Spatiotemporal Heterogeneity in the Distribution of Chikungunya and Zika Virus Case Incidences during their 2014 to 2016 Epidemics in Barranquilla, Colombia

Thomas C. McHale, Claudia M. Romero-Vivas, Claudio Fronterre, Pedro Arango-Padilla, Naomi R. Waterlow, Chad D. Nix, Andrew K. Falconar and Jorge Cano
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Thomas C. McHale: Department of Disease Control, London School of Hygiene and Tropical Medicine, Faculty of Infectious and Tropical Diseases, London WCIE 7HT, UK
Claudia M. Romero-Vivas: Departamento de Medicina, Universidad del Norte, Barranquilla 081007, Colombia
Claudio Fronterre: Department of Disease Control, London School of Hygiene and Tropical Medicine, Faculty of Infectious and Tropical Diseases, London WCIE 7HT, UK
Pedro Arango-Padilla: Programa de Prevención y Control de Enfermedades Trasmitidas por Vectores, Secretaria de Salud Distrital, Barranquilla 081007, Colombia
Naomi R. Waterlow: Department of Disease Control, London School of Hygiene and Tropical Medicine, Faculty of Infectious and Tropical Diseases, London WCIE 7HT, UK
Chad D. Nix: Department of Disease Control, London School of Hygiene and Tropical Medicine, Faculty of Infectious and Tropical Diseases, London WCIE 7HT, UK
Andrew K. Falconar: Departamento de Medicina, Universidad del Norte, Barranquilla 081007, Colombia
Jorge Cano: Department of Disease Control, London School of Hygiene and Tropical Medicine, Faculty of Infectious and Tropical Diseases, London WCIE 7HT, UK

IJERPH, 2019, vol. 16, issue 10, 1-21

Abstract: Chikungunya virus (CHIKV) and Zika virus (ZIKV) have recently emerged as globally important infections. This study aimed to explore the spatiotemporal heterogeneity in the occurrence of CHIKV and ZIKV outbreaks throughout the major international seaport city of Barranquilla, Colombia in 2014 and 2016 and the potential for clustering. Incidence data were fitted using multiple Bayesian Poisson models based on multiple explanatory variables as potential risk factors identified from other studies and options for random effects. A best fit model was used to analyse their case incidence risks and identify any risk factors during their epidemics. Neighbourhoods in the northern region were hotspots for both CHIKV and ZIKV outbreaks. Additional hotspots occurred in the southwestern and some eastern/southeastern areas during their outbreaks containing part of, or immediately adjacent to, the major circular city road with its import/export cargo warehouses and harbour area. Multivariate conditional autoregressive models strongly identified higher socioeconomic strata and living in a neighbourhood near a major road as risk factors for ZIKV case incidences. These findings will help to appropriately focus vector control efforts but also challenge the belief that these infections are driven by social vulnerability and merit further study both in Barranquilla and throughout the world’s tropical and subtropical regions.

Keywords: Chikungunya virus; Zika virus; spatial clustering; Bayesian Poisson models; conditional autoregressive models; socioeconomic risk factors; environmental risk factors (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2019
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