Performance of Digital Contact Tracing Tools for COVID-19 Response in Singapore: Cross-Sectional Study

Effectiveness of probabilistic contact tracing in epidemic containment: The role of superspreaders and transmission path reconstruction

The recent COVID-19 pandemic underscores the significance of early stage nonpharmacological intervention strategies. The widespread use of masks and the systematic implementation of contact tracing strategies provide a potentially equally effective and socially less impactful alternative to more conventional approaches, such as large-scale mobility restrictions. However, manual contact tracing faces strong limitations in accessing the network of contacts, and the scalability of currently implemented protocols for smartphone-based digital contact tracing becomes impractical during the rapid expansion phases of the outbreaks, due to the surge in exposure notifications and associated tests. A substantial improvement in digital contact tracing can be obtained through the integration of probabilistic techniques for risk assessment that can more effectively guide the allocation of diagnostic tests. In this study, we first quantitatively analyze the diagnostic and social costs associated with these containment measures based on contact tracing, employing three state-of-the-art models of SARS-CoV-2 spreading. Our results suggest that probabilistic techniques allow for more effective mitigation at a lower cost. Secondly, our findings reveal a remarkable efficacy of probabilistic contact-tracing techniques in performing backward and multistep tracing and capturing superspreading events.

Estimating the impact of test-trace-isolate-quarantine systems on SARS-CoV-2 transmission in Australia

BACKGROUND

Australian states and territories used test-trace-isolate-quarantine (TTIQ) systems extensively in their response to the COVID-19 pandemic in 2020-2021. We report on an analysis of Australian case data to estimate the impact of test-trace-isolate-quarantine systems on SARS-CoV-2 transmission.

METHODS

Our analysis uses a novel mathematical modelling framework and detailed surveillance data on COVID-19 cases including dates of infection and dates of isolation. First, we directly translate an empirical distribution of times from infection to isolation into reductions in potential for onward transmission during periods of relatively low caseloads (tens to hundreds of reported cases per day). We then apply a simulation approach, validated against case data, to assess the impact of case-initiated contact tracing on transmission during a period of relatively higher caseloads and system stress (up to thousands of cases per day).

RESULTS

We estimate that under relatively low caseloads in the state of New South Wales (tens of cases per day), TTIQ contributed to a 54% reduction in transmission. Under higher caseloads in the state of Victoria (hundreds of cases per day), TTIQ contributed to a 42% reduction in transmission. Our results also suggest that case-initiated contact tracing can support timely quarantine in times of system stress (thousands of cases per day).

CONCLUSION

Contact tracing systems for COVID-19 in Australia were highly effective and adaptable in supporting the national suppression strategy from 2020-21, prior to the emergence of the Omicron variant in November 2021. TTIQ systems were critical to the maintenance of the strong suppression strategy and were more effective when caseloads were (relatively) low.

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.

Identifying Contact Time Required for Secondary Transmission of Clostridioides difficile Infections by Using Real-Time Locating System

Considering patient room shortages and prevalence of other communicable diseases, reassessing the isolation of patients with Clostridioides difficile infection (CDI) is imperative. We conducted a retrospective study to investigate the secondary CDI transmission rate in a hospital in South Korea, where patients with CDI were not isolated. Using data from a real-time locating system and electronic medical records, we investigated patients who had both direct and indirect contact with CDI index patients. The primary outcome was secondary CDI transmission, identified by whole-genome sequencing. Among 909 direct and 2,711 indirect contact cases, 2 instances of secondary transmission were observed (2 [0.05%] of 3,620 cases), 1 transmission via direct contact and 1 via environmental sources. A low level of direct contact (113 minutes) was required for secondary CDI transmission. Our findings support the adoption of exhaustive standard preventive measures, including environmental decontamination, rather than contact isolation of CDI patients in nonoutbreak settings.

Leveraging Bluetooth low-energy technology to improve contact tracing among healthcare personnel in hospital setting during the coronavirus disease 2019 (COVID-19) pandemic

To improve contact tracing for healthcare workers, we built and configured a Bluetooth low-energy system. We predicted close contacts with great accuracy and provided an additional contact yield of 14.8%. This system would decrease the effective reproduction number by 56% and would unnecessarily quarantine 0.74% of employees weekly.

Use of a digital contact tracing system in Singapore to mitigate COVID-19 spread

BACKGROUND

Contact tracing has been essential to reducing spread of COVID-19. Singapore leveraged technology to assist with contact tracing efforts using a Bluetooth-based app and token platform called 'TraceTogether'.

METHODS

We reviewed the impact of this system during the country's Delta and Omicron waves (24 August 2021 to 17 February 2022) to identify differences in number of close contacts and time savings between full automation using TraceTogether alone as compared to manual contact tracing supplemented by TraceTogether. Characteristics of digital contact tracing app or token users were reviewed. Thereafter, the number of close contacts identified by manual and digital contact tracing methods, and the number of confirmed COVID-19 cases among contacts were analysed. The difference in time taken for identification of close contacts was also determined.

FINDINGS

Adoption rate for TraceTogether was high, with 93.3% of cases having a registered device. There was a 9.8 h (34.9%) reduction in time savings for close contacts to be informed using TraceTogether alone compared to manual contact tracing supplemented by TraceTogether. The proportion of close contacts automatically identified through TraceTogether alone and turned positive was 3.6%. For those identified through manual contact tracing supplemented by TraceTogether, this proportion was 12.5% and 6.2% for those served quarantine orders and health risk warnings respectively.

INTERPRETATION

The high adoption rate of 'TraceTogether' suggest that digital solutions remain a promising option to improve contact tracing in future epidemics. This may have been through its concurrent use with vaccine differentiated public health measures and policies which engender public trust. There is future potential for utilising such technology in managing communicable diseases to achieve good public health outcomes.

Community-Based Digital Contact Tracing of Emerging Infectious Diseases: Design and Implementation Study With Empirical COVID-19 Cases

BACKGROUND

Contact tracing for containing emerging infectious diseases such as COVID-19 is resource intensive and requires digital transformation to enable timely decision-making.

OBJECTIVE

This study demonstrates the design and implementation of digital contact tracing using multimodal health informatics to efficiently collect personal information and contain community outbreaks. The implementation of digital contact tracing was further illustrated by 3 empirical SARS-CoV-2 infection clusters.

METHODS

The implementation in Changhua, Taiwan, served as a demonstration of the multisectoral informatics and connectivity between electronic health systems needed for digital contact tracing. The framework incorporates traditional travel, occupation, contact, and cluster approaches and a dynamic contact process enabled by digital technology. A centralized registry system, accessible only to authorized health personnel, ensures privacy and data security. The efficiency of the digital contact tracing system was evaluated through a field study in Changhua.

RESULTS

The digital contact tracing system integrates the immigration registry, communicable disease report system, and national health records to provide real-time information about travel, occupation, contact, and clusters for potential contacts and to facilitate a timely assessment of the risk of COVID-19 transmission. The digitalized system allows for informed decision-making regarding quarantine, isolation, and treatment, with a focus on personal privacy. In the first cluster infection, the system monitored 665 contacts and isolated 4 (0.6%) cases; none of the contacts (0/665, 0%) were infected during quarantine. The estimated reproduction number of 0.92 suggests an effective containment strategy for preventing community-acquired outbreak. The system was also used in a cluster investigation involving foreign workers, where none of the 462 contacts (0/462, 0%) tested positive for SARS-CoV-2.

