Smartphone apps in the COVID-19 pandemic

Perspectives on Emergency Preparedness Among Indigenous Pacific People in Hawaii: A Qualitative Study

PURPOSE

This study sought an improved understanding of household emergency preparedness (EP) among Native Hawaiian, Pacific Islander, and Filipino (Indigenous Pacific People [IPP]) parents in Hawaii.

DESIGN

We conducted an exploratory qualitative descriptive study with 60-minute interviews occurring from October 2022 through March 2023. A semi-structured interview guide exploring participant household EP was employed.

METHODS

Prospective participants were females who identified as IPP, caregivers of a 0-12-year-old child, spoke English, and received health services at a federally qualified health center clinic. Two researchers conducted qualitative content analysis on interview transcripts. Initial coding of transcripts identified broad categories or themes. The process was reviewed continuously to verify data and coding procedures. Three investigators independently verified final themes and subthemes.

FINDINGS

Participants (N=25) were female, between 30-49 years of age (68%), had received some college education (60%), and were fully employed (68%). Major themes included: 1) Perceptions of family EP and current behaviors, 2) Barriers and challenges to family EP, and 3) Perspectives on strategies to improve family EP. Subthemes included risk perception for emergencies; family EP practices; health protection and pandemic preparedness; lack of knowledge and experience; social, cultural and economic barriers; and clinic-based, technology-driven, and community-based interventions.

CONCLUSION

Factors impeding access to healthcare services also impede family EP among IPP groups and their ability to mitigate the impact of future public health emergencies.

CLINICAL EVIDENCE

Targeted, innovative interventions, including ones led by health clinics and those that utilize technology, are needed to overcome common barriers faced and to facilitate the uptake of household EP behaviors among IPP families.

COVID-19 Vaccine Effectiveness and Digital Pandemic Surveillance in Germany (eCOV Study): Web Application-Based Prospective Observational Cohort Study

BACKGROUND

The COVID-19 pandemic posed significant challenges to global health systems. Efficient public health responses required a rapid and secure collection of health data to improve the understanding of SARS-CoV-2 and examine the vaccine effectiveness (VE) and drug safety of the novel COVID-19 vaccines.

OBJECTIVE

This study (COVID-19 study on vaccinated and unvaccinated subjects over 16 years; eCOV study) aims to (1) evaluate the real-world effectiveness of COVID-19 vaccines through a digital participatory surveillance tool and (2) assess the potential of self-reported data for monitoring key parameters of the COVID-19 pandemic in Germany.

METHODS

Using a digital study web application, we collected self-reported data between May 1, 2021, and August 1, 2022, to assess VE, test positivity rates, COVID-19 incidence rates, and adverse events after COVID-19 vaccination. Our primary outcome measure was the VE of SARS-CoV-2 vaccines against laboratory-confirmed SARS-CoV-2 infection. The secondary outcome measures included VE against hospitalization and across different SARS-CoV-2 variants, adverse events after vaccination, and symptoms during infection. Logistic regression models adjusted for confounders were used to estimate VE 4 to 48 weeks after the primary vaccination series and after third-dose vaccination. Unvaccinated participants were compared with age- and gender-matched participants who had received 2 doses of BNT162b2 (Pfizer-BioNTech) and those who had received 3 doses of BNT162b2 and were not infected before the last vaccination. To assess the potential of self-reported digital data, the data were compared with official data from public health authorities.

RESULTS

We enrolled 10,077 participants (aged ≥16 y) who contributed 44,786 tests and 5530 symptoms. In this young, primarily female, and digital-literate cohort, VE against infections of any severity waned from 91.2% (95% CI 70.4%-97.4%) at week 4 to 37.2% (95% CI 23.5%-48.5%) at week 48 after the second dose of BNT162b2. A third dose of BNT162b2 increased VE to 67.6% (95% CI 50.3%-78.8%) after 4 weeks. The low number of reported hospitalizations limited our ability to calculate VE against hospitalization. Adverse events after vaccination were consistent with previously published research. Seven-day incidences and test positivity rates reflected the course of the pandemic in Germany when compared with official numbers from the national infectious disease surveillance system.

CONCLUSIONS

Our data indicate that COVID-19 vaccinations are safe and effective, and third-dose vaccinations partially restore protection against SARS-CoV-2 infection. The study showcased the successful use of a digital study web application for COVID-19 surveillance and continuous monitoring of VE in Germany, highlighting its potential to accelerate public health decision-making. Addressing biases in digital data collection is vital to ensure the accuracy and reliability of digital solutions as public health tools.

