Use of a mobile application for Ebola contact tracing and monitoring in northern Sierra Leone: a proof-of-concept study

Using mHealth Technologies for Case Finding in Tuberculosis and Other Infectious Diseases in Africa: Systematic Review

BACKGROUND

Mobile health (mHealth) technologies are increasingly used in contact tracing and case finding, enhancing and replacing traditional methods for managing infectious diseases such as Ebola, tuberculosis, COVID-19, and HIV. However, the variations in their development approaches, implementation scopes, and effectiveness introduce uncertainty regarding their potential to improve public health outcomes.

OBJECTIVE

We conducted this systematic review to explore how mHealth technologies are developed, implemented, and evaluated. We aimed to deepen our understanding of mHealth's role in contact tracing, enhancing both the implementation and overall health outcomes.

METHODS

We searched and reviewed studies conducted in Africa focusing on tuberculosis, Ebola, HIV, and COVID-19 and published between 1990 and 2023 using the PubMed, Scopus, Web of Science, and Google Scholar databases. We followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines to review, synthesize, and report the findings from articles that met our criteria.

RESULTS

We identified 11,943 articles, but only 19 (0.16%) met our criteria, revealing a large gap in technologies specifically aimed at case finding and contact tracing of infectious diseases. These technologies addressed a broad spectrum of diseases, with a predominant focus on Ebola and tuberculosis. The type of technologies used ranged from mobile data collection platforms and smartphone apps to advanced geographic information systems (GISs) and bidirectional communication systems. Technologies deployed in programmatic settings, often developed using design thinking frameworks, were backed by significant funding and often deployed at a large scale but frequently lacked rigorous evaluations. In contrast, technologies used in research settings, although providing more detailed evaluation of both technical performance and health outcomes, were constrained by scale and insufficient funding. These challenges not only prevented these technologies from being tested on a wider scale but also hindered their ability to provide actionable and generalizable insights that could inform public health policies effectively.

CONCLUSIONS

Overall, this review underscored a need for organized development approaches and comprehensive evaluations. A significant gap exists between the expansive deployment of mHealth technologies in programmatic settings, which are typically well funded and rigorously developed, and the more robust evaluations necessary to ascertain their effectiveness. Future research should consider integrating the robust evaluations often found in research settings with the scale and developmental rigor of programmatic implementations. By embedding advanced research methodologies within programmatic frameworks at the design thinking stage, mHealth technologies can potentially become technically viable and effectively meet specific contact tracing health outcomes to inform policy effectively.

Hits and Misses: Digital Contact Tracing in a Pandemic

Traditional contact tracing is one of the most powerful weapons people have in the battle against a pandemic, especially when vaccines do not yet exist or do not afford complete protection from infection. But the effectiveness of contact tracing hinges on its ability to find infected people quickly and obtain accurate information from them. Therefore, contact tracing inherits the challenges associated with the fallibilities of memory. Against this backdrop, digital contact tracing is the "dream scenario"-an unobtrusive, vigilant, and accurate recorder of danger that should outperform manual contact tracing on every dimension. There is reason to celebrate the success of digital contact tracing. Indeed, epidemiologists report that digital contact tracing probably reduced the incidence of COVID-19 cases by at least 25% in many countries, a feat that would have been hard to match with its manual counterpart. Yet there is also reason to speculate that digital contact tracing delivered on only a fraction of its potential because it almost completely ignored the relevant psychological science. We discuss the strengths and weaknesses of digital contact tracing, its hits and misses in the COVID-19 pandemic, and its need to be integrated with the science of human behavior.

Availability of published evidence on coverage, cost components, and funding support for digitalisation of infectious disease surveillance in Africa, 2003-2022: a systematic review

BACKGROUND

The implementation of digital disease surveillance systems at national levels in Africa have been challenged by many factors. These include user applicability, utility of IT features but also stable financial support. Funding closely intertwines with implementations in terms of geographical reach, disease focus, and sustainability. However, the practice of evidence sharing on geographical and disease coverage, costs, and funding sources for improving the implementation of these systems on the continent is unclear.

OBJECTIVES

To analyse the key characteristics and availability of evidence for implementing digital infectious disease surveillance systems in Africa namely their disease focus, geographical reach, cost reporting, and external funding support.

METHODS

We conducted a systematic review of peer-reviewed and grey literature for the period 2003 to 2022 (PROSPERO registration number: CRD42022300849). We searched five databases (PubMed, MEDLINE over Ovid, EMBASE, Web of Science, and Google Scholar) and websites of WHO, Africa CDC, and public health institutes of African countries. We mapped the distribution of projects by country; identified reported implementation cost components; categorised the availability of data on cost components; and identified supporting funding institutions outside Africa.

RESULTS

A total of 29 reports from 2,033 search results were eligible for analysis. We identified 27 projects implemented in 13 countries, across 32 sites. Of these, 24 (75%) were pilot projects with a median duration of 16 months, (IQR: 5-40). Of the 27 projects, 5 (19%) were implemented for HIV/AIDs and tuberculosis, 4 (15%) for malaria, 4 (15%) for all notifiable diseases, and 4 (15%) for One Health. We identified 17 cost components across the 29 reports. Of these, 11 (38%) reported quantified costs for start-up capital, 10 (34%) for health personnel compensation, 9 (31%) for training and capacity building, 8 (28%) for software maintenance, and 7(24%) for surveillance data transmission. Of 65 counts of external funding sources, 35 (54%) were governmental agencies, 15 (23%) foundations, and 7 (11%) UN agencies.

CONCLUSIONS

The evidence on costing data for the digitalisation of surveillance and outbreak response in the published literature is sparse in quantity, limited in detail, and without a standardised reporting format. Most initial direct project costs are substantially donor dependent, short lived, and thus unsustainable.

Tracing the Untraceables: A Joint Outbreak Investigation With Law Enforcement Using a Geographic Information System

The application of geospatial data often allows the tracing of people who are involved in activities of an illegal nature. In June 2021, we estimated the true magnitude of the spread of COVID-19 within the networks of escort-karaoke bars in Seoul, Republic of Korea, using geographic information system (GIS)-based contact tracing that was applied to our epidemiological investigation. Our joint rapid response team, composed of epidemic investigation officers and police personnel, identified 19 paper-traced cases and 158 GIS-traced cases from 5,692 confirmed cases in Seoul during the study period (June to July 2021). Our findings suggest that collaboration with law enforcement agencies and the use of overlaid satellite imagery in outbreak investigations enhances high vigilance and reduces the risk of potential breaches of human rights in the process.

Using call detail records to determine mobility patterns of different socio-demographic groups in the western area of Sierra Leone during early COVID-19 crisis

Human mobility patterns created from mobile phone call detail records (CDRs) can provide an essential resource in data-poor environments to monitor the effects of health outbreaks. Analysis of this data can be instrumental for understanding the movement pattern of populations allowing governments to set and refine policies to respond to community health risks. Building on CDR mobility analysis techniques, this research set out to test whether combining CDR mobility indicators with socio-economic information can illustrate differences between different socio-economic groups' exposure risks to COVID-19. The work focuses on the Western Area of Sierra Leone which houses the capital Freetown because it lacks existing mobility data and therefore can be a great example of how CDR can be transformed for this use. To determine mobility patterns, we applied the radius of gyration, regularity of movement, and motif types analytics commonly used in CDR research. We then applied a clustering algorithm to these results to understand user trends. Then we compared the results of the three methods with socio-economic status determined from census data in the same geography. The results show the daily movement of cell phone users of lower socio-economic status covered greater distances in the Western Area before and after lockdown, thereby showing a greater risk to COVID-19. The research also shows that groups of higher social status decreased mobility significantly after lockdown and did not return to pre-COVID-19 levels, unlike lower-social status groups.

A community-based contact isolation strategy to reduce the spread of Ebola virus disease: an analysis of the 2018-2020 outbreak in the Democratic Republic of the Congo

INTRODUCTION

Despite tremendous progress in the development of diagnostics, vaccines and therapeutics for Ebola virus disease (EVD), challenges remain in the implementation of holistic strategies to rapidly curtail outbreaks. We investigated the effectiveness of a community-based contact isolation strategy to limit the spread of the disease in the Democratic Republic of Congo (DRC).

