Evidence map›Paper›PMID 34065581›Full record

ArticleEntropy (Basel, Switzerland)2021

Improvement of Contact Tracing with Citizen's Distributed Risk Maps.

Miguel Rebollo, Rosa María Benito, Juan Carlos Losada, Javier Galeano

Abstract read
In one paragraph

Article in Entropy (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

4 authors.

Miguel RebolloVRAIn-Valencian Research Institute for Artificial Intelligence, Universitat Politècnica de València, 46022 Valencia, Spain.ORCID 0000-0002-5115-8751
Rosa María BenitoComplex Systems Group, Universidad Politécnica de Madrid, 28040 Madrid, Spain.
Juan Carlos LosadaComplex Systems Group, Universidad Politécnica de Madrid, 28040 Madrid, Spain.ORCID 0000-0002-4373-603X
Javier GaleanoComplex Systems Group, Universidad Politécnica de Madrid, 28040 Madrid, Spain.ORCID 0000-0003-0706-4317

Funding

Horizon 2020 Framework Programme 952215Spanish Ministry of Science, Innovation and Universities PGC2018-093854-B-I00bSpanish Ministry of Science, Innovation and Universities RTI2018-095390-B-C32
6 · The paper itself

Abstract

The rapid spread of COVID-19 has demonstrated the need for accurate information to contain its diffusion. Technological solutions are a complement that can help citizens to be informed about the risk in their environment. Although measures such as contact traceability have been successful in some countries, their use raises society's resistance. This paper proposes a variation of the consensus processes in directed networks to create a risk map of a determined area. The process shares information with trusted contacts: people we would notify in the case of being infected. When the process converges, each participant would have obtained the risk map for the selected zone. The results are compared with the pilot project's impact testing of the Spanish contact tracing app (RadarCOVID). The paper also depicts the results combining both strategies: contact tracing to detect potential infections and risk maps to avoid movements into conflictive areas. Although some works affirm that contact tracing apps need 60% of users to control the propagation, our results indicate that a 40% could be enough. On the other hand, the elaboration of risk maps could work with only 20% of active installations, but the effect is to delay the propagation instead of reducing the contagion. With both active strategies, this methodology is able to significantly reduce infected people with fewer participants.

Indexed as

collaborationcomplex networkconsensuscontact tracingCOVIDrisk map

Identifiers

PMID34065581
PMCPMC8160685

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.