Understanding India's urban dengue surveillance: A qualitative policy analysis of Hyderabad district.

Dengue's re-emerging epidemiology poses a major global health threat. India contributes significantly to the global communicable disease burden has been declared highly dengue-endemic, exposing public health authorities to severe challenges. Our study aims to provide a deeper understanding of India's urban dengue surveillance policies as well as to explore the organisation, functioning and integration of existing disease control pillars. We conducted a qualitative regional case study, consisting of semi-structured expert interviews and observational data, covering the urban region of Hyderabad in South India. Our findings indicate that Hyderabad's dengue surveillance system predominantly relies on public reporting units, neglecting India's large private health sector. The surveillance system requires further strengthening and additional efforts to efficiently integrate existing governmental initiatives at all geographical levels and administrative boundaries. We concluded with recommendations for improved consistency, accuracy, efficiency and reduction of system fragmentation to enhance the integration of dengue surveillance and improved health information in urban India. Finally, our study underlines India's overall need to increase investment in public health and health infrastructures. That requires coordinated and multi-level action targeting the development of a competent, effective and motivated public health cadre, as well as truly integrated surveillance and epidemic response infrastructure, for dengue and beyond

Enrollment and Retention of Participants in Remote Digital Health Studies: Scoping Review and Framework Proposal

BACKGROUND Digital technologies are increasingly used in health research to collect real-world data from wider populations. A new wave of digital health studies relies primarily on digital technologies to conduct research entirely remotely. Remote digital health studies hold promise to significant cost and time advantages over traditional, in-person studies. However, such studies have been reported to typically suffer from participant attrition, the sources for which are still largely understudied. OBJECTIVE To contribute to future remote digital health study planning, we present a conceptual framework and hypotheses for study enrollment and completion. The framework introduces 3 participation criteria that impact remote digital health study outcomes: (1) participant motivation profile and incentives or nudges, (2) participant task complexity, and (3) scientific requirements. The goal of this study is to inform the planning and implementation of remote digital health studies from a person-centered perspective. METHODS We conducted a scoping review to collect information on participation in remote digital health studies, focusing on methodological aspects that impact participant enrollment and retention. Comprehensive searches were conducted on the PubMed, CINAHL, and Web of Science databases, and additional sources were included in our study from citation searching. We included digital health studies that were fully conducted remotely, included information on at least one of the framework criteria during recruitment, onboarding or retention phases of the studies, and included study enrollment or completion outcomes. Qualitative analyses were performed to synthesize the findings from the included studies. RESULTS We report qualitative findings from 37 included studies that reveal high values of achieved median participant enrollment based on target sample size calculations, 128% (IQR 100%-234%), and median study completion, 48% (IQR 35%-76%). Increased median study completion is observed for studies that provided incentives or nudges to extrinsically motivated participants (62%, IQR 43%-78%). Reducing task complexity for participants in the absence of incentives or nudges did not improve median study enrollment (103%, IQR 102%-370%) or completion (43%, IQR 22%-60%) in observational studies, in comparison to interventional studies that provided more incentives or nudges (median study completion rate of 55%, IQR 38%-79%). Furthermore, there were inconsistencies in measures of completion across the assessed remote digital health studies, where only around half of the studies with completion measures (14/27, 52%) were based on participant retention throughout the study period. CONCLUSIONS Few studies reported on participatory factors and study outcomes in a consistent manner, which may have limited the evidence base for our study. Our assessment may also have suffered from publication bias or unrepresentative study samples due to an observed preference for participants with digital literacy skills in digital health studies. Nevertheless, we find that future remote digital health study planning can benefit from targeting specific participant profiles, providing incentives and nudges, and reducing study complexity to improve study outcomes

Patient Perceptions of In Vivo Versus Virtual Reality Exposures for the Treatment of Anxiety Disorders: Cross-Sectional Survey Study

