implemented centralised IoT contact tracing devices were tested and compared demonstrating their efficiency results.

Minimizing Viral Transmission in COVID-19 Like Pandemics: Technologies, Challenges, and Opportunities

Coronavirus (COVID-19) pandemic has incurred huge loss to human lives throughout the world. Scientists, researchers, and doctors are trying their best to develop and distribute the COVID-19 vaccine throughout the world at the earliest. In current circumstances, different tracking systems are utilized to control or stop the spread of the virus till the whole population of the world gets vaccinated. To track and trace patients in COVID-19 like pandemics, various tracking systems based on different technologies are discussed and compared in this paper. These technologies include, cellular, cyber, satellite-based radio navigation and low range wireless technologies. The main aim of this paper is to conduct a comprehensive survey that can overview all such tracking systems, which are used in minimizing the spread of COVID-19 like pandemics. This paper also highlights the shortcoming of each tracking systems and suggests new mechanisms to overcome such limitations. In addition, the authors propose some futuristic approaches to track patients in prospective pandemics, based on artificial intelligence and big data analysis. Potential research directions, challenges, and the introduction of next-generation tracking systems for minimizing the spread of prospective pandemics, are also discussed at the end.

A robust tracking system for COVID-19 like pandemic using advanced hybrid technologies

In order to track patients in coronavirus (COVID-19) like pandemic, this paper proposes a novel model based on hybrid advance technologies, which is capable to trace and track COVID-19 affectees with high accuracy. The hybrid technologies include, cellular, cyber and low range wireless technologies. This technique is capable to trace patients through call data record using cellular technology, voice over Internet protocol calls using cyber technology and physical contact without having a call history using low range wireless technologies. The proposed model is also capable to trace COVID-19 suspects. In addition to tracking, the proposed model is capable to provide surveillance capability as well by geo tagging the patients. In case of any violation by the patients an alert is sent to the concerned department. The proposed model is cost effective and privacy preserved as the entire process is carried out under the umbrella of a concerned government department. The potential outcomes of the proposed model are tracking of COVID-19 patients, monitoring of isolated patients, tracking of suspected ones and inform the mass about the safest path to use.

Use of digital technologies for public health surveillance during the COVID-19 pandemic: A scoping review

Throughout the COVID-19 pandemic, a variety of digital technologies have been leveraged for public health surveillance worldwide. However, concerns remain around the rapid development and deployment of digital technologies, how these technologies have been used, and their efficacy in supporting public health goals. Following the five-stage scoping review framework, we conducted a scoping review of the peer-reviewed and grey literature to identify the types and nature of digital technologies used for surveillance during the COVID-19 pandemic and the success of these measures. We conducted a search of the peer-reviewed and grey literature published between 1 December 2019 and 31 December 2020 to provide a snapshot of questions, concerns, discussions, and findings emerging at this pivotal time. A total of 147 peer-reviewed and 79 grey literature publications reporting on digital technology use for surveillance across 90 countries and regions were retained for analysis. The most frequently used technologies included mobile phone devices and applications, location tracking technologies, drones, temperature scanning technologies, and wearable devices. The utility of digital technologies for public health surveillance was impacted by factors including uptake of digital technologies across targeted populations, technological capacity and errors, scope, validity and accuracy of data, guiding legal frameworks, and infrastructure to support technology use. Our findings raise important questions around the value of digital surveillance for public health and how to ensure successful use of technologies while mitigating potential harms not only in the context of the COVID-19 pandemic, but also during other infectious disease outbreaks, epidemics, and pandemics.

Prevention of COVID-19 pandemic through technological innovation: ensuring global innovative capability, absorptive capacity, and adaptive healthcare competency

The study examines the role of technology transfer in preventing communicable diseases, including COVID-19, in a heterogeneous panel of selected 65 countries. The study employed robust least square regression and innovation accounting matrixes to get robust inferences. The results found that overall technological innovation, including innovative capability, absorptive capacity, and healthcare competency, helps reduce infectious diseases, including the COVID-19 pandemic. Patent applications, scientific and technical journal articles, trade openness, hospital beds, and physicians are the main factors supporting the reduction of infectious diseases, including the COVID-19 pandemic. Due to inadequate research and development, healthcare infrastructure expenditures have caused many communicable diseases. The increasing number of mobile phone subscribers and healthcare expenditures cannot minimize the coronavirus pandemic globally. The impulse response function shows an increasing number of patent applications, mobile penetration, and hospital beds that will likely decrease infectious diseases, including COVID-19. In contrast, insufficient resource spending would likely increase death rates from contagious diseases over a time horizon. It is high time to digitalize healthcare policies to control coronavirus worldwide.

Challenges of Telemedicine during the COVID-19 pandemic: a systematic review

BACKGROUND

The COVID-19 pandemic has prompted the decrease of in-person visits to reduce the risk of virus transmission. Telemedicine is an efficient communication tool employed between healthcare providers and patients that prevents the risk of exposure to infected persons. However, telemedicine use is not infallible; its users reported multiple issues that complicated the expansion of this technology. So, this systematic review aimed to explore the barriers and challenges of telemedicine use during the pandemic and to propose solutions for improving future use.

METHODS

A systematic review was conducted following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) statement. PubMed, Scopus, Web of Science, Academic Search Complete, CINAHL, Embase, and Science Direct were used to look for articles addressing barriers and challenges, in addition to articles proposing solutions. Studies were screened by title and abstract, followed by a full-text review. Risk of bias assessment was done using Critical Appraisal Skills Program for qualitative studies, Newcastle-Ottawa Scale for cross-sectional studies, and A MeaSurement Tool to Assess Systematic Reviews for systematic reviews. After the extraction of data, a narrative synthesis and analysis of the outcomes were performed.