METHODS

We did a quasi-experimental comparison study. Eligible participants were EVD contacts registered from 12 June 2019 to 18 May 2020 in Beni and Mabalako Health Zones. Intervention group participants were isolated to specific community sites for the duration of their follow-up. Comparison group participants underwent contact tracing without isolation. The primary outcome was measured as the reproduction number (R) in the two groups. Secondary outcomes were the delay from symptom onset to isolation and case management, case fatality rate (CFR) and vaccination uptake.

RESULTS

27 324 EVD contacts were included in the study; 585 in the intervention group and 26 739 in the comparison group. The intervention group generated 32 confirmed cases (5.5%) in the first generation, while the comparison group generated 87 (0.3%). However, the 32 confirmed cases arising from the intervention contacts did not generate any additional transmission (R=0.00), whereas the 87 confirmed cases arising from the comparison group generated 99 secondary cases (R=1.14). The average delay between symptom onset and case isolation was shorter (1.3 vs 4.8 days; p<0.0001), CFR lower (12.5% vs 48.4%; p=0.0001) and postexposure vaccination uptake higher (86.0% vs 56.8%; p<0.0001) in the intervention group compared with the comparison group. A significant difference was also found between intervention and comparison groups in survival rate at the discharge of hospitalised confirmed patients (87.9% vs 47.7%, respectively; p=0.0004).

CONCLUSION

The community-based contact isolation strategy used in DRC shows promise as a potentially effective approach for the rapid cessation of EVD transmission, highlighting the importance of rapidly implemented, community-oriented and trust-building control strategies.

Evaluation of Sexually Transmitted Disease Surveillance System Electronic Laboratory Processing in Florida: Automating Case Creation, Reporting, and Closure of Chlamydia and Gonorrhea Cases

BACKGROUND

Each year, Florida Department of Health staff process hundreds of thousands of electronically received laboratory results for chlamydia (CT) and gonorrhea (GC). These processing steps are currently performed manually in Florida's surveillance system and divert from other sexually transmitted disease prevention efforts. We developed processes that would automate these procedures and evaluated the impact on potential programmatic time savings.

METHODS

We evaluated 575,952 electronic CT/GC laboratory results from January 2019 to December 2021. Laboratory results were processed through the newly automated procedures and algorithms. Expected time savings were projected using conservative estimates of 1 minute saved every time an automated process replaced a current manual procedure: profile matching, profile creation, event record creation, case review, and case reporting. Exceptions to automatic case reporting applied to certain higher-priority populations needing intervention.

RESULTS

During this period, 297,348 electronic CT/GC laboratory results were received for people with no previous recorded history of sexually transmitted diseases and required profile creation. In total, 386,763 new surveillance infection records were created for reporting. Of reported cases, 127,345 were from higher-priority groups. The proposed automations would have saved an estimated 33,121 hours of staff time, about 11,040 hours or the work of 5.3 full-time staff annually.

CONCLUSIONS

Automating current CT/GC laboratory processing would save thousands of personnel hours that could be redirected to higher-priority activities. Flexibility in prioritization criteria for automated case reporting allows programs to adjust automation to disease prevention priorities and resources. Similar automation procedures could be developed by other jurisdictions or health programs.

Project design and technology trade-offs for implementing a large-scale sexual and reproductive health mHealth intervention: Lessons from Sierra Leone

Background

The Coronavirus 2019 (COVID-19) pandemic threatened decades of progress in sexual and reproductive health (SRH) and gender-based violence as attendance at health facilities plummeted and service uptake dwindled. Similarly, misinformation regarding COVID-19 was rife. The demographics in Sierra Leone are diverse in the education, economic, and rural/urban divide. Telecommunications coverage, phone ownership, and preference for information access medium also vary greatly in Sierra Leone.

Aim

The aim of the intervention was to reach Sierra Leoneans at scale with information about SRH during the early stages of the COVID-19 pandemic. This paper presents the approach and insights from designing and implementing a large-scale mobile health (mHealth) messaging campaign.

Method

Between April and July 2020, a cross-sectional multichannel SRH messaging campaign was designed and launched in Sierra Leone. Through a secondary analysis of project implementation documents and process evaluation of the messaging campaign report, the project design trade-offs and contextual factors for success were identified and documented.

Result

A total of 1.16 million recorded calls were initiated and 35.46 million text messages (short message service, SMS) were sent to telecommunication subscribers through a two-phased campaign. In phase one, only 31% of the 1,093,606 automated calls to 290,000 subscribers were picked up, dropping significantly at 95% confidence level (p = 1) after each of the four weeks. In addition, the listening duration dropped by one-third when a message was repeated compared to the first 3 weeks. Lessons from phase one were used to design an SMS and radio campaign in the scale-up phase. Evidence from our analysis suggests that the successful scaling of mHealth interventions during a pandemic will benefit from formative research and depend on at least six factors, including the following: (1) the delivery channels’ selection strategy; (2) content development and scheduling; (3) the persona categorization of youths; (4) stakeholder collaboration strategies; (5) technology trade-offs; and (6) cost considerations.

Discussion and Conclusion

The design and implementation of a large-scale messaging campaign is a complex endeavor that requires research, collaboration with other diverse stakeholders, and careful planning. Key success ingredients are the number of messages to be delivered, the format, cost considerations, and whether engagement is necessary. Lessons for similar low-and-middle-income countries are discussed.

Widening or narrowing inequalities? The equity implications of digital tools to support COVID-19 contact tracing: A qualitative study

Background

As digital tools are increasingly used to support COVID‐19 contact tracing, the equity implications must be considered. As part of a study to understand the public's views of digital contact tracing tools developed for the national ‘Test and Protect’ programme in Scotland, we aimed to explore the views of groups often excluded from such discussions. This paper reports on their views about the potential for contact tracing to exacerbate inequalities.

Methods

A qualitative study was carried out; interviews were conducted with key informants from organizations supporting people in marginalized situations, followed by interviews and focus groups with people recruited from these groups. Participants included, or represented, minority ethnic groups, asylum seekers and refugees and those experiencing multiple disadvantage including severe and enduring poverty.

Results

A total of 42 people participated: 13 key informants and 29 members of the public. While public participants were supportive of contact tracing, key informants raised concerns. Both sets of participants spoke about how contact tracing, and its associated digital tools, might increase inequalities. Barriers included finances (inability to afford smartphones or the data to ensure access to the internet); language (digital tools were available only in English and required a degree of literacy, even for English speakers); and trust (many marginalized groups distrusted statutory organizations and there were concerns that data may be passed to other organizations). One strength was that NHS Scotland, the data guardian, is seen as a generally trustworthy organization. Poverty was recognized as a barrier to people's ability to self‐isolate. Some participants were concerned about giving contact details of individuals who might struggle to self‐isolate for financial reasons.

Conclusions

The impact of contact tracing and associated digital tools on marginalized populations needs careful monitoring. This should include the contact tracing process and the ability of people to self‐isolate. Regular clear messaging from trusted groups and community members could help maintain trust and participation in the programme.

Patient and Public Contribution

Our patient and public involvement coapplicant, L. L., was involved in all aspects of the study including coauthorship. Interim results were presented to our local Public and Patient Involvement and Engagement Group, who commented on interpretation and made suggestions about further recruitment.

Privacy and contact tracing efficacy

As the COVID-19 pandemic emerged, public health authorities and software designers considered the possibility that smartphones could be used for contact tracing to control disease spread. Smartphone-based contact tracing was attractive in part because it promised to allow the tracing of contacts that might not be reported using traditional contact tracing methods. Comprehensive contact tracing raises distinctive privacy concerns, however, that have not been previously explored. Contacts outside of an individual's ordinary social network are more likely to be privacy-sensitive, making fear that such contacts will be disclosed a potential disincentive to adoption of smartphone contact tracing. Here, we modify the standard SEIR infectious disease transmission model to incorporate contact tracing and perform a series of simulations aimed at studying the importance of tracing socially distant (and potentially privacy-sensitive) contacts. We find that, for a simple model network, ensuring that distant contacts are traced is surprisingly unimportant as long as contact tracing adoption is sufficiently high. These results suggest that policy-makers designing contact tracing systems should be willing to trade off comprehensiveness for more widespread adoption.

