Identification of Hazard and Socio-Demographic Patterns of Dengue Infections in a Colombian Subtropical Region from 2015 to 2020: Cox Regression Models and Statistical Analysis

Santiago Ortiz; Alexandra Catano-Lopez; Henry Velasco; Juan P Restrepo; Andrés Pérez-Coronado; Henry Laniado; Víctor Leiva

doi:10.3390/tropicalmed8010030

Identification of Hazard and Socio-Demographic Patterns of Dengue Infections in a Colombian Subtropical Region from 2015 to 2020: Cox Regression Models and Statistical Analysis

Trop Med Infect Dis. 2022 Dec 30;8(1):30. doi: 10.3390/tropicalmed8010030.

Authors

Santiago Ortiz¹, Alexandra Catano-Lopez¹, Henry Velasco¹, Juan P Restrepo¹, Andrés Pérez-Coronado¹, Henry Laniado¹, Víctor Leiva²

Affiliations

¹ School of Applied Sciences and Engineering, Universidad EAFIT, Medellín 050022, Colombia.
² School of Industrial Engineering, Pontificia Universidad Católica de Valparaíso, Valparaíso 2362807, Chile.

Abstract

Dengue is a disease of high interest for public health in the affected localities. Dengue virus is transmitted by Aedes species and presents hyperendemic behaviors in tropical and subtropical regions. Colombia is one of the countries most affected by the dengue virus in the Americas. Its central-west region is a hot spot in dengue transmission, especially the Department of Antioquia, which has suffered from multiple dengue outbreaks in recent years (2015-2016 and 2019-2020). In this article, we perform a retrospective analysis of the confirmed dengue cases in Antioquia, discriminating by both subregions and dengue severity from 2015 to 2020. First, we conduct an exploratory analysis of the epidemic data, and then a statistical survival analysis is carried out using a Cox regression model. Our findings allow the identification of the hazard and socio-demographic patterns of dengue infections in the Colombian subtropical region of Antioquia from 2015 to 2020.

Keywords: arbovirus; clinical deterioration; endemic; proportional hazard; tropical diseases.

Grants and funding

This research was partially funded by Universidad EAFIT, grant number 954-000002 (S.O., A.C.-L., H.L.) and by Ministerio de Ciencia Tecnología e Innovación de Colombia, projects (I) Formación de Capital Humano de Alto Nivel–Universidad EAFIT—Corte 2 Nacional, BPIN 2020000100778 (H.V.), (II) Convocatoria 757 2016 Doctorados Nacionales FP44842-061-2018 (A.P.-C.) and (III) Convocatoria 909-2 2022 (S.O., A.C.-L.). This research was also partially funded by project grant FONDECYT 1200525 (V.L.) from the National Agency for Research and Development (ANID) of the Chilean government under the Ministry of Science, Technology, Knowledge, and Innovation. The funders had no role in study design, data collection and analysis, publication decisions, or manuscript preparation.