Risk estimation of SARS-CoV-2 transmission from bluetooth low energy measurements

Sattler, Felix; Ma, Jackie; Wagner, Patrick; Neumann, David; Wenzel, Markus; Schäfer, Reiner; Samek, Wojciech; Müller, Klaus Robert; Wiegand, Thomas

doi:10.1038/s41746-020-00340-0

Cited by 29 publications

(31 citation statements)

References 12 publications

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“…DCT apps often use Bluetooth technology to (temporarily) record proximity events between 2 phones running the app. 1 , 2 , 3 If users are diagnosed with COVID-19, they can use the app to declare the diagnosis and recent contacts are instantly, automatically, and anonymously notified of their risk and asked to self-quarantine. Various countries already use DCT apps (eg, Germany and Singapore), but in other countries such an app was not (yet) introduced at the time that we conducted our study (eg, The Netherlands and Sweden).…”

Section: Introductionmentioning

confidence: 99%

“…Because a person’s choice to install a DCT app is not only influenced by impacts they experience themselves, but also by effects on public health as well as the greater good, 9 we also included 3 societal effects in our experiment that might affect uptake, according to the literature: (1) decrease in the number of deaths, 9 , 10 (2) decrease in the number of households facing long-term financial problems, 9 and (3) the number of people quarantined at home as a result of an incorrect notification by the app. 3 , 5 Therefore, the key objective of our study is to investigate the extent to which uptake of a DCT app among the Dutch population is affected by its configurations, its societal effects, as well as by government policies toward such an app, and whether preferences differ between subgroups in the population. We have addressed these questions through a DCE.…”

Section: Introductionmentioning

confidence: 99%

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Societal Effects Are a Major Factor for the Uptake of the Coronavirus Disease 2019 (COVID-19) Digital Contact Tracing App in The Netherlands

et al. 2021

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Objectives Our study investigates the extent to which uptake of a COVID-19 digital contact-tracing (DCT) app among the Dutch population is affected by its configurations, its societal effects, and government policies toward such an app. Methods We performed a discrete choice experiment among Dutch adults including 7 attributes, that is, who gets a notification, waiting time for testing, possibility for shops to refuse customers who have not installed the app, stopping condition for contact tracing, number of people unjustifiably quarantined, number of deaths prevented, and number of households with financial problems prevented. The data were analyzed by means of panel mixed logit models. Results The prevention of deaths and financial problems of households had a very strong influence on the uptake of the app. Predicted app uptake rates ranged from 24% to 78% for the worst and best possible app for these societal effects. We found a strong positive relationship between people’s trust in government and people’s propensity to install the DCT app. Conclusions The uptake levels we find are much more volatile than the uptake levels predicted in comparable studies that did not include societal effects in their discrete choice experiments. Our finding that the societal effects are a major factor in the uptake of the DCT app results in a chicken-or-the-egg causality dilemma. That is, the societal effects of the app are severely influenced by the uptake of the app, but the uptake of the app is severely influenced by its societal effects.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Societal Effects Are a Major Factor for the Uptake of the Coronavirus Disease 2019 (COVID-19) Digital Contact Tracing App in The Netherlands

et al. 2021

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“…If one of the proximity contacts tests positive for SARS-CoV-2, all other app users with relevant proximity within the window of infectivity are warned by the app. While the accuracy is not perfect, it appears to be fit for the purpose of DPT [11,12], as also evidenced by reports of alerted app users who tested positive (eg, [13]).…”

Section: The Use Of Digital Tools For Pandemic Mitigationmentioning

confidence: 97%

“…A more novel approach to proximity tracing is based on peer-to-peer tracking, such as through Bluetooth low energy beacons [10]. In this approach, apps send out signals that include a user-specific identification number, which are then received by smartphones within a certain radius [11]. The signal strength correlates with proximity (the stronger the signal, the closer the sending device), which can be leveraged to determine proximity contacts that occurred within a distance that potentially enables SARS-CoV-2 transmission.…”

Section: The Use Of Digital Tools For Pandemic Mitigationmentioning

confidence: 99%

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

Wyl¹

2021

JMIR Mhealth Uhealth

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Background Several countries have released digital proximity tracing (DPT) apps to complement manual contact tracing for combatting the SARS-CoV-2 pandemic. DPT aims to notify app users about proximity exposures to persons infected with SARS-CoV-2 so that they can self-quarantine. The success of DPT apps depends on user acceptance and the embedding of DPT into the pandemic mitigation strategy. Objective By searching for media articles published during the first 3 months after DPT launch, the implementation of DPT in Switzerland was evaluated to inform similar undertakings in other countries. The second aim of the study was to create a link between reported DPT implementation challenges and normalization process theory for planning and optimizing complex digital health interventions, which can provide useful guidance for decision-making in DPT design and implementation. Methods A Swiss media database was searched for articles on the Swiss DPT app (SwissCovid) published in German or French between July 4 and October 3, 2020. In a structured process, topics were extracted and clustered manually from articles that were deemed pertinent. Extracted topics were mapped to four NPT constructs, which reflected the flow of intervention development from planning, stakeholder onboarding, and execution to critical appraisal. Coherence constructs describe sense-making by stakeholders, cognitive participation constructs reflect participants’ efforts to create engagement with the intervention, collective actions refer to intervention execution and joint stakeholder efforts to make the intervention work, and reflexive monitoring refers to collective risk-benefit appraisals to create improvements. Results Out of 94 articles deemed pertinent and selected for closer inspection, 38 provided unique information on implementation challenges. Five challenge areas were identified: communication challenges, challenges for DPT to interface with other processes, fear of resource competition with established pandemic mitigation measures, unclear DPT effectiveness, and obstacles to greater user coverage and compliance. Specifically, several articles mentioned unclear DPT benefits to affect commitment and to raise fears among different health system actors regarding resource competition. Moreover, media reports indicated process interface challenges such as delays or unclear responsibilities in the notification cascade, as well as misunderstandings and unmet communication needs from health system actors. Finally, reports suggested misaligned incentives, not only for app usage by the public but also for process engagement by other actors in the app notification cascade. NPT provided a well-fitting framework to contextualize the different DPT implementation challenges and to highlight improvement strategies, namely a better alignment of stakeholder incentives, or stakeholder-specific communication to address their concerns about DPT. Conclusions Early experiences from one of the first adopters of DPT indicate that nontechnical implementation challenges may affect the effectiveness of DPT. The NPT analysis provides a novel perspective on DPT implementation and stresses the need for stakeholder inclusion in development and operationalization.

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“…We define E v u (t) as the exposure score of the contact event between user u and v at time t which we calculate from the work described in [18]. In this work, the authors design multiple models to determine the severity of a contact event between two individuals.…”

Section: B Mathematical Model For Probability Of An User Being Positmentioning

confidence: 99%

PAARS: Privacy Aware Access Regulation System

Anjum

Mohammed

2020

2020 11th IEEE Annual Ubiquitous Computing, Electronics &Amp; Mobile Communication Conference (UEMCON)

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Risk estimation of SARS-CoV-2 transmission from bluetooth low energy measurements

Cited by 29 publications

References 12 publications

Societal Effects Are a Major Factor for the Uptake of the Coronavirus Disease 2019 (COVID-19) Digital Contact Tracing App in The Netherlands

Societal Effects Are a Major Factor for the Uptake of the Coronavirus Disease 2019 (COVID-19) Digital Contact Tracing App in The Netherlands

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

PAARS: Privacy Aware Access Regulation System

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