RESULTS

Among 1194 papers identified, only 27 studies were included. Barriers and challenges were assembled under 7 categories: technical aspects, privacy, data confidentiality and reimbursement, physical examination and diagnostics, special populations, training of healthcare providers and patients, doctor-patient relationship, and acceptability. Poor internet connection and lack of universal access to technology were among the technical barriers. Concerns about patient privacy and reimbursement hindered the use of telemedicine too. Physical examination and certain procedures were impossible to perform via telemedicine. Training both healthcare providers and patients was deficient. The doctor-patient relationship was troubled by telemedicine, and both healthcare providers and patients were reluctant to use telemedicine.

CONCLUSION

Widespread use of telemedicine is still hampered by various barriers and challenges. Healthcare providers should work with various stakeholders to implement the proposed solutions. More research and policy changes are essential to optimize telemedicine utilization.

Tracing app technology: an ethical review in the COVID-19 era and directions for post-COVID-19

We conducted a systematic literature review on the ethical considerations of the use of contact tracing app technology, which was extensively implemented during the COVID-19 pandemic. The rapid and extensive use of this technology during the COVID-19 pandemic, while benefiting the public well-being by providing information about people's mobility and movements to control the spread of the virus, raised several ethical concerns for the post-COVID-19 era. To investigate these concerns for the post-pandemic situation and provide direction for future events, we analyzed the current ethical frameworks, research, and case studies about the ethical usage of tracing app technology. The results suggest there are seven essential ethical considerations-privacy, security, acceptability, government surveillance, transparency, justice, and voluntariness-in the ethical use of contact tracing technology. In this paper, we explain and discuss these considerations and how they are needed for the ethical usage of this technology. The findings also highlight the importance of developing integrated guidelines and frameworks for implementation of such technology in the post- COVID-19 world.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10676-022-09659-6.

Contact tracing and mobility pattern detection during pandemics – a trajectory cluster based approach

Purpose

A wide number of technologies are currently in store to harness the challenges posed by pandemic situations. As such diseases transmit by way of person-to-person contact or by any other means, the World Health Organization had recommended location tracking and tracing of people either infected or contacted with the patients as one of the standard operating procedures and has also outlined protocols for incident management. Government agencies use different inputs such as smartphone signals and details from the respondent to prepare the travel log of patients. Each and every event of their trace such as stay points, revisit locations and meeting points is important. More trained staffs and tools are required under the traditional system of contact tracing. At the time of the spiralling patient count, the time-bound tracing of primary and secondary contacts may not be possible, and there are chances of human errors as well. In this context, the purpose of this paper is to propose an algorithm called SemTraClus-Tracer, an efficient approach for computing the movement of individuals and analysing the possibility of pandemic spread and vulnerability of the locations.

Design/methodology/approach

Pandemic situations push the world into existential crises. In this context, this paper proposes an algorithm called SemTraClus-Tracer, an efficient approach for computing the movement of individuals and analysing the possibility of pandemic spread and vulnerability of the locations. By exploring the daily mobility and activities of the general public, the system identifies multiple levels of contacts with respect to an infected person and extracts semantic information by considering vital factors that can induce virus spread. It grades different geographic locations according to a measure called weightage of participation so that vulnerable locations can be easily identified. This paper gives directions on the advantages of using spatio-temporal aggregate queries for extracting general characteristics of social mobility. The system also facilitates room for the generation of various information by combing through the medical reports of the patients.

Findings

It is identified that context of movement is important; hence, the existing SemTraClus algorithm is modified by accounting for four important factors such as stay point, contact presence, stay time of primary contacts and waypoint severity. The priority level can be reconfigured according to the interest of authority. This approach reduces the overwhelming task of contact tracing. Different functionalities provided by the system are also explained. As the real data set is not available, experiments are conducted with similar data and results are shown for different types of journeys in different geographical locations. The proposed method efficiently handles computational movement and activity analysis by incorporating various relevant semantics of trajectories. The incorporation of cluster-based aggregate queries in the model do away with the computational headache of processing the entire mobility data.

Research limitations/implications

As the trajectory of patients is not available, the authors have used the standard data sets for experimentation, which serve the purpose.

Originality/value

This paper proposes a framework infrastructure that allows the emergency response team to grab multiple information based on the tracked mobility details of a patient and facilitates room for various activities for the mitigation of pandemics such as the prediction of hotspots, identification of stay locations and suggestion of possible locations of primary and secondary contacts, creation of clusters of hotspots and identification of nearby medical assistance. The system provides an efficient way of activity analysis by computing the mobility of people and identifying features of geographical locations where people travelled. While formulating the framework, the authors have reviewed many different implementation plans and protocols and arrived at the conclusion that the core strategy followed is more or less the same. For the sake of a reference model, the Indian scenario is adopted for defining the concepts.

Application of Telemedicine in COVID-19: A Bibliometric Analysis

Background

Telemedicine as a tool that can reduce potential disease spread and fill a gap in healthcare has been increasingly applied during the COVID-19 pandemic. Many studies have summarized telemedicine's technologies or the diseases' applications. However, these studies were reviewed separately. There is a lack of a comprehensive overview of the telemedicine technologies, application areas, and medical service types.

Objective

We aimed to investigate the research direction of telemedicine at COVID-19 and to clarify what kind of telemedicine technology is used in what diseases, and what medical services are provided by telemedicine.

Methods

Publications addressing telemedicine in COVID-19 were retrieved from the PubMed database. To extract bibliographic information and do a bi-clustering analysis, we used Bicomb and gCLUTO. The co-occurrence networks of diseases, technology, and healthcare services were then constructed and shown using R-studio and the Gephi tool.

Results

We retrieved 5,224 research papers on telemedicine at COVID-19 distributed among 1460 journals. Most articles were published in the Journal of Medical Internet Research (166/5,224, 3.18%). The United States published the most articles on telemedicine. The research clusters comprised 6 clusters, which refer to mental health, mhealth, cross-infection control, and self-management of diseases. The network analysis revealed a triple relation with diseases, technologies, and health care services with 303 nodes and 5,664 edges. The entity “delivery of health care” was the node with the highest betweenness centrality at 6,787.79, followed by “remote consultation” (4,395.76) and “infection control” (3,700.50).

