A joint spatial marked point process model for dengue and severe dengue in Medellin, Colombia.

Abstract

The spatial distribution of surveillance-reported dengue cases and severity are usually analyzed separately, assuming independence between the spatial distribution of non-severe and severe cases. Given the availability of data for the individual geo-location of surveillance-notified dengue cases, we conducted a cross-sectional study to model non-severe and severe dengue simultaneously, identifying the spatial patterns of dengue distribution, using individual and area level covariates within a hierarchical Bayesian model. Results showed that age and socioeconomic status were associated with dengue presence, and there was evidence of clustering for overall cases but not for severity. Our findings inform decision making to address the preparedness or implementation of dengue control strategies at the local level.