CONCLUSIONS

By integrating the multisectoral database, the contact tracing process can be digitalized to provide the information required for risk assessment and decision-making in a timely manner to contain a community-acquired outbreak when facing the outbreak of emerging infectious disease.

Innovative applications of artificial intelligence in zoonotic disease management

Zoonotic diseases, transmitted between humans and animals, pose a substantial threat to global public health. In recent years, artificial intelligence (AI) has emerged as a transformative tool in the fight against diseases. This comprehensive review discusses the innovative applications of AI in the management of zoonotic diseases, including disease prediction, early diagnosis, drug development, and future prospects. AI-driven predictive models leverage extensive datasets to predict disease outbreaks and transmission patterns, thereby facilitating proactive public health responses. Early diagnosis benefits from AI-powered diagnostic tools that expedite pathogen identification and containment. Furthermore, AI technologies have accelerated drug discovery by identifying potential drug targets and optimizing candidate drugs. This review addresses these advancements, while also examining the promising future of AI in zoonotic disease control. We emphasize the pivotal role of AI in revolutionizing our approach to managing zoonotic diseases and highlight its potential to safeguard the health of both humans and animals on a global scale.

A Situational Analysis of the Impact of the COVID-19 Pandemic on Digital Health Research Initiatives in South Asia

The objective of this paper was to evaluate and compare the quantity and sustainability of digital health initiatives in the South Asia region before and during the COVID-19 pandemic. The study used a two-step methodology of (a) descriptive analysis of digital health research articles published from 2016 to 2021 from South Asia in terms of stratification of research articles based on diseases and conditions they were developed, geography, and tasks wherein the initiative was applied and (b) a simple and replicable tool developed by authors to assess the sustainability of digital health initiatives using experimental or observational study designs. The results of the descriptive analysis highlight the following: (a) there was a 40% increase in the number of studies reported in 2020 when compared to 2019; (b) the three most common areas wherein substantive digital health research has been focused are health systems strengthening, ophthalmic disorders, and COVID-19; and (c) remote consultation, health information delivery, and clinical decision support systems are the top three commonly developed tools. We developed and estimated the inter-rater operability of the sustainability assessment tool ascertained with a Kappa value of 0.806 (±0.088). We conclude that the COVID-19 pandemic has had a positive impact on digital health research with an improvement in the number of digital health initiatives and an improvement in the sustainability score of studies published during the COVID-19 pandemic.

Harnessing a real-time location system for contact tracing in a busy emergency department

BACKGROUND

With the persistent threat of emerging infectious diseases (EIDs), digital contact tracing (CT) tools can augment conventional CT for the prevention of healthcare-associated infectious disease transmission. However, their performance has yet to be evaluated comprehensively in the fast-paced emergency department (ED) setting.

OBJECTIVE

This study compared the CT performance of a radiofrequency identification (RFID)-based real-time location system (RTLS) with conventional electronic medical record (EMR) review against continuous direct observation of close contacts ('gold standard') in a busy ED during the coronavirus disease 2019 pandemic period.

METHODS

This cross-sectional study was conducted at the ED of a large tertiary care hospital in Singapore from December 2020 to April 2021. CT performance [sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and kappa] of the RTLS, EMR review and a combination of the two approaches (hybrid CT) was compared with direct observation. Finally, the mean absolute error (MAE) in the duration of each contact episode found via the RTLS and direct observation was calculated.

RESULTS

In comparison with EMR review, both the RTLS and the hybrid CT approach had higher sensitivity (0.955 vs 0.455 for EMR review) and a higher NPV (0.997 vs 0.968 for EMR review). The RTLS had the highest PPV (0.777 vs 0.714 for EMR review vs 0.712 for hybrid CT). The RTLS had the strongest agreement with direct observation (kappa=0.848). The MAE between contact durations of 80 direct observations and their respective RTLS contact times was 1.81 min.

CONCLUSION

The RTLS was validated to be a high-performing CT tool, with significantly higher sensitivity than conventional CT via EMR review. The RTLS can be used with confidence in time-strapped EDs for time-sensitive CT for the prevention of healthcare-associated transmission of EIDs.

Individual level analysis of digital proximity tracing for COVID-19 in Belgium highlights major bottlenecks

To complement labour-intensive conventional contact tracing, digital proximity tracing was implemented widely during the COVID-19 pandemic. However, the privacy-centred design of the dominant Google-Apple exposure notification framework has hindered assessment of its effectiveness. Between October 2021 and January 2022, we systematically collected app use and notification receipt data within a test and trace programme targeting around 50,000 university students in Leuven, Belgium. Due to low success rates in each studied step of the digital notification cascade, only 4.3% of exposed contacts (CI: 2.8-6.1%) received such notifications, resulting in 10 times more cases detected through conventional contact tracing. Moreover, the infection risk of digitally traced contacts (5.0%; CI: 3.0-7.7%) was lower than that of conventionally traced non-app users (9.8%; CI: 8.8-10.7%; p = 0.002). Contrary to common perception as near instantaneous, there was a 1.2-day delay (CI: 0.6-2.2) between case PCR result and digital contact notification. These results highlight major limitations of a digital proximity tracing system based on the dominant framework.

The promise of digital healthcare technologies

Digital health technologies have been in use for many years in a wide spectrum of healthcare scenarios. This narrative review outlines the current use and the future strategies and significance of digital health technologies in modern healthcare applications. It covers the current state of the scientific field (delineating major strengths, limitations, and applications) and envisions the future impact of relevant emerging key technologies. Furthermore, we attempt to provide recommendations for innovative approaches that would accelerate and benefit the research, translation and utilization of digital health technologies.

Correlating global trends in COVID-19 cases with online symptom checker self-assessments

BACKGROUND

Online symptom checkers are digital health solutions that provide a differential diagnosis based on a user's symptoms. During the coronavirus disease 2019 (COVID-19) pandemic, symptom checkers have become increasingly important due to physical distance constraints and reduced access to in-person medical consultations. Furthermore, various symptom checkers specialised in the assessment of COVID-19 infection have been produced.

OBJECTIVES

Assess the correlation between COVID-19 risk assessments from an online symptom checker and current trends in COVID-19 infections. Analyse whether those correlations are reflective of various country-wise quality of life measures. Lastly, determine whether the trends found in symptom checker assessments predict or lag relative to those of the COVID-19 infections.

MATERIALS AND METHODS

In this study, we compile the outcomes of COVID-19 risk assessments provided by the symptom checker Symptoma (www.symptoma.com) in 18 countries with suitably large user bases. We analyse this dataset's spatial and temporal features compared to the number of newly confirmed COVID-19 cases published by the respective countries.