Precision Medicine-Are We There Yet? A Narrative Review of Precision Medicine's Applicability in Primary Care

Precision medicine (PM), also termed stratified, individualised, targeted, or personalised medicine, embraces a rapidly expanding area of research, knowledge, and practice. It brings together two emerging health technologies to deliver better individualised care: the many "-omics" arising from increased capacity to understand the human genome and "big data" and data analytics, including artificial intelligence (AI). PM has the potential to transform an individual's health, moving from population-based disease prevention to more personalised management. There is however a tension between the two, with a real risk that this will exacerbate health inequalities and divert funds and attention from basic healthcare requirements leading to worse health outcomes for many. All areas of medicine should consider how this will affect their practice, with PM now strongly encouraged and supported by government initiatives and research funding. In this review, we discuss examples of PM in current practice and its emerging applications in primary care, such as clinical prediction tools that incorporate genomic markers and pharmacogenomic testing. We look towards potential future applications and consider some key questions for PM, including evidence of its real-world impact, its affordability, the risk of exacerbating health inequalities, and the computational and storage challenges of applying PM technologies at scale.

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

Introduction

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

Methods

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

Results

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

Discussion

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

Use of Digital COVID-19 Exposure Notifications at a Large Gathering: Survey Analysis of Public Health Conference Attendees

BACKGROUND

WA Notify was Washington State's smartphone-based COVID-19 digital exposure notification (EN) tool, which was used to help limit the spread of COVID-19 between November 30, 2020, and May 11, 2023. Following the 2022 Washington State Public Health Association Annual Conference, attendees who had WA Notify activated began receiving ENs alerting them to a possible COVID-19 exposure during the conference. A survey was emailed to all conference attendees to measure WA Notify adoption, mechanisms through which attendees received ENs, and self-reported engagement in protective behaviors postexposure.

OBJECTIVE

This study aimed to learn more about the experiences of WA Notify adopters and nonadopters who may have been exposed to COVID-19 at a large group gathering.

METHODS

A web-based survey administered through REDCap (Research Electronic Data Capture; Vanderbilt University) was sent to all attendees of the Washington State Public Health Association conference. Self-reported demographic information and characteristics of respondents were summarized. Regression models were used to estimate relative risks to compare WA Notify adoption and testing behaviors between groups.

RESULTS

Of the 464 total registered attendees who were sent the survey, 205 (44%) responses were received; 201 eligible attendees were included in this analysis. Of those, 149 (74%) respondents reported having WA Notify activated on their phones at the time of the conference. Among respondents with WA Notify activated, 54% (n=77) reported learning of their potential exposure from a WA Notify EN. Respondents who reported that they did not have WA Notify activated and learned of their potential exposure via the event-wide email from conference organizers were 39% less likely to test for COVID-19 compared to respondents with WA Notify activated who learned of their potential exposure from the email (relative risk 0.61, 95% CI 0.40-0.93; P=.02), and this gap was even larger when compared to respondents who learned of their exposure from a WA Notify EN. The most commonly cited reason for not having WA Notify activated was privacy concerns (n=17, 35%), followed by not wanting to receive ENs (n=6, 12%) and being unaware of WA Notify (n=5, 10%).

CONCLUSIONS

Digital EN systems are an important tool to directly and anonymously notify close contacts of potential exposures and provide guidance on the next steps in a timely manner. Given the privacy concerns, there is still a need for increasing transparency surrounding EN technology to increase uptake by the public if this technology were to be used in the future to slow the spread of communicable diseases.

Distinguishing Immunologic and Behavioral Effects of Vaccination

The interpretation of vaccine efficacy estimands is subtle, even in randomized trials designed to quantify the immunologic effects of vaccination. In this article, we introduce terminology to distinguish between different vaccine efficacy estimands and clarify their interpretations. This allows us to explicitly consider the immunologic and behavioral effects of vaccination, and establish that policy-relevant estimands can differ substantially from those commonly reported in vaccine trials. We further show that a conventional vaccine trial allows the identification and estimation of different vaccine estimands under plausible conditions if one additional post-treatment variable is measured. Specifically, we utilize a "belief variable" that indicates the treatment an individual believed they had received. The belief variable is similar to "blinding assessment" variables that are occasionally collected in placebo-controlled trials in other fields. We illustrate the relations between the different estimands, and their practical relevance, in numerical examples based on an influenza vaccine trial.

Colonialism in the new digital health agenda

The advancement of digital technologies has stimulated immense excitement about the possibilities of transforming healthcare, especially in resource-constrained contexts. For many, this rapid growth presents a 'digital health revolution'. While this is true, there are also dangers that the proliferation of digital health in the global south reinforces existing colonialities. Underpinned by the rhetoric of modernity, rationality and progress, many countries in the global south are pushing for digital health transformation in ways that ignore robust regulation, increase commercialisation and disregard local contexts, which risks heightened inequalities. We propose a decolonial agenda for digital health which shifts the liner and simplistic understanding of digital innovation as the magic wand for health justice. In our proposed approach, we argue for both conceptual and empirical reimagination of digital health agendas in ways that centre indigenous and intersectional theories. This enables the prioritisation of local contexts and foregrounds digital health regulatory infrastructures as a possible site of both struggle and resistance. Our decolonial digital health agenda critically reflects on who is benefitting from digital health systems, centres communities and those with lived experiences and finally introduces robust regulation to counter the social harms of digitisation.

