Evidence map›Paper›PMID 37521135›Full record

ArticleGeoscience frontiers2022

Assessment of SARS-CoV-2 airborne infection transmission risk in public buses.

M Bertone, A Mikszewski, L Stabile, G Riccio, G Cortellessa, F R d'Ambrosio, V Papa, L Morawska, G Buonanno

Abstract read
In one paragraph

Article in Geoscience frontiers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
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  4. Review
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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

9 authors.

M BertoneDepartment of Civil and Mechanical Engineering, University of Cassino and Southern Lazio, Cassino, FR, Italy.
A MikszewskiCIUS Building Performance Lab, The City University of New York, New York, NY, USA.
L StabileDepartment of Civil and Mechanical Engineering, University of Cassino and Southern Lazio, Cassino, FR, Italy.
G RiccioDepartment of Industrial Engineering, University of Naples "Federico II", Italy.
G CortellessaDepartment of Civil and Mechanical Engineering, University of Cassino and Southern Lazio, Cassino, FR, Italy.
F R d'AmbrosioDepartment of Industrial Engineering, University of Salerno, Italy.
V PapaDepartment of Motor Sciences and Wellness, University of Naples "Parthenope", Italy.
L MorawskaInternational Laboratory for Air Quality and Health, Queensland University of Technology, Brisbane, Queensland, Australia.
G BuonannoDepartment of Civil and Mechanical Engineering, University of Cassino and Southern Lazio, Cassino, FR, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Public transport environments are thought to play a key role in the spread of SARS-CoV-2 worldwide. Indeed, high crowding indexes (i.e. high numbers of people relative to the vehicle size), inadequate clean air supply, and frequent extended exposure durations make transport environments potential hotspots for transmission of respiratory infections. During the COVID-19 pandemic, generic mitigation measures (e.g. physical distancing) have been applied without also considering the airborne transmission route. This is due to the lack of quantified data about airborne contagion risk in transport environments. In this study, we apply a novel combination of close proximity and room-scale risk assessment approaches for people sharing public transport environments to predict their contagion risk due to SARS-CoV-2 respiratory infection. In particular, the individual infection risk of susceptible subjects and the transmissibility of SARS-CoV-2 (expressed through the reproduction number) are evaluated for two types of buses, differing in terms of exposure time and crowding index: urban and long-distance buses. Infection risk and reproduction number are calculated for different scenarios as a function of the ventilation rates (both measured and estimated according to standards), crowding indexes, and travel times. The results show that for urban buses, the close proximity contribution significantly affects the maximum occupancy to maintain a reproductive number of <1. In particular, full occupancy of the bus would be permitted only for an infected subject breathing, whereas for an infected subject speaking, masking would be required. For long-distance buses, full occupancy of the bus can be maintained only if specific mitigation solutions are simultaneously applied. For example, for an infected person speaking for 1 h, appropriate filtration of the recirculated air and simultaneous use of FFP2 masks would permit full occupancy of the bus for a period of almost 8 h. Otherwise, a high percentage of immunized persons (>80%) would be needed.

Indexed as

Airborne transmissionAir exchange rateBusMaximum occupancySARS-CoV-2Transport microenvironment

Identifiers

PMID37521135
PMCPMC9006420

What OpenQuestion holds

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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.