RESULTS

We find an average correlation of 0.342 between the number of Symptoma users assessed to have a high risk of a COVID-19 infection and the official COVID-19 infection numbers. Further, we show a significant relationship between that correlation and the self-reported health of a country. Lastly, we find that the symptom checker is, on average, ahead (median +3 days) of the official infection numbers for most countries.

CONCLUSION

We show that online symptom checkers can capture the national-level trends in coronavirus infections. As such, they provide a valuable and unique information source in policymaking against pandemics, unrestricted by conventional resources.

Addressing Complexity in the Pandemic Context: How Systems Thinking Can Facilitate Understanding of Design Aspects for Preventive Technologies

The COVID-19 pandemic constitutes a wicked problem that is defined by rapidly evolving and dynamic conditions, where the physical world changes (e.g., pathogens mutate) and, in parallel, our understanding and knowledge rapidly progress. Various preventive measures have been developed or proposed to manage the situation, including digital preventive technologies to support contact tracing or physical distancing. The complexity of the pandemic and the rapidly evolving nature of the situation pose challenges for the design of effective preventive technologies. The aim of this conceptual paper is to apply a systems thinking model, DSRP (distinctions, systems, relations, perspectives) to explain the underlying assumptions, patterns, and connections of the pandemic domain, as well as to identify potential leverage points for design of preventive technologies. Two different design approaches, contact tracing and nudging for distance, are compared, focusing on how their design and preventive logic are related to system complexity. The analysis explains why a contact tracing technology involves more complexity, which can challenge both implementation and user understanding. A system utilizing nudges can operate using a more distinct system boundary, which can benefit understanding and implementation. However, frequent nudges might pose challenges for user experience. This further implies that these technologies have different contextual requirements and are useful at different levels in society. The main contribution of this work is to show how systems thinking can organize our understanding and guide the design of preventive technologies in the context of epidemics and pandemics.

Nurse, Give Me the News! Understanding Support for and Opposition to a COVID-19 Health Screening System

Helping the sick and protecting the vulnerable has long been the credo of the health profession. In response to the coronavirus-disease-2019 (COVID-19 pandemic), hospitals and healthcare institutions have rapidly employed public health measures to mitigate patient and staff infection. This paper investigates staff and visitor responses to the COVID-19 eGate health screening system; a self-service technology (SST) which aims to protect health care workers and facilities from COVID-19. Our study evaluates the in situ deployment of the eGate, and employs a System Usability Scale (SUS) and questionnaire (n = 220) to understand staff and visitor's acceptance of the eGate. In detailing the themes relevant to those who advocate for the system and those who oppose it, we contribute towards a more detailed understanding of the use and non-use of health-screening SSTs. We conclude with a series of considerations for the design of future interactive screening systems within hospitals.

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.

Defining Key Performance Indicators for the California COVID-19 Exposure Notification System (CA Notify)

OBJECTIVES

Toward common methods for system monitoring and evaluation, we proposed a key performance indicator framework and discussed lessons learned while implementing a statewide exposure notification (EN) system in California during the COVID-19 epidemic.

MATERIALS AND METHODS

California deployed the Google Apple Exposure Notification framework, branded CA Notify, on December 10, 2020, to supplement traditional COVID-19 contact tracing programs. For system evaluation, we defined 6 key performance indicators: adoption, retention, sharing of unique codes, identification of potential contacts, behavior change, and impact. We aggregated and analyzed data from December 10, 2020, to July 1, 2021, in compliance with the CA Notify privacy policy.

RESULTS

We estimated CA Notify adoption at nearly 11 million smartphone activations during the study period. Among 1 654 201 CA Notify users who received a positive test result for SARS-CoV-2, 446 634 (27%) shared their unique code, leading to ENs for other CA Notify users who were in close proximity to the SARS-CoV-2-positive individual. We identified at least 122 970 CA Notify users as contacts through this process. Contact identification occurred a median of 4 days after symptom onset or specimen collection date of the user who received a positive test result for SARS-CoV-2.

PRACTICE IMPLICATIONS

Smartphone-based EN systems are promising new tools to supplement traditional contact tracing and public health interventions, particularly when efficient scaling is not feasible for other approaches. Methods to collect and interpret appropriate measures of system performance must be refined while maintaining trust and privacy.

Contact tracing using real-time location system (RTLS): a simulation exercise in a tertiary hospital in Singapore

OBJECTIVE

We aim to assess the effectiveness of contact tracing using real-time location system (RTLS) compared with the conventional (electronic medical records (EMRs)) method via an emerging infectious disease (EID) outbreak simulation exercise. The aims of the study are: (1) to compare the time taken to perform contact tracing and list of contacts identified for RTLS versus EMR; (2) to compare manpower and manpower-hours required to perform contact tracing for RTLS versus EMR; and (3) to extrapolate the cost incurred by RTLS versus EMR.

DESIGN

Prospective case study.

SETTING

Sengkang General Hospital, a 1000-bedded public tertiary hospital in Singapore.

PARTICIPANTS

1000 out of 4000 staff wore staff tags in this study.

INTERVENTIONS

A simulation exercise to determine and compare the list of contacts, time taken, manpower and manpower-hours required between RTLS and conventional methods of contact tracing. Cost of both methods were compared.

PRIMARY AND SECONDARY OUTCOME MEASURES

List of contacts, time taken, manpower required, manpower-hours required and cost incurred.

RESULTS

RTLS identified almost three times the number of contacts compared with conventional methods, while achieving that with a 96.2% reduction in time taken, 97.6% reduction in manpower required and 97.5% reduction in manpower-hours required. However, RTLS incurred significant equipment cost and might take many contact tracing episodes before providing economic benefit.

CONCLUSION

Although costly, RTLS is effective in contact tracing. RLTS might not be ready at present time to replace conventional methods, but with further refinement, RTLS has the potential to be the gold standard in contact tracing methods of the future, particularly in the current pandemic.

Moving toward a common goal via cross-sector collaboration: lessons learned from SARS to COVID-19 in Singapore

Background

The spread of COVID-19 has taken a toll on many countries and its healthcare system over the last two years. Governments have sought to mitigate the repercussions of the pandemic by implementing aggressive top-down control measures and introducing immense fiscal spending. Singapore is no exception to this trend. Owing to a whole-of-society approach, Singapore is still being lauded globally for its relatively successful record at controlling both community and trans-border spread. One notable effort by the Singapore government has taken place through its cross-sectoral collaborative partnerships with the private stakeholders behind the success.

Methods/results

In an attempt to better explain Singapore’s robust yet strategic response to COVID-19, this study focuses on how the experience of the SARS outbreak has informed the government’s collaborative efforts with other stakeholders in society, beyond mere transnational cooperation. Taking a comparative case study approach in the specific context of Singapore, we perform a content analysis of related government documents, mainstream newspaper articles, and academic journal articles in an inductive manner. By closely comparing two global healthcare outbreaks, we note four differences in approach. First, during the COVID-19 pandemic, Singapore has focused on securing sufficient essential healthcare resources with contingency plans to strengthen preparedness. Second, the government has actively harnessed the capacity of private entities to promote the resilience of the healthcare system and the community. Third, Singapore’s management policies have been made not only in a top-down, centralized style during the initial response stage, but also with a greater proportion of bottom-up approaches, particularly as the pandemic trudges on. More interestingly, the multi-faceted repercussions of COVID-19 have gradually opened the door to a greater variety of collaborative partnerships in sectors beyond healthcare services. The participating stakeholders include, but are not limited to, local and international business actors, non-profit organizations, academia and other countries. Lastly, as the pandemic has continued, the Singapore government has managed outward to tap the expertise and knowledge of the private sector, in particular leveraging science and technology to improve control measures and putting supportive programs into practice.

