Evidence map›Paper›PMID 32836917›Full record

ArticleChaos, solitons, and fractals2020

Effect of the early use of antivirals on the COVID-19 pandemic. A computational network modeling approach.

José-María Benlloch, Juan-Carlos Cortés, David Martínez-Rodríguez, Raul-S Julián, Rafael-J Villanueva

Open access · greenAbstract read
In one paragraph

Article in Chaos, solitons, and fractals, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.6field-weighted citation impact, top 25% of its field
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

8 citing papers in PubMed, 19 citations in OpenAlex.

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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

5 authors at 2 institutions in 1 country.

José-María BenllochInstituto de Instrumentación para Imagen Molecular (I3M), Universitat Politècnica de València, Valencia, Spain.
Juan-Carlos CortésInstituto Universitario de Matemática Multidisciplinar, Universitat Politècnica de València, Valencia, Spain.
David Martínez-RodríguezInstituto Universitario de Matemática Multidisciplinar, Universitat Politècnica de València, Valencia, Spain.
Raul-S JuliánInstituto Universitario de Matemática Multidisciplinar, Universitat Politècnica de València, Valencia, Spain.
Rafael-J VillanuevaInstituto Universitario de Matemática Multidisciplinar, Universitat Politècnica de València, Valencia, Spain.
Universitat Politècnica de València · ESInstituto de Instrumentación para Imagen Molecular · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

It seems that we are far from controlling COVID-19 pandemics, and, consequently, returning to a fully normal life. Until an effective vaccine is found, safety measures as the use of face masks, social distancing, washing hands regularly, etc., have to be taken. Also, the use of appropriate antivirals in order to alleviate the symptoms, to control the severity of the illness and to prevent the transmission, could be a good option that we study in this work. In this paper, we propose a computational random network model to study the transmission dynamics of COVID-19 in Spain. Once the model has been calibrated and validated, we use it to simulate several scenarios where effective antivirals are available. The results show how the early use of antivirals may significantly reduce the incidence of COVID-19 and may avoid a new collapse of the health system.

Indexed as

Antiviral effectivenessComputational random network modelCOVID-19Transmission dynamics

Identifiers

PMID32836917
PMCPMC7434368
OpenAlexW3049749382

What OpenQuestion holds

Textmetadata
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.