Spatial analysis of dengue clusters at department, municipality and local scales in the southwest of Colombia, 2014-2019

• Published in: Tropical medicine and infectious disease Vol. 8; no. 5; pp. 1 - 29
• Main Authors: Marceló-Díaz, Catalina, Lesmes, María Camila, Santamaría, Erika, Salamanca, José Alejandro, Fuya, Patricia, Cadena, Horacio, Muñoz-Laiton, Paola, Morales, Carlos Andrés
• Format: Journal Article
• Language: English
• Published: Basel, Switzerland MDPI 02.05.2023; MDPI AG
• Subjects: Aedes; Aedes aegypti; Analysis; Arbovirus infections; Climate; Cluster analysis; Contingency planning; Dengue; Dengue fever; Disease; Epidemics; Epidemiology; Forests; Getis-Ord Gi; Laboratories; Mosquitoes as carriers of disease; Poisson regression; Public health; pupae index; Spatial analysis; spatio-temporal analysis; Surveillance; Transmission; Vectors (Biology); Colombia; Aedes aegypti; pupae index; Getis-Ord Gi; Poisson regression; spatio-temporal analysis
• ISSN: 2414-6366; 2414-6366
• DOI: 10.3390/tropicalmed8050262

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, Patia 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 b1-b105 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 Patia is in an operational scenario of a high transmission of dengue.