Conclusions

The results of this study highlight widely use of telemedicine during COVID-19. Most studies relate to the delivery of health care and mental health services. Technologies were primarily via mobile devices to deliver health care, remote consultation, control infection, and contact tracing. The study assists researchers in comprehending the knowledge structure in this sector, enabling them to discover critical topics and choose the best match for their survey work.

On the use of telemedicine in the context of COVID-19: legal aspects and a systematic review of technology

Purpose

The aim of this study was to carry out a systematic review of telemedicine technology and to discuss the role of legislation in the application of telemedicine technology within the scope of COVID-19.

Methods

The search for papers was conducted in the databases Cochrane Central, MEDLINE, and Embase. The keywords considered for this systematic review were (coronavirus OR “2019-nCoV” OR 2019nCoV OR nCoV2019 OR “nCoV-2019” OR “COVID-19” OR COVID19 OR “HCoV-19” OR HCoV19 OR CoV OR “2019 novel*” OR Ncov OR “n-cov” OR “SARS-CoV-2” OR “SARSCoV-2” OR “SARSCoV2” OR “SARSCoV2” OR SARSCov19 OR “SARS-Cov19” OR “SARS-Cov-19” OR “severe acute respiratory syndrome*” OR ((corona* OR corono*) AND (virus* OR viral* OR virinae*))) AND ((telemedicine OR telehealth OR “remote assessment” OR telemonitoring)). The review process was carried out by six independent reviewers, using the PRISMA-P method.

Results

As a result, a total of 34 papers were selected, which addressed the study of telemedicine technologies used in times of endemics, epidemics, and pandemics, focusing on COVID-19.

Conclusion

Telemedicine allows for care in remote areas and at a lower cost to the patient and, in the current situation, it can reduce the number of contagions as well as the occupation of beds in health facilities. Telemedicine may suffer from limitations, mainly due to current legislation, but in this pandemic era of COVID-19, several countries around the world have made their laws more flexible to allow more widespread use of telemedicine.

CN, F.V. J, P. V, K. J. Mobile technologies for contact tracing and prevention of COVID-19 positive cases: a cross- sectional study

Purpose

The purpose of this paper is to review the techniques for versatile advancements in contact tracing for the coronavirus disease 2019 (COVID-19) positive cases in this pandemic and to introduce the way of using the mobile location information collected within the country India. As the method, an exploratory review of current measures was conducted for confirmed COVID-19 contact tracing after understanding the current situation of the world. This paper has examined the way of using free locational information in an innovative way to reduce the spread of COVID-19 spread.

Design/methodology/approach

COVID-19 pandemic is the utmost global economic and health challenge of the century. One powerful and consistent procedure to slow down the spread and decrease the effect of COVID-19 is to track the essential and auxiliary contacts of confirmed COVID-19 positive cases by using contact-tracing innovation.

Findings

Although it takes the information from various clients, there are numerous odds in the information. The sincere measures were taken by the authors to avoid the abuse of information by any kind. A portion of the tips for keeping information from getting abused is on the whole, the information ought to be with just higher specialists, and they ought not to have the authorization to impart information to anybody.

Originality/value

This paper helps to track the COVID-19 positive cases as of now by using the field information assortment and outbreak examination stages. At the same time, mobile location information used inside the current guideline, rules for information handlers must incorporate measures to reduce the abusing of information.

Achieving data privacy for decision support systems in times of massive data sharing

The world is suffering from a new pandemic of Covid-19 that is affecting human lives. The collection of records for Covid-19 patients is necessary to tackle that situation. The decision support systems (DSS) are used to gather that records. The researchers access the patient's data through DSS and perform predictions on the severity and effect of the Covid-19 disease; in contrast, unauthorized users can also access the data for malicious purposes. For that reason, it is a challenging task to protect Covid-19 patient data. In this paper, we proposed a new technique for protecting Covid-19 patients' data. The proposed model consists of two folds. Firstly, Blowfish encryption uses to encrypt the identity attributes. Secondly, it uses Pseudonymization to mask identity and quasi-attributes, then all the data links with one another, such as the encrypted, masked, sensitive, and non-sensitive attributes. In this way, the data becomes more secure from unauthorized access.

A Smart Contract-Based Dynamic Consent Management System for Personal Data Usage under GDPR

A massive amount of sensitive personal data is being collected and used by scientists, businesses, and governments. This has led to unprecedented threats to privacy rights and the security of personal data. There are few solutions that empower individuals to provide systematic consent agreements on distinct personal information and control who can collect, access, and use their data for specific purposes and periods. Individuals should be able to delegate consent rights, access consent-related information, and withdraw their given consent at any time. We propose a smart-contract-based dynamic consent management system, backed by blockchain technology, targeting personal data usage under the general data protection regulation. Our user-centric dynamic consent management system allows users to control their personal data collection and consent to its usage throughout the data lifecycle. Transaction history and logs are recorded in a blockchain that provides trusted tamper-proof data provenance, accountability, and traceability. A prototype of our system was designed and implemented to demonstrate its feasibility. The acceptability and reliability of the system were assessed by experimental testing and validation processes. We also analyzed the security and privacy of the system and evaluated its performance.

