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Open accessJournal ArticleDOI: 10.2196/23362

Barriers to the Large-Scale Adoption of a COVID-19 Contact Tracing App in Germany: Survey Study.

02 Mar 2021-Journal of Medical Internet Research (JMIR Publications Inc., Toronto, Canada)-Vol. 23, Iss: 3
Abstract: Background: During the COVID-19 pandemic, one way to reduce further transmissions of SARS-CoV-2 is the widespread use of contact tracing apps Such apps keep track of proximity contacts and warn contacts of persons who tested positive for an infection Objective: In this study, we analyzed potential barriers to the large-scale adoption of the official contact tracing app that was introduced in Germany on June 16, 2020 Methods: Survey data were collected from 3276 adults during the week the app was introduced using an offline-recruited, probability-based online panel of the general adult population in Germany Results: We estimate that 81% of the population aged 18 to 77 years possess the devices and ability to install the official app and that 35% are also willing to install and use it Potential spreaders show high access to devices required to install the app (92%) and high ability to install the app (91%) but low willingness (31%) to correctly adopt the app, whereas for vulnerable groups, the main barrier is access (62%) Conclusions: The findings suggest a pessimistic view on the effectiveness of app-based contact tracing to contain the COVID-19 pandemic We recommend targeting information campaigns at groups with a high potential to spread the virus but who are unwilling to install and correctly use the app, in particular men and those aged between 30 and 59 years In addition, vulnerable groups, in particular older individuals and those in lower-income households, may be provided with equipment and support to overcome their barriers to app adoption

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Topics: Population (52%)
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Open accessJournal ArticleDOI: 10.2196/27882
26 Mar 2021-
Abstract: Background: Adoption and evaluation of contact tracing tools based on information and communications technology may expand the reach and efficacy of traditional contact tracing methods in fighting COVID-19. The Dutch Ministry of Health, Welfare and Sports initiated and developed CoronaMelder, a COVID-19 contact tracing app. This app is based on a Google/Apple Exposure Notification approach and aims to combat the spread of the coronavirus among individuals by notifying those who are at increased risk of infection due to proximity to someone who later tests positive for COVID-19. The app should support traditional contact tracing by faster tracing and greater reach compared to regular contact tracing procedures. Objective: The main goal of this study is to investigate whether the CoronaMelder is able to support traditional contact tracing employed by public health authorities. To achieve this, usability tests were conducted to answer the following question: is the CoronaMelder user-friendly, understandable, reliable and credible, and inclusive? Methods: Participants (N=44) of different backgrounds were recruited: youth with varying educational levels, youth with an intellectual disability, migrants, adults (aged 40-64 years), and older adults (aged >65 years) via convenience sampling in the region of Twente in the Netherlands. The app was evaluated with scenario-based, think-aloud usability tests and additional interviews. Findings were recorded via voice recordings, observation notes, and the Dutch User Experience Questionnaire, and some participants wore eye trackers to measure gaze behavior. Results: Our results showed that the app is easy to use, although problems occurred with understandability and accessibility. Older adults and youth with a lower education level did not understand why or under what circumstances they would receive notifications, why they must share their key (ie, their assigned identifier), and what happens after sharing. In particular, youth in the lower-education category did not trust or understand Bluetooth signals, or comprehend timing and follow-up activities after a risk exposure notification. Older adults had difficulties multitasking (speaking with a public health worker and simultaneously sharing the key in the app). Public health authorities appeared to be unprepared to receive support from the app during traditional contact tracing because their telephone conversation protocol lacks guidance, explanation, and empathy. Conclusions: The study indicated that the CoronaMelder app is easy to use, but participants experienced misunderstandings about its functioning. The perceived lack of clarity led to misconceptions about the app, mostly regarding its usefulness and privacy-preserving mechanisms. Tailored and targeted communication through, for example, public campaigns or social media, is necessary to provide correct information about the app to residents in the Netherlands. Additionally, the app should be presented as part of the national coronavirus measures instead of as a stand-alone app offered to the public. Public health workers should be trained to effectively and empathetically instruct users on how to use the CoronaMelder app.

