Evidence map›Paper›PMID 33083564›Full record

ArticleNPJ digital medicine2020

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

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

Abstract read
In one paragraph

Article in NPJ digital medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–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

15 citing papers in PubMed.

  1. Observational
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Projecting the criticality of COVID-19 transmission in India using GIS and machine learning methods.Journal of safety science and resilience = An quan ke xue yu ren xing (Ying wen) · 2021
    Article
  12. Article
  13. Societal Effects Are a Major Factor for the Uptake of the Coronavirus Disease 2019 (COVID-19) Digital Contact Tracing App in The Netherlands.Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research · 2021
    Article
  14. Article
  15. 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

9 authors.

Felix SattlerFraunhofer Heinrich Hertz Institute, 10587 Berlin, Germany.
Jackie MaFraunhofer Heinrich Hertz Institute, 10587 Berlin, Germany.
Patrick WagnerFraunhofer Heinrich Hertz Institute, 10587 Berlin, Germany.
David NeumannFraunhofer Heinrich Hertz Institute, 10587 Berlin, Germany.
Markus WenzelFraunhofer Heinrich Hertz Institute, 10587 Berlin, Germany.
Ralf SchäferFraunhofer Heinrich Hertz Institute, 10587 Berlin, Germany.
Wojciech SamekFraunhofer Heinrich Hertz Institute, 10587 Berlin, Germany.ORCID 0000-0002-6283-3265
Klaus-Robert MüllerDepartment of Electrical Engineering and Computer Science, Technische Universität Berlin, 10587 Berlin, Germany.ORCID 0000-0002-3861-7685
Thomas WiegandFraunhofer Heinrich Hertz Institute, 10587 Berlin, Germany.ORCID 0000-0002-1121-2581

Funding

Bundesministerium für Bildung und Forschung (Federal Ministry of Education and Research) 01IS14013ABundesministerium für Bildung und Forschung (Federal Ministry of Education and Research) 01IS18025ABundesministerium für Bildung und Forschung (Federal Ministry of Education and Research) 01IS18037ABundesministerium für Bildung und Forschung (Federal Ministry of Education and Research) 01IS18037I
6 · The paper itself

Abstract

Digital contact tracing approaches based on Bluetooth low energy (BLE) have the potential to efficiently contain and delay outbreaks of infectious diseases such as the ongoing SARS-CoV-2 pandemic. In this work we propose a machine learning based approach to reliably detect subjects that have spent enough time in close proximity to be at risk of being infected. Our study is an important proof of concept that will aid the battery of epidemiological policies aiming to slow down the rapid spread of COVID-19.

Indexed as

Computer scienceRisk factorsViral infection

Identifiers

PMID33083564
PMCPMC7538938

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.