Importance of Public Transport Networks for Reconciling the Spatial Distribution of Dengue and the Association of Socio-Economic Factors with Dengue Risk in Bangkok, Thailand
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- ISIDORE Id: 10670/1.6bbc0f...
- halshs: halshs-03770080
- doi: 10.3390/ijerph191610123
- PUBMED: 36011755
- PUBMEDCENTRAL: PMC9408777
- WOS: 000845787200001
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info:eu-repo/semantics/altIdentifier/doi/10.3390/ijerph191610123
Ce document est lié à :
info:eu-repo/semantics/altIdentifier/pmid/36011755
Ce document est lié à :
info:eu-repo/grantAgreement/EC/FP7/282378/EU/Dengue research Framework for Resisting Epidemics in Europe/DENFREE
http://creativecommons.org/licenses/by/ , info:eu-repo/semantics/OpenAccess
Mots-clés
dengue socio-economic risk spatial clusters mobility transport system Bangkok -bio]/Ecology, environment/HealthSujets proches
Dengue fever Breakbone feverCiter ce document
Bertrand Lefebvre et al., « Importance of Public Transport Networks for Reconciling the Spatial Distribution of Dengue and the Association of Socio-Economic Factors with Dengue Risk in Bangkok, Thailand », HAL SHS (Sciences de l’Homme et de la Société), ID : 10.3390/ijerph191610123
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Résumé
Dengue is the most widespread mosquito-borne viral disease of man and spreading at an alarming rate. Socio-economic inequality has long been thought to contribute to providing an environment for viral propagation. However, identifying socio-economic (SE) risk factors is confounded by intra-urban daily human mobility, with virus being ferried across cities. This study aimed to identify SE variables associated with dengue at a subdistrict level in Bangkok, analyse how they explain observed dengue hotspots and assess the impact of mobility networks on such associations. Using meteorological, dengue case, national statistics, and transport databases from the Bangkok authorities, we applied statistical association and spatial analyses to identify SE variables associated with dengue and spatial hotspots and the extent to which incorporating transport data impacts the observed associations. We identified three SE risk factors at the subdistrict level: lack of education, % of houses being cement/brick, and number of houses as being associated with increased risk of dengue. Spatial hotspots of dengue were found to occur consistently in the centre of the city, but which did not entirely have the socio-economic risk factor characteristics. Incorporation of the intra-urban transport network, however, much improved the overall statistical association of the socio-economic variables with dengue incidence and reconciled the incongruous difference between the spatial hotspots and the SE risk factors. Our study suggests that incorporating transport networks enables a more real-world analysis within urban areas and should enable improvements in the identification of risk factors.
