Evidence map›Paper›PMID 35397458›Full record

ArticleJournal of colloid and interface science2022

Pathways to community transmission of COVID-19 due to rapid evaporation of respiratory virulets.

Mitali Basak, Shirsendu Mitra, Dipankar Bandyopadhyay

Abstract read
In one paragraph

Article in Journal of colloid and interface science, 2022. 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. 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

3 authors.

Mitali BasakCentre for Nanotechnology, Indian Institute of Technology Guwahati, Assam 781039, India.
Shirsendu MitraDepartment of Chemical Engineering, Indian Institute of Technology Guwahati, Assam 781039, India.
Dipankar BandyopadhyayCentre for Nanotechnology, Indian Institute of Technology Guwahati, Assam 781039, India; Department of Chemical Engineering, Indian Institute of Technology Guwahati, Assam 781039, India; School of Health Sciences and Technology,Indian Institute of Technology Guwahati, Assam 781039, India. Electronic address: dipban@iitg.ac.in.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

hypothesisThe formation of virus-laden colloidal respiratory microdroplets - the sneeze or cough virulets and their evaporation driven miniaturization in the open air are found to have a significant impact on the community transmission of COVID-19 pandemic. SIMULATION DETAILS: We simulate the motions and trajectories of virulets by employing laminar fluid flow coupled with droplet tracing physics. A force field analysis has been included considering the gravity, drag, and inertial forces to unleash some of the finer features of virulet trajectories leading to the droplet and airborne transmissions of the virus. Furthermore, an analytical model corroborates temperature (T) and relative humidity (RH) controlled droplet miniaturization.

resultsThe study elucidates that the tiny (1-50 µm) and intermediate (60-100 µm) size ranged virulets tend to form bioaerosol and facilitate an airborne transmission while the virulets of larger dimensions (300 to 500 µm) are more prone to gravity dominated droplet transmission. Subsequently, the mapping between the T and RH guided miniaturization of virulets with the COVID-19 cases for six different cities across the globe justifies the significant contribution of miniaturization-based bioaerosol formation for community transmission of the pandemic.

Indexed as

COVID-19CoughHumansPandemicsPhysical PhenomenaSneezingCommunity transmissionCOVID–19EvaporationRespiratory dropletsViral load

Identifiers

PMID35397458
PMCPMC8986321

What OpenQuestion holds

Textmetadata
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Registered trials

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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.