Preprint Article Version 1 This version is not peer-reviewed

Spatiotemporal Heterogeneity in the Distribution of Chikungunya and Zika Virus Case Incidences and Risk Factors During Their Epidemics in Barranquilla, Colombia, between 2014 and 2016: An Ecological Study

Version 1 : Received: 4 February 2019 / Approved: 5 February 2019 / Online: 5 February 2019 (14:25:34 CET)

How to cite: McHale, T.C.; Romero-Vivas, C.M.; Fronterre, C..; Arango-Padilla, P..; Falconar, A.K.; Waterlow, N.R.; Nix, C..; Cano, J. Spatiotemporal Heterogeneity in the Distribution of Chikungunya and Zika Virus Case Incidences and Risk Factors During Their Epidemics in Barranquilla, Colombia, between 2014 and 2016: An Ecological Study. Preprints 2019, 2019020054 (doi: 10.20944/preprints201902.0054.v1). McHale, T.C.; Romero-Vivas, C.M.; Fronterre, C..; Arango-Padilla, P..; Falconar, A.K.; Waterlow, N.R.; Nix, C..; Cano, J. Spatiotemporal Heterogeneity in the Distribution of Chikungunya and Zika Virus Case Incidences and Risk Factors During Their Epidemics in Barranquilla, Colombia, between 2014 and 2016: An Ecological Study. Preprints 2019, 2019020054 (doi: 10.20944/preprints201902.0054.v1).

Abstract

Chikungunya virus (CHIKV) and Zika virus (ZIKV) have recently emerged as global infections with consequential disability adjusted life years (DALYs) and economic burden. This study aimed to explore the spatiotemporal heterogeneity in the occurrence of CHIKV and ZIKV outbreaks throughout Barranquilla, Colombia during 2014 and 2016 and explored the potential for clustering. Incidence data were fitted using multiple Bayesian Poisson models based on a suite of explanatory variables as potential risk factors and multiple options for random effects. A best fit model was used to analyse the case incidence risk for both epidemics to identify any risk factors during their epidemics. Neighbourhoods in the northern region of Barranquilla were hotspots for the outbreaks of both CHIKV and ZIKV. Additional hotspots occurred in the south-western and central regions of the CHIKV and ZIKV outbreaks, respectively. Multivariate conditional autoregressive models strongly identified higher socioeconomic strata (SES) and residing in detached houses as risk factors for ZIKV case incidences. These novel findings challenge the belief that these infections are driven by social vulnerability and merits further study both in Barranquilla and throughout the tropical and subtropical regions of the world. 

Subject Areas

Chikungunya virus, Zika virus, spatial clustering, Bayesian Poisson models, conditional autoregressive models, socioeconomic risk factors, environmental risk factors

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