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Published VersionCC BY V4.0, Open Access
Journal article
Mapping dengue susceptibility in Dhaka city: a geospatial multi-criteria approach integrating environmental and demographic factors
Spatial Information Research, Vol.33, pp.1-16
2025
Abstract
Dengue, a rapidly spreading mosquito-borne disease, poses a serious public health threat in tropical cities like Dhaka, Bangladesh-one of the world's most densely populated megacities. In 2023 alone, Dhaka experienced its worst outbreak, recording 321,179 cases and 1,705 deaths. This study aims to assess dengue susceptibility across Dhaka using a geospatial Multi-Criteria Decision-Making (MCDM) approach. Fourteen environmental and demographic factors were selected, and thematic raster layers were developed and weighted using the Analytical Hierarchy Process (AHP). These layers were integrated to generate spatial dengue susceptibility maps, highlighting risk zones across the city. Findings reveal that southern and southeastern Dhaka, particularly under the South City Corporation, are highly susceptible based on environmental factors. Demographic analysis shows moderate to very high susceptibility in central and southern wards, with population density and proximity to waterlogged areas identified as key drivers. The model was validated through field surveys with 80 stakeholders, with 67.5% agreeing with the susceptibility classifications. This study provides a scalable and transferable framework for dengue risk assessment and can inform targeted interventions in other endemic regions. The results offer critical guidance for urban health planning, vector control, and resource allocation to mitigate dengue and similar vector-borne diseases.
Details
- Title
- Mapping dengue susceptibility in Dhaka city: a geospatial multi-criteria approach integrating environmental and demographic factors
- Authors
- Muhammad Al-Amin Hoque (Corresponding Author) - Jagannath UniversityMd. Limon Sardar - Jagannath UniversitySharif A. Mukul - University of the Sunshine Coast, Queensland, School of Science, Technology and EngineeringBiswajeet Pradhan - University of Technology Sydney
- Publication details
- Spatial Information Research, Vol.33, pp.1-16
- Publisher
- Springer
- Date published
- 2025
- DOI
- 10.1007/s41324-025-00635-y
- ISSN
- 2366-3294; 2366-3286
- Copyright note
- This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
- Data Availability
- Data sets generated during the current study are available from the corresponding author on reasonable request.
- Organisation Unit
- Tropical Forests and People Research Centre
- Language
- English
- Record Identifier
- 991144503302621
- Output Type
- Journal article
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