Effectiveness of non-pharmaceutical public health interventions against COVID-19: A systematic review and meta-analysis

Non-Pharmaceutical Public Health Interventions (NPHIs) have been used by different countries to control the spread of the COVID-19. Despite available evidence regarding the effectiveness of NPHSs, there is still no consensus about how policymakers can trust these results. Studies on the effectiveness of NPHSs are single studies conducted in specific communities. Therefore, they cannot individually prove if these interventions have been effective in reducing the spread of the infection and its adverse health outcomes. In this systematic review, we aimed to examine the effects of NPHIs on the COVID-19 case growth rate, death growth rate, Intensive Care Unit (ICU) admission, and reproduction number in countries, where NPHIs have been implemented. We searched relevant electronic databases, including Medline (via PubMed), Scopus, CINAHL, Web of Science, etc. from late December 2019 to February 1, 2021. The key terms were primarily drawn from Medical Subject Heading (MeSh and Emtree), literature review, and opinions of experts. Peer-reviewed quasi-experimental studies were included in the review. The PROSPERO registration number is CRD42020186855. Interventions were NPHIs categorized as lockdown, stay-at-home orders, social distancing, and other interventions (mask-wearing, contact tracing, and school closure). We used PRISMA 2020 guidance for abstracting the data and used Cochrane Effective Practice and Organization of Practice (EPOC) Risk of Bias Tool for quality appraisal of the studies. Hartung-Knapp-Sidik-Jonkman random-effects model was performed. Main outcomes included COVID-19 case growth rate (percentage daily changes), COVID-19 mortality growth rate (percentage daily changes), COVID-19 ICU admission (percentage daily changes), and COVID-19 reproduction number changes. Our search strategies in major databases yielded 12,523 results, which decreased to 7,540 articles after eliminating duplicates. Finally, 35 articles qualified to be included in the systematic review among which 23 studies were included in the meta-analysis. Although studies were from both low-income and high-income countries, the majority of them were from the United States (13 studies) and China (five studies). Results of the meta-analysis showed that adoption of NPHIs has resulted in a 4.68% (95% CI, -6.94 to -2.78) decrease in daily case growth rates, 4.8% (95 CI, -8.34 to -1.40) decrease in daily death growth rates, 1.90 (95% CI, -2.23 to -1.58) decrease in the COVID-19 reproduction number, and 16.5% (95% CI, -19.68 to -13.32) decrease in COVID-19 daily ICU admission. A few studies showed that, early enforcement of lockdown, when the incidence rate is not high, contributed to a shorter duration of lockdown and a lower increase of the case growth rate in the post-lockdown era. The majority of NPHIs had positive effects on restraining the COVID-19 spread. With the problems that remain regarding universal access to vaccines and their effectiveness and considering the drastic impact of the nationwide lockdown and other harsh restrictions on the economy and people's life, such interventions should be mitigated by adopting other NPHIs such as mass mask-wearing, patient/suspected case isolation strategies, and contact tracing. Studies need to address the impact of NPHIs on the population's other health problems than COVID-19.

Modelling Representative Population Mobility for COVID-19 Spatial Transmission in South Africa

The COVID-19 pandemic starting in the first half of 2020 has changed the lives of everyone across the world. Reduced mobility was essential due to it being the largest impact possible against the spread of the little understood SARS-CoV-2 virus. To understand the spread, a comprehension of human mobility patterns is needed. The use of mobility data in modelling is thus essential to capture the intrinsic spread through the population. It is necessary to determine to what extent mobility data sources convey the same message of mobility within a region. This paper compares different mobility data sources by constructing spatial weight matrices at a variety of spatial resolutions and further compares the results through hierarchical clustering. We consider four methods for constructing spatial weight matrices representing mobility between spatial units, taking into account distance between spatial units as well as spatial covariates. This provides insight for the user into which data provides what type of information and in what situations a particular data source is most useful.

Leveraging mobile health technology towards Achieving Universal Health Coverage in Nigeria

Universal Health Coverage (UHC) is ensuring everyone has access to quality health services needed without suffering any financial hardship. Most African countries including Nigeria are striving to meet this target since the declaration but so far, as of 2020, Nigeria has only made little progress in achieving this goal which was declared to be achieved by 2030. Meanwhile, incorporating Mobile health technology (mHealth) has prospective benefits for achieving UHC by improving access to health care services particularly for those in hard-to-reach communities, enhancing knowledge and access to health information for health workers and communities leading to; increase in productivity of the health workforce, and access to quality healthcare services. Although mHealth has good prospect of promoting the achievement of UHC in Nigeria but there are limitations of poor power supply, poor data collection from evidence-based researches, and restricted access to mobile phones and internet especially in core rural communities in Nigeria. We aim to discuss how mHealth can be leveraged on in promoting achievement of UHC and the challenges associated with incorporating appropriate technology in the Nigerian healthcare system.

Effectiveness of Contact Tracing for Viral Disease Mitigation and Suppression: Evidence-Based Review

BACKGROUND

Contact tracing in association with quarantine and isolation is an important public health tool to control outbreaks of infectious diseases. This strategy has been widely implemented during the current COVID-19 pandemic. The effectiveness of this nonpharmaceutical intervention is largely dependent on social interactions within the population and its combination with other interventions. Given the high transmissibility of SARS-CoV-2, short serial intervals, and asymptomatic transmission patterns, the effectiveness of contact tracing for this novel viral agent is largely unknown.

OBJECTIVE

This study aims to identify and synthesize evidence regarding the effectiveness of contact tracing on infectious viral disease outcomes based on prior scientific literature.

METHODS

An evidence-based review was conducted to identify studies from the PubMed database, including preprint medRxiv server content, related to the effectiveness of contact tracing in viral outbreaks. The search dates were from database inception to July 24, 2020. Outcomes of interest included measures of incidence, transmission, hospitalization, and mortality.

RESULTS

Out of 159 unique records retrieved, 45 (28.3%) records were reviewed at the full-text level, and 24 (15.1%) records met all inclusion criteria. The studies included utilized mathematical modeling (n=14), observational (n=8), and systematic review (n=2) approaches. Only 2 studies considered digital contact tracing. Contact tracing was mostly evaluated in combination with other nonpharmaceutical interventions and/or pharmaceutical interventions. Although some degree of effectiveness in decreasing viral disease incidence, transmission, and resulting hospitalizations and mortality was observed, these results were highly dependent on epidemic severity (R0 value), number of contacts traced (including presymptomatic and asymptomatic cases), timeliness, duration, and compliance with combined interventions (eg, isolation, quarantine, and treatment). Contact tracing effectiveness was particularly limited by logistical challenges associated with increased outbreak size and speed of infection spread.

