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Spatial Analysis of Dengue Clusters at Department, Municipality and Local Scales in the Southwest of Colombia, 2014–2019

Dengue is an arbovirus transmitted by mosquitoes of the genus Aedes and is one of the 15 main public health problems in the world, including Colombia. Where limited financial resources create a problem for management, there is a need for the department to prioritize target areas for public health im...

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Autores principales: Marceló-Díaz, Catalina, Lesmes, María Camila, Santamaría, Erika, Salamanca, José Alejandro, Fuya, Patricia, Cadena, Horacio, Muñoz-Laiton, Paola, Morales, Carlos Andrés
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10222113/
https://www.ncbi.nlm.nih.gov/pubmed/37235310
http://dx.doi.org/10.3390/tropicalmed8050262
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author Marceló-Díaz, Catalina
Lesmes, María Camila
Santamaría, Erika
Salamanca, José Alejandro
Fuya, Patricia
Cadena, Horacio
Muñoz-Laiton, Paola
Morales, Carlos Andrés
author_facet Marceló-Díaz, Catalina
Lesmes, María Camila
Santamaría, Erika
Salamanca, José Alejandro
Fuya, Patricia
Cadena, Horacio
Muñoz-Laiton, Paola
Morales, Carlos Andrés
author_sort Marceló-Díaz, Catalina
collection PubMed
description Dengue is an arbovirus transmitted by mosquitoes of the genus Aedes and is one of the 15 main public health problems in the world, including Colombia. Where limited financial resources create a problem for management, there is a need for the department to prioritize target areas for public health implementation. This study focuses on a spatio-temporal analysis to determine the targeted area to manage the public health problems related to dengue cases. To this end, three phases at three different scales were carried out. First, for the departmental scale, four risk clusters were identified in Cauca (RR ≥ 1.49) using the Poisson model, and three clusters were identified through Getis-Ord Gi* hotspots analysis; among them, Patía municipality presented significantly high incidence rates in the time window (2014–2018). Second, on the municipality scale, altitude and minimum temperature were observed to be more relevant than precipitation; considering posterior means, no spatial autocorrelation for the Markov Chain Monte Carlo was found (Moran test ˂ 1.0), and convergence was reached for b(1)–b(105) with 20,000 iterations. Finally, on the local scale, a clustered pattern was observed for dengue cases distribution (nearest neighbour index, NNI = 0.202819) and the accumulated number of pupae (G = 0.70007). Two neighbourhoods showed higher concentrations of both epidemiological and entomological hotspots. In conclusion, the municipality of Patía is in an operational scenario of a high transmission of dengue.
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spelling pubmed-102221132023-05-28 Spatial Analysis of Dengue Clusters at Department, Municipality and Local Scales in the Southwest of Colombia, 2014–2019 Marceló-Díaz, Catalina Lesmes, María Camila Santamaría, Erika Salamanca, José Alejandro Fuya, Patricia Cadena, Horacio Muñoz-Laiton, Paola Morales, Carlos Andrés Trop Med Infect Dis Article Dengue is an arbovirus transmitted by mosquitoes of the genus Aedes and is one of the 15 main public health problems in the world, including Colombia. Where limited financial resources create a problem for management, there is a need for the department to prioritize target areas for public health implementation. This study focuses on a spatio-temporal analysis to determine the targeted area to manage the public health problems related to dengue cases. To this end, three phases at three different scales were carried out. First, for the departmental scale, four risk clusters were identified in Cauca (RR ≥ 1.49) using the Poisson model, and three clusters were identified through Getis-Ord Gi* hotspots analysis; among them, Patía municipality presented significantly high incidence rates in the time window (2014–2018). Second, on the municipality scale, altitude and minimum temperature were observed to be more relevant than precipitation; considering posterior means, no spatial autocorrelation for the Markov Chain Monte Carlo was found (Moran test ˂ 1.0), and convergence was reached for b(1)–b(105) with 20,000 iterations. Finally, on the local scale, a clustered pattern was observed for dengue cases distribution (nearest neighbour index, NNI = 0.202819) and the accumulated number of pupae (G = 0.70007). Two neighbourhoods showed higher concentrations of both epidemiological and entomological hotspots. In conclusion, the municipality of Patía is in an operational scenario of a high transmission of dengue. MDPI 2023-05-02 /pmc/articles/PMC10222113/ /pubmed/37235310 http://dx.doi.org/10.3390/tropicalmed8050262 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Marceló-Díaz, Catalina
Lesmes, María Camila
Santamaría, Erika
Salamanca, José Alejandro
Fuya, Patricia
Cadena, Horacio
Muñoz-Laiton, Paola
Morales, Carlos Andrés
Spatial Analysis of Dengue Clusters at Department, Municipality and Local Scales in the Southwest of Colombia, 2014–2019
title Spatial Analysis of Dengue Clusters at Department, Municipality and Local Scales in the Southwest of Colombia, 2014–2019
title_full Spatial Analysis of Dengue Clusters at Department, Municipality and Local Scales in the Southwest of Colombia, 2014–2019
title_fullStr Spatial Analysis of Dengue Clusters at Department, Municipality and Local Scales in the Southwest of Colombia, 2014–2019
title_full_unstemmed Spatial Analysis of Dengue Clusters at Department, Municipality and Local Scales in the Southwest of Colombia, 2014–2019
title_short Spatial Analysis of Dengue Clusters at Department, Municipality and Local Scales in the Southwest of Colombia, 2014–2019
title_sort spatial analysis of dengue clusters at department, municipality and local scales in the southwest of colombia, 2014–2019
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10222113/
https://www.ncbi.nlm.nih.gov/pubmed/37235310
http://dx.doi.org/10.3390/tropicalmed8050262
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