The hospital at home in the USA: current status and future prospects

The annual cost of hospital care services in the US has risen to over $1 trillion despite relatively worse health outcomes compared to similar nations. These trends accentuate a growing need for innovative care delivery models that reduce costs and improve outcomes. HaH-a program that provides patients acute-level hospital care at home-has made significant progress over the past two decades. Technological advancements in remote patient monitoring, wearable sensors, health information technology infrastructure, and multimodal health data processing have contributed to its rise across hospitals. More recently, the COVID-19 pandemic brought HaH into the mainstream, especially in the US, with reimbursement waivers that made the model financially acceptable for hospitals and payors. However, HaH continues to face serious challenges to gain widespread adoption. In this review, we evaluate the peer-reviewed evidence and discuss the promises, challenges, and what it would take to tap into the future potential of HaH.

Perceptions of the Agency and Responsibility of the NHS COVID-19 App on Twitter: Critical Discourse Analysis

BACKGROUND

Since September 2020, the National Health Service (NHS) COVID-19 contact-tracing app has been used to mitigate the spread of COVID-19 in the United Kingdom. Since its launch, this app has been a part of the discussion regarding the perceived social agency of decision-making algorithms. On the social media website Twitter, a plethora of views about the app have been found but only analyzed for sentiment and topic trajectories thus far, leaving the perceived social agency of the app underexplored.

OBJECTIVE

We aimed to examine the discussion of social agency in social media public discourse regarding algorithm-operated decisions, particularly when the artificial intelligence agency responsible for specific information systems is not openly disclosed in an example such as the COVID-19 contact-tracing app. To do this, we analyzed the presentation of the NHS COVID-19 App on Twitter, focusing on the portrayal of social agency and the impact of its deployment on society. We also aimed to discover what the presentation of social agents communicates about the perceived responsibility of the app.

METHODS

Using corpus linguistics and critical discourse analysis, underpinned by social actor representation, we used the link between grammatical and social agency and analyzed a corpus of 118,316 tweets from September 2020 to July 2021 to see whether the app was portrayed as a social actor.

RESULTS

We found that active presentations of the app-seen mainly through personalization and agency metaphor-dominated the discourse. The app was presented as a social actor in 96% of the cases considered and grew in proportion to passive presentations over time. These active presentations showed the app to be a social actor in 5 main ways: informing, instructing, providing permission, disrupting, and functioning. We found a small number of occasions on which the app was presented passively through backgrounding and exclusion.

CONCLUSIONS

Twitter users presented the NHS COVID-19 App as an active social actor with a clear sense of social agency. The study also revealed that Twitter users perceived the app as responsible for their welfare, particularly when it provided instructions or permission, and this perception remained consistent throughout the discourse, particularly during significant events. Overall, this study contributes to understanding how social agency is discussed in social media discourse related to algorithmic-operated decisions This research offers valuable insights into public perceptions of decision-making digital contact-tracing health care technologies and their perceptions on the web, which, even in a postpandemic world, may shed light on how the public might respond to forthcoming interventions.

Digital thErapy For Improved tiNnitus carE Study (DEFINE): Protocol for a randomised controlled trial

Tinnitus is a common health condition, affecting approximately 15% of the UK population. The tinnitus treatment with the strongest evidence base is Cognitive Behavioural Therapy (CBT), with standard tinnitus therapy typically augmented with education, relaxation and other techniques. Availability of CBT and conventional tinnitus therapy more broadly is limited for tinnitus sufferers. The DEFINE trial aims to assess whether smartphone-delivered tinnitus therapy, the Oto app, is as effective as current standard care, one-to-one therapist-delivered tinnitus treatment for the treatment of tinnitus in adults. The trial is registered in the ISRCTN Registry: ISRCTN99577932. DEFINE is an open-label, non-inferiority, prospective, parallel design, randomised-controlled trial. Recruitment, interventions and assessments will be remote, enabling UK-wide participant involvement. 198 participants aged 18 years or more will be recruited via social media advertisement or via primary care physicians. A screening process will identify those with tinnitus that impacts health-related quality of life, and following consent smartphone-based audiometry will be performed. Randomisation 1:1 to the Oto app or one-to-one therapist-led tinnitus therapy will be performed centrally by computer, matching groups for age, sex and hearing level. Following participant allocation, the Oto app will be provided for immediate use, or a one-to-one remote therapy appointment booked to occur within approximately 1 week, with up to 6 sessions delivered. Participant outcomes will be collected at 4,12, 26 and 52 weeks via questionnaire and phone call. The primary outcome is the change in Tinnitus Functional Index (TFI) total score measured at 26 weeks following allocation. Adverse events will be recorded. A health economic evaluation in the form of a cost-utility analysis will be performed using data from participant submitted EuroQol 5D-5L and Health Utilities Index Mark 3 scores and resource use data. Trial results will be made publicly available, including a plain English summary.