CONCLUSIONS

Timely deployment of contact tracing strategically layered with other nonpharmaceutical interventions could be an effective public health tool for mitigating and suppressing infectious outbreaks by decreasing viral disease incidence, transmission, and resulting hospitalizations and mortality.

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.

Keep Moving Forward: Health Informatics and Information Management beyond the COVID-19 Pandemic

Objectives: To identify gaps and challenges in health informatics and health information management during the COVID-19 pandemic. To describe solutions and offer recommendations that can address the identified gaps and challenges.

Methods: A literature review of relevant peer-reviewed and grey literature published from January 2020 to December 2020 was conducted to inform the paper.

Results: The literature revealed several themes regarding health information management and health informatics challenges and gaps: information systems and information technology infrastructure; data collection, quality, and standardization; and information governance and use. These challenges and gaps were often driven by public policy and funding constraints.

Conclusions: COVID-19 exposed complexities related to responding to a world-wide, fast moving, quickly spreading novel virus. Longstanding gaps and ongoing challenges in the local, national, and global health and public health information systems and data infrastructure must be addressed before we are faced with another global pandemic.

Development, Acceptance, and Concerns Surrounding App-Based Services to Overcome the COVID-19 Outbreak in South Korea: Web-Based Survey Study

Background

Since the COVID-19 outbreak, South Korea has been engaged in various efforts to overcome the pandemic. One of them is to provide app-based COVID-19–related services to the public. As the pandemic continues, a need for various apps has emerged, including COVID-19 apps that can support activities aimed at overcoming the COVID-19 pandemic.

Objective

We aimed to determine which apps were considered the most necessary according to users and evaluate the current status of the development of COVID-19–related apps in South Korea. We also aimed to determine users’ acceptance and concerns related to using apps to support activities to combat COVID-19.

Methods

We collected data from 1148 users from a web-based survey conducted between November 11 and December 6, 2020. Basic statistical analysis, multiple response analysis, and the Wilcoxon rank sum test were performed using R software. We then manually classified the current status of the development of COVID-19–related apps.

Results

In total, 68.4% (785/1148) of the respondents showed high willingness to protect themselves from COVID-19 by using related apps. Users considered the epidemiological investigation app to be the most necessary app (709/1148, 61.8%) overall, followed by the self-management app for self-isolation (613/1148, 53.4%), self-route management app (605/1148, 52.7%), COVID-19 symptom management app (483/1148, 42.1%), COVID-19–related information provision app (339/1148, 29.5%), and mental health management app (270/1148, 23.5%). Despite the high intention to use these apps, users were also concerned about privacy issues and media exposure. Those who had an underlying disease and had experience using COVID-19–related apps showed significantly higher intentions to use those apps (P=.05 and P=.01, respectively).

Conclusions

Targeting users is very important in order to design and develop the most necessary apps. Furthermore, to gain the public’s trust and make the apps available to as many people as possible, it is vital to develop diverse apps in which privacy protection is maximized.

Digital Contact Tracing Applications during COVID-19: A Scoping Review about Public Acceptance

Digital contact tracing applications (CTAs) have been one of the most widely discussed technical methods of controlling the COVID-19 outbreak. The effectiveness of this technology and its ethical justification depend highly on public acceptance and adoption. This study aims to describe the current knowledge about public acceptance of CTAs and identify individual perspectives, which are essential to consider concerning CTA acceptance and adoption. In this scoping review, 25 studies from four continents across the globe are compiled, and critical topics are identified and discussed. The results show that public acceptance varies across national cultures and sociodemographic strata. Lower acceptance among people who are mistrusting, socially disadvantaged, or those with low technical skills suggest a risk that CTAs may amplify existing inequities. Regarding determinants of acceptance, eight themes emerged, covering both attitudes and behavioral perspectives that can influence acceptance, including trust, privacy concerns, social responsibility, perceived health threat, experience of and access to technologies, performance expectancy and perceived benefits, and understanding. Furthermore, widespread misconceptions about the CTA function are a topic in need of immediate attention to ensure the safe use of CTAs. The intention-action gap is another topic in need of more research.

How Culture and Sociopolitical Tensions Might Influence People’s Acceptance of COVID-19 Control Measures That Use Individual-Level Georeferenced Data

This study extends an earlier study in the United States and South Korea on people’s privacy concerns for and acceptance of COVID-19 control measures that use individual-level georeferenced data (IGD). Using a new dataset collected via an online survey in Hong Kong, we first examine the influence of culture and recent sociopolitical tensions on people’s privacy concerns for and acceptance of three types of COVID-19 control measures that use IGD: contact tracing, self-quarantine monitoring, and location disclosure. We then compare Hong Kong people’s views with the views of people in the United States and South Korea using the pooled data of the three study areas. The results indicate that, when compared to people in the United States and South Korea, people in Hong Kong have a lower acceptance rate for digital contact tracing and higher acceptance rates for self-quarantine monitoring using e-wristbands and location disclosure. Further, there is geographic heterogeneity in the age and gender differences in privacy concerns, perceived social benefits, and acceptance of COVID-19 control measures: young people (age < 24) and women in Hong Kong and South Korea have greater privacy concerns than men. Further, age and gender differences in privacy concerns, perceived social benefits, and acceptance of COVID-19 control measures in Hong Kong and South Korea are larger than those in the United States, and people in Hong Kong have the largest age and gender differences in privacy concerns, perceived social benefits, and acceptance of COVID-19 measures among the three study areas.

Overcoming COVID-19 in China despite shortcomings of the public health system: what can we learn?

