Evidence map›Paper›PMID 40477377›Full record

ArticleCase studies in thermal engineering2021

Evaluating heating, ventilation, and air-conditioning systems toward minimizing the airborne transmission risk of Mucormycosis and COVID-19 infections in built environment.

Micheal A William, María José Suárez-López, Silvia Soutullo, Ahmed A Hanafy

Abstract read
In one paragraph

Article in Case studies in thermal engineering, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
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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

4 authors.

Micheal A WilliamMechanical Engineering, School of Engineering, The Knowledge Hub, Coventry University, Cairo, Egypt.
María José Suárez-LópezEDZE (Energía), Campus de Viesques, Universidad de Oviedo, 33204, Gijón, Asturias, Spain.
Silvia SoutulloUnidad de Eficiencia Energética en la Edificación, CIEMAT, Madrid, Spain.
Ahmed A HanafyMechanical Engineering Department, College of Engineering & Technology, Arab Academy for Science, Technology & Maritime Transport, Alexandria, Egypt.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This ongoing global pandemic of the COVID-19 has generated a significant international concern for our respiratory health. For instance, the breakout of the COVID-19 pandemic was directly linked to the spread of infectious particles in indoor environments between humans, underlining the significance of rigorous and effective actions to limit the transmission of diseases. Recently, Mucormycosis infections in COVID-19 patients have been identified. This investigation aims to investigate potential infection control HVAC solutions for indoor environments, as well as their core mechanisms for reducing infectious disease risk through simulation models of a valid building in a hot climatic region. Considering recent international recommendations, the investigation relies on a methodology of testing a validated building energy model to several systems in the light of infectious diseases prevention. All proposed models are exposed to cost analysis in line with carbon emissions, and indoor thermal conditions. The analysis outlined through parametric simulations, the effectiveness of the proposed DOAS in supplying 100% fresh ventilation air and enhancing the control of the indoor relative humidity simultaneously. Finally, through an enviro-economic assessment, the study concluded that the DOAS model reduced the CO

Indexed as

Building simulationCarbon footprintCOVID-19Energy-efficiencyMucormycosis

Identifiers

PMID40477377
PMCPMC8527735

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.