Conclusion

The evidence from our focused analyses demonstrates that the nature and scale of the COVID-19 pandemic produced more collaborative partnerships between the public and private sectors in Singapore as compared with the SARS outbreak. What is more, our findings offer evidence that through adaptive learning from the prior global healthcare outbreak, plus some trial and error during the initial phase of the ongoing pandemic, public- and private-sector partners, both in and outside of the healthcare service sector, have tended to “act alike,” working together to achieve a common goal. Both have been socially responsible, providing public services to people in need to promote the rapid resilience of the community, and sharing the associated risks. Overall, this study has deep and wide implications for other governments and policy makers who are still struggling to maximize essential resources and minimize the negative impacts of the healthcare crisis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12992-022-00873-x.

Educate to transform: An innovative experience for faculty training

Learning-focussed educational models require the development of pedagogical, methodological, assessment and technological competences among the faculty community. The COVID-19 pandemic has accentuated the need for this training. This study evaluates the impact of the training project "Educate to Transform" on teacher attitudes, knowledge and on the implementation of innovative teaching methodologies. There were 695 faculty participants in the program conducted at the Universidad Francisco de Vitoria (UFV). Participants included full-time professors (FULL-PROF) and part-time professors (PART-PROF). The measurement instrument was validated using the entire sample and a subsample of 357 participants was used to analyse the impact of the program (pre and post measurement). Professor attitudes and knowledge of or familiarity with innovative methodologies and their application in the classroom were evaluated. The findings show that the program improved the attitudes of teachers towards innovation, raised the level of awareness and number of methodologies implemented in the classroom. The methodology towards more experiential and collaborative learning is effective in transforming teaching practice. Furthermore, the implementation of the program through the CANVAS platform, making teachers live the experience as learners, seems to have contributed to improve the teachers' attitude towards the LMS. The only difference found among the participants was a worse attitude towards innovation on the part of medical teachers, with a clearly differentiated profile of teachers and students, as well as a greater implementation of active methodologies by teachers with a lower teaching load. Overall, it may be concluded that the program achieved its proposed objectives.

The value of social interactions and incentives on the use of a digital contact tracing tool post COVID-19 lockdown in Singapore

We assessed the preferences and trade-offs for social interactions, incentives, and being traced by a digital contact tracing (DCT) tool post lockdown in Singapore by a discrete choice experiment (DCE) among 3839 visitors of a large public hospital in Singapore between July 2020 – February 2021. Respondents were sampled proportionately by gender and four age categories (21 – 80 years). The DCE questionnaire had three attributes (1. Social interactions, 2. Being traced by a DCT tool, 3. Incentives to use a DCT tool) and two levels each. Panel fixed conditional logit model was used to analyse the data. Respondents were more willing to trade being traced by a DCT tool for social interactions than incentives and unwilling to trade social interactions for incentives. The proportion of respondents preferring no incentives and could only be influenced by their family members increases with age. Among proponents of monetary incentives, the preferred median value for a month’s usage of DCT tools amounted to S$10 (USD7.25) and S$50 (USD36.20) for subsidies and lucky draw. In conclusion, DCE can be used to elicit profile-specific preferences to optimize the uptake of DCT tools during a pandemic. Social interactions are highly valued by the population, who are willing to trade them for being traced by a DCT tool during the COVID-19 pandemic. Although a small amount of incentive is sufficient to increase the satisfaction of using a DCT tool, incentives alone may not increase DCT tool uptake.

Impact of Hospital Characteristics and Governance Structure on the Adoption of Tracking Technologies for Clinical and Supply Chain Use: Longitudinal Study of US Hospitals

Background

Despite the increasing adoption rate of tracking technologies in hospitals in the United States, few empirical studies have examined the factors involved in such adoption within different use contexts (eg, clinical and supply chain use contexts). To date, no study has systematically examined how governance structures impact technology adoption in different use contexts in hospitals. Given that the hospital governance structure fundamentally governs health care workflows and operations, understanding its critical role provides a solid foundation from which to explore factors involved in the adoption of tracking technologies in hospitals.

Objective

This study aims to compare critical factors associated with the adoption of tracking technologies for clinical and supply chain uses and examine how governance structure types affect the adoption of tracking technologies in hospitals.

Methods

This study was conducted based on a comprehensive and longitudinal national census data set comprising 3623 unique hospitals across 50 states in the United States from 2012 to 2015. Using mixed effects population logistic regression models to account for the effects within and between hospitals, we captured and examined the effects of hospital characteristics, locations, and governance structure on adjustments to the innate development of tracking technology over time.

Results

From 2012 to 2015, we discovered that the proportion of hospitals in which tracking technologies were fully implemented for clinical use increased from 36.34% (782/2152) to 54.63% (1316/2409), and that for supply chain use increased from 28.58% (615/2152) to 41.3% (995/2409). We also discovered that adoption factors impact the clinical and supply chain use contexts differently. In the clinical use context, compared with hospitals located in urban areas, hospitals in rural areas (odds ratio [OR] 0.68, 95% CI 0.56-0.80) are less likely to fully adopt tracking technologies. In the context of supply chain use, the type of governance structure influences tracking technology adoption. Compared with hospitals not affiliated with a health system, implementation rates increased as hospitals affiliated with a more centralized health system—1.9-fold increase (OR 1.87, 95% CI 1.60-2.13) for decentralized or independent hospitals, 2.4-fold increase (OR 2.40, 95% CI 2.07-2.80) for moderately centralized health systems, and 3.1-fold increase for centralized health systems (OR 3.07, 95% CI 2.67-3.53).

Conclusions

As the first of such type of studies, we provided a longitudinal overview of how hospital characteristics and governance structure jointly affect adoption rates of tracking technology in both clinical and supply chain use contexts, which is essential for developing intelligent infrastructure for smart hospital systems. This study informs researchers, health care providers, and policy makers that hospital characteristics, locations, and governance structures have different impacts on the adoption of tracking technologies for clinical and supply chain use and on health resource disparities among hospitals of different sizes, locations, and governance structures.

Physician perceptions of surveillance: Wearables, Apps, and Chatbots for COVID-19

Background and Purpose

To characterize the global physician community's opinions on the use of digital tools for COVID-19 public health surveillance and self-surveillance.

Materials and Methods

Cross-sectional, random, stratified survey done on Sermo, a physician networking platform, between September 9 and 15, 2020. We aimed to sample 1000 physicians divided among the USA, EU, and rest of the world. The survey questioned physicians on the risk-benefit ratio of digital tools, as well as matters of data privacy and trust.