Patient-provider experiences with chronic non-communicable disease care during COVID-19 lockdowns in rural Uganda: A qualitative analysis

Non-communicable diseases (NCDs) are a growing health burden in Sub-Saharan Africa and especially Uganda, where they account for over one third of all deaths. During the COVID-19 pandemic, public health control measures such as societal "lockdowns" had a significant impact on longitudinal NCD care though no studies have looked at the lived experience around NCD care during the pandemic. Our objective was to understand the experience of NCD care for both patients and providers in southwestern Uganda during the COVID-19 pandemic. We conducted in-depth, in-person qualitative interviews with 20 patients living with hypertension, diabetes, and/or cardiac disease purposefully selected from the outpatient clinics at Mbarara Regional Referral Hospital and 11 healthcare providers from public health facilities in Mbarara, southwestern Uganda. We analyzed transcripts according to conventional content analysis. We identified four major themes that emerged from the interviews; (1) difficulty accessing medication; (2) food insecurity; (3) barriers to the delivery of NCD clinical care and (4) alternative forms of care. Pre-existing challenges with NCD care were exacerbated during COVID-19 lockdown periods and care was severely disrupted, leading to worsened patient health and even death. The barriers to care were exacerbations of underlying systemic problems with NCD care delivery that require targeted interventions. Future work should leverage digital health interventions, de-centralizing NCD care, improving follow-up, providing social supports to NCD patients, and rectifying supply chain issues.

A Digital Mask-Voiceprint System for Postpandemic Surveillance and Tracing Based on the STRONG Strategy

Lockdowns and border closures due to COVID-19 imposed mental, social, and financial hardships in many societies. Living with the virus and resuming normal life are increasingly being advocated due to decreasing virus severity and widespread vaccine coverage. However, current trends indicate a continued absence of effective contingency plans to stop the next more virulent variant of the pandemic. The COVID-19-related mask waste crisis has also caused serious environmental problems and virus spreads. It is timely and important to consider how to precisely implement surveillance for the dynamic clearance of COVID-19 and how to efficiently manage discarded masks to minimize disease transmission and environmental hazards. In this viewpoint, we sought to address this issue by proposing an appropriate strategy for intelligent surveillance of infected cases and centralized management of mask waste. Such an intelligent strategy against COVID-19, consisting of wearable mask sample collectors (masklect) and voiceprints and based on the STRONG (Spatiotemporal Reporting Over Network and GPS) strategy, could enable the resumption of social activities and economic recovery and ensure a safe public health environment sustainably.

Characterizing the role of human behavior in the effectiveness of contact-tracing applications

Introduction

Although numerous countries relied on contact-tracing (CT) applications as an epidemic control measure against the COVID-19 pandemic, the debate around their effectiveness is still open. Most studies indicate that very high levels of adoption are required to stop disease progression, placing the main interest of policymakers in promoting app adherence. However, other factors of human behavior, like delays in adherence or heterogeneous compliance, are often disregarded.

Methods

To characterize the impact of human behavior on the effectiveness of CT apps we propose a multilayer network model reflecting the co-evolution of an epidemic outbreak and the app adoption dynamics over a synthetic population generated from survey data. The model was initialized to produce epidemic outbreaks resembling the first wave of the COVID-19 pandemic and was used to explore the impact of different changes in behavioral features in peak incidence and maximal prevalence.

Results

The results corroborate the relevance of the number of users for the effectiveness of CT apps but also highlight the need for early adoption and, at least, moderate levels of compliance, which are factors often not considered by most policymakers.

Discussion

The insight obtained was used to identify a bottleneck in the implementation of several apps, such as the Spanish CT app, where we hypothesize that a simplification of the reporting system could result in increased effectiveness through a rise in the levels of compliance.

Effect of physical exercise on sleep quality in college students: Mediating role of smartphone use

OBJECTIVE

To investigate the effect of physical exercise on sleep quality and the mediating effect of smartphone use behavior in college students.

METHODS

A cross-sectional study design was adopted. An online survey of 5,075 college students was conducted using the Physical Activity Rating Scale-3, the Pittsburgh Sleep Quality Index, and the Mobile Phone Addiction Tendency Scale.

RESULTS

The sleep quality of college students was poor, and the proportion of college students with good sleep quality was 23.567%. A significant correlation existed between sleep quality and physical exercise (r = -0.159, P < 0.001) and mobile phone addiction (r = 0.355, P < 0.001). Physical exercise can predict sleep quality in college students (β = -0.011, P < 0.001). Smartphone use plays a part in mediating the process by which physical exercise affects sleep quality.

CONCLUSION

Chinese college students have poor sleep quality. Physical exercise and smartphone use behavior are important factors affecting the sleep quality of college students. Physical exercise can directly predict the sleep quality of college students and can predict the sleep quality of college students through the mediating effect of smartphone use behavior.

