Evidence map›Paper›PMID 41154925›Full record

ArticleInternational journal of environmental research and public health2025

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

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

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Karina Lalangui-VivancoCentro de Investigación en Salud Pública y Epidemiología Clínica (CISPEC), Facultad Ciencias de la Salud Eugenio Espejo, Universidad UTE, Quito 170527, Ecuador.ORCID 0000-0001-8506-4107
Emmanuelle QuentinCentro de Investigación en Salud Pública y Epidemiología Clínica (CISPEC), Facultad Ciencias de la Salud Eugenio Espejo, Universidad UTE, Quito 170527, Ecuador.ORCID 0000-0001-5600-2361
Marco Sánchez-MurilloInstituto Nacional de Investigación en Salud Pública, INSPI Dr. Leopoldo Izquieta Pérez, Centro de Investigación EpiSIG, Quito 170136, Ecuador.ORCID 0000-0002-3719-8589
Max Cotera-MantillaInstituto Nacional de Investigación en Salud Pública, INSPI Dr. Leopoldo Izquieta Pérez, Centro de Investigación EpiSIG, Quito 170136, Ecuador.ORCID 0000-0002-1560-2130
Luis LoorFacultad Ciencias de la Salud, Carrera de Medicina, Universidad Laica Eloy Alfaro de Manabí, Manta 130222, Ecuador.ORCID 0000-0002-8267-7351
Milton EspinozaFacultad Ciencias de la Salud, Carrera de Medicina, Universidad Laica Eloy Alfaro de Manabí, Manta 130222, Ecuador.ORCID 0000-0002-6945-660X
Johanna Mabel Sánchez-RodríguezFacultad Ciencias de la Salud, Carrera de Medicina, Universidad Laica Eloy Alfaro de Manabí, Manta 130222, Ecuador.ORCID 0000-0002-7799-1151
Mauricio EspinelFacultad Ciencias de la Salud, Carrera de Medicina, Universidad Laica Eloy Alfaro de Manabí, Manta 130222, Ecuador.
Patricio PonceInstituto Nacional de Investigación en Salud Pública, INSPI Dr. Leopoldo Izquieta Pérez, Centro de Investigación CIREV, Quito 170136, Ecuador.ORCID 0000-0002-7627-1056
Varsovia CevallosInstituto Nacional de Investigación en Salud Pública, INSPI Dr. Leopoldo Izquieta Pérez, Centro de Investigación CIREV, Quito 170136, Ecuador.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

DengueAedesAnimalsCitiesEcuadorHumansModels, TheoreticalMosquito VectorsSpatial Analysisarboviral infectious diseasesdengueEcuadorspatial modeling

Identifiers

PMID41154925
PMCPMC12564221

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.