Quantifying crowding-ventilation effect on respiratory infections.

Wei Jia, Pan Cheng, Jian Hang, Hua Qian, Yuguo Li

Abstract read

In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Wei JiaDepartment of Mechanical Engineering, The University of Hong Kong, Hong Kong, 999077, China.ORCID http://orcid.org/0000-0001-7962-1376

Pan ChengDepartment of Mechanical Engineering, The University of Hong Kong, Hong Kong, 999077, China.

Jian HangSchool of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, 519082, China.

Hua QianSchool of Energy and Environment, Southeast University, Nanjing, 211189, China.ORCID http://orcid.org/0000-0002-7237-7806

Yuguo LiDepartment of Mechanical Engineering, The University of Hong Kong, Hong Kong, 999077, China. liyg@hku.hk.ORCID http://orcid.org/0000-0002-2281-4529

Funding

Research Grants Council, University Grants Committee (RGC, UGC) 17204725Research Grants Council, University Grants Committee (RGC, UGC) 17206723Research Grants Council, University Grants Committee (RGC, UGC) C7104-21G

6 · The paper itself

Abstract

Crowded and poorly ventilated indoor spaces drive outbreaks of respiratory infections such as coronavirus disease 2019 (COVID-19), often leading to superspreading events. While overcrowding heightens risk, its interplay with space size and ventilation remains underexplored. We introduce a framework to assess this risk, using effective clean flow rate, which combines clean airflow (outdoor air, filtration, ultraviolet germicidal irradiation) with volume-time air clearance (VTAC), i.e., dilution from indoor air volume per person over time, and intake fraction time, which quantifies aerosol exposure risk independent of infectious quanta generation. Analysis of real outbreak data from jails, earthquake shelters, and dormitories shows modest spaciousness (16-32 m

Indexed as

COVID-19CrowdingRespiratory Tract InfectionsVentilationAerosolsHumansPandemicsSARS-CoV-2Aerosols

Identifiers

PMID42168191

DOI10.1038/s41467-026-73470-w

PMCPMC13385827

What OpenQuestion holds

Textmetadata

LicenceCC BY-NC-ND

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.