Human-centred artificial intelligence for mobile health sensing: challenges and opportunities

Advances in wearable sensing and mobile computing have enabled the collection of health and well-being data outside of traditional laboratory and hospital settings, paving the way for a new era of mobile health. Meanwhile, artificial intelligence (AI) has made significant strides in various domains, demonstrating its potential to revolutionize healthcare. Devices can now diagnose diseases, predict heart irregularities and unlock the full potential of human cognition. However, the application of machine learning (ML) to mobile health sensing poses unique challenges due to noisy sensor measurements, high-dimensional data, sparse and irregular time series, heterogeneity in data, privacy concerns and resource constraints. Despite the recognition of the value of mobile sensing, leveraging these datasets has lagged behind other areas of ML. Furthermore, obtaining quality annotations and ground truth for such data is often expensive or impractical. While recent large-scale longitudinal studies have shown promise in leveraging wearable sensor data for health monitoring and prediction, they also introduce new challenges for data modelling. This paper explores the challenges and opportunities of human-centred AI for mobile health, focusing on key sensing modalities such as audio, location and activity tracking. We discuss the limitations of current approaches and propose potential solutions.

Global mosquito observations dashboard (GMOD): creating a user-friendly web interface fueled by citizen science to monitor invasive and vector mosquitoes

BACKGROUND

Mosquitoes and the diseases they transmit pose a significant public health threat worldwide, causing more fatalities than any other animal. To effectively combat this issue, there is a need for increased public awareness and mosquito control. However, traditional surveillance programs are time-consuming, expensive, and lack scalability. Fortunately, the widespread availability of mobile devices with high-resolution cameras presents a unique opportunity for mosquito surveillance. In response to this, the Global Mosquito Observations Dashboard (GMOD) was developed as a free, public platform to improve the detection and monitoring of invasive and vector mosquitoes through citizen science participation worldwide.

METHODS

GMOD is an interactive web interface that collects and displays mosquito observation and habitat data supplied by four datastreams with data generated by citizen scientists worldwide. By providing information on the locations and times of observations, the platform enables the visualization of mosquito population trends and ranges. It also serves as an educational resource, encouraging collaboration and data sharing. The data acquired and displayed on GMOD is freely available in multiple formats and can be accessed from any device with an internet connection.

RESULTS

Since its launch less than a year ago, GMOD has already proven its value. It has successfully integrated and processed large volumes of real-time data (~ 300,000 observations), offering valuable and actionable insights into mosquito species prevalence, abundance, and potential distributions, as well as engaging citizens in community-based surveillance programs.

CONCLUSIONS

GMOD is a cloud-based platform that provides open access to mosquito vector data obtained from citizen science programs. Its user-friendly interface and data filters make it valuable for researchers, mosquito control personnel, and other stakeholders. With its expanding data resources and the potential for machine learning integration, GMOD is poised to support public health initiatives aimed at reducing the spread of mosquito-borne diseases in a cost-effective manner, particularly in regions where traditional surveillance methods are limited. GMOD is continually evolving, with ongoing development of powerful artificial intelligence algorithms to identify mosquito species and other features from submitted data. The future of citizen science holds great promise, and GMOD stands as an exciting initiative in this field.

Interplay of Digital Proximity App Use and SARS-CoV-2 Vaccine Uptake in Switzerland: Analysis of Two Population-Based Cohort Studies

Objectives: Our study aims to evaluate developments in vaccine uptake and digital proximity tracing app use in a localized context of the SARS-CoV-2 pandemic. Methods: We report findings from two population-based longitudinal cohorts in Switzerland from January to December 2021. Failure time analyses and Cox proportional hazards regression models were conducted to assess vaccine uptake and digital proximity tracing app (SwissCovid) uninstalling outcomes. Results: We observed a dichotomy of individuals who did not use the SwissCovid app and did not get vaccinated, and who used the SwissCovid app and got vaccinated during the study period. Increased vaccine uptake was observed with SwissCovid app use (aHR, 1.51; 95% CI: 1.40-1.62 [CI-DFU]; aHR, 1.79; 95% CI: 1.62-1.99 [CSM]) compared to SwissCovid app non-use. Decreased SwissCovid uninstallation risk was observed for participants who got vaccinated (aHR, 0.55; 95% CI: 0.38-0.81 [CI-DFU]; aHR, 0.45; 95% CI: 0.27-0.78 [CSM]) compared to participants who did not get vaccinated. Conclusion: In evolving epidemic contexts, these findings underscore the need for communication strategies as well as flexible digital proximity tracing app adjustments that accommodate different preventive measures and their anticipated interactions.

Engaging a national-scale cohort of smart thermometer users in participatory surveillance

Participatory surveillance systems crowdsource individual reports to rapidly assess population health phenomena. The value of these systems increases when more people join and persistently contribute. We examine the level of and factors associated with engagement in participatory surveillance among a retrospective, national-scale cohort of individuals using smartphone-connected thermometers with a companion app that allows them to report demographic and symptom information. Between January 1, 2020 and October 29, 2022, 1,325,845 participants took 20,617,435 temperature readings, yielding 3,529,377 episodes of consecutive readings. There were 1,735,805 (49.2%) episodes with self-reported symptoms (including reports of no symptoms). Compared to before the pandemic, participants were more likely to report their symptoms during pandemic waves, especially after the winter wave began (September 13, 2020) (OR across pandemic periods range from 3.0 to 4.0). Further, symptoms were more likely to be reported during febrile episodes (OR = 2.6, 95% CI = 2.6-2.6), and for new participants, during their first episode (OR = 2.4, 95% CI = 2.4-2.5). Compared with participants aged 50-65 years old, participants over 65 years were less likely to report their symptoms (OR = 0.3, 95% CI = 0.3-0.3). Participants in a household with both adults and children (OR = 1.6 [1.6-1.7]) were more likely to report symptoms. We find that the use of smart thermometers with companion apps facilitates the collection of data on a large, national scale, and provides real time insight into transmissible disease phenomena. Nearly half of individuals using these devices are willing to report their symptoms after taking their temperature, although participation varies among individuals and over pandemic stages.