BACKGROUND Psychotherapy, and particularly exposure therapy, has been proven to be an effective treatment for many anxiety disorders, including social and specific phobias, as well as posttraumatic stress disorders. Currently, exposures are underused and mostly delivered in vivo. Virtual reality exposure therapy (VRET) offers a more flexible delivery mechanism that has the potential to address some of the implementation barriers of in vivo exposures while retaining effectiveness. Yet, there is little evidence on how patients perceive different exposure therapy methods. OBJECTIVE This study aims to explore the perceptions of individuals with anxiety disorders toward in vivo and VRET. Our findings can inform therapists about the degree of patient interest in both methods while exploring the demand for VRET as an alternative and novel treatment approach. METHODS Web-based survey assessing the (1) interest in, (2) willingness to use, (3) comfort with, (4) enthusiasm toward, and (5) perceived effectiveness of exposure therapy when delivered in vivo and through VR. Participants included individuals with specific phobia, social phobia, posttraumatic stress disorder, or acute stress disorder or reaction. Participants were presented with educational videos about in vivo and VRET and asked to provide their perceptions quantitatively and qualitatively through a rated scale and free-text responses. RESULTS In total, 184 surveys were completed and analyzed, in which 82% (n=151) of participants reported being willing to receive in vivo exposures and 90.2% (n=166) reported willingness to receive VRET. Participants reported higher interest in, comfort with, enthusiasm toward, and perceived effectiveness of VRET compared to in vivo. Most reported in vivo concerns were linked to (1) increased anxiety, (2) feelings of embarrassment or shame, and (3) exacerbation of current condition. Most reported VRET concerns were linked to (1) risk of side effects including increased anxiety, (2) efficacy uncertainty, and (3) health insurance coverage. The most frequently mentioned VRET benefits include (1) privacy, (2) safety, (3) the ability to control exposures, (4) comfort, (5) the absence of real-life consequences, (6) effectiveness, and (7) customizability to a wider variety of exposures. CONCLUSIONS On average, our participants expressed positive perceptions toward exposure therapy, with slightly more positive perceptions of VRET over in vivo exposures. Despite valid personal concerns and some misconceptions, our findings emphasize that VRET provides an opportunity to get much-needed therapy to patients in ways that are more acceptable and less concerning

Promoting participation in remote digital health studies: An expert interview study

BACKGROUND Remote digital health studies are on the rise and promise to reduce the operational inefficiencies of in-person research. However, they encounter specific challenges in maintaining participation (enrollment and retention) due to their exclusive reliance on technology across all study phases. OBJECTIVE The goal of this study was to collect experts' opinions on how to facilitate participation in remote digital health studies. METHOD We conducted 13 semi-structured interviews with principal investigators, researchers, and software developers who had recent experiences with remote digital health studies. Informed by the Unified Theory of Acceptance and Use of Technology (UTAUT) framework, we performed a thematic analysis and mapped various approaches to successful study participation. RESULTS Our analyses revealed four themes: (1) study planning to increase participation, where experts suggest that remote digital health studies should be planned based on adequate knowledge of what motivates, engages, and disengages a target population; (2) participant enrollment, highlighting that enrollment strategies should be selected carefully, attached to adequate support, and focused on inclusivity; (3) participant retention, with strategies that minimize the effort and complexity of study tasks and ensure that technology is adapted and responsive to participant needs, and (4) requirements for study planning focused on the development of relevant guidelines to foster participation in future studies. CONCLUSIONS Our findings highlight the significant requirements for seamless technology and researcher involvement in enabling high remote digital health study participation. Future studies can benefit from collected experiences and the development of guidelines to inform planning that balances participant and scientific requirements

Challenges in implementing cultural adaptations of digital health interventions

Differences in the access and use of digital health interventions are driven by culture, in addition to economic and physical factors. To avoid the systematic exclusion of traditionally underserved cultural groups, creating inclusive digital health interventions is essential. One way to achieve this is through cultural adaptations, defined as the systematic modification of an existing intervention that aligns with a target audience's cultural norms, beliefs, and values. In theory, cultural adaptations can potentially increase the reach and engagement of digital health interventions. However, the evidence of whether and how that is achieved is limited. Justifying, planning, and implementing an adaptation comes with various challenges and takes time and money. This perspective provides a critical overview of the field's current state and emphasizes the need for technology-specific frameworks that address when and how to culturally adapt digital health interventions

The Organization, Implementation, and Functioning of Dengue Surveillance in India-A Systematic Scoping Review.