Statistical Analysis Used

Descriptive statistics examined physicians' characteristics and opinions by age group, gender, frontline status, and geographic region. ANOVA, t-test, and Chi-square tests with P < 0.05 were viewed as qualitatively different. As this was an exploratory study, we did not adjust for small cell sizes or multiplicity. We used JMP Pro 15 (SAS), as well as Protobi.

Results

The survey was completed by 1004 physicians with a mean (standard deviation) age of 49.14 (12) years. Enthusiasm was highest for self-monitoring smartwatches (66%) and contact tracing apps (66%) and slightly lower (48-56%) for other tools. Trust was highest for health providers (68%) and lowest for technology companies (30%). Most respondents (69.8%) felt that loosening privacy standards to fight the pandemic would lead to misuse of privacy in the future.

Conclusion

The survey provides foundational insights into how physicians think of surveillance.

A Cross-Sectional Study of Knowledge, Attitudes, and Practices concerning COVID-19 Outbreaks in the General Population in Malang District, Indonesia

Lack of knowledge often leads to nonchalant attitudes and improper practices that expose people to greater risks during a pandemic. Therefore, improving the general public’s knowledge, attitudes, and practices (KAP) concerning coronavirus disease (COVID-19) can play a pivotal role in reducing the risks, especially in a country such as Indonesia with its scarcity of health resources for testing and tracing. Using the case of Malang District, this study set out to evaluate KAP regarding COVID-19 and its risk factors immediately after the Malang health authorities implemented various preventive measures. A population-based survey involving 3425 individuals was carried out between 1 May and 20 May 2020. Our findings revealed that less than half of the respondents demonstrated accurate knowledge (25.3%), positive attitudes (36.6%), or frequent best practices (48.8%) with regard to COVID-19 prevention. The results of logistic regression analyses showed that more accurate knowledge was associated with more positive attitudes and more frequent best practices (OR = 1.603, p-value < 0.001; OR = 1.585, p-value < 0.001, respectively). More positive attitudes were also associated with more frequent best practices (OR = 1.126, p-value < 0.001). The level of KAP varied according to sociodemographic characteristics, access to the services of community health workers, and mobile health technology for COVID-19 screening. Some global health proposals to improve health behaviors among the general public in the context of the scarcity of health resource settings are suggested based on the study findings.

Vaccines alone are no silver bullets: a modeling study on the impact of efficient contact tracing on COVID-19 infection and transmission in Malaysia

BACKGROUND

The computer simulation presented in this study aimed to investigate the effect of contact tracing on coronavirus disease 2019 (COVID-19) transmission and infection in the context of rising vaccination rates.

METHODS

This study proposed a deterministic, compartmental model with contact tracing and vaccination components. We defined contact tracing effectiveness as the proportion of contacts of a positive case that was successfully traced and the vaccination rate as the proportion of daily doses administered per population in Malaysia. Sensitivity analyses on the untraced and infectious populations were conducted.

RESULTS

At a vaccination rate of 1.4%, contact tracing with an effectiveness of 70% could delay the peak of untraced asymptomatic cases by 17 d and reduce it by 70% compared with 30% contact tracing effectiveness. A similar trend was observed for symptomatic cases when a similar experiment setting was used. We also performed sensitivity analyses by using different combinations of contact tracing effectiveness and vaccination rates. In all scenarios, the effect of contact tracing on COVID-19 incidence persisted for both asymptomatic and symptomatic cases.

CONCLUSIONS

While vaccines are progressively rolled out, efficient contact tracing must be rapidly implemented concurrently to reach, find, test, isolate and support the affected populations to bring COVID-19 under control.

Effectiveness evaluation of digital contact tracing for COVID-19 in New South Wales, Australia

BACKGROUND

Digital proximity tracing apps were rolled out early in the COVID-19 pandemic in many countries to complement conventional contact tracing. Empirical evidence about their benefits for pandemic response remains scarce. We evaluated the effectiveness and usefulness of COVIDSafe, Australia's national smartphone-based proximity tracing app for COVID-19.

METHODS

In this prospective study, done in New South Wales (NSW), Australia, we included all individuals in the state who were older than 12 years with confirmed, locally acquired SARS-CoV-2 infection between May 4 and Nov 4, 2020. We used data from the NSW Notifiable Conditions Information Management System, the national COVIDSafe database, and information from case interviews, including information on app usage, the number of app-suggested contacts, and the number of app-suggested contacts determined by public health staff to be actual close contacts. We calculated the positive predictive value and sensitivity of COVIDSafe, its additional contact yield, and the number of averted public exposure events. Semi-structured interviews with public health staff were done to assess the app's perceived usefulness.

FINDINGS

There were 619 confirmed COVID-19 cases with more than 25 300 close contacts identified by conventional contact tracing during the study period. COVIDSafe was used by 137 (22%) cases and detected 205 contacts, 79 (39%) of whom met the close contact definition. Its positive predictive value was therefore 39%. 35 (15%) of the 236 close contacts who could have been expected to have been using the app during the study period were identified by the app, making its estimated sensitivity 15%. 79 (0·3%) of the estimated 25 300 contacts in NSW were app-suggested and met the close contact definition. The app detected 17 (<0·1%) additional close contacts who were not identified by conventional contact tracing. COVIDSafe generated a substantial additional perceived workload for public health staff and was not considered useful.

INTERPRETATION

The low uptake of the app among cases probably led to a reduced sensitivity estimate in our study, given that only contacts who were using the app could be detected. COVIDSafe was not sufficiently effective to make a meaningful contribution to the COVID-19 response in Australia's most populous state over a 6 month period. We provide an empirical evaluation of this digital contact tracing app that questions the potential benefits of digital contact tracing apps to the public health response to COVID-19. Effectiveness evaluations should be integrated into future implementations of proximity contact tracing systems to justify their investment.

FUNDING

New South Wales Ministry of Health (Australia); National Health and Medical Research Council (Australia).

Digital Contact Tracing Applications against COVID-19: A Systematic Review

OBJECTIVE

The novel coronavirus 2019 (COVID-19) pandemic has triggered public anxiety around the world. So far, the evidence suggests that prevention on a public scale is the most effective health measure for thwarting the progress of COVID-19. Another critical aspect of preventing COVID-19 is contact tracing. We aimed to investigate the effectiveness of digital contact tracing applications currently available in the context of the COVID-19 pandemic.

METHODS

We undertook a systematic review and narrative synthesis of all literature relating to digital contact tracing applications in the context of COVID-19. We searched 3 major scientific databases. Only articles that were published in English and were available as full-text articles were selected for review. Data were extracted and narrative syntheses conducted.

RESULTS

Five studies relating to COVID-19 were included in the review. Our results suggest that digitalized contact tracing methods can be beneficial for impeding the progress of COVID-19. Three key themes were generated from this systematic review. First, the critical mass of adoption of applications must be attained at the population level before the sensitivity and positive predictive value of the solution can be increased. Second, usability factors such as access, ease of use, and the elimination of barriers are essential in driving this uptake. Third, privacy must be ensured where possible as it is the single most significant barrier against achieving critical mass.

CONCLUSION

Contact tracing methods have proved to be beneficial for impeding the progress of COVID-19 as compared to older, more labour-intensive manual methods.