Assessing the acceptability of COVID-19 vaccine and its booster dose

BACKGROUND AND OBJECTIVE

Coronavirus disease of 2019 (COVID-19) vaccinations are essential to control the pandemic and prevent severe COVID-19 infections. This study aims to assess the acceptability of the COVID-19 vaccine and the factors that impact the intention to take the COVID-19 vaccine and its booster dose.

METHODS

A cross-sectional study was conducted in Saudi Arabia and Jordan. The study used a self-administered web-based survey (questionnaire) for data collection that was distributed via social media platforms from May 2022 to July 2022.

RESULTS

In this study, among 518 participants, 54.4% had already received two doses of the COVID-19 vaccine, and out of the participants who didn't receive the booster dose, 19.9% declared a definite willingness to receive it, while 42% had already taken a booster dose, which indicated good acceptance. After adjustment for significant background characteristics, a significant association between the country and receiving the COVID-19 vaccine, the intention to get the vaccine, and infection with COVID-19 were found, in addition to a significant association between the country and the participants' opinion that electronic applications helped them to follow their vaccine schedule were found (p < .001). Also, the results showed that participants' attitudes were significantly associated with educational level and age groups (p ≤ .001, p = .032, respectively). There was a significant association between the intention to receive the vaccine booster dose and the country (p < .001). The Saudi participants were willing to get the booster dose seven times more than the Jordanians, furthermore, there was a significant association between taking the vaccine booster dose in the country, as well as age group, working in the medical field, previous COVID-19 infection, and the intention to vaccinate the children (p < .001, p = .030, .031, .025, < .001, respectively).

CONCLUSION

Overall, our results emphasize a positive response and a positive attitude toward COVID-19 vaccination. In addition, define the groups to be targeted with effective communication regarding the COVID-19 vaccine and its booster dose.

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Implementing and Maintaining a SARS-CoV-2 Exposure Notification Application for Mobile Phones: The Finnish Experience

Exposure notification applications (ENAs) or digital proximity tracing apps were used in several countries during the COVID-19 pandemic. In this viewpoint, we share our experience of implementing and running the Finnish ENA (Koronavilkku), one of the national ENAs with the highest proportion of users during the pandemic. With the aim of strengthening public trust and increasing app uptake, there was a strong prioritization of privacy and data security for the end user throughout the ENA development. This, in turn, limited the use of the app as a tool for health care professionals and deeper insight into its potential effectiveness. The ENA was designed to supplement conventional contact tracing, rather than replace it, and to serve as an early warning system and a trigger for action for the user in case of potential exposure. The predefined target of 40% uptake in the population was achieved within 3 months of the ENA launch. We consider easy-to-understand information produced together with communication experts crucial during the changing pandemic situation. This information educated people about the app as one component in mitigating the pandemic. As the pandemic and its mitigation evolved, the ENA also needed adapting and updating. A few months after its launch, Finland joined European interoperability, which allowed the ENA to share information with ENAs of other countries. We added automatic token issuing to the ENA as of mid-2021. If added earlier and more comprehensively, automatization could have more effectively saved resources in health care services and prevented overburdening contact tracing teams, while also notifying potentially exposed individuals quicker and more reliably. In the spring of 2021, the number of active apps started to gradually decline. Quarantine and testing practices for asymptomatic vaccinated individuals following exposure to the virus were eased and home tests became more common, eventually replacing laboratory testing for much of the population. Taken together, this led to decreased token issuance, which weakened the potential public health usefulness of the app. A self-service option for token issuance would likely have prolonged the lifespan of the app. The ENA was discontinued in mid-2022. Regularly conducted surveys would have helped gain timely knowledge on the use and effectiveness of the app for better responding to the changing needs during the pandemic.

Digital Health Dashboards for Decision-Making to Enable Rapid Responses During Public Health Crises: Replicable and Scalable Methodology

BACKGROUND

The COVID-19 pandemic has reiterated the need for cohesive, collective, and deliberate societal efforts to address inherent inefficiencies in our health systems and overcome decision-making gaps using real-time data analytics. To achieve this, decision makers need independent and secure digital health platforms that engage citizens ethically to obtain big data, analyze and convert big data into real-time evidence, and finally, visualize this evidence to inform rapid decision-making.

OBJECTIVE

The objective of this study is to develop replicable and scalable jurisdiction-specific digital health dashboards for rapid decision-making to ethically monitor, mitigate, and manage public health crises via systems integration beyond health care.