Dengue´s re-emerging epidemiology poses a major global health threat. In India, dengue contributes significantly to the global communicable disease burden, and has been declared highly endemic. This study aims to identify and critically appraise India's dengue surveillance system. We conducted a systematic literature review, searching Medline, Web of Sciences, Global Health, and Indian Journals. We conducted a narrative synthesis and thematic analysis. Eighteen studies fulfilled eligibility. Organizationally, most studies referred to the National Vector Borne Disease Control Programme, primarily responsible for overall vector and disease control, as well as the Integrated Disease Surveillance Programme, responsible for reporting, outbreak identification, and integration. Surveillance implementation was mostly framed as passive, sentinel, and hospital-based. Reporting varies from weekly to monthly, flowing from primary healthcare centres to district and national authorities. Dengue confirmation is only recognized if conducted with government-distributed MAC-ELISA tests. The surveillance system predominantly relies on public reporting units. In terms of functioning, current surveillance seems to have improved dengue reporting as well the system's detection capacities. Emergency and outbreak responses are often described as timely; however, they are challenged by underreporting, weak data reliability, lack of private reporting, and system fragmentation. Concluding, India's dengue surveillance structure remains weak. Efforts to create an infrastructure of communication, cooperation, and integration are evident, however, not achieved yet

Digital health for chronic disease management: An exploratory method to investigating technology adoption potential

INTRODUCTION The availability of consumer-facing health technologies for chronic disease management is skyrocketing, yet most are limited by low adoption rates. Improving adoption requires a better understanding of a target population's previous exposure to technology. We propose a low-resource approach of capturing and clustering technology exposure, as a mean to better understand patients and target health technologies. METHODS Using Multiple Sclerosis (MS) as a case study, we applied exploratory multivariate factorial analyses to survey data from the Swiss MS Registry. We calculated individual-level factor scorings, aiming to investigate possible technology adoption clusters with similar digital behavior patterns. The resulting clusters were transformed using radar and then compared across sociodemographic and health status characteristics. RESULTS Our analysis included data from 990 respondents, resulting in three clusters, which we defined as the (1) average users, (2) health-interested users, and (3) low frequency users. The average user uses consumer-facing technology regularly, mainly for daily, regular activities and less so for health-related purposes. The health-interested user also uses technology regularly, for daily activities as well as health-related purposes. The low-frequency user uses technology infrequently. CONCLUSIONS Only about 10% of our sample has been regularly using (adopting) consumer-facing technology for MS and health-related purposes. That might indicate that many of the current consumer-facing technologies for MS are only attractive to a small proportion of patients. The relatively low-resource exploratory analyses proposed here may allow for a better characterization of prospective user populations and ultimately, future patient-facing technologies that will be targeted to a broader audience

Long COVID Citizen Scientists: Developing a Needs-Based Research Agenda by Persons Affected by Long COVID

BACKGROUND Long-term health consequences following acute SARS-CoV-2 infection, referred to as post-COVID-19 condition or Long COVID, are increasing, with population-based prevalence estimates for adults at around 20%. Persons affected by Long COVID report various health problems, yet evidence to guide clinical decision making remains scarce. OBJECTIVE The present study aimed to identify Long COVID research priorities using a citizen science approach and solely considering the needs of those affected. METHODS This citizen science study followed an iterative process of patient needs identification, evaluation and prioritisation. A Long COVID Citizen Science Board (21 persons with Long COVID, and seven with myalgic encephalomyelitis/chronic fatigue syndrome) and a Long COVID Working Group (25 persons with Long COVID, four patients with myalgic encephalomyelitis/chronic fatigue syndrome and one relative) were formed. The study included four activities: three remote meetings and one online survey. First, Board members identified the needs and research questions. Second, Working Group members and persons affected by Long COVID (241 respondents, 85.5% with Long COVID, 14.5% with myalgic encephalomyelitis/chronic fatigue syndrome and 7.1% relatives) evaluated the research questions on a 1-5 Likert scale using an online survey. Then the Board gave feedback on this evaluation. Finally, Board members set the priorities for research through voting and discussion. RESULTS Sixty-eight research questions were generated by the Board and categorised into four research domains (medicine, healthcare services, socioeconomics and burden of disease) and 14 subcategories. Their average importance ratings were moderate to high and varied from 3.41 (standard deviation = 1.16) for sex-specific diagnostics to 4.86 (standard deviation = 0.41) for medical questions on treatment. Five topics were prioritised: "treatment, rehabilitation and chronic care management", "availability of interfaces for treatment continuity", "availability of healthcare structures", "awareness and knowledge among professionals" and "prevalence of Long COVID in children and adolescents". CONCLUSIONS To our knowledge, this is the first study developing a citizen-driven, explicitly patient-centred research agenda with persons affected by Long COVID, setting it apart from existing multi-stakeholder efforts. The identified priorities could guide future research and funding allocation. Our methodology establishes a framework for citizen-driven research agendas, suitable for transfer to other diseases