How is “solidarity” understood in discussions about contact tracing apps? An overview

Background

In the context of the COVID-19 pandemic, there is much discussion about contact tracing apps, their use to contain the spread of the virus as well as the ethical, legal, and social aspects of their development, implementation, acceptance, and use. In these discussions, authors frequently mention “solidarity” when making key points in arguments. At the same time, authors rarely specify how they understand “solidarity”. This lack of specification about how they understand “solidarity” can lead to misunderstandings in discussions.

Objective

To prevent such misunderstandings, it is important to specify how one understands “solidarity” when mentioning it in the discussions on contact tracing apps. Therefore, the aim of this paper is to elaborate how “solidarity” is understood in the context of contact tracing apps, i.e., how different authors understand “solidarity” when using it in discussions about these apps.

Methods

In order to find out how different authors understand “solidarity” when discussing contact tracing apps, I conduct a literature review. I collect papers from several databases, inductively work out central differences and similarities between the different uses of “solidarity”, and use them to code and analyze relevant passages.

Results

In the final sample, five different understandings of “solidarity” in the context of contact tracing apps can be identified. These understandings differ in how different authors (1) imagine the basic concept of solidarity, i.e., what “solidarity” refers to, (2) how they temporally relate solidarity to contact tracing apps, and (3) how they perceive the causal interactions between solidarity and contact tracing apps, i.e., the different ways in which solidarity and contact tracing apps influence each other.

Conclusions

The five understandings of “solidarity” in the context of contact tracing apps presented here can serve as guidance for how “solidarity” can be understood in discussions—thus contributing to a better mutual understanding and preventing communicative misunderstandings.

Data Management and Privacy Policy of COVID-19 Contact-Tracing Apps: Systematic Review and Content Analysis

Background

COVID-19 digital contact-tracing apps were created to assist public health authorities in curbing the pandemic. These apps require users’ permission to access specific functions on their mobile phones, such as geolocation, Bluetooth or Wi-Fi connections, or personal data, to work correctly. As these functions have privacy repercussions, it is essential to establish how contact-tracing apps respect users’ privacy.

Objective

This study aimed to systematically map existing contact-tracing apps and evaluate the permissions required and their privacy policies. Specifically, we evaluated the type of permissions, the privacy policies’ readability, and the information included in them.

Methods

We used custom Google searches and existing lists of contact-tracing apps to identify potentially eligible apps between May 2020 and November 2021. We included contact-tracing or exposure notification apps with a Google Play webpage from which we extracted app characteristics (eg, sponsor, number of installs, and ratings). We used Exodus Privacy to systematically extract the number of permissions and classify them as dangerous or normal. We computed a Permission Accumulated Risk Score representing the threat level to the user’s privacy. We assessed the privacy policies’ readability and evaluated their content using a 13-item checklist, which generated a Privacy Transparency Index. We explored the relationships between app characteristics, Permission Accumulated Risk Score, and Privacy Transparency Index using correlations, chi-square tests, or ANOVAs.

Results

We identified 180 contact-tracing apps across 152 countries, states, or territories. We included 85.6% (154/180) of apps with a working Google Play page, most of which (132/154, 85.7%) had a privacy policy document. Most apps were developed by governments (116/154, 75.3%) and totaled 264.5 million installs. The average rating on Google Play was 3.5 (SD 0.7). Across the 154 apps, we identified 94 unique permissions, 18% (17/94) of which were dangerous, and 30 trackers. The average Permission Accumulated Risk Score was 22.7 (SD 17.7; range 4-74, median 16) and the average Privacy Transparency Index was 55.8 (SD 21.7; range 5-95, median 55). Overall, the privacy documents were difficult to read (median grade level 12, range 7-23); 67% (88/132) of these mentioned that the apps collected personal identifiers. The Permission Accumulated Risk Score was negatively associated with the average App Store ratings (r=−0.20; P=.03; 120/154, 77.9%) and Privacy Transparency Index (r=−0.25; P<.001; 132/154, 85.7%), suggesting that the higher the risk to one’s data, the lower the apps’ ratings and transparency index.

Conclusions

Many contact-tracing apps were developed covering most of the planet but with a relatively low number of installs. Privacy-preserving apps scored high in transparency and App Store ratings, suggesting that some users appreciate these apps. Nevertheless, privacy policy documents were difficult to read for an average audience. Therefore, we recommend following privacy-preserving and transparency principles to improve contact-tracing uptake while making privacy documents more readable for a wider public.

Epidemiological challenges in pandemic coronavirus disease (COVID-19): Role of artificial intelligence

World is now experiencing a major health calamity due to the coronavirus disease (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus clade 2. The foremost challenge facing the scientific community is to explore the growth and transmission capability of the virus. Use of artificial intelligence (AI), such as deep learning, in (i) rapid disease detection from x-ray or computed tomography (CT) or high-resolution CT (HRCT) images, (ii) accurate prediction of the epidemic patterns and their saturation throughout the globe, (iii) forecasting the disease and psychological impact on the population from social networking data, and (iv) prediction of drug-protein interactions for repurposing the drugs, has attracted much attention. In the present study, we describe the role of various AI-based technologies for rapid and efficient detection from CT images complementing quantitative real-time polymerase chain reaction and immunodiagnostic assays. AI-based technologies to anticipate the current pandemic pattern, prevent the spread of disease, and face mask detection are also discussed. We inspect how the virus transmits depending on different factors. We investigate the deep learning technique to assess the affinity of the most probable drugs to treat COVID-19. This article is categorized under:Application Areas > Health CareAlgorithmic Development > Biological Data MiningTechnologies > Machine Learning.

Analysis of mHealth research: mapping the relationship between mobile apps technology and healthcare during COVID-19 outbreak

BACKGROUND

Mobile health applications (mHealth apps) offer enormous promise for illness monitoring and treatment to improve the provided medical care and promote health and wellbeing.

OBJECTIVE

We applied bibliometric quantitative analysis and network visualization to highlight research trends and areas of particular interest. We expect by summarizing the trends in mHealth app research, our work will serve as a roadmap for future investigations.

METHODS

Relevant English publications were extracted from the Scopus database. VOSviewer (version 1.6.17) was used to build coauthorship networks of authors, countries, and the co-occurrence networks of author keywords.

RESULTS

We analyzed 550 published articles on mHealth apps from 2020 to February 1, 2021. The yearly publications increased from 130 to 390 in 2021. JMIR mHealth and uHealth (33/550, 6.0%), J. Med. Internet Res. (27/550, 4.9%), JMIR Res. Protoc. (22/550, 4.0%) were the widest journals for these publications. The United States has the largest number of publications (143/550, 26.0%), and England ranks second (96/550, 17.5%). The top three productive authors were: Giansanti D., Samuel G., Lucivero F., and Zhang L. Frequent authors' keywords have formed major 4 clusters representing the hot topics in the field: (1) artificial intelligence and telehealthcare; (2) digital contact tracing apps, privacy and security concerns; (3) mHealth apps and mental health; (4) mHealth apps in public health and health promotion.

CONCLUSIONS

mHealth apps undergo current developments, and they remain hot topics in COVID-19. These findings might be useful in determining future perspectives to improve infectious disease control and present innovative solutions for healthcare.

Digital Solutions for Community and Primary Health Workers: Lessons From Implementations in Africa

The agenda for Universal Health Coverage has driven the exploration of various innovative approaches to expanding health services to the general population. As more African countries have adopted digital health tools as part of the strategic approach to expanding health services, there is a need for defining a standard framework for implementation across board. Therefore, there is a need to review and employ an evidence-based approach to inform managing challenges, adopting best approaches, and implement informed recommendations. We reviewed a variety of digital health tools applied to different health conditions in primary care settings and highlighted the challenges faced, approaches that worked and relevant recommendations. These include limited coverage and network connectivity, lack of technological competence, lack of power supply, limited mobile phone usage and application design challenges. Despite these challenges, this review suggests that mHealth solutions could attain effective usage when healthcare workers receive adequate onsite training, deploying applications designed in an intuitive and easy to understand approach in a manner that fits into the users existing workflows, and involvement of the stakeholders at all levels in the design, planning, and implementation stages of the interventions.

