Space-Time Clusters and Co-occurrence of Chikungunya and Dengue Fever in Colombia from 2015 to 2016

Authors: Michael R Desjardins*, University of North Carolina at Charlotte, Ari Whiteman , University of North Carolina at Charlotte, Irene Casas, Louisiana Tech University, Eric Delmelle, University of North Carolina at Charlotte
Topics: Medical and Health Geography, Geographic Information Science and Systems, Spatial Analysis & Modeling
Keywords: space-time statistics, vector-borne diseases, clusters, GIS, Colombia
Session Type: Paper
Day: 4/10/2018
Start / End Time: 8:00 AM / 9:40 AM
Room: Lafayette, Marriott, River Tower Elevators, 41st Floor
Presentation File: No File Uploaded

Vector-borne diseases (VBDs) infect over one billion people and are responsible for over one million deaths each year,
globally. Chikungunya (CHIKV) and Dengue Fever (DENF) are emerging VBDs due to overpopulation, increases in
urbanization, climate change, and other factors. Colombia has recently experienced severe outbreaks of each of the
two aforementioned mosquito-borne diseases. Both viruses are transmitted by the Aedes mosquitoes and are
preventable with a variety of surveillance and vector control measures (e.g. insecticides, reduction of open containers,
etc.). Spatiotemporal statistics can facilitate the surveillance of VBD outbreaks by informing public health officials
where to allocate resources to mitigate future outbreaks. We utilize the Kulldorff space-time scan statistic to identify
and compare statistically significant space-time clusters of CHIKV and DENF in Colombia during the outbreaks
occurring in 2015 and 2016. We visualize the results in a three-dimensional environment to examine the size and
duration of the clusters. We further examine co-occurrences (cluster overlapping) of DENF and CHIKV in space and
time, which is critical to identify regions that may have experienced the greatest burden of VBDs. Our approach is the
first of its kind to examine multiple VBDs in Colombia simultaneously, while the 3D visualizations are a novel way of
illustrating the dynamics of space-time clusters of disease.

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