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Topics: Contact tracing (51%), mHealth (51%)

3 Citations


Open accessJournal ArticleDOI: 10.1007/S00500-021-05948-2
28 Jun 2021-
Abstract: The coronavirus disease 2019 (COVID-19) was first reported in December 2019 in Wuhan, China, and then moved to almost every country showing an unprecedented outbreak. The world health organization declared COVID-19 a pandemic. Since then, millions of people were infected, and millions have lost their lives all around the globe. By the end of 2020, effective vaccines that could prevent the fast spread of the disease started to loom on the horizon. Nevertheless, isolation, social distancing, face masks, and quarantine are the best-known measures, in the time being, to fight the pandemic. On the other hand, contact tracing is an effective procedure in tracking infections and saving others' lives. In this paper, we devise a new approach using a hybrid harmony search (HHS) algorithm that casts the problem of finding strongly connected components (SCCs) to contact tracing. This new approach is named as hybrid harmony search contact tracing (HHS-CT) algorithm. The hybridization is achieved by integrating the stochastic hill climbing into the operators' design of the harmony search algorithm. The HHS-CT algorithm is compared to other existing algorithms of finding SCCs in directed graphs, where it showed its superiority over these algorithms. The devised approach provides a 77.18% enhancement in terms of run time and an exceptional average error rate of 1.7% compared to the other existing algorithms of finding SCCs.

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Topics: Harmony search (54%), Hill climbing (53%)

2 Citations


Open accessJournal ArticleDOI: 10.2196/27768
Abstract: Background: Several countries have implemented mobile apps in an attempt to trace close contacts of patients with COVID-19 and, in turn, reduce the spread of SARS-CoV-2. However, the effectiveness of this approach depends on the adherence of a large segment of the population. Objective: The aims of this study were to evaluate the acceptability of a COVID-19 contact tracing mobile app among the French population and to investigate the barriers to its use. Methods: The Health Literacy Survey 2019 questioned 1003 people in France during the COVID-19 pandemic on the basis of quota sampling. The survey collected sociodemographic characteristics and health literacy data, as well as information on participants' communication with caregivers, trust in institutions, and COVID-19 knowledge and preventive behaviors. The acceptability of a mobile app for contact tracing was measured by a single question, the responses to which were grouped into three modalities: app-supporting, app-willing, and app-reluctant. Multinomial logistic regression analysis was performed to identify the factors associated with the acceptability of a mobile app during the COVID-19 pandemic. Results: Only 19.2% (193/1003) of all participants were app-supporting, whereas half of them (504/1003, 50.3%) were reluctant. The factors associated with willingness or support toward the contact tracing app included lower financial deprivation (app-willing: adjusted odds ratio [aOR] 0.8, 95% CI 0.69-0.93; app-supporting: aOR 0.7, 95% CI 0.58-0.84) and higher perceived usefulness of using a mobile app to send completed health questionnaires to doctors (app-willing: aOR 2.3, 95% CI 1.70-3.26; app-supporting: aOR 3.1, 95% CI 2.04-4.82). Furthermore, the likelihood of supporting the mobile app increased with age over 60 years (aOR 1.9, 95% CI 1.13-3.22), trust in political representatives (aOR 2.7, 95% CI 1.72-4.23), feeling concerned about the pandemic situation (aOR 2.2, 95% CI 1.47-3.32), and knowledge about the transmission of COVID-19 (aOR 2.0, 95% CI 1.39-2.96). Conclusions: The most socioeconomically precarious people, who are at a higher risk of SARS-CoV-2 infection, are also the most reluctant to using a contact tracing mobile app. Therefore, optimal adherence can only be effective with a targeted discourse on public health benefits to adopt such an app, which should be combined with a reduction in inequalities by acting on structural determinants.

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Topics: Population (52%), Contact tracing (51%), Health literacy (51%)

2 Citations


Open accessPosted ContentDOI: 10.1101/2021.03.04.21252924
08 Mar 2021-medRxiv
Abstract: Objectives: To conduct an independent study investigating how adults perceive the usability, and functionality of the NHS COVID-19 app. This study aims to highlight strengths, and provide recommendations to improve adoption of future contact tracing developments. Design: A 60-item, anonymous online questionnaire, disseminated through social media outlets and email-lists by a team from Imperial College London. Setting: England Participants: Convenience sample of 1036 responses, from participants aged 18 and above, between December 2020 to February 2021. Primary Outcome Measures: Evaluate the compliance and public attitude towards the NHS COVID-19 app, regarding its functionality and features. This included whether participants expectations were met, and their thoughts on the app privacy and security. Furthermore, to distinguish how usability, perception, and adoption differed with varying demographics and user values. Results: Fair app compliance was identified, with the app meeting expectations of 62.1% of participants who stated they downloaded it after weighted analysis. However, participants finding the interface challenging were less likely to read information in the app and had a lesser understanding of its functionality. Furthermore, lack of understanding regarding the apps functionality and privacy concerns were possibly reasons why users did not download it. A readability analysis of the text revealed that app information was conveyed at a level which might only be accessible to under 60% of the population. The study highlighted issues related to the potential of false positives caused by the design choices in the Check-In feature. Conclusion: This study showed that while the NHS COVID-19 app was viewed positively, there remained issues regarding participants perceived knowledge of the app functionality, potentially affecting compliance. Therefore, we recommended improvements regarding the delivery and presentation of the apps information, and highlighted the potential need for the ability to check out of venues to reduce the number of false positive contacts.