Factors Influencing the Adoption of Contact Tracing Applications: Systematic Review and Recommendations

Background

The emergence of new variants of COVID-19 causing breakthrough infections and the endemic potential of the coronavirus are an indication that digital contact tracing apps (CTAs) may continue to be useful for the long haul. However, the uptake of these apps in many countries around the world has been low due to several factors militating against their adoption and usage.

Objective

In this systematic review, we set out to uncover the key factors that facilitate or militate against the adoption of CTAs, which researchers, designers and other stakeholders should focus on in future iterations to increase their adoption and effectiveness in curbing the spread of COVID-19.

Data Sources

Seven databases, including PubMed, CINAHL, Scopus, Web of Service, IEEE Xplore, ACM Digital Library, and Google Scholar, were searched between October 30 and January 31, 2020. A total of 777 articles were retrieved from the databases, with 13 of them included in the systematic review after screening.

Study Eligibility Criteria Participants and Intervention

The criteria for including articles in the systematic review were that they could be user studies from any country around the world, must be peer-reviewed, written in English, and focused on the perception and adoption of COVID-19 contact tracing and/or exposure notification apps. Other criteria included user study design could be quantitative, qualitative, or mixed, and must have been conducted during the COVID-19 pandemic, which began in the early part of 2020.

Study Appraisal and Synthesis Methods

Three researchers searched seven databases (three by the first author, and two each by the second and third authors) and stored the retrieved articles in a collaborative Mendeley reference management system online. After the removal of duplicates, each researcher independently screened one third of the articles based on title/abstract. Thereafter, all three researchers collectively screened articles that were in the borderline prior to undergoing a full-text review. Then, each of the three researchers conducted a full-text review of one-third of the eligible articles to decide the final articles to be included in the systematic review. Next, all three researchers went through the full text of each borderline article to determine their appropriateness and relevance. Finally, each researcher extracted the required data from one-third of the included articles into a collaborative Google spreadsheet and the first author utilized the data to write the review.

Results

This review identified 13 relevant articles, which found 56 factors that may positively or negatively impact the adoption of CTAs. The identified factors were thematically grouped into ten categories: privacy and trust, app utility, facilitating conditions, social-cognitive factors, ethical concerns, perceived technology threats, perceived health threats, technology familiarity, persuasive design, and socio-demographic factors. Of the 56 factors, privacy concern turned out to be the most frequent factor of CTA adoption (12/13), followed by perceived benefit (7/13), perceived trust (6/13), and perceived data security risk (6/13). In the structural equation models presented by the authors of the included articles, a subset of the 56 elicited factors (e.g., perceived benefit and privacy concern) explains 16 to 77% of the variance of users' intention to download, install, or use CTAs to curb the spread of COVID-19. Potential adoption rates of CTA range from 19% (in Australia) to 75% (in France, Italy, Germany, United Kingdom, and United States). Moreover, actual adoption rates range from 37% (in Australia) to 50% (in Germany). Finally, most of the studies were carried out in Europe (66.7%), followed by North America (13.3%), and Australia, Asia, and South America (6.7% each).

Conclusion

The results suggest that future CTA iterations should give priority to privacy protection through minimal data collection and transparency, improving contact tracing benefits (personal and social), and fostering trust through laudable gestures such as delegating contact tracing to public health authorities, making source code publicly available and stating who will access user data, when, how, and what it will be used for. Moreover, the results suggest that data security and tailored persuasive design, involving reward, self-monitoring, and social-location monitoring features, have the potential of improving CTA adoption. Hence, in addition to addressing issues relating to utility, privacy, trust, and data security, we recommend the integration of persuasive features into future designs of CTAs to improve their motivational appeal, adoption, and the user experience.

Systematic Review Registration

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021259080 PROSPERO, identifier CRD42021259080.

Digital Contact Tracing Apps for COVID-19: Development of a Citizen-Centered Evaluation Framework

Background

The silent transmission of COVID-19 has led to an exponential growth of fatal infections. With over 4 million deaths worldwide, the need to control and stem transmission has never been more critical. New COVID-19 vaccines offer hope. However, administration timelines, long-term protection, and effectiveness against potential variants are still unknown. In this context, contact tracing and digital contact tracing apps (CTAs) continue to offer a mechanism to help contain transmission, keep people safe, and help kickstart economies. However, CTAs must address a wide range of often conflicting concerns, which make their development/evolution complex. For example, the app must preserve citizens’ privacy while gleaning their close contacts and as much epidemiological information as possible.

Objective

In this study, we derived a compare-and-contrast evaluative framework for CTAs that integrates and expands upon existing works in this domain, with a particular focus on citizen adoption; we call this framework the Citizen-Focused Compare-and-Contrast Evaluation Framework (C³EF) for CTAs.

Methods

The framework was derived using an iterative approach. First, we reviewed the literature on CTAs and mobile health app evaluations, from which we derived a preliminary set of attributes and organizing pillars. These attributes and the probing questions that we formulated were iteratively validated, augmented, and refined by applying the provisional framework against a selection of CTAs. Each framework pillar was then subjected to internal cross-team scrutiny, where domain experts cross-checked sufficiency, relevancy, specificity, and nonredundancy of the attributes, and their organization in pillars. The consolidated framework was further validated on the selected CTAs to create a finalized version of C³EF for CTAs, which we offer in this paper.

Results

The final framework presents seven pillars exploring issues related to CTA design, adoption, and use: (General) Characteristics, Usability, Data Protection, Effectiveness, Transparency, Technical Performance, and Citizen Autonomy. The pillars encompass attributes, subattributes, and a set of illustrative questions (with associated example answers) to support app design, evaluation, and evolution. An online version of the framework has been made available to developers, health authorities, and others interested in assessing CTAs.

Conclusions

Our CTA framework provides a holistic compare-and-contrast tool that supports the work of decision-makers in the development and evolution of CTAs for citizens. This framework supports reflection on design decisions to better understand and optimize the design compromises in play when evolving current CTAs for increased public adoption. We intend this framework to serve as a foundation for other researchers to build on and extend as the technology matures and new CTAs become available.

Mining user reviews of COVID contact-tracing apps: An exploratory analysis of nine European apps

CONTEXT

More than 78 countries have developed COVID contact-tracing apps to limit the spread of coronavirus. However, many experts and scientists cast doubt on the effectiveness of those apps. For each app, a large number of reviews have been entered by end-users in app stores.

OBJECTIVE

Our goal is to gain insights into the user reviews of those apps, and to find out the main problems that users have reported. Our focus is to assess the "software in society" aspects of the apps, based on user reviews.

METHOD

We selected nine European national apps for our analysis and used a commercial app-review analytics tool to extract and mine the user reviews. For all the apps combined, our dataset includes 39,425 user reviews.

RESULTS

Results show that users are generally dissatisfied with the nine apps under study, except the Scottish ("Protect Scotland") app. Some of the major issues that users have complained about are high battery drainage and doubts on whether apps are really working.

CONCLUSION

Our results show that more work is needed by the stakeholders behind the apps (e.g., app developers, decision-makers, public health experts) to improve the public adoption, software quality and public perception of these apps.

Diagnosis of COVID-19, vitality of emerging technologies and preventive measures

Coronavirus diseases-2019 (COVID-19) is becoming increasing serious and major threat to public health concerns. As a matter of fact, timely testing enhances the life-saving judgments on treatment and isolation of COVID-19 infected individuals at possible earliest stage which ultimately suppresses spread of infectious diseases. Many government and private research institutes and manufacturing companies are striving to develop reliable tests for prompt quantification of SARS-CoV-2. In this review, we summarize existing diagnostic methods as manual laboratory-based nucleic acid assays for COVID-19 and their limitations. Moreover, vitality of rapid and point of care serological tests together with emerging biosensing technologies has been discussed in details. Point of care tests with characteristics of rapidity, accurateness, portability, low cost and requiring non-specific devices possess great suitability in COVID-19 diagnosis and detection. Besides, this review also sheds light on several preventive measures to track and manage disease spread in current and future outbreaks of diseases.

