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Population Movement and Vector-Borne Disease Transmission

Differentiating Spatial–Temporal Diffusion Patterns of Commuting and Noncommuting Dengue Cases

Dados Bibliográficos

ID8377129
AutoresTzai-Hung Wen (0000-0002-3526-0203), Tzai‐hung Wen (0000-0002-9151-8336, National Taiwan University), Min-Hau Lin (National Taiwan University), Chi-Tai Fang, Chi‐Tai Fang (0000-0002-7380-1699, National Taiwan University)
Ano2012
Volume102
Fascículo5
Páginas1026-1037
Data de publicação2012-09-01
Peer ReviewedSim
Open AccessNão
TipoARTICLE
PeriódicoAnnals of the Association of American Geographers (JOURNAL)
Identificadores do periódicoISSN: 0004-5608 • E-ISSN: 1467-8306
EditoraInforma UK Limited (PUBLISHER • GB)
DOI10.1080/00045608.2012.671130
OpenAlexW1988690895
IdiomaEN
Citações recebidas7
Referências citadas16

Commuters who acquire dengue infections could be an important route for the transmission of the virus from their homes to workplaces. Understanding the effects of routine human movement on dengue transmission can be helpful in identifying high-risk areas for effective intervention. This study investigated the effects of local environmental and demographic characteristics to clarify the role of the daily commute in dengue transmission. We analyzed the clustering patterns of space–time distances between commuting and noncommuting dengue cases from June 2007 to January 2008 in Tainan City, Taiwan. We also analyzed the network topology of space–time distances to identify possible key individuals and conducted time-to-event analysis for geographic diffusion through commuting versus noncommuting dengue cases. Our significant findings indicate that most of the space–time distances of noncommuting cases clustered within 100 m and one week, whereas commuting cases clustered within 2 to 4 km and one to five weeks. Analysis of the temporality of the geographical diffusion by villages showed that commuting cases diffuse more rapidly across villages than noncommuting cases in the late epidemic period. The role of commuting was identified as a significant risk factor contributing to epidemic diffusion (hazard ratio: 3.08, p value < 0.05). Local neighborhood characteristics (number of vacant grounds and empty houses) are independent facilitating factors for diffusion through both noncommuting cases and commuting cases (hazard ratio: 1.035 and 1.022, respectively, both p < 0.05). Higher population density is a significant risk factor only for diffusion through commuters (hazard ratio: 1.174). In summary, noncommuters, mostly elderly adults and housewives, might initiate local outbreaks, whereas commuters carrying the virus to geographically distant areas cause large-scale epidemics

Biology · Cartography · Dengue fever · Dengue virus · Geography · Hazard · Population · Socioeconomics · Sociology · Transmission (telecommunications) · Computer Science · COVID-19 epidemiological studies · Demography · Ecology · Medicine · Mosquito-borne diseases and control · Urban Transport and Accessibility · Virology

  • Analyzing the spatio-temporal relationship between dengue vector larval density and land-use using factor analysis and spatial ring mapping

    Open Access•Muhammad Shahzad Sarfraz, Nitin Kumar Tripathi et al.•BMC Public Health•2012

  • Examining the Effect of the Environment and Commuting Flow from/to Epidemic Areas on the Spread of Dengue Fever

    Open Access•Shuli Zhou, Suhong Zhou et al.•International Journal of…•2019

  • Spatiotemporal heterogeneous allocation to support service area response

    Open Access•Xin Feng, Alan T Murray•Computers Environment and Urban…•2020

  • Regional transport and its association with tuberculosis in the Shandong province of China, 2009–2011

    Open Access•Erjia Ge, Poh-Chin Lai et al.•Journal of Transport Geography•2015

  • Multivariate analysis of the dengue virus in Sri Lanka using the ordination method

    Open Access•Naomi W Lazarus•GeoJournal•2019

  • The Networked Community of Urban Mobility during the Pandemic

    Open Access•Wei Chien Benny Chin, Chen-Chieh Feng et al.•Annals of the American…•2024

  • Epidemic Forest

    Meifang Li, Xun Shi et al.•Annals of the American…•2019

  • Centrality in social networks conceptual clarification

    Open Access•Linton C Freeman•Social Networks•1978

  • Airports, localities and disease

    Open Access•Adam Warren, Morag Bell et al.•Health & Place•2010

  • Spatial Vulnerability to Dengue in a Brazilian Urban Area During a 7-Year Surveillance

    Open Access•Maria Cristina De Mattos Almeida, Waleska Teixeira Caiaffa et al.•Journal of Urban Health•2007

Obras citantes distintas7
Citações por ano0,5
Intervalo de citações2012 - 2024 (13)
Velocidade de citaçãorecent
Altamente citadoNão
Tipos de citaçãoNeutras: 7
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