Evidence map›Paper›PMID 36742376›Full record

ArticleEngineering with computers2023

A computational framework for transmission risk assessment of aerosolized particles in classrooms.

Kendrick Tan, Boshun Gao, Cheng-Hau Yang, Emily L Johnson, Ming-Chen Hsu, Alberto Passalacqua, Adarsh Krishnamurthy, Baskar Ganapathysubramanian

Abstract read
In one paragraph

Article in Engineering with computers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

8 authors.

Kendrick TanDepartment of Mechanical Engineering, Iowa State University, Ames, IA 50011 USA.
Boshun GaoDepartment of Mechanical Engineering, Iowa State University, Ames, IA 50011 USA.
Cheng-Hau YangDepartment of Mechanical Engineering, Iowa State University, Ames, IA 50011 USA.
Emily L JohnsonDepartment of Mechanical Engineering, Iowa State University, Ames, IA 50011 USA.
Ming-Chen HsuDepartment of Mechanical Engineering, Iowa State University, Ames, IA 50011 USA.
Alberto PassalacquaDepartment of Mechanical Engineering, Iowa State University, Ames, IA 50011 USA.
Adarsh KrishnamurthyDepartment of Mechanical Engineering, Iowa State University, Ames, IA 50011 USA.
Baskar GanapathysubramanianDepartment of Mechanical Engineering, Iowa State University, Ames, IA 50011 USA.

Funding

Biomechanical indicators of bicuspid aortic valve dysfunctionR01HL142504 · NHLBI · UNIVERSITY OF TEXAS AT AUSTIN · PI GORMAN, ROBERT C, HSU, MING-CHEN · 2018 to 2021
$2.9M
NHLBI NIH HHS R01 HL142504
6 · The paper itself

Abstract

Infectious airborne diseases like the recent COVID-19 pandemic render confined spaces high-risk areas. However, in-person activities like teaching in classroom settings and government services are often expected to continue or restart quickly. It becomes important to evaluate the risk of airborne disease transmission while accounting for the physical presence of humans, furniture, and electronic equipment, as well as ventilation. Here, we present a computational framework and study based on detailed flow physics simulations that allow straightforward evaluation of various seating and operating scenarios to identify risk factors and assess the effectiveness of various mitigation strategies. These scenarios include seating arrangement changes, presence/absence of computer screens, ventilation rate changes, and presence/absence of mask-wearing. This approach democratizes risk assessment by automating a key bottleneck in simulation-based analysis-creating an adequately refined mesh around multiple complex geometries. Not surprisingly, we find that wearing masks (with at least 74% inward protection efficiency) significantly reduced transmission risk against unmasked and infected individuals. While the use of face masks is known to reduce the risk of transmission, we perform a systematic computational study of the transmission risk due to variations in room occupancy, seating layout and air change rates. In addition, our findings on the efficacy of face masks further support use of face masks. The availability of such an analysis approach will allow education administrators, government officials (courthouses, police stations), and hospital administrators to make informed decisions on seating arrangements and operating procedures. Supplementary Information: The online version contains supplementary material available at 10.1007/s00366-022-01773-9.

Indexed as

Aerosolized particulate transferCFDClassroomRisk assessment

Identifiers

PMID36742376
PMCPMC9884603

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.