# Spatial Modeling of the Potential Distribution of Dengue in the City of Manta, Ecuador

**Authors:** Karina Lalangui-Vivanco, Emmanuelle Quentin, Marco Sánchez-Murillo, Max Cotera-Mantilla, Luis Loor, Milton Espinoza, Johanna Mabel Sánchez-Rodríguez, Mauricio Espinel, Patricio Ponce, Varsovia Cevallos

PMC · DOI: 10.3390/ijerph22101521 · International Journal of Environmental Research and Public Health · 2025-10-04

## TL;DR

This study models dengue risk in Manta, Ecuador, using environmental and socioeconomic data to identify high-risk areas for targeted interventions.

## Contribution

A novel spatial modeling approach combining MaxEnt and multi-criteria analysis to identify dengue risk clusters in a coastal urban setting.

## Key findings

- Population density, sewer access, and river proximity were key predictors of dengue risk.
- Three high-risk clusters were identified in southern, northwestern, and northeastern Manta.
- The coastal strip had lower dengue suitability due to low rainfall and vegetation.

## Abstract

In Ecuador, the transmission of dengue has steadily increased in recent decades, particularly in coastal cities like Manta, where the conditions are favorable for the proliferation of the Aedes aegypti mosquito. The objective of this study was to model the spatial distribution of dengue transmission risk in Manta, a coastal city in Ecuador with consistently high incidence rates. A total of 148 georeferenced dengue cases from 2018 to 2021 were collected, and environmental and socioeconomic variables were incorporated into a maximum entropy model (MaxEnt). Additionally, climate and social zoning were performed using a multi-criteria model in TerrSet. The MaxEnt model demonstrated excellent predictive ability (training AUC = 0.916; test AUC = 0.876) and identified population density, sewer system access, and distance to rivers as the primary predictors. Three high-risk clusters were identified in the southern, northwestern, and northeastern parts of the city, while the coastal strip showed lower suitability due to low rainfall and vegetation. These findings reveal the strong spatial heterogeneity of dengue risk at the neighborhood level and provide operational information for targeted interventions. This approach can support more efficient surveillance, resource allocation, and community action in coastal urban areas affected by vector-borne diseases.

## Linked entities

- **Diseases:** dengue (MONDO:0005502)
- **Species:** Aedes aegypti (taxon 7159)

## Full-text entities

- **Diseases:** vector-borne diseases (MESH:D000079426), Dengue (MESH:D003715)

## Full text

_Full body text omitted from this summary view._ Fetch the complete paper as Markdown: https://tomesphere.com/paper/PMC12564221/full.md

## Figures

5 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12564221/full.md

## References

24 references — full list in the complete paper: https://tomesphere.com/paper/PMC12564221/full.md

---
Source: https://tomesphere.com/paper/PMC12564221