Public opinion of the Irish “COVID Tracker” digital contact tracing App: A national survey

Objective

This study aims to gather public opinion on the Irish “COVID Tracker” digital contact tracing (DCT) App, with particular focus on App usage, usability, usefulness, technological issues encountered, and potential changes to the App.

Methods

A 35-item online questionnaire was deployed for 10 days in October 2020, 3 months after the launch of the Irish DCT App.

Results

A total of 2889 completed responses were recorded, with 2553 (88%) respondents currently using the App. Although four in five users felt the App is easy to download, is easy to use and looks professional, 615 users (22%) felt it had slowed down their phone, and 757 (28%) felt it had a negative effect on battery life. Seventy-nine percent of respondents reported the App's main function is to aid contact tracing. Inclusion of national COVID-19 trends is a useful ancillary function according to 87% of respondents, and there was an appetite for more granular local data. Overall, 1265 (44%) respondents believed the App is helping the national effort, while 1089 (38%) were unsure.

Conclusions

DCT Apps may potentially augment traditional contact tracing methods. Despite some reports of negative effects on phone performance, just 7% of users who have tried the App have deleted it. Ancillary functionality, such as up-to-date regional COVID-19, may encourage DCT App use. This study describes general positivity toward the Irish COVID Tracker App among users but also highlights the need for transparency on effectiveness of App-enabled contact tracing and for study of non-users to better establish barriers to use.

Toward a Common Performance and Effectiveness Terminology for Digital Proximity Tracing Applications

Digital proximity tracing (DPT) for Sars-CoV-2 pandemic mitigation is a complex intervention with the primary goal to notify app users about possible risk exposures to infected persons. DPT not only relies on the technical functioning of the proximity tracing application and its backend server, but also on seamless integration of health system processes such as laboratory testing, communication of results (and their validation), generation of notification codes, manual contact tracing, and management of app-notified users. Policymakers and DPT operators need to know whether their system works as expected in terms of speed or yield (performance) and whether DPT is making an effective contribution to pandemic mitigation (also in comparison to and beyond established mitigation measures, particularly manual contact tracing). Thereby, performance and effectiveness are not to be confused. Not only are there conceptual differences but also diverse data requirements. For example, comparative effectiveness measures may require information generated outside the DPT system, e.g., from manual contact tracing. This article describes differences between performance and effectiveness measures and attempts to develop a terminology and classification system for DPT evaluation. We discuss key aspects for critical assessments of whether the integration of additional data measurements into DPT apps may facilitate understanding of performance and effectiveness of planned and deployed DPT apps. Therefore, the terminology and a classification system may offer some guidance to DPT system operators regarding which measurements to prioritize. DPT developers and operators may also make conscious decisions to integrate measures for epidemic monitoring but should be aware that this introduces a secondary purpose to DPT. Ultimately, the integration of further information (e.g., regarding exact exposure time) into DPT involves a trade-off between data granularity and linkage on the one hand, and privacy on the other. More data may lead to better epidemiological information but may also increase the privacy risks associated with the system, and thus decrease public DPT acceptance. Decision-makers should be aware of the trade-off and take it into account when planning and developing DPT systems or intending to assess the added value of DPT relative to the existing contact tracing systems.

Pilot Evaluations of Two Bluetooth Contact Tracing Approaches on a University Campus: Mixed Methods Study

BACKGROUND

Many have proposed the use of Bluetooth technology to help scale up contact tracing for COVID-19. However, much remains unknown about the accuracy of this technology in real-world settings, the attitudes of potential users, and the differences between delivery formats (mobile app vs carriable or wearable devices).

OBJECTIVE

We pilot tested 2 separate Bluetooth contact tracing technologies on a university campus to evaluate their sensitivity and specificity, and to learn from the experiences of the participants.

METHODS

We used a convergent mixed methods study design, and participants included graduate students and researchers working on a university campus during June and July 2020. We conducted separate 2-week pilot studies for each Bluetooth technology. The first was for a mobile phone app ("app pilot"), and the second was for a small electronic "tag" ("tag pilot"). Participants validated a list of Bluetooth-identified contacts daily and reported additional close contacts not identified by Bluetooth. We used these data to estimate sensitivity and specificity. Participants completed a postparticipation survey regarding appropriateness, usability, acceptability, and adherence, and provided additional feedback via free text. We used tests of proportions to evaluate differences in survey responses between participants from each pilot, paired t tests to measure differences between compatible survey questions, and qualitative analysis to evaluate the survey's free-text responses.

RESULTS

Among 25 participants in the app pilot, 53 contact interactions were identified by Bluetooth and an additional 61 by self-report. Among 17 participants in the tag pilot, 171 contact interactions were identified by Bluetooth and an additional 4 by self-report. The tag had significantly higher sensitivity compared with the app (46/49, 94% vs 35/61, 57%; P<.001), as well as higher specificity (120/126, 95% vs 123/141, 87%; P=.02). Most participants felt that Bluetooth contact tracing was appropriate on campus (26/32, 81%), while significantly fewer participants felt that using other technologies, such as GPS or Wi-Fi, was appropriate (17/31, 55%; P=.02). Most participants preferred technology developed and managed by the university rather than a third party (27/32, 84%) and preferred not to have tracing apps on their personal phones (21/32, 66%), due to "concerns with privacy." There were no significant differences in self-reported adherence rates across pilots.

CONCLUSIONS

Convenient and carriable Bluetooth technology may improve tracing efficiency while alleviating privacy concerns by shifting data collection away from personal devices. With accuracy comparable to, and in this case, superior to, mobile phone apps, such approaches may be suitable for workplace or school settings with the ability to purchase and maintain physical devices.

Use of clinical data to augment healthcare worker contact tracing during the COVID-19 pandemic

OBJECTIVE

This work examined the secondary use of clinical data from the electronic health record (EHR) for screening our healthcare worker (HCW) population for potential exposures to patients with coronavirus disease 2019.

MATERIALS AND METHODS

We conducted a cross-sectional study at a free-standing, quaternary care pediatric hospital comparing first-degree, patient-HCW pairs identified by the hospital's COVID-19 contact tracing team (CTT) to those identified using EHR clinical event data (EHR Report). The primary outcome was the number of patient-HCW pairs detected by each process.

RESULTS

Among 233 patients with COVID-19, our EHR Report identified 4,116 patient-HCW pairs, including 2,365 (30.0%) of the 7,890 pairs detected by the CTT. The EHR Report also revealed 1,751 pairs not identified by the CTT. The highest number of patient-HCW pairs per patient was detected in the inpatient care venue. Nurses comprised the most frequently identified HCW role overall.

CONCLUSION

Automated methods to screen HCWs for potential exposure to patients with COVID-19 using clinical event data from the EHR are likely to improve epidemiologic surveillance by contact tracing programs and represent a viable and readily available strategy which should be considered by other institutions.

Public perception on the use of digital contact tracing tools post COVID-19 lockdown: Sentiment analysis and opinion mining (Preprint)

Background

Singapore’s national digital contact-tracing (DCT) tool—TraceTogether—attained an above 70% uptake by December 2020 after a slew of measures. Sentiment analysis can help policymakers to assess public sentiments on the implementation of new policy measures in a short time, but there is a paucity of sentiment analysis studies on the usage of DCT tools.