BACKGROUND AND OBJECTIVE

The COVID-19 pandemic started in Wuhan, China, in December 2019. Although there are some doubts about the reporting of cases and deaths in China, it seems that this country was able to control the epidemic more effectively than many other countries. In this paper, we would like to analyze the measures taken in China and compare them with other countries in order to find out what they can learn from China.

METHODS

We develop a system dynamics model of the COVID-19 pandemic in Wuhan. Based on a number of simulations we analyze the impact of changing parameters, such as contact rates, on the development of a second wave.

RESULTS

Although China's health care system seems to be poorly financed and inefficient, the epidemic was brought under control in a comparably short period of time and no second wave was experienced in Wuhan until today. The measures to contain the epidemic do not differ from what was implemented in other countries, but China applied them very early and rigorously. For instance, the consequent implementation of health codes and contact-tracking technology contributed to contain the disease and effectively prevented the second and third waves.

CONCLUSIONS

China's success in fighting COVID-19 is based on a very strict implementation of a set of measures, including digital management. While other countries discuss relaxing the lock-down at a rate of 50 per 100,000 inhabitants, China started local lock-downs at a rate of 3 per 100,000. We call for a public debate whether this policy would be feasible for more liberal countries as well.

Lessons from countries implementing find, test, trace, isolation and support policies in the rapid response of the COVID-19 pandemic: a systematic review

OBJECTIVE

To systematically learn lessons from the experiences of countries implementing find, test, trace, isolate, support (FTTIS) in the first wave of the COVID-19 pandemic.

DESIGN, DATA SOURCES AND ELIGIBILITY CRITERIA

We searched MEDLINE (PubMed), Cochrane Library, SCOPUS and JSTOR, initially between 31 May 2019 and 21 January 2021. Research articles and reviews on the use of contact tracing, testing, self-isolation and quarantine for COVID-19 management were included in the review.

DATA EXTRACTION AND SYNTHESIS

We extracted information including study objective, design, methods, main findings and implications. These were tabulated and a narrative synthesis was undertaken given the diverse research designs, methods and implications.

RESULTS

We identified and included 118 eligible studies. We identified the core elements of an effective find, test, trace, isolate, support (FTTIS) system needed to interrupt the spread of a novel infectious disease, where treatment or vaccination was not yet available, as pertained in the initial stages of the COVID-19 pandemic. We report methods used to shorten case finding time, improve accuracy and efficiency of tests, coordinate stakeholders and actors involved in an FTTIS system, support individuals isolating and make appropriate use of digital tools.

CONCLUSIONS

We identified in our systematic review the key components of an FTTIS system. These include border controls, restricted entry, inbound traveller quarantine and comprehensive case finding; repeated testing to minimise false diagnoses and pooled testing in resource-limited circumstances; extended quarantine period and the use of digital tools for contact tracing and self-isolation. Support for mental or physical health and livelihoods is needed for individuals undergoing self-isolation/quarantine. An integrated system with rolling-wave planning can best use effective FTTIS tools to respond to the fast-changing COVID-19 pandemic. Results of the review may inform countries considering implementing these measures.

State of the Art in Adoption of Contact Tracing Apps and Recommendations Regarding Privacy Protection and Public Health: Systematic Review

BACKGROUND

During the COVID-19 pandemic, contact tracing apps have received a lot of public attention. The ongoing debate highlights the challenges of the adoption of data-driven innovation. We reflect on how to ensure an appropriate level of protection of individual data and how to maximize public health benefits that can be derived from the collected data.

OBJECTIVE

The aim of the study was to analyze available COVID-19 contact tracing apps and verify to what extent public health interests and data privacy standards can be fulfilled simultaneously in the process of the adoption of digital health technologies.

METHODS

A systematic review of PubMed and MEDLINE databases, as well as grey literature, was performed to identify available contact tracing apps. Two checklists were developed to evaluate (1) the apps' compliance with data privacy standards and (2) their fulfillment of public health interests. Based on both checklists, a scorecard with a selected set of minimum requirements was created with the goal of estimating whether the balance between the objective of data privacy and public health interests can be achieved in order to ensure the broad adoption of digital technologies.

RESULTS

Overall, 21 contact tracing apps were reviewed. In total, 11 criteria were defined to assess the usefulness of each digital technology for public health interests. The most frequently installed features related to contact alerting and governmental accountability. The least frequently installed feature was the availability of a system of medical or organizational support. Only 1 app out of 21 (5%) provided a threshold for the population coverage needed for the digital solution to be effective. In total, 12 criteria were used to assess the compliance of contact tracing apps with data privacy regulations. Explicit user consent, voluntary use, and anonymization techniques were among the most frequently fulfilled criteria. The least often implemented criteria were provisions of information about personal data breaches and data gathered from children. The balance between standards of data protection and public health benefits was achieved best by the COVIDSafe app and worst by the Alipay Health Code app.

CONCLUSIONS

Contact tracing apps with high levels of compliance with standards of data privacy tend to fulfill public health interests to a limited extent. Simultaneously, digital technologies with a lower level of data privacy protection allow for the collection of more data. Overall, this review shows that a consistent number of apps appear to comply with standards of data privacy, while their usefulness from a public health perspective can still be maximized.

The Belt and Road Initiative and disease control amid the COVID-19 pandemic

The Belt and Road Initiative (BRI) provides a critical platform to fight COVID-19 through the strengthened collaboration, improved supply chain, elevated digital infrastructure, and more sustainable financing. BRI that integrate health with economic development may offer a new paradigm for building a resilient health system to address disease epidemics.

