Evidence map›Paper›PMID 39758204›Full record

ArticleFrontiers in public health2024

Prevention and control of infectious disease transmission in subways: an improved susceptible-exposed-infected-recovered model.

Fang Zhou, Fang Hou, Jiangtao Wang, Qiaoyun Ma, Lanfen Luo

Abstract read
In one paragraph

Article in Frontiers in public health, 2024. 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

5 authors.

Fang ZhouCollege of Information and Management Science, Henan Agricultural University, Zhengzhou, China.
Fang HouCollege of Information and Management Science, Henan Agricultural University, Zhengzhou, China.
Jiangtao WangCollege of Information and Management Science, Henan Agricultural University, Zhengzhou, China.
Qiaoyun MaCollege of Information and Management Science, Henan Agricultural University, Zhengzhou, China.
Lanfen LuoCollege of Information and Management Science, Henan Agricultural University, Zhengzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: A well-connected transportation network unites localities but also accelerates the transmission of infectious diseases. Subways-an important aspect of daily travel in big cities-are high-risk sites for the transmission of urban epidemics. Intensive research examining the transmission mechanisms of infectious diseases in subways is necessary to ascertain the risk of disease transmission encountered by commuters. Methods: In this study, we improve the susceptible-exposed-infected-recovered (SEIR) model and propose the susceptible-exposed-infected-asymptomatic infected (SEIA) model. First, we added asymptomatic patients to the improved model as a parameter to explore the role of asymptomatic patients in the transmission of infectious diseases in a subway. The numbers of boarding and alighting passengers were added to the model as two time-varying parameters to simulate the exchange of passengers at each station. Results: The improved model could simulate the transmission of infectious diseases in subways and identify the key factors of transmission. We then produced an example of the transmission of coronavirus disease (COVID-19) in a subway using real subway passenger data substituted into the model for the calculations. Discussion: We ascertained that the number of exposed people continuously increased with the operation of the subway. Asymptomatic patients had a greater impact on the transmission of infectious diseases than infected people in the course of transmission. The SEIA model constructed in this study accurately determined the spread of infectious diseases in a subway and may also be applicable to studies on the transmission of infectious diseases in other urban public transport systems.

Indexed as

COVID-19CitiesCommunicable Disease ControlCommunicable DiseasesHumansModels, TheoreticalSARS-CoV-2TransportationTravelasymptomatic patientinfectious disease transmissioninfectious prevention and controlSEIAsubway protection measures

Identifiers

PMID39758204
PMCPMC11697590

What OpenQuestion holds

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LicenceCC BY
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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.