Exploring the impact of residential mobility on cluster detection of chlamydia infections: results from surveillance data of Kalamazoo County, Michigan

Authors: Michael Richard Desjardins*, University of North Carolina - Charlotte; Center for Applied Geographic Information Science, Claudio Owusu, University of North Carolina - Charlotte; Center for Applied Geographic Information Science, Kathleen Baker, Western Michigan University , Eric Delmelle, University of North Carolina - Charlotte; Center for Applied Geographic Information Science
Topics: Medical and Health Geography, Geographic Information Science and Systems, Geography and Urban Health
Keywords: GIS, Infectious Disease, Residential Mobility, Geovisualization, Space-Time Statistics
Session Type: Paper
Day: 4/4/2019
Start / End Time: 9:55 AM / 11:35 AM
Room: Truman, Marriott, Mezzanine Level
Presentation File: No File Uploaded


Chlamydia is the most commonly treated sexually transmitted infection in the United States, particularly in young adults between the ages of 15 and 24 years old. In Kalamazoo County (Michigan), the rate of chlamydia infections has increased since 2006 and is currently twice the average rate of Michigan. With the increasing health risk and economic cost associated with chlamydia, targeted intervention programs will benefit from knowing how disease patterns change in both space and time. This will enable early primary and secondary prevention of the disease, particularly among high risk populations. Using retrospective data obtained from the Michigan Disease Surveillance System for Kalamazoo County (2006 - 2014), we identify space-time clusters of chlamydia using the space-time scan statistic. We compare space-time clusters that assume a fixed residence throughout the study period to clusters that account for residential mobility. We also visualize the space-time clusters in a three-dimensional (3D) environment to depict the space-time dynamics of the clusters. Our findings highlight how assuming fixed residence in longitudinal studies in epidemiology can result in inaccurate relative risk estimates and other space-time characteristics. Surveillance systems should include the residential history of target populations to improve the understanding of residential mobility's influence on STI transmission and other infectious diseases. This will help improve public health strategies that can reduce the burden future outbreaks, especially when resources are limited.

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