Pular para o conteúdo principal

ETHNOS_APP

Início • Busca • Periódicos • Lista 0

Impact of Different Transportation Modes on the Transmission of Covid-19

Correlation and Strategies from a Case Study in Wuhan, China

Dados Bibliográficos

ID15468359
AutoresDanwen Bao (0000-0001-5302-0652, Nanjing University of Aeronautics and Astronautics), Liping Yin (0000-0002-4254-5717, Nanjing University of Aeronautics and Astronautics, autor correspondente), Shijia Tian (0000-0002-0149-6939, Nanjing University of Aeronautics and Astronautics), Jialin Lv (Nanjing University of Aeronautics and Astronautics), Yanjun Wang (0000-0002-8178-9925, Nanjing University of Aeronautics and Astronautics), Jian Wang (0000-0001-6128-1254, Southeast University), Chaohao Liao (Civil Aviation Administration of China)
Ano2022
Volume19
Fascículo23
Páginas15705-15705
Data de publicação2022-11-25
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoInternational Journal of Environmental Research and Public Health (JOURNAL)
Identificadores do periódicoISSN: 1661-7827 • E-ISSN: 1660-4601
EditoraMultidisciplinary Digital Publishing Institute (PUBLISHER • CH)
DOI10.3390/ijerph192315705
PMID36497781
OpenAlexW4310607710
IdiomaEN
Citações recebidas2
Referências citadas19

Transportation is the main carrier of population movement, so it is significant to clarify how different transportation modes influence epidemic transmission. This paper verified the relationship between different levels of facilities and epidemic transmission by use of the K-means clustering method and the Mann-Whitney U test. Next, quantile regression and negative binomial regression were adopted to evaluate the relationship between transportation modes and transmission patterns. Finally, this paper proposed a control efficiency indicator to assess the differentiated strategies. The results indicated that the epidemic appeared 2-3 days earlier in cities with strong hubs, and the diagnoses were nearly fourfold than in other cities. In addition, air and road transportation were strongly associated with transmission speed, while railway and road transportation were more correlated with severity. A prevention strategy that considered transportation facility levels resulted in a reduction of the diagnoses of about 6%, for the same cost. The results of different strategies may provide valuable insights for cities to develop more efficient control measures and an orderly restoration of public transportation during the steady phase of the epidemic

2019-20 coronavirus outbreak · China · Coronavirus disease 2019 (COVID-19 · Correlation · Disease · Environmental health · Geography · Outbreak · Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 · Telecommunications · Transmission (telecommunications · Computer Science · COVID-19 epidemiological studies · COVID-19 Pandemic Impacts · Data-Driven Disease Surveillance · Mathematics · Medicine · Internal Medicine · Virology

  • Analysis of Covid-19 outbreak in Hubei province based on Tencent's location big data

    Open Access•Lei Hua, Ran et al.•Frontiers in Public Health•2023

  • Tracking the Uneven Outcomes of Covid-19 on Racial and Ethnic Groups

    Open Access•Ariel R Belasen, Alan T Belasen et al.•Journal of Racial and Ethnic…•2024

  • Roles of Different Transport Modes in the Spatial Spread of the 2009 Influenza A(H1N1) Pandemic in Mainland China

    Open Access•J Cai, Bo Xu et al.•International Journal of…•2019

  • Covid-19 and the aviation industry

    Open Access•Anyu Liu, Yoo Ri Kim et al.•Annals of Tourism Research•2021

  • Airline networks and the international diffusion of severe acute respiratory syndrome (Sars)

    Open Access•John T Bowen, Christian Laroe•Geographical Journal•2006

Obras citantes distintas2
Citações por ano0,67
Intervalo de citações2023 - 2024 (2)
Velocidade de citaçãorecent
Altamente citadoNão
Tipos de citaçãoNeutras: 2
Ethnos_APP • Projeto Open Source • Licença MIT • Frontend v2.0.0 • Privacidade e Cookies • Documentação da API: api.ethnos.app/docs • Código da API: GitHub • DOI: 10.5281/zenodo.17049435 • Código do Frontend: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae