Spatial Modeling of the Potential Distribution of Dengue in the City of Manta, Ecuador
Abstract
1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Data Sources
2.3. Spatial Modeling of the Potential Distribution of Dengue
2.4. Multicriteria Model for Zoning Climatic and Social Variables
3. Results
3.1. Potential Habitat Distribution
3.2. Climatic and Social Zoning
4. Discussion
4.1. Hotspots and Their Epidemiological Significance
4.2. Population Density as the Dominant Driver
4.3. Coastal Gradient and Climatic Buffering
4.4. Operational Implications for Dengue Control in Manta
4.5. Limitations
4.6. Future Research Directions
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Abbreviations
MSP | Ministry of Public Health |
INEC | Instituto Nacional de Estadísticas y Censos |
PCA | Principal Component Analysis |
MaxEnt | Maximum Entropy Model |
GIS | Geographic Information System |
ROC | Receiver Operating Characteristic |
SDM | Spatial Decision Modeling |
AUC | Area Under the Curve |
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Explicative Variable | Measure Unit | Time | Time Unit |
---|---|---|---|
Elevation | m | 2000 | Year |
Precipitation | mm | 2018–2021 | Monthly |
Vegetation index | [−1.0 to +1.0] | 2018–2021 | 16 days |
Day temperature | °C | 2018–2021 | Monthly |
Night temperature | °C | 2018–2021 | Monthly |
Population | Density (inhab./ha) | 2020 (projection) | Census |
Sewer system access | % without sewer access | 2010 | Census |
Drinking water access | % without water access | 2010 | Census |
Housing condition | % of population in poorly maintained housing | 2010 | Census |
Rivers | Distance to rivers | 2020 | Year |
Favorable Zones | Area ha (%) | Population Affected (%) | Cases (%) * | Case Density (Cases/ha) |
---|---|---|---|---|
High | 957.38 (17.87) | 118,409 (47.21) | 84 (58.33) | 0.088 |
Medium | 1191.36 (22.24) | 96,752 (38.58) | 42 (29.17) | 0.036 |
Low | 3209.27 (59.90) | 35,635 (14.21) | 18 (12.5) | 0.006 |
Total | 5358 (100) | 250,796 (100) | 144 (100) | — |
Variable | Percent Contribution (%) |
---|---|
Population | 72.3 |
Sewer system access | 13 |
Distance to rivers | 2.5 |
Night temperature | 2.4 |
Drinking water access | 2.4 |
Precipitation | 1.9 |
Housing condition | 1.9 |
Vegetation index | 1.6 |
Elevation | 1.2 |
Day temperature | 0.7 |
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Share and Cite
Lalangui-Vivanco, K.; Quentin, E.; Sánchez-Murillo, M.; Cotera-Mantilla, M.; Loor, L.; Espinoza, M.; Sánchez-Rodríguez, J.M.; Espinel, M.; Ponce, P.; Cevallos, V. Spatial Modeling of the Potential Distribution of Dengue in the City of Manta, Ecuador. Int. J. Environ. Res. Public Health 2025, 22, 1521. https://doi.org/10.3390/ijerph22101521
Lalangui-Vivanco K, Quentin E, Sánchez-Murillo M, Cotera-Mantilla M, Loor L, Espinoza M, Sánchez-Rodríguez JM, Espinel M, Ponce P, Cevallos V. Spatial Modeling of the Potential Distribution of Dengue in the City of Manta, Ecuador. International Journal of Environmental Research and Public Health. 2025; 22(10):1521. https://doi.org/10.3390/ijerph22101521
Chicago/Turabian StyleLalangui-Vivanco, Karina, Emmanuelle Quentin, Marco Sánchez-Murillo, Max Cotera-Mantilla, Luis Loor, Milton Espinoza, Johanna Mabel Sánchez-Rodríguez, Mauricio Espinel, Patricio Ponce, and Varsovia Cevallos. 2025. "Spatial Modeling of the Potential Distribution of Dengue in the City of Manta, Ecuador" International Journal of Environmental Research and Public Health 22, no. 10: 1521. https://doi.org/10.3390/ijerph22101521
APA StyleLalangui-Vivanco, K., Quentin, E., Sánchez-Murillo, M., Cotera-Mantilla, M., Loor, L., Espinoza, M., Sánchez-Rodríguez, J. M., Espinel, M., Ponce, P., & Cevallos, V. (2025). Spatial Modeling of the Potential Distribution of Dengue in the City of Manta, Ecuador. International Journal of Environmental Research and Public Health, 22(10), 1521. https://doi.org/10.3390/ijerph22101521