A First Look at Privacy Analysis of COVID-19 Contact-Tracing Mobile Applications

Today's smartphones are equipped with a large number of powerful value-added sensors and features, such as a low-power Bluetooth sensor, powerful embedded sensors, such as the digital compass, accelerometer, GPS sensors, Wi-Fi capabilities, microphone, humidity sensors, health tracking sensors, and a camera, etc. These value-added sensors have revolutionized the lives of the human being in many ways, such as tracking the health of the patients and the movement of doctors, tracking employees movement in large manufacturing units, monitoring the environment, etc. These embedded sensors could also be used for large-scale personal, group, and community sensing applications especially tracing the spread of certain diseases. Governments and regulators are turning to use these features to trace the people's thoughts to have symptoms of certain diseases or viruses, e.g., COVID-19. The outbreak of COVID-19 in December 2019, has seen a surge of the mobile applications for tracing, tracking, and isolating the persons showing COVID-19 symptoms to limit the spread of the disease to the larger community. The use of embedded sensors could disclose private information of the users, thus potentially bring a threat to the privacy and security of users. In this article, we analyzed a large set of smartphone applications that have been designed to contain the spread of the COVID-19 virus and bring the people back to normal life. Specifically, we have analyzed what type of permission these smartphone apps require, whether these permissions are necessary for the track and trace, how data from the user devices are transported to the analytic center, and analyzing the security measures these apps have deployed to ensure the privacy and security of users.

Psychological factors shaping public responses to COVID-19 digital contact tracing technologies in Germany

The COVID-19 pandemic has seen one of the first large-scale uses of digital contact tracing to track a chain of infection and contain the spread of a virus. The new technology has posed challenges both for governments aiming at high and effective uptake and for citizens weighing its benefits (e.g., protecting others' health) against the potential risks (e.g., loss of data privacy). Our cross-sectional survey with repeated measures across four samples in Germany ([Formula: see text]) focused on psychological factors contributing to the public adoption of digital contact tracing. We found that public acceptance of privacy-encroaching measures (e.g., granting the government emergency access to people's medical records or location tracking data) decreased over the course of the pandemic. Intentions to use contact tracing apps-hypothetical ones or the Corona-Warn-App launched in Germany in June 2020-were high. Users and non-users of the Corona-Warn-App differed in their assessment of its risks and benefits, in their knowledge of the underlying technology, and in their reasons to download or not to download the app. Trust in the app's perceived security and belief in its effectiveness emerged as psychological factors playing a key role in its adoption. We incorporate our findings into a behavioral framework for digital contact tracing and provide policy recommendations.

Expanding telemedicine to reduce the burden on the healthcare systems and poverty in Africa for a post-coronavirus disease 2019 (COVID-19) pandemic reformation

The coronavirus disease 2019 (COVID-19) global public health emergency, has exposed the fragility of health systems. Access to healthcare became a scarce commodity as healthcare providers and resource-poor populations became victims of the novel corona virus. Therefore, this study focuses on Africa's readiness to integrate telemedicine into the weak health systems and its adoption may help alleviate poor healthcare and poverty after COVID-19. We conducted a narrative review through different search strategies in Scopus on January 20, 2021, to identify available literature reporting implementation of various telemedicine modes in Africa from January 1, 2011 to December 31, 2020. We summarized 54 studies according to geographies, field, and implementation methods. The results show a willingness to adopt telemedicine in the resource-poor settings and hard-to-reach populations, which will bring relief to the inadequate healthcare systems and alleviate poverty of those who feel the burden of healthcare cost the most. With adequate government financing, telemedicine promises to enhance the treating of communicable and non-communicable diseases as well as support health infrastructure. It can also alleviate poverty among vulnerable groups and hard-to-reach communities in Africa with adequate government financing. However, given the lack of funding in Africa, the challenges in implementing telemedicine require global and national strategies before it can yield promising results. This is especially true in regards to alleviating the multidimensionality of poverty in post-COVID-19 Africa.

Data and Digital Solutions to Support Surveillance Strategies in the Context of the COVID-19 Pandemic

Background: In order to prevent spread and improve control of infectious diseases, public health experts need to closely monitor human and animal populations. Infectious disease surveillance is an established, routine data collection process essential for early warning, rapid response, and disease control. The quantity of data potentially useful for early warning and surveillance has increased exponentially due to social media and other big data streams. Digital epidemiology is a novel discipline that includes harvesting, analysing, and interpreting data that were not initially collected for healthcare needs to enhance traditional surveillance. During the current COVID-19 pandemic, the importance of digital epidemiology complementing traditional public health approaches has been highlighted. Objective: The aim of this paper is to provide a comprehensive overview for the application of data and digital solutions to support surveillance strategies and draw implications for surveillance in the context of the COVID-19 pandemic and beyond. Methods: A search was conducted in PubMed databases. Articles published between January 2005 and May 2020 on the use of digital solutions to support surveillance strategies in pandemic settings and health emergencies were evaluated. Results: In this paper, we provide a comprehensive overview of digital epidemiology, available data sources, and components of 21st-century digital surveillance, early warning and response, outbreak management and control, and digital interventions. Conclusions: Our main purpose was to highlight the plausible use of new surveillance strategies, with implications for the COVID-19 pandemic strategies and then to identify opportunities and challenges for the successful development and implementation of digital solutions during non-emergency times of routine surveillance, with readiness for early-warning and response for future pandemics. The enhancement of traditional surveillance systems with novel digital surveillance methods opens a direction for the most effective framework for preparedness and response to future pandemics.

The Clinical Information Systems Response to the COVID-19 Pandemic

OBJECTIVE

The year 2020 was predominated by the coronavirus disease 2019 (COVID-19) pandemic. The objective of this article is to review the areas in which clinical information systems (CIS) can be and have been utilized to support and enhance the response of healthcare systems to pandemics, focusing on COVID-19.

METHODS

PubMed/MEDLINE, Google Scholar, the tables of contents of major informatics journals, and the bibliographies of articles were searched for studies pertaining to CIS, pandemics, and COVID-19 through October 2020. The most informative and detailed studies were highlighted, while many others were referenced.

RESULTS

CIS were heavily relied upon by health systems and governmental agencies worldwide in response to COVID-19. Technology-based screening tools were developed to assist rapid case identification and appropriate triaging. Clinical care was supported by utilizing the electronic health record (EHR) to onboard frontline providers to new protocols, offer clinical decision support, and improve systems for diagnostic testing. Telehealth became the most rapidly adopted medical trend in recent history and an essential strategy for allowing safe and effective access to medical care. Artificial intelligence and machine learning algorithms were developed to enhance screening, diagnostic imaging, and predictive analytics - though evidence of improved outcomes remains limited. Geographic information systems and big data enabled real-time dashboards vital for epidemic monitoring, hospital preparedness strategies, and health policy decision making. Digital contact tracing systems were implemented to assist a labor-intensive task with the aim of curbing transmission. Large scale data sharing, effective health information exchange, and interoperability of EHRs remain challenges for the informatics community with immense clinical and academic potential. CIS must be used in combination with engaged stakeholders and operational change management in order to meaningfully improve patient outcomes.

CONCLUSION

Managing a pandemic requires widespread, timely, and effective distribution of reliable information. In the past year, CIS and informaticists made prominent and influential contributions in the global response to the COVID-19 pandemic.

Contact Tracing Apps: Lessons Learned on Privacy, Autonomy, and the Need for Detailed and Thoughtful Implementation

The global and national response to the COVID-19 pandemic has been inadequate due to a collective lack of preparation and a shortage of available tools for responding to a large-scale pandemic. By applying lessons learned to create better preventative methods and speedier interventions, the harm of a future pandemic may be dramatically reduced. One potential measure is the widespread use of contact tracing apps. While such apps were designed to combat the COVID-19 pandemic, the time scale in which these apps were deployed proved a significant barrier to efficacy. Many companies and governments sprinted to deploy contact tracing apps that were not properly vetted for performance, privacy, or security issues. The hasty development of incomplete contact tracing apps undermined public trust and negatively influenced perceptions of app efficacy. As a result, many of these apps had poor voluntary public uptake, which greatly decreased the apps' efficacy. Now, with lessons learned from this pandemic, groups can better design and test apps in preparation for the future. In this viewpoint, we outline common strategies employed for contact tracing apps, detail the successes and shortcomings of several prominent apps, and describe lessons learned that may be used to shape effective contact tracing apps for the present and future. Future app designers can keep these lessons in mind to create a version that is suitable for their local culture, especially with regard to local attitudes toward privacy-utility tradeoffs during public health crises.