METHODS

The primary approach in the development of the digital health dashboard was the use of global digital citizen science to tackle pandemics like COVID-19. The first step in the development process was to establish an 8-member Citizen Scientist Advisory Council via Digital Epidemiology and Population Health Laboratory's community partnerships. Based on the consultation with the council, three critical needs of citizens were prioritized: (1) management of household risk of COVID-19, (2) facilitation of food security, and (3) understanding citizen accessibility of public services. Thereafter, a progressive web application (PWA) was developed to provide daily services that address these needs. The big data generated from citizen access to these PWA services are set up to be anonymized, aggregated, and linked to the digital health dashboard for decision-making, that is, the dashboard displays anonymized and aggregated data obtained from citizen devices via the PWA. The digital health dashboard and the PWA are hosted on the Amazon Elastic Compute Cloud server. The digital health dashboard's interactive statistical navigation was designed using the Microsoft Power Business Intelligence tool, which creates a secure connection with the Amazon Relational Database server to regularly update the visualization of jurisdiction-specific, anonymized, and aggregated data.

RESULTS

The development process resulted in a replicable and scalable digital health dashboard for decision-making. The big data relayed to the dashboard in real time reflect usage of the PWA that provides households the ability to manage their risk of COVID-19, request food when in need, and report difficulties and issues in accessing public services. The dashboard also provides (1) delegated community alert system to manage risks in real time, (2) bidirectional engagement system that allows decision makers to respond to citizen queries, and (3) delegated access that provides enhanced dashboard security.

CONCLUSIONS

Digital health dashboards for decision-making can transform public health policy by prioritizing the needs of citizens as well as decision makers to enable rapid decision-making. Digital health dashboards provide decision makers the ability to directly communicate with citizens to mitigate and manage existing and emerging public health crises, a paradigm-changing approach, that is, inverting innovation by prioritizing community needs, and advancing digital health for equity.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR1-10.2196/46810.

Mental Health Professionals' Attitudes Toward Digital Mental Health Apps and Implications for Adoption in Portugal: Mixed Methods Study

BACKGROUND

Digital health apps are among the most visible facets of the ongoing digital transition in health care, with mental health-focused apps as one of the main therapeutic areas. However, concerns regarding their scientific robustness drove regulators to establish evaluation procedures, with Germany's Digitale Gesundheitsanwendungen program pioneering in app prescription with costs covered by statutory health insurance. Portugal gathers a set of conditions and requirements that position it as an excellent test bed for digital health apps. Its daunting mental health landscape reinforces the potential interest in new interventions. To understand if they would be acceptable, we need to understand the supply side's attitudes and perceptions toward them, that is, those of psychiatrists and psychologists.

OBJECTIVE

This study aims to understand the attitudes and expectations of psychiatrists and psychologists toward digital mental health apps (DMHAs) in the Portuguese context, as well as perceived benefits, barriers, and actions to support their adoption.

METHODS

We conducted a 2-stage sequential mixed methods study. Stage 1 consisted of a cross-sectional web survey adapted to the Portuguese context that was delivered to mental health professionals and psychologists. Stage 2 complemented the insights of the web survey results with a key opinion leader analysis.

RESULTS

A total of 160 complete survey responses were recorded, most of which were from psychologists. This is the most extensive study on mental health professionals' attitudes and perceptions of DMHAs in Portugal. A total of 87.2% (136/156) of the respondents supported the opportunity to prescribe DMHAs. Increased health literacy (139/160, 86.9%), wider adherence to treatment (137/160, 85.6%), and proper disease management (127/160, 79.4%) were the most frequently agreed upon benefits of DMHAs. However, only less than half (68/156, 43.6%) of the respondents planned to prescribe or recommend DMHAs, with psychologists being more favorable than psychiatrists. Professionals faced substantial barriers, such as a lack of information on DMHAs (154/160, 96.3%), the level of initial training effort (115/160, 71.9%), and the need for adjustments of clinical processes and records (113/160, 70.6%). Professionals reported that having more information on the available apps and their suitability for health objectives (151/160, 94.4%), more scientific evidence of the validity of the apps as a health intervention (147/160, 91.9%), and established recommendations of apps by specific clinical guidelines or professional societies (145/160, 90.6%) would be essential to foster adoption.

CONCLUSIONS

More information about DMHAs regarding their clinical validity and how they work is necessary so that such an intervention can be adopted in Portugal. Recommendations from professional and scientific societies, as well as from governmental bodies, are strongly encouraged. Although the benefits of and the barriers to using these apps are consensual, more evidence, along with further promotion of mental health professionals' digital literacy, is needed.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/41040.