Objective

We sought to understand the public’s knowledge of, concerns with, and sentiments on the use of TraceTogether over time and their preferences for the type of TraceTogether tool.

Methods

We conducted a cross-sectional survey at a large public hospital in Singapore after the COVID-19 lockdown, from July 2020 through February 2021. In total, 4097 respondents aged 21-80 years were sampled proportionately by sex and 4 age groups. The open-ended responses were processed and analyzed using natural language processing tools. We manually corrected the language and logic errors and replaced phrases with words available in the syuzhet sentiment library without altering the original meaning of the phrases. The sentiment scores were computed by summing the scores of all the tokens (phrases split into smaller units) in the phrase. Stopwords (prepositions and connectors) were removed, followed by implementing the bag-of-words model to calculate the bigram and trigram occurrence in the data set. Demographic and time filters were applied to segment the responses.

Results

Respondents’ knowledge of and concerns with TraceTogether changed from a focus on contact tracing and Bluetooth activation in July-August 2020 to QR code scanning and location check-ins in January-February 2021. Younger males had the highest TraceTogether uptake (24/40, 60%), while older females had the lowest uptake (8/34, 24%) in the first half of July 2020. This trend was reversed in mid-October after the announcement on mandatory TraceTogether check-ins at public venues. Although their TraceTogether uptake increased over time, older females continued to have lower sentiment scores. The mean sentiment scores were the lowest in January 2021 when the media reported that data collected by TraceTogether were used for criminal investigations. Smartphone apps were initially preferred over tokens, but the preference for the type of TraceTogether tool equalized over time as tokens became accessible to the whole population. The sentiments on token-related comments became more positive as the preference for tokens increased.

Conclusions

The public’s knowledge of and concerns with the use of a mandatory DCT tool varied with the national regulations and public communications over time with the evolution of the COVID-19 pandemic. Effective communications tailored to subpopulations and greater transparency in data handling will help allay public concerns with data misuse and improve trust in the authorities. Having alternative forms of the DCT tool can increase the uptake of and positive sentiments on DCT.

COVID-19 digital contact tracing applications and techniques: A review post initial deployments

The coronavirus disease 2019 (COVID-19) is a severe global pandemic that has claimed millions of lives and continues to overwhelm public health systems in many countries. The spread of COVID-19 pandemic has negatively impacted the human mobility patterns such as daily transportation-related behavior of the public. There is a requirement to understand the disease spread patterns and its routes among neighboring individuals for the timely implementation of corrective measures at the required placement. To increase the effectiveness of contact tracing, countries across the globe are leveraging advancements in mobile technology and Internet of Things (IoT) to aid traditional manual contact tracing to track individuals who have come in close contact with identified COVID-19 patients. Even as the first administration of vaccines begins in 2021, the COVID-19 management strategy will continue to be multi-pronged for the foreseeable future with digital contact tracing being a vital component of the response along with the use of preventive measures such as social distancing and the use of face masks. After some months of deployment of digital contact tracing technology, deeper insights into the merits of various approaches and the usability, privacy, and ethical trade-offs involved are emerging. In this paper, we provide a comprehensive analysis of digital contact tracing solutions in terms of their methodologies and technologies in the light of the new data emerging about international experiences of deployments of digital contact tracing technology. We also provide a discussion on open challenges such as scalability, privacy, adaptability and highlight promising directions for future work.

One Year on: An Overview of Singapore's Response to COVID-19-What We Did, How We Fared, How We Can Move Forward

Background-One year has passed since the first COVID-19 case in Singapore. This scoping review commemorates Singaporean researchers that have expanded the knowledge on this novel virus. We aim to provide an overview of healthcare-related articles published in peer-reviewed journals, authored by the Singapore research community about COVID-19 during the first year of the pandemic. Methods-This was reported using the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) protocol. It included healthcare-related articles about COVID-19 published between 23 January 2020 and 22 January 2021 with a Singapore-affiliated author. MEDLINE, Embase, Scopus, Web of Science, CINAHL, PsycINFO, Google Scholar, and local journals were searched. The articles were screened independently by two reviewers. Results-The review included 504 articles. Most of the articles narrated the changes to hospital practice (210), while articles on COVID-19 pathology (94) formed most of the non-narrative papers. Publications on public health (61) and the indirect impacts to clinical outcomes (45) were other major themes explored by the research community. The remaining articles detailed the psychological impact of the pandemic (35), adaptations of medical education (30), and narratives of events (14). Conclusion-Amidst a resurgence of community cases involving variant COVID-19 strains, the resources from the research community will provide valuable guidance to navigate these uncertain times.

Managing Pandemics with Health Informatics: Successes and Challenges

INTRODUCTION

The novel COVID-19 pandemic struck the world unprepared. This keynote outlines challenges and successes using data to inform providers, government officials, hospitals, and patients in a pandemic.

METHODS

The authors outline the data required to manage a novel pandemic including their potential uses by governments, public health organizations, and individuals.

RESULTS

An extensive discussion on data quality and on obstacles to collecting data is followed by examples of successes in clinical care, contact tracing, and forecasting. Generic local forecast model development is reviewed followed by ethical consideration around pandemic data. We leave the reader with thoughts on the next inevitable outbreak and lessons learned from the COVID-19 pandemic.

CONCLUSION

COVID-19 must be a lesson for the future to direct us to better planning and preparing to manage the next pandemic with health informatics.

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.

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.

Best Practice Guidance for Digital Contact Tracing Apps: A Cross-disciplinary Review of the Literature

BACKGROUND

Digital contact tracing apps have the potential to augment contact tracing systems and disrupt COVID-19 transmission by rapidly identifying secondary cases prior to the onset of infectiousness and linking them into a system of quarantine, testing, and health care worker case management. The international experience of digital contact tracing apps during the COVID-19 pandemic demonstrates how challenging their design and deployment are.

OBJECTIVE

This study aims to derive and summarize best practice guidance for the design of the ideal digital contact tracing app.

METHODS

A collaborative cross-disciplinary approach was used to derive best practice guidance for designing the ideal digital contact tracing app. A search of the indexed and gray literature was conducted to identify articles describing or evaluating digital contact tracing apps. MEDLINE was searched using a combination of free-text terms and Medical Subject Headings search terms. Gray literature sources searched were the World Health Organization Institutional Repository for Information Sharing, the European Centre for Disease Prevention and Control publications library, and Google, including the websites of many health protection authorities. Articles that were acceptable for inclusion in this evidence synthesis were peer-reviewed publications, cohort studies, randomized trials, modeling studies, technical reports, white papers, and media reports related to digital contact tracing.