COVID-19 mitigation by digital contact tracing and contact prevention (app-based social exposure warnings)

A plethora of measures are being combined in the attempt to reduce SARS-CoV-2 spread. Due to its sustainability, contact tracing is one of the most frequently applied interventions worldwide, albeit with mixed results. We evaluate the performance of digital contact tracing for different infection detection rates and response time delays. We also introduce and analyze a novel strategy we call contact prevention, which emits high exposure warnings to smartphone users according to Bluetooth-based contact counting. We model the effect of both strategies on transmission dynamics in SERIA, an agent-based simulation platform that implements population-dependent statistical distributions. Results show that contact prevention remains effective in scenarios with high diagnostic/response time delays and low infection detection rates, which greatly impair the effect of traditional contact tracing strategies. Contact prevention could play a significant role in pandemic mitigation, especially in developing countries where diagnostic and tracing capabilities are inadequate. Contact prevention could thus sustainably reduce the propagation of respiratory viruses while relying on available technology, respecting data privacy, and most importantly, promoting community-based awareness and social responsibility. Depending on infection detection and app adoption rates, applying a combination of digital contact tracing and contact prevention could reduce pandemic-related mortality by 20-56%.

Availability and Use of Mobile Health Technology for Disease Diagnosis and Treatment Support by Health Workers in the Ashanti Region of Ghana: A Cross-Sectional Survey

Mobile health (mHealth) technologies have been identified as promising strategies for improving access to healthcare delivery and patient outcomes. However, the extent of availability and use of mHealth among healthcare professionals in Ghana is not known. The study’s main objective was to examine the availability and use of mHealth for disease diagnosis and treatment support by healthcare professionals in the Ashanti Region of Ghana. A cross-sectional survey was carried out among 285 healthcare professionals across 100 primary healthcare clinics in the Ashanti Region with an adopted survey tool. We obtained data on the participants’ background, available health infrastructure, healthcare workforce competency, ownership of a mobile wireless device, usefulness of mHealth, ease of use of mHealth, user satisfaction, and behavioural intention to use mHealth. Descriptive statistics were conducted to characterise healthcare professionals’ demographics and clinical features. Multivariate logistic regression analysis was performed to explore the influence of the demographic factors on the availability and use of mHealth for disease diagnosis and treatment support. STATA version 15 was used to complete all the statistical analyses. Out of the 285 healthcare professionals, 64.91% indicated that mHealth is available to them, while 35.08% have no access to mHealth. Of the 185 healthcare professionals who have access to mHealth, 98.4% are currently using mHealth to support healthcare delivery. Logistic regression model analysis significantly (p < 0.05) identified that factors such as the availability of mobile wireless devices, phone calls, text messages, and mobile apps are associated with HIV, TB, medication adherence, clinic appointments, and others. There is a significant association between the availability of mobile wireless devices, text messages, phone calls, mobile apps, and their use for disease diagnosis and treatment compliance from the chi-square test analysis. The findings demonstrate a low level of mHealth use for disease diagnosis and treatment support by healthcare professionals at rural clinics. We encourage policymakers to promote the implementation of mHealth in rural clinics.

TraceAll: A Real-Time Processing for Contact Tracing Using Indoor Trajectories

The rapid spread of infectious diseases is a major public health problem. Recent developments in fighting these diseases have heightened the need for a contact tracing process. Contact tracing can be considered an ideal method for controlling the transmission of infectious diseases. The result of the contact tracing process is performing diagnostic tests, treating for suspected cases or self-isolation, and then treating for infected persons; this eventually results in limiting the spread of diseases. This paper proposes a technique named TraceAll that traces all contacts exposed to the infected patient and produces a list of these contacts to be considered potentially infected patients. Initially, it considers the infected patient as the querying user and starts to fetch the contacts exposed to him. Secondly, it obtains all the trajectories that belong to the objects moved nearby the querying user. Next, it investigates these trajectories by considering the social distance and exposure period to identify if these objects have become infected or not. The experimental evaluation of the proposed technique with real data sets illustrates the effectiveness of this solution. Comparative analysis experiments confirm that TraceAll outperforms baseline methods by 40% regarding the efficiency of answering contact tracing queries.

Implementation of a volunteer contact tracing program for COVID-19 in the United States: A qualitative focus group study

Background

Contact tracing is an important tool for suppressing COVID-19 but has been difficult to adapt to the conditions of a public health emergency. This study explored the experiences and perspectives of volunteer contact tracers in order to identify facilitators, challenges, and novel solutions for implementing COVID-19 contact tracing.

Methods

As part of a study to evaluate an emergently established volunteer contact tracing program for COVID-19 in New Haven, Connecticut, April-June 2020, we conducted focus groups with 36 volunteer contact tracers, thematically analyzed the data, and synthesized the findings using the RE-AIM implementation framework.

Results

To successfully reach cases and contacts, participants recommended identifying clients’ outreach preferences, engaging clients authentically, and addressing sources of mistrust. Participants felt that the effectiveness of successful isolation and quarantine was contingent on minimizing delays in reaching clients and on systematically assessing and addressing their nutritional, financial, and housing needs. They felt that successful adoption of a volunteer-driven contact tracing model depended on the ability to recruit self-motivated contact tracers and provide rapid training and consistent, supportive supervision. Participants noted that implementation could be enhanced with better management tools, such as more engaging interview scripts, user-friendly data management software, and protocols for special situations and populations. They also emphasized the value of coordinating outreach efforts with other involved providers and agencies. Finally, they believed that long-term maintenance of a volunteer-driven program requires monetary or educational incentives to sustain participation.

Conclusions

This is one of the first studies to qualitatively examine implementation of a volunteer-run COVID-19 contact tracing program. Participants identified facilitators, barriers, and potential solutions for improving implementation of COVID-19 contact tracing in this context. These included standardized communication skills training, supportive supervision, and peer networking to improve implementation, as well as greater cooperation with outside agencies, flexible scheduling, and volunteer incentives to promote sustainability.

Drivers of egovernment adoption amidst COVID-19 pandemic: The Information Adoption Model (IAM) approach

The study scrutinized the behavioral adoption of informational e-government services among Chinese citizens in the midst of the COVID-19 pandemic. A structural equation modeling (SEM) technique was applied for the data analysis using Smart PLS 3.0 statistical software. The results show that information quality, information credibility, and ease of COVID-19 informational e-government services are significant in determining citizens’ perception of the usefulness of COVID-19 information shared on e-government platforms. Also, the study revealed that the perceived usefulness of COVID-19 informational e-government services was significant in predicting citizens’ intention to adopt and recommend COVID-19 informational e-government services. The theoretical and practical implications of these findings are interrogated further.

Innovation and possible long-term impact driven by COVID-19: Manufacturing, personal protective equipment and digital technologies

It is known that discrete events causing extreme societal and economic pressures as well as technological opportunity are major driving factors of innovation. Due to the presence of both of these factors during the COVID-19 pandemic it was hypothesized that there would be significant on-going innovation throughout society during the pandemic, with many of the innovations having the ability to have long-term societal impact. Analysis of literature and patent databases determined sectors of accelerated innovation to include manufacturing, personal protective equipment and digital technologies. The ability of flexible and advanced manufacturing technologies to provide more adaptable production capabilities that are less susceptible to disruption, make it likely that these technologies will be incorporated further, changing the way many manufacturing firms operate. Collaboration has increased, demonstrating increases in problem-solving efficiency; however, concerns around intellectual property is likely to reduce the long-term impact of these procedural changes. Advancements in personal protective equipment and disinfection technologies may have the long-term impact of reducing waste production and triggering changes in cleaning protocols throughout society. Digital technologies such as telemedicine, data collection, artificial intelligence and communication technologies were found to have undergone significant innovation, with possible impacts such as large-scale systemic shifts, and changes in how governments, corporations, the scientific community and the public interact.