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1 Citations


Open accessJournal ArticleDOI: 10.1111/RSSA.12749
Carina Cornesse1, Ulrich Krieger1, Marie-Lou Sohnius1, Marina Fikel1  +9 moreInstitutions (1)
Abstract: The outbreak of COVID-19 has sparked a sudden demand for fast, frequent and accurate data on the societal impact of the pandemic. This demand has highlighted a divide in survey data collection: Most probability-based social surveys, which can deliver the necessary data quality to allow valid inference to the general population, are slow, infrequent and ill-equipped to survey people during a lockdown. Most non-probability online surveys, which can deliver large amounts of data fast, frequently and without interviewer contact, however, cannot provide the data quality needed for population inference. Well aware of this chasm in the data landscape, at the onset of the pandemic, we set up the Mannheim Corona Study (MCS), a rotating panel survey with daily data collection on the basis of the long-standing probability-based online panel infrastructure of the German Internet Panel (GIP). The MCS has provided academics and political decision makers with key information to understand the social and economic developments during the early phase of the pandemic. This paper describes the panel adaptation process, demonstrates the power of the MCS data on its own and when linked to other data sources, and evaluates the data quality achieved by the MCS fast-response methodology. © 2021 The Authors. Journal of the Royal Statistical Society: Series A (Statistics in Society) published by John Wiley & Sons Ltd on behalf of Royal Statistical Society.

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Topics: Survey data collection (57%), Data quality (55%), Population (52%) ... read more

1 Citations


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25 results found


Open accessJournal ArticleDOI: 10.18637/JSS.V045.I03
Abstract: The R package mice imputes incomplete multivariate data by chained equations. The software mice 1.0 appeared in the year 2000 as an S-PLUS library, and in 2001 as an R package. mice 1.0 introduced predictor selection, passive imputation and automatic pooling. This article documents mice, which extends the functionality of mice 1.0 in several ways. In mice, the analysis of imputed data is made completely general, whereas the range of models under which pooling works is substantially extended. mice adds new functionality for imputing multilevel data, automatic predictor selection, data handling, post-processing imputed values, specialized pooling routines, model selection tools, and diagnostic graphs. Imputation of categorical data is improved in order to bypass problems caused by perfect prediction. Special attention is paid to transformations, sum scores, indices and interactions using passive imputation, and to the proper setup of the predictor matrix. mice can be downloaded from the Comprehensive R Archive Network. This article provides a hands-on, stepwise approach to solve applied incomplete data problems.

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Topics: Imputation (statistics) (61%), Pooling (53%), Model selection (50%)

7,115 Citations



Open accessJournal ArticleDOI: 10.2196/JMIR.6.3.E34
Abstract: An error in the CHERRIES statement has been corrected (J Med Internet Res 2004;6[3]:e34). In the original paper, in table 1, denominator and numerator were flipped in the recommendations on how response rates (view rate, participation rate, and completion rate) should be calculated. The view rate should be the ratio of unique survey visitors divided by unique site visitors. The participation rate should be the ratio of those who agreed to participate divided by unique first survey page visitors. The completion rate is the ratio of the number of people who finished the survey divided by those who agreed to participate. The corrections have been made in the table in both columns. [J Med Internet Res 2012;14(1):e8]

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1,746 Citations


Open accessJournal ArticleDOI: 10.1126/SCIENCE.ABB6936
Luca Ferretti1, Chris Wymant1, Michelle Kendall1, Lele Zhao1  +5 moreInstitutions (1)
31 Mar 2020-Science
Abstract: The newly emergent human virus SARS-CoV-2 (severe acute respiratory syndrome-coronavirus 2) is resulting in high fatality rates and incapacitated health systems. Preventing further transmission is a priority. We analyzed key parameters of epidemic spread to estimate the contribution of different transmission routes and determine requirements for case isolation and contact tracing needed to stop the epidemic. Although SARS-CoV-2 is spreading too fast to be contained by manual contact tracing, it could be controlled if this process were faster, more efficient, and happened at scale. A contact-tracing app that builds a memory of proximity contacts and immediately notifies contacts of positive cases can achieve epidemic control if used by enough people. By targeting recommendations to only those at risk, epidemics could be contained without resorting to mass quarantines ("lockdowns") that are harmful to society. We discuss the ethical requirements for an intervention of this kind.

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Topics: Contact tracing (51%)

1,692 Citations