Developing and testing of an Early Warning mobileHealth screening and risk scoring application for preventing heath worker in-hospital transmission of Covid-19: A feasibility study

BACKGROUND

Hospitals have been identified as very high-risk places for Covid-19 transmission between health workers and non-covid-19 patients. Health care workers are the most at risk population to contract and transmit the infection especially to the already vulnerable non-Covid-19 patients. In Low-income countries, routine testing is not feasible due to the high cost of testing therefore presenting the risk of un-controlled transmission within the non Covid-19 treatment wards. This challenge necessitated the development of an affordable intermediary screening tool that would enable early identification of potentially infected health care workers and for early real time DNA-PCR testing prioritization. This would limit the contact time of potentially infected health care workers with the patients but also efficiently utilize the limited testing kits.

OBJECTIVE

To describe an early warning in-hospital risk analysis mobile application for screening Covid-19 and determine the feasibility and user friendliness among health care workers.

METHODS

Materials and methods: Using the WHO, Ministry of Health of Uganda guidelines on the case definition of Covid-19, we developed a screening questionnaire tool for risk assessment of Covid-19. Specific signs and symptoms were weighted based on how prevalent they were among Covid-19 patients and subsequently an algorithm developed for the various case scenarios of Covid-19. Risk sores were computed based on the symptoms and contact history and a daily risk category assigned based on the risk score. The questionnaire, flow charts and algorithms were then integrated into an android mobile application. Following the launch, 100 health care workers in the directorate of surgical services used the application for one month and the feasibility and consistence of use as well as user friendliness was evaluated. Health care workers would submit their daily risk scores and high-risk staff would be selected for testing and further intervention including treatment.

RESULTS

Results: The primary result of this research project was the development of a mobile based daily early warning system for in-hospital transmission of Covid-19. Overall, the EWAS mobile application was found to be feasible with over 69% of the health care workers having logged more than 67% of the required times. Over 93% of the participants reported the tool as easy to use.

CONCLUSIONS

Conclusion: The EWAS mobile application is a feasible and user-friendly daily risk scoring tool for preventing in-hospital transmission of Covid-19. Despite it, not being designed to be a diagnostic but a screening tool, there is a need to evaluate its sensitivity in predicting persons likely to have contracted Covid-19.

CLINICALTRIAL

Implementing Public Health Strategies-The Need for Educational Initiatives: A Systematic Review

In the absence of a specific treatment or vaccines, public health strategies are the main measures to use in the initial stages of a pandemic to allow surveillance of infectious diseases. During the ongoing global pandemic of coronavirus disease 2019 (COVID-19), several countries initiated various public health strategies, such as contact tracing and quarantine. The present study aims to conduct a systematic literature review to identify the presence of educational initiatives that promote the implementation of public health strategies before public health emergencies, with a special focus on contact tracing applications. Using Science Direct, PubMed, Scopus, and Gothenburg University search engines, all published scientific articles were included, while conference, reports, and non-scientific papers were excluded. The outcomes of the reviewed studies indicate that the effective implementation of public health strategies depends on the peoples' willingness to participate and collaborate with local authorities. Several factors may influence such willingness, of which ethical, psychological, and practical factors seem to be the most important and frequently discussed. Moreover, individual willingness and readiness of a community may also vary based on the acquired level of knowledge about the incident and its cause and available management options. Educational initiatives, proper communication, and timely information at the community level were found to be the necessary steps to counteract misinformation and to promote a successful implementation of public health strategies and attenuate the effects of a pandemic. The systematic review conducted as a part of this study would benefit the relevant stakeholders and policy makers and assist with effective designing and implementation.

A hover view over effectual approaches on pandemic management for sustainable cities - The endowment of prospective technologies with revitalization strategies

The COVID-19 pandemic affects all of society and hinders day-to-day activities from a straightforward perspective. The pandemic has an influential impact on almost everything and the characteristics of the pandemic remain unclear. This ultimately leads to ineffective strategic planning to manage the pandemic. This study aims to elucidate the typical pandemic characteristics in line with various temporal phases and its associated measures that proved effective in controlling the pandemic. Besides, an insight into diverse country's approaches towards pandemic and their consequences is provided in brief. Understanding the role of technologies in supporting humanity gives new perspectives to effectively manage the pandemic. Such role of technologies is expressed from the viewpoint of seamless connectivity, rapid communication, mobility, technological influence in healthcare, digitalization influence, surveillance and security, Artificial Intelligence (AI), and Internet of Things (IoT). Furthermore, some insightful scenarios are framed where the full-fledged implementation of technologies is assumed, and the reflected pandemic impacts in such scenarios are analyzed. The framed scenarios revolve around the digitalized energy sector, an enhanced supply chain system with effective customer-retailer relationships to support the city during the pandemic scenario, and an advanced tracking system for containing virus spread. The study is further extended to frame revitalization strategies to highlight the expertise where significant attention needs to be provided in the post-pandemic period as well as to nurture sustainable development. Finally, the current pandemic scenario is analyzed in terms of occurred changes and is mapped into SWOT factors. Using Fuzzy Technique for Order of Preference by Similarity to Ideal Solution based Multi-Criteria Decision Analysis, these SWOT factors are analyzed to determine where prioritized efforts are needed to focus so as to traverse towards sustainable cities. The results indicate that the enhanced crisis management ability and situational need to restructure the economic model emerges to be the most-significant SWOT factor that can ultimately support humanity for making the cities sustainable.

A scope of mobile health solutions in COVID-19 pandemics

Background and aim

COVID-19 has become an international emergency. The use of digital solutions can be effective in managing, preventing, and overcoming the further spread of infectious disease outbreaks. Accordingly, the use of mobile-health (m-health) technologies has the potential to promote public health. This review aimed to study the application of m-health solutions for the management of the COVID-19 outbreak.

Methods

The search strategy was done in Medline (PubMed), Embase, IEEE, and Google Scholar by using related keywords to m-health and COVID-19 on July 6, 2020. English papers that used m-health technologies for the COVID-19 outbreak were included.