Biological characteristics and biomarkers of novel SARS-CoV-2 facilitated rapid development and implementation of diagnostic tools and surveillance measures

Existing coronavirus named as a severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has speeded its spread across the globe immediately after emergence in China, Wuhan region, at the end of the year 2019. Different techniques, including genome sequencing, structural feature classification by electron microscopy, and chest imaging using computed tomography, are primarily used to diagnose and screen SARS-CoV-2 suspected individuals. Determination of the viral structure, surface proteins, and genome sequence has provided a design blueprint for the diagnostic investigations of novel SARS-CoV-2 virus and rapidly emerging diagnostic technologies, vaccine trials, and cell-entry-inhibiting drugs. Here, we describe recent understandings on the spike glycoprotein (S protein), receptor-binding domain (RBD), and angiotensin-converting enzyme 2 (ACE2) and their receptor complex. This report also aims to review recently established diagnostic technologies and developments in surveillance measures for SARS-CoV-2 as well as the characteristics and performance of emerging techniques. Smartphone apps for contact tracing can help nations to conduct surveillance measures before a vaccine and effective medicines become available. We also describe promising point-of-care (POC) diagnostic technologies that are under consideration by researchers for advancement beyond the proof-of-concept stage. Developing novel diagnostic techniques needs to be facilitated to establish automatic systems, without any personal involvement or arrangement to curb an existing SARS-CoV-2 epidemic crisis, and could also be appropriate for avoiding the emergence of a future epidemic crisis.

Accounting for health inequities in the design of contact tracing interventions: A rapid review

Background

Contact tracing has been a central control measure for coronavirus disease 2019 (COVID-19) transmission. However, without consideration of the needs of specific populations, public health interventions can exacerbate health inequities.

Aim

The purpose of this rapid review was to determine if and how health inequities were included in the design of contact tracing interventions in epidemic settings.

Methods

A search of the electronic databases MEDLINE and Web of Science was conducted. The following inclusion criteria were applied for article selection: (1) described the design of contact tracing interventions, (2) published between 2013 and 2020 in English, French, Spanish, Chinese, or Portuguese, (3) and included at least 50% of empiricism, according to the Automated Classifier of Texts on Scientific Studies (ATCER) tool. Various tools were used to extract data.

Results

Following screening of the titles and abstracts of 230 articles, 39 met the inclusion criteria. Only seven references were retained after full text review. None of the selected studies considered health inequities in the design of contact tracing interventions.

Conclusions

The use of tools/concepts for incorporating health inequities, such as the REFLEX-ISS tool, and ‘proportionate universalism’ when designing contact tracing interventions, would enable practitioners, decision-makers, and researchers to better consider health inequities.

Mobile health applications for disease screening and treatment support in low-and middle-income countries: A narrative review

The advances in mobile technologies and applications are driving the transformation in health services delivery globally. Mobile phone penetration is increasing exponentially in low-and middle-income countries, hence using mobile phones for healthcare services could reach more people in resource-limited settings than the traditional forms of healthcare provision. The review presents recent literature on facilitators and barriers of implementing mHealth for disease screening and treatment support in low-and middle-income countries. We searched for relevant literature from the following electronic databases: MEDLINE; CINAHL with full text via EBSCOhost; Science Direct; PubMed; Google Scholar and Web of Science using the keywords for relevant studies. We searched for published studies from 2015 to August 2020 with no language limitations. A total of 721 articles identified, 125 articles met the inclusion criteria and were included in the qualitative synthesis. The review demonstrates relevant facilitators for the implementation of mHealth, which includes knowledge, attitudes, and perceptions of stakeholders on the use of mHealth and the performance of mHealth for disease diagnosis in low and-middle-income countries. Barriers and challenges hindering the implementation of mHealth applications were also identified. We proposed a framework for improving the implementation of mHealth for disease screening and treatment support in low-and middle-income countries.

A Comprehensive Review of Detection Methods for SARS-CoV-2

Recently, the outbreak of the coronavirus disease 2019 (COVID-19), caused by the SARS-CoV-2 virus, in China and its subsequent spread across the world has caused numerous infections and deaths and disrupted normal social activity. Presently, various techniques are used for the diagnosis of SARS-CoV-2 infection, with various advantages and weaknesses to each. In this paper, we summarize promising methods, such as reverse transcription-polymerase chain reaction (RT-PCR), serological testing, point-of-care testing, smartphone surveillance of infectious diseases, nanotechnology-based approaches, biosensors, amplicon-based metagenomic sequencing, smartphone, and wastewater-based epidemiology (WBE) that can also be utilized for the detection of SARS-CoV-2. In addition, we discuss principles, advantages, and disadvantages of these detection methods, and highlight the potential methods for the development of additional techniques and products for early and fast detection of SARS-CoV-2.

How should diagnostic kits development adapt quickly in COVID 19-like pandemic models? Pros and cons of sensory platforms used in COVID-19 sensing

As COVID-19 has reached pandemic status and the number of cases continues to grow, widespread availability of diagnostic testing is critical in helping identify and control the emergence of this rapidly spreading and serious illness. However, a lacking in making a quick reaction to the threat and starting early development of diagnostic sensing tools has had an important impact globally. In this regard, here we will review critically the current developed diagnostic tools in response to the COVID-19 pandemic and compare the different types through the discussion of their pros and cons such as nucleic acid detection tests (including PCR and CRISPR), antibody and protein-based diagnosis tests. In addition, potential technologies that are under development such as on-site diagnosis platforms, lateral flow, and portable PCR units are discussed. Data collection and epidemiological analysis could also be an interesting factor to incorporate with the emerging technologies especially with the wide access to smartphones. Lastly, a SWOT analysis and perspectives on how the development of novel sensory platforms should be treated by the different decision-makers are analyzed.

Mobile health approaches to disease surveillance in Africa; Wellvis COVID triage tool

COVID-19 has rapidly spread across the globe and was declared a pandemic by the World Health Organization (WHO). The COVID-19 infection continues to spread across Africa. In Africa, mobile phone applications have been used for the surveillance and reporting of infectious diseases such as malaria, measles, polio, and other notifiable diseases as mandated by the WHO. A good example is the early warning alert and response system. We developed an eight-question triage tool using the Nigerian Centre for Disease Control surveillance case definitions for new coronavirus disease. Based on the assessed risk level we offered advice and guidance on the next steps. A user-administered tool such as this is vital to COVID19 control. It is also significant in relieving the burden on health systems, providing information on national health guidelines for prevention and control, fostering the participation of citizens, and giving them the next steps, pandemic control efforts become more effective.

The experience of contact tracing in Singapore in the control of COVID-19: highlighting the use of digital technology

Purpose

Containing the coronavirus disease 2019 (COVID-19) pandemic would require aggressive contact tracing and isolation of suspected or confirmed COVID-19 cases. Models in published literature have suggested that digital rather than manual contact tracing might be more effective in containing the pandemic. This article seeks to examine the forms of contact tracing that Singapore, a highly dense city-state, adopts with a focus on new innovations including the use of digital technology.

Methods

An exploratory literature search in PubMed, MEDLINE and EMBASE for studies reviewing technological approaches and responses to COVID-19 was performed. Information published by national agencies was also analysed to ascertain how technology was utilised in contact tracing.

Results

Contact tracing in Singapore is overseen by the Ministry of Health (MOH). COVID-19 cases are interviewed on their whereabouts during a backward and forward activity mapping process to identify close contacts. Extensive contact tracing even involving the police and serological tools have helped to establish links between cases and closed several local clusters. Examination of patient’s digital footprint has helped in contact tracing. Other digital technology introduced includes SafeEntry and TraceTogether. SafeEntry is a cloud-based visitor registration system while TraceTogether is a mobile phone application which operates by exchanging anonymised identifiers between nearby phones via Bluetooth connection.

Conclusion

Digital contact tracing is likely to expand and continue to complement human-based contact tracing for the current and future pandemics. However, at this juncture, it is not ready to replace the manual and meticulous work that only Singapore contact tracers can achieve.

