A joint spatial marked point process model for dengue and severe dengue in Medellin, Colombia. (June 2022) - Carabali, Mabel; Schmidt, Alexandra M.; Restrepo, Berta N.; Kaufman, Jay S.
Highlights: A model to jointly assess the spatial distribution of reported dengue and severity. We account for uncertainty in the surveillance-reported dengue while modeling severe cases. We assess spatial clustering of dengue and severe dengue cases in Medellin. Non-monotonic distribution of reported dengue cases across socioeconomic status. 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 spatial analysis to model non-severe and severe dengue simultaneously, using a hierarchical Bayesian model. We fit a joint model to the spatial pattern formed by dengue cases as well as to the severity status of the cases. 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.