Effectiveness of chatbots on COVID vaccine confidence and acceptance in Thailand, Hong Kong, and Singapore

Chatbots have become an increasingly popular tool in the field of health services and communications. Despite chatbots' significance amid the COVID-19 pandemic, few studies have performed a rigorous evaluation of the effectiveness of chatbots in improving vaccine confidence and acceptance. In Thailand, Hong Kong, and Singapore, from February 11th to June 30th, 2022, we conducted multisite randomised controlled trials (RCT) on 2,045 adult guardians of children and seniors who were unvaccinated or had delayed vaccinations. After a week of using COVID-19 vaccine chatbots, the differences in vaccine confidence and acceptance were compared between the intervention and control groups. Compared to non-users, fewer chatbot users reported decreased confidence in vaccine effectiveness in the Thailand child group [Intervention: 4.3 % vs. Control: 17%, P = 0.023]. However, more chatbot users reported decreased vaccine acceptance [26% vs. 12%, P = 0.028] in Hong Kong child group and decreased vaccine confidence in safety [29% vs. 10%, P = 0.041] in Singapore child group. There was no statistically significant change in vaccine confidence or acceptance in the Hong Kong senior group. Employing the RE-AIM framework, process evaluation indicated strong acceptance and implementation support for vaccine chatbots from stakeholders, with high levels of sustainability and scalability. This multisite, parallel RCT study on vaccine chatbots found mixed success in improving vaccine confidence and acceptance among unvaccinated Asian subpopulations. Further studies that link chatbot usage and real-world vaccine uptake are needed to augment evidence for employing vaccine chatbots to advance vaccine confidence and acceptance.

Epidemiological impacts of the NHS COVID-19 app in England and Wales throughout its first year

The NHS COVID-19 app was launched in England and Wales in September 2020, with a Bluetooth-based contact tracing functionality designed to reduce transmission of SARS-CoV-2. We show that user engagement and the app's epidemiological impacts varied according to changing social and epidemic characteristics throughout the app's first year. We describe the interaction and complementarity of manual and digital contact tracing approaches. Results of our statistical analyses of anonymised, aggregated app data include that app users who were recently notified were more likely to test positive than app users who were not recently notified, by a factor that varied considerably over time. We estimate that the app's contact tracing function alone averted about 1 million cases (sensitivity analysis 450,000-1,400,000) during its first year, corresponding to 44,000 hospital cases (SA 20,000-60,000) and 9,600 deaths (SA 4600-13,000).

Digital health in the era of COVID-19: Reshaping the next generation of healthcare

COVID-19 is one of the most deadly diseases to have stricken us in recent decades. In the fight against this disease, governments and stakeholders require all the assistance they can get from various systems, including digital health interventions. Digital health technologies are supporting the tracking of the COVID-19 outbreak, diagnosing patients, expediting the process of finding potential medicines and vaccines, and disinfecting the environment, The establishment of electronic medical and health records, computerized clinical decision support systems, telemedicine, and mobile health have shown the potential to strengthen the healthcare system. Recently, these technologies have aided the health sector in a variety of ways, including prevention, early diagnosis, treatment adherence, medication safety, care coordination, documentation, data management, outbreak tracking, and pandemic surveillance. On the other hand, implementation of such technologies has questions of cost, compatibility with existing systems, disruption in patient-provider interactions, and sustainability, calling for more evidence on clinical utility and economic evaluations to help shape the next generation of healthcare. This paper argues how digital health interventions assist in the fight against COVID-19 and their opportunities, implications, and limitations.

Participatory disease surveillance for a mass gathering — a prospective cohort study on COVID-19, Germany 2021

Background

Mass gatherings (MGs) such as music festivals and sports events have been associated with a high risk of SARS-CoV-2 transmission. On-site research can foster knowledge of risk factors for infections and improve risk assessments and precautionary measures at future MGs. We tested a web-based participatory disease surveillance tool to detect COVID-19 infections at and after an outdoor MG by collecting self-reported COVID-19 symptoms and tests.

Methods

We conducted a digital prospective observational cohort study among fully immunized attendees of a sports festival that took place from September 2 to 5, 2021 in Saxony-Anhalt, Germany. Participants used our study app to report demographic data, COVID-19 tests, symptoms, and their contact behavior. This self-reported data was used to define probable and confirmed COVID-19 cases for the full “study period” (08/12/2021 – 10/31/2021) and within the 14-day “surveillance period” during and after the MG, with the highest likelihood of an MG-related COVID-19 outbreak (09/04/2021 – 09/17/2021).

Results

A total of 2,808 of 9,242 (30.4%) event attendees participated in the study. Within the study period, 776 individual symptoms and 5,255 COVID-19 tests were reported. During the 14-day surveillance period around and after the MG, seven probable and seven PCR-confirmed COVID-19 cases were detected. The confirmed cases translated to an estimated seven-day incidence of 125 per 100,000 participants (95% CI [67.7/100,000, 223/100,000]), which was comparable to the average age-matched incidence in Germany during this time. Overall, weekly numbers of COVID-19 cases were fluctuating over the study period, with another increase at the end of the study period.

Conclusion

COVID-19 cases attributable to the mass gathering were comparable to the Germany-wide age-matched incidence, implicating that our active participatory disease surveillance tool was able to detect MG-related infections. Further studies are needed to evaluate and apply our participatory disease surveillance tool in other mass gathering settings.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-14505-x.