Results

Of the 2046 papers identified, 16 were included in this study. M-health had been used for various aims such as early detection, fast screening, patient monitoring, information sharing, education, and treatment in response to the COVID-19 outbreak. M-health solutions were classified into four use case categories: prevention, diagnosis, treatment, and protection. The mobile phone-based app and short text massaging were the most frequently used modalities, followed by wearables, portable screening devices, mobile-telehealth, and continuous telemetry monitor during the pandemics.

Conclusion

It appears that m-health technologies played a positive role during the COVID-19 outbreak. Given the extensive capabilities of m-health solutions, investigation and use of all potential applications of m-health should be considered for combating the current Epidemics and mitigating its negative impacts.

The risk of racial bias while tracking influenza-related content on social media using machine learning

OBJECTIVE

Machine learning is used to understand and track influenza-related content on social media. Because these systems are used at scale, they have the potential to adversely impact the people they are built to help. In this study, we explore the biases of different machine learning methods for the specific task of detecting influenza-related content. We compare the performance of each model on tweets written in Standard American English (SAE) vs African American English (AAE).

MATERIALS AND METHODS

Two influenza-related datasets are used to train 3 text classification models (support vector machine, convolutional neural network, bidirectional long short-term memory) with different feature sets. The datasets match real-world scenarios in which there is a large imbalance between SAE and AAE examples. The number of AAE examples for each class ranges from 2% to 5% in both datasets. We also evaluate each model's performance using a balanced dataset via undersampling.

RESULTS

We find that all of the tested machine learning methods are biased on both datasets. The difference in false positive rates between SAE and AAE examples ranges from 0.01 to 0.35. The difference in the false negative rates ranges from 0.01 to 0.23. We also find that the neural network methods generally has more unfair results than the linear support vector machine on the chosen datasets.

CONCLUSIONS

The models that result in the most unfair predictions may vary from dataset to dataset. Practitioners should be aware of the potential harms related to applying machine learning to health-related social media data. At a minimum, we recommend evaluating fairness along with traditional evaluation metrics.

Contact Tracing and the COVID-19 Response in Africa: Best Practices, Key Challenges, and Lessons Learned from Nigeria, Rwanda, South Africa, and Uganda

Most African countries have recorded relatively lower COVID-19 burdens than Western countries. This has been attributed to early and strong political commitment and robust implementation of public health measures, such as nationwide lockdowns, travel restrictions, face mask wearing, testing, contact tracing, and isolation, along with community education and engagement. Other factors include the younger population age strata and hypothesized but yet-to-be confirmed partially protective cross-immunity from parasitic diseases and/or other circulating coronaviruses. However, the true burden may also be underestimated due to operational and resource issues for COVID-19 case identification and reporting. In this perspective article, we discuss selected best practices and challenges with COVID-19 contact tracing in Nigeria, Rwanda, South Africa, and Uganda. Best practices from these country case studies include sustained, multi-platform public communications; leveraging of technology innovations; applied public health expertise; deployment of community health workers; and robust community engagement. Challenges include an overwhelming workload of contact tracing and case detection for healthcare workers, misinformation and stigma, and poorly sustained adherence to isolation and quarantine. Important lessons learned include the need for decentralization of contact tracing to the lowest geographic levels of surveillance, rigorous use of data and technology to improve decision-making, and sustainment of both community sensitization and political commitment. Further research is needed to understand the role and importance of contact tracing in controlling community transmission dynamics in African countries, including among children. Also, implementation science will be critically needed to evaluate innovative, accessible, and cost-effective digital solutions to accommodate the contact tracing workload.

Exploring the effectiveness of telehealth interventions for diagnosis, contact tracing and care of Corona Virus Disease of 2019 (COVID19) patients in sub Saharan Africa: a rapid review

The efficacy of leveraging telehealth services on clinical outcomes remains scarcely documented. We conducted a rapid review to explore the effectiveness of telehealth interventions for the diagnosis, contact tracing and care of the corona virus disease of 2019 in sub Saharan Africa. Using MEDLINE, Science Direct and Cochrane Library databases, a review was conducted during the month of July 2020 of peer reviewed articles reporting on the use of telehealth interventions in sub-Saharan Africa. All the studies were assessed against the inclusion criteria by two independent reviewers. The 7 studies included in the synthesis were conducted in 2 countries [Nigeria (× 1), Zimbabwe (× 1)], and commentaries covering the entire sub Saharan Africa in general (× 4) and to Uganda (× 1). All the included articles and commentaries were published in 2020. We established that mobile applications are effective in providing information for referrals of potential patients infected by COVID 19 and provides convenient access to routine care without the risk of exposure through close contact. In countries such as Nigeria, mobile positioning data significantly improved decision making, capacity and scope of contact tracing and surveillance of known contacts of confirmed cases. We noted that collaborations between the government, mobile network operators and technology companies were utilised for successful mobile positioning data tracing interventions for COVID patients. Mobile applications such as the Vula platform in South Africa were also noted as effective in providing psychological support to health care workers attending to patients.

Telemedicine and e-Health research solutions in literature for combatting COVID-19: a systematic review

COVID-19 had led to severe clinical manifestations. In the current scenario, 98 794 942 people are infected, and it has responsible for 2 124 193 deaths around the world as reported by World Health Organization on 25 January 2021. Telemedicine has become a critical technology for providing medical care to patients by trying to reduce transmission of the virus among patients, families, and doctors. The economic consequences of coronavirus have affected the entire world and disrupted daily life in many countries. The development of telemedicine applications and eHealth services can significantly help to manage pandemic worldwide better. Consequently, the main objective of this paper is to present a systematic review of the implementation of telemedicine and e-health systems in the combat to COVID-19. The main contribution is to present a comprehensive description of the state of the art considering the domain areas, organizations, funding agencies, researcher units and authors involved. The results show that the United States and China have the most significant number of studies representing 42.11% and 31.58%, respectively. Furthermore, 35 different research units and 9 funding agencies are involved in the application of telemedicine systems to combat COVID-19.