Evidence map›Paper›PMID 35070645›Full record

ReviewSustainable cities and society2022

Airborne and aerosol pathogen transmission modeling of respiratory events in buildings: An overview of computational fluid dynamics.

Yahya Sheikhnejad, Reihaneh Aghamolaei, Marzieh Fallahpour, Hamid Motamedi, Mohammad Moshfeghi, Parham A Mirzaei, Hadi Bordbar

Abstract readReview
In one paragraph

Review in Sustainable cities and society, 2022. 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
–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

8 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Occurrence of pathogenicJournal of water and health · 2024
    Article
  5. Article
  6. Article
  7. Article
  8. 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

7 authors.

Yahya SheikhnejadCentre for Mechanical Technology and Automation, Department of Mechanical Engineering, Universidade de Aveiro, Aveiro 3810-193, Portugal.
Reihaneh AghamolaeiSchool of Mechanical and Manufacturing Engineering, Faculty of Engineering and Computing, Dublin City University, Dublin 9, Whitehall, Ireland.
Marzieh FallahpourSchool of Mechanical and Manufacturing Engineering, Faculty of Engineering and Computing, Dublin City University, Dublin 9, Whitehall, Ireland.
Hamid MotamediDepartment of Mechanical Engineering, Tarbiat Modares University, Iran.
Mohammad MoshfeghiDepartment of Mechanical Engineering, Sogang University, Seoul, South Korea.
Parham A MirzaeiArchitecture & Built Environment Department, University of Nottingham, University Park, Nottingham, UK.
Hadi BordbarSchool of Engineering, Aalto University, Finland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pathogen droplets released from respiratory events are the primary means of dispersion and transmission of the recent pandemic of COVID-19. Computational fluid dynamics (CFD) has been widely employed as a fast, reliable, and inexpensive technique to support decision-making and to envisage mitigatory protocols. Nonetheless, the airborne pathogen droplet CFD modeling encounters limitations due to the oversimplification of involved physics and the intensive computational demand. Moreover, uncertainties in the collected clinical data required to simulate airborne and aerosol transport such as droplets' initial velocities, tempo-spatial profiles, release angle, and size distributions are broadly reported in the literature. There is a noticeable inconsistency around these collected data amongst many reported studies. This study aims to review the capabilities and limitations associated with CFD modeling. Setting the CFD models needs experimental data of respiratory flows such as velocity, particle size, and number distribution. Therefore, this paper briefly reviews the experimental techniques used to measure the characteristics of airborne pathogen droplet transmissions together with their limitations and reported uncertainties. The relevant clinical data related to pathogen transmission needed for postprocessing of CFD data and translating them to safety measures are also reviewed. Eventually, the uncertainty and inconsistency of the existing clinical data available for airborne pathogen CFD analysis are scurtinized to pave a pathway toward future studies ensuing these identified gaps and limitations.

Indexed as

AerosolAirborne pathogenBuildingsCFDCOVID19Droplet releaseRespiratory events

Identifiers

PMID35070645
PMCPMC8767784

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.