Evidence map›Paper›PMID 35365709›Full record

ArticleScientific reports2022

Listening to bluetooth beacons for epidemic risk mitigation.

Gilles Barthe, Roberta De Viti, Peter Druschel, Deepak Garg, Manuel Gomez-Rodriguez, Pierfrancesco Ingo, Heiner Kremer, Matthew Lentz, Lars Lorch, Aastha Mehta and 1 more

Abstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. COVID-19 Pandemic Risk Assessment: Systematic Review.Risk management and healthcare policy · 2024
    Review
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Gilles BartheMax Planck Institute for Security and Privacy, Universitätsstraße 140, 44799, Bochum, Germany.
Roberta De VitiMax Planck Institute for Software Systems, Paul-Ehrlich-Straße 26, 67663, Kaiserslautern, Germany.
Peter DruschelMax Planck Institute for Software Systems, Paul-Ehrlich-Straße 26, 67663, Kaiserslautern, Germany.
Deepak GargMax Planck Institute for Software Systems, Paul-Ehrlich-Straße 26, 67663, Kaiserslautern, Germany.
Manuel Gomez-RodriguezMax Planck Institute for Software Systems, Paul-Ehrlich-Straße 26, 67663, Kaiserslautern, Germany. manuelgr@mpi-sws.org.
Pierfrancesco IngoMax Planck Institute for Software Systems, Paul-Ehrlich-Straße 26, 67663, Kaiserslautern, Germany.
Heiner KremerMax Planck Institute for Intelligent Systems, Max-Planck-Ring 4, 72076, Tübingen, Germany.
Matthew LentzDuke University, Durham, NC, 27708, USA.
Lars LorchETH Zürich, Rämistrasse 101, 8092, Zürich, Switzerland.
Aastha MehtaUniversity of British Columbia, Vancouver, BC, V6T 1Z4, Canada.
Bernhard SchölkopfMax Planck Institute for Intelligent Systems, Max-Planck-Ring 4, 72076, Tübingen, Germany. bs@tuebingen.mpg.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ongoing COVID-19 pandemic let to efforts to develop and deploy digital contact tracing systems to expedite contact tracing and risk notification. Unfortunately, the success of these systems has been limited, partly owing to poor interoperability with manual contact tracing, low adoption rates, and a societally sensitive trade-off between utility and privacy. In this work, we introduce a new privacy-preserving and inclusive system for epidemic risk assessment and notification that aims to address these limitations. Rather than capturing pairwise encounters between user devices as done by existing systems, our system captures encounters between user devices and beacons placed in strategic locations where infection clusters may originate. Epidemiological simulations using an agent-based model demonstrate that, by utilizing location and environmental information and interoperating with manual contact tracing, our system can increase the accuracy of contact tracing actions and may help reduce epidemic spread already at low adoption.

Indexed as

COVID-19PandemicsAuscultationContact TracingHumansPrivacy

Identifiers

PMID35365709
PMCPMC8973681

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.