Beyond high hopes: A scoping review of the 2019-2021 scientific discourse on machine learning in medical imaging

Machine learning has become a key driver of the digital health revolution. That comes with a fair share of high hopes and hype. We conducted a scoping review on machine learning in medical imaging, providing a comprehensive outlook of the field's potential, limitations, and future directions. Most reported strengths and promises included: improved (a) analytic power, (b) efficiency (c) decision making, and (d) equity. Most reported challenges included: (a) structural barriers and imaging heterogeneity, (b) scarcity of well-annotated, representative and interconnected imaging datasets (c) validity and performance limitations, including bias and equity issues, and (d) the still missing clinical integration. The boundaries between strengths and challenges, with cross-cutting ethical and regulatory implications, remain blurred. The literature emphasizes explainability and trustworthiness, with a largely missing discussion about the specific technical and regulatory challenges surrounding these concepts. Future trends are expected to shift towards multi-source models, combining imaging with an array of other data, in a more open access, and explainable manner

Performance of the Swiss Digital Contact-Tracing App Over Various SARS-CoV-2 Pandemic Waves: Repeated Cross-sectional Analyses

Background: Digital proximity-tracing apps have been deployed in multiple countries to assist with SARS-CoV-2 pandemic mitigation efforts. However, it is unclear how their performance and effectiveness were affected by changing pandemic contexts and new viral variants of concern. Objective: The aim of this study is to bridge these knowledge gaps through a countrywide digital proximity-tracing app effectiveness assessment, as guided by the World Health Organization/European Center for Prevention and Disease Control (WHO/ECDC) indicator framework to evaluate the public health effectiveness of digital proximity-tracing solutions. Methods: We performed a descriptive analysis of the digital proximity-tracing app SwissCovid in Switzerland for 3 different periods where different SARS-CoV-2 variants of concern (ie, Alpha, Delta, and Omicron, respectively) were most prevalent. In our study, we refer to the indicator framework for the evaluation of public health effectiveness of digital proximity-tracing apps of the WHO/ECDC. We applied this framework to compare the performance and effectiveness indicators of the SwissCovid app. Results: Average daily registered SARS-CoV-2 case rates during our assessment period from January 25, 2021, to March 19, 2022, were 20 (Alpha), 54 (Delta), and 350 (Omicron) per 100,000 inhabitants. The percentages of overall entered authentication codes from positive tests into the SwissCovid app were 9.9% (20,273/204,741), 3.9% (14,372/365,846), and 4.6% (72,324/1,581,506) during the Alpha, Delta, and Omicron variant phases, respectively. Following receipt of an exposure notification from the SwissCovid app, 58% (37/64, Alpha), 44% (7/16, Delta), and 73% (27/37, Omicron) of app users sought testing or performed self-tests. Test positivity among these exposure-notified individuals was 19% (7/37) in the Alpha variant phase, 29% (2/7) in the Delta variant phase, and 41% (11/27) in the Omicron variant phase compared to 6.1% (228,103/3,755,205), 12% (413,685/3,443,364), and 41.7% (1,784,951/4,285,549) in the general population, respectively. In addition, 31% (20/64, Alpha), 19% (3/16, Delta), and 30% (11/37, Omicron) of exposure-notified app users reported receiving mandatory quarantine orders by manual contact tracing or through a recommendation by a health care professional. Conclusions: In constantly evolving pandemic contexts, the effectiveness of digital proximity-tracing apps in contributing to mitigating pandemic spread should be reviewed regularly and adapted based on changing requirements. The WHO/ECDC framework allowed us to assess relevant domains of digital proximity tracing in a holistic and systematic approach. Although the Swisscovid app mostly worked, as reasonably expected, our analysis revealed room for optimizations and further performance improvements. Future implementation of digital proximity-tracing apps should place more emphasis on social, psychological, and organizational aspects to reduce bottlenecks and facilitate their use in pandemic contexts. Keywords: COVID-19; SARS-CoV-2; SwissCovid app; Switzerland; contact-tracing app; digital contact tracing; digital proximity; digital tool; exposure notification; mobile app; public health; surveillance; variant of concern