RESULTS

Ethical, user experience, privacy and data protection, technical, clinical and societal, and evaluation considerations were identified from the literature. The ideal digital contact tracing app should be voluntary and should be equitably available and accessible. User engagement could be enhanced by small financial incentives, enabling users to tailor aspects of the app to their particular needs and integrating digital contact tracing apps into the wider public health information campaign. Adherence to the principles of good data protection and privacy by design is important to convince target populations to download and use digital contact tracing apps. Bluetooth Low Energy is recommended for a digital contact tracing app's contact event detection, but combining it with ultrasound technology may improve a digital contact tracing app's accuracy. A decentralized privacy-preserving protocol should be followed to enable digital contact tracing app users to exchange and record temporary contact numbers during contact events. The ideal digital contact tracing app should define and risk-stratify contact events according to proximity, duration of contact, and the infectiousness of the case at the time of contact. Evaluating digital contact tracing apps requires data to quantify app downloads, use among COVID-19 cases, successful contact alert generation, contact alert receivers, contact alert receivers that adhere to quarantine and testing recommendations, and the number of contact alert receivers who subsequently are tested positive for COVID-19. The outcomes of digital contact tracing apps' evaluations should be openly reported to allow for the wider public to review the evaluation of the app.

CONCLUSIONS

In conclusion, key considerations and best practice guidance for the design of the ideal digital contact tracing app were derived from the literature.

Challenges for Nontechnical Implementation of Digital Proximity Tracing During the COVID-19 Pandemic: Media Analysis of the SwissCovid App

BACKGROUND

Several countries have released digital proximity tracing (DPT) apps to complement manual contact tracing for combatting the SARS-CoV-2 pandemic. DPT aims to notify app users about proximity exposures to persons infected with SARS-CoV-2 so that they can self-quarantine. The success of DPT apps depends on user acceptance and the embedding of DPT into the pandemic mitigation strategy.

OBJECTIVE

By searching for media articles published during the first 3 months after DPT launch, the implementation of DPT in Switzerland was evaluated to inform similar undertakings in other countries. The second aim of the study was to create a link between reported DPT implementation challenges and normalization process theory for planning and optimizing complex digital health interventions, which can provide useful guidance for decision-making in DPT design and implementation.

METHODS

A Swiss media database was searched for articles on the Swiss DPT app (SwissCovid) published in German or French between July 4 and October 3, 2020. In a structured process, topics were extracted and clustered manually from articles that were deemed pertinent. Extracted topics were mapped to four NPT constructs, which reflected the flow of intervention development from planning, stakeholder onboarding, and execution to critical appraisal. Coherence constructs describe sense-making by stakeholders, cognitive participation constructs reflect participants' efforts to create engagement with the intervention, collective actions refer to intervention execution and joint stakeholder efforts to make the intervention work, and reflexive monitoring refers to collective risk-benefit appraisals to create improvements.

RESULTS

Out of 94 articles deemed pertinent and selected for closer inspection, 38 provided unique information on implementation challenges. Five challenge areas were identified: communication challenges, challenges for DPT to interface with other processes, fear of resource competition with established pandemic mitigation measures, unclear DPT effectiveness, and obstacles to greater user coverage and compliance. Specifically, several articles mentioned unclear DPT benefits to affect commitment and to raise fears among different health system actors regarding resource competition. Moreover, media reports indicated process interface challenges such as delays or unclear responsibilities in the notification cascade, as well as misunderstandings and unmet communication needs from health system actors. Finally, reports suggested misaligned incentives, not only for app usage by the public but also for process engagement by other actors in the app notification cascade. NPT provided a well-fitting framework to contextualize the different DPT implementation challenges and to highlight improvement strategies, namely a better alignment of stakeholder incentives, or stakeholder-specific communication to address their concerns about DPT.

CONCLUSIONS

Early experiences from one of the first adopters of DPT indicate that nontechnical implementation challenges may affect the effectiveness of DPT. The NPT analysis provides a novel perspective on DPT implementation and stresses the need for stakeholder inclusion in development and operationalization.

Blockchain-Based Digital Contact Tracing Apps for COVID-19 Pandemic Management: Issues, Challenges, Solutions, and Future Directions

The COVID-19 pandemic has caused substantial global disturbance by affecting more than 42 million people (as of the end of October 2020). Since there is no medication or vaccine available, the only way to combat it is to minimize transmission. Digital contact tracing is an effective technique that can be utilized for this purpose, as it eliminates the manual contact tracing process and could help in identifying and isolating affected people. However, users are reluctant to share their location and contact details due to concerns related to the privacy and security of their personal information, which affects its implementation and extensive adoption. Blockchain technology has been applied in various domains and has been proven to be an effective approach for handling data transactions securely, which makes it an ideal choice for digital contact tracing apps. The properties of blockchain such as time stamping and immutability of data may facilitate the retrieval of accurate information on the trail of the virus in a transparent manner, while data encryption assures the integrity of the information being provided. Furthermore, the anonymity of the user's identity alleviates some of the risks related to privacy and confidentiality concerns. In this paper, we provide readers with a detailed discussion on the digital contact tracing mechanism and outline the apps developed so far to combat the COVID-19 pandemic. Moreover, we present the possible risks, issues, and challenges associated with the available contact tracing apps and analyze how the adoption of a blockchain-based decentralized network for handling the app could provide users with privacy-preserving contact tracing without compromising performance and efficiency.

Digital Contact Tracing Based on a Graph Database Algorithm for Emergency Management During the COVID-19 Epidemic: Case Study

BACKGROUND

The COVID-19 epidemic is still spreading globally. Contact tracing is a vital strategy in epidemic emergency management; however, traditional contact tracing faces many limitations in practice. The application of digital technology provides an opportunity for local governments to trace the contacts of individuals with COVID-19 more comprehensively, efficiently, and precisely.

OBJECTIVE

Our research aimed to provide new solutions to overcome the limitations of traditional contact tracing by introducing the organizational process, technical process, and main achievements of digital contact tracing in Hainan Province.

METHODS

A graph database algorithm, which can efficiently process complex relational networks, was applied in Hainan Province; this algorithm relies on a governmental big data platform to analyze multisource COVID-19 epidemic data and build networks of relationships among high-risk infected individuals, the general population, vehicles, and public places to identify and trace contacts. We summarized the organizational and technical process of digital contact tracing in Hainan Province based on interviews and data analyses.

RESULTS

An integrated emergency management command system and a multi-agency coordination mechanism were formed during the emergency management of the COVID-19 epidemic in Hainan Province. The collection, storage, analysis, and application of multisource epidemic data were realized based on the government's big data platform using a centralized model. The graph database algorithm is compatible with this platform and can analyze multisource and heterogeneous big data related to the epidemic. These practices were used to quickly and accurately identify and trace 10,871 contacts among hundreds of thousands of epidemic data records; 378 closest contacts and a number of public places with high risk of infection were identified. A confirmed patient was found after quarantine measures were implemented by all contacts.

CONCLUSIONS

During the emergency management of the COVID-19 epidemic, Hainan Province used a graph database algorithm to trace contacts in a centralized model, which can identify infected individuals and high-risk public places more quickly and accurately. This practice can provide support to government agencies to implement precise, agile, and evidence-based emergency management measures and improve the responsiveness of the public health emergency response system. Strengthening data security, improving tracing accuracy, enabling intelligent data collection, and improving data-sharing mechanisms and technologies are directions for optimizing digital contact tracing.