Evidence map›Paper›PMID 33842101›Full record

ArticleAPL materials2021

Fight against COVID-19: The case of antiviral surfaces.

Kamyar Shirvanimoghaddam, Mohammad Karbalaei Akbari, Ram Yadav, Adil K Al-Tamimi, Minoo Naebe

Abstract read
In one paragraph

Article in APL materials, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing 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

26 citing papers in PubMed.

  1. Article
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  12. Passive antifouling and active self-disinfecting antiviral surfaces.Chemical engineering journal (Lausanne, Switzerland : 1996) · 2022
    Review
  13. Article
  14. Article
  15. Article
  16. Antiviral potential of nanoparticles for the treatment of Coronavirus infections.Journal of trace elements in medicine and biology : organ of the Society for Minerals and Trace Elements (GMS) · 2022
    Review
  17. Review
  18. Ag-enriched TiOMaterials chemistry and physics · 2022
    Article
  19. Review
  20. 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

5 authors.

Kamyar ShirvanimoghaddamCarbon Nexus, Institute for Frontier Materials, Deakin University, Geelong, Australia.ORCID 0000-0002-8136-8389
Mohammad Karbalaei AkbariFaculty of Science, Department of Solid State Sciences, Ghent University, Ghent, Belgium.
Ram YadavCarbon Nexus, Institute for Frontier Materials, Deakin University, Geelong, Australia.
Adil K Al-TamimiCivil Engineering Department, American University of Sharjah, Sharjah, United Arab Emirates.
Minoo NaebeCarbon Nexus, Institute for Frontier Materials, Deakin University, Geelong, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic is the largest global public health outbreak in the 21st century so far. Based on World Health Organization reports, the main source of SARS-CoV-2 infection is transmission of droplets released when an infected person coughs, sneezes, or exhales. Viral particles can remain in the air and on the surfaces for a long time. These droplets are too heavy to float in air and rapidly fall down onto the surfaces. To minimize the risk of the infection, entire surrounding environment should be disinfected or neutralized regularly. Development of the antiviral coating for the surface of objects that are frequently used by the public could be a practical route to prevent the spread of the viral particles and inactivation of the transmission of the viruses. In this short review, the design of the antiviral coating to combat the spread of different viruses has been discussed and the technological attempts for minimizing the coronavirus outbreak have been highlighted.

Identifiers

PMID33842101
PMCPMC8017599

What OpenQuestion holds

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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.