Finding STI clusters in the District of Columbia using space time analysis.

Authors: Suparna Das*, HIV/AIDS, Hepatitis, STD and TB Administration, DC Department of Health, Adam Allston, HIV/AIDS, Hepatitis, STD and TB Administration, DC Department of Health, Kerri Dorsey, George Washington University
Topics: Medical and Health Geography, Spatial Analysis & Modeling, Geography and Urban Health
Keywords: STI clusters, Space time, SatScan, policy makers
Session Type: Paper
Day: 4/12/2018
Start / End Time: 3:20 PM / 5:00 PM
Room: Studio 6, Marriott, 2nd Floor
Presentation File: No File Uploaded

Sexually transmitted infections (STIs) have long been an underestimated opponent in the public health battle. The liability of STIs falls excessively on the young, poor, minorities and women and STI repeaters form a substantial number of these patients. Post-treatment recurrent infection may result from reinfection and resistant infection which was not cured through the treatment. STIs continue to have a major impact on the health of people in the US and particularly in the nation’s capital. Thus geographic public health surveillance is recommended as an effective method for identifying infectious disease outbreaks which are critical for establishing effective control efforts. STI surveillance data from HIV/AIDS, Hepatitis, STD, & TB Administration (HAHSTA) within DC Department of Health. There were 10100 repeaters identified using an algorithm of first name, last name, date of birth and date of diagnosis from the total of 54266. The STI cluster analysis in this study has following distinct objectives, 1. Retrospective analysis using STI data from 2010 – 2015 to identify where the repeat STI clusters were located. 2. Prospective space-time analysis for the early detