Population Movement and Vector-Borne Disease Transmission
Differentiating Spatial–Temporal Diffusion Patterns of Commuting and Noncommuting Dengue Cases
Bibliographic Data
| ID | 8377129 |
|---|---|
| Authors | Tzai-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) |
| Year | 2012 |
| Volume | 102 |
| Issue | 5 |
| Pages | 1026-1037 |
| Publication date | 2012-09-01 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Annals of the Association of American Geographers (JOURNAL) |
| Journal identifiers | ISSN: 0004-5608 • E-ISSN: 1467-8306 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/00045608.2012.671130 |
| OpenAlex | W1988690895 |
| Language | EN |
| Citations received | 7 |
| References cited | 16 |
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
Examining the Effect of the Environment and Commuting Flow from/to Epidemic Areas on the Spread of Dengue Fever
Spatiotemporal heterogeneous allocation to support service area response
Regional transport and its association with tuberculosis in the Shandong province of China, 2009–2011
Multivariate analysis of the dengue virus in Sri Lanka using the ordination method
The Networked Community of Urban Mobility during the Pandemic
Epidemic Forest
| Unique citing works | 7 |
|---|---|
| Citations per year | 0,5 |
| Citation span | 2012 - 2024 (13) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 7 |