A review and content analysis of national apps for COVID-19 management using Mobile Application Rating Scale (MARS)

The expansion of mobile health apps for the management of COVID-19 grew exponentially in recent months. However, no study has evaluated these apps. The objective of this study was to develop a reliable measure and rate the quality of COVID-19 mobile health apps, to eventually provide a roadmap for future mHealth app development. In this study, we used COVID-related keywords to identify apps for iOS and Android devices. 13 apps (13.5% of the total number of apps identified) were selected for evaluation. App quality was assessed independently using MARS by two reviewers. Search queries yielded a total of 97 potentially relevant apps, of which 13 met our final inclusion criteria. Kendall's coefficient of concordance value for the inter-rater agreement was 0.93 (p = .03). COVID-19 GOV PK app had the highest average MARS score (4.7/5), and all of the apps had acceptable MARS scores (> 3.0). This study suggests that most COVID-related apps meet acceptable criteria for quality, content, or functionality, and they must highlight esthetic and interesting features for overall quality improvement to be welcomed by users.

[Acceptability of the use of mobile phones for HIV management in Togo]

OBJECTIVE

To describe the acceptability and factors associated with the use of mobile telephones in the care of people living with HIV (PLHIV) in Lom&#233;, Togo.

METHOD

A cross-sectional study was conducted from January&#160;5th to March&#160;31st, 2018 in Lom&#233;. PLHIV were recruited from the Department of Infectious and Tropical Diseases of the teaching hospital &#8220;CHU Sylvanus Olympio&#8221; and the NGO &#8220;Espoir Vie Togo&#8221;. Socio-demographic and clinical data, mobile phone possession and acceptability of communication with health professionals using a mobile phone were collected with a standardized questionnaire during a face-to-face interview.

RESULTS

A total of 259 PLHIV (79.6% women) were recruited. The mean age (&#177; standard deviation) of PLHIV was 43.7 &#177; 9.8&#160;years and the majority (95.4%) had a mobile phone. Almost all (98.1%) of respondents declared that mobile phone could be a means to maintain contact with a health professional. Phone calls (43.0%), text messages (SMS) (35.1%), and voice messages (20.0%) were the preferred means of communication with health professionals. Factors associated with the acceptability of receiving SMS from a&#160;health professional were age &lt;&#160;44&#160;years and having at least a secondary level of education.

CONCLUSION

PLHIV are receptive to the integration of mobile technology into the management of their condition. M-health could be an opportunity to improve the management of HIV infection in Togo.

Automated and partly automated contact tracing: a systematic review to inform the control of COVID-19

Evidence for the use of automated or partly automated contact-tracing tools to contain severe acute respiratory syndrome coronavirus 2 is scarce. We did a systematic review of automated or partly automated contact tracing. We searched PubMed, EMBASE, OVID Global Health, EBSCO Medical COVID Information Portal, Cochrane Library, medRxiv, bioRxiv, arXiv, and Google Advanced for articles relevant to COVID-19, severe acute respiratory syndrome, Middle East respiratory syndrome, influenza, or Ebola virus, published from Jan 1, 2000, to April 14, 2020. We also included studies identified through professional networks up to April 30, 2020. We reviewed all full-text manuscripts. Primary outcomes were the number or proportion of contacts (or subsequent cases) identified. Secondary outcomes were indicators of outbreak control, uptake, resource use, cost-effectiveness, and lessons learnt. This study is registered with PROSPERO (CRD42020179822). Of the 4036 studies identified, 110 full-text studies were reviewed and 15 studies were included in the final analysis and quality assessment. No empirical evidence of the effectiveness of automated contact tracing (regarding contacts identified or transmission reduction) was identified. Four of seven included modelling studies that suggested that controlling COVID-19 requires a high population uptake of automated contact-tracing apps (estimates from 56% to 95%), typically alongside other control measures. Studies of partly automated contact tracing generally reported more complete contact identification and follow-up compared with manual systems. Automated contact tracing could potentially reduce transmission with sufficient population uptake. However, concerns regarding privacy and equity should be considered. Well designed prospective studies are needed given gaps in evidence of effectiveness, and to investigate the integration and relative effects of manual and automated systems. Large-scale manual contact tracing is therefore still key in most contexts.

Extensions and adaptations of existing medical information system in order to reduce social contacts during COVID-19 pandemic

OBJECTIVE

The main objective of this paper is the reduction of the COVID-19 pandemic spread by increasing the degree of social distancing by using and upgrading the existing Medical Information System (MIS).

MATERIAL AND METHODS

The existing MIS MEDIS.NET, currently used in the largest health center in the Balkans, has been adapted and further developed.

RESULTS

During the adaptation of existing MIS MEDIS.NET 4 new and 9 existing modules were developed. A quick questionnaire for the smart triage of patients was also implemented.

DISCUSSION

The adapted MIS successfully influenced the reduction of social contacts within the Health Center Nis. The need for the arrival of children and their parents to receive appropriate health certificates for the school enrolment is reduced. The therapy of chronic patients has been prolonged for 6 months via an electronic prescription. An online service for the communication between patients and the chosen physicians is provided. Possible social contacts and exposure to the viral environment of patients are reduced by making appointments in extended slots and at determined physical locations. Patients are notified per SMS or email about the availability of chosen and physician on duty. The social distancing of patients and physicians is also established by sending laboratory analyses per email or SMS. Keeping the central registry for COVID-19 is enabled throughout the country.

CONCLUSION

The smart adaptation of MIS, and its collaboration with other state systems can significantly influence the reduction of social contacts and thus mitigate the consequences of COVID-19 pandemic.

Contact Tracing: An Opportunity for Social Work to Lead

Since the novel coronavirus disease (COVID-19) first emerged in December 2019, there have been unprecedented efforts worldwide to contain and mitigate the rapid spread of the virus through evidence-based public health measures. As a component of pandemic response in the United States, efforts to develop, launch, and scale-up contact tracing initiatives are rapidly expanding, yet the presence of social work is noticeably absent. In this paper, we identify the specialized skill set necessary for high quality contact tracing in the COVID-19 era and explore its alignment with social work competencies and skills. Described are current examples of contact tracing efforts, and an argument for greater social work leadership, based on the profession's ethics, competencies and person-in-environment orientation is offered. In light of the dire need for widespread high-quality contact tracing, social work is well-positioned to participate in interprofessional efforts to design, oversee and manage highly effective front-line contact tracing efforts.

Motivations for Social Distancing and App Use as Complementary Measures to Combat the COVID-19 Pandemic: Quantitative Survey Study

Background

The current COVID-19 pandemic is showing negative effects on human health as well as on social and economic life. It is a critical and challenging task to revive public life while minimizing the risk of infection. Reducing interactions between people by social distancing is an effective and prevalent measure to reduce the risk of infection and spread of the virus within a community. Current developments in several countries show that this measure can be technologically accompanied by mobile apps; meanwhile, privacy concerns are being intensively discussed.

Objective

The aim of this study was to examine central cognitive variables that may constitute people’s motivations for social distancing, using an app, and providing health-related data requested by two apps that differ in their direct utility for the individual user. The results may increase our understanding of people’s concerns and convictions, which can then be specifically addressed by public-oriented communication strategies and appropriate political decisions.

Methods

This study refers to the protection motivation theory, which is adaptable to both health-related and technology-related motivations. The concept of social trust was added. The quantitative survey included answers from 406 German-speaking participants who provided assessments of data security issues, trust components, and the processes of threat and coping appraisal related to the prevention of SARS-CoV-2 infection by social distancing. With respect to apps, one central focus was on the difference between a contact tracing app and a data donation app.

Results

Multiple regression analyses showed that the present model could explain 55% of the interindividual variance in the participants’ motivation for social distancing, 46% for using a contact tracing app, 42% for providing their own infection status to a contact tracing app, and 34% for using a data donation app. Several cognitive components of threat and coping appraisal were related to motivation measurements. Trust in other people’s social distancing behavior and general trust in official app providers also played important roles; however, the participants’ age and gender did not. Motivations for using and accepting a contact tracing app were higher than those for using and accepting a data donation app.

Conclusions

This study revealed some important cognitive factors that constitute people’s motivation for social distancing and using apps to combat the COVID-19 pandemic. Concrete implications for future research, public-oriented communication strategies, and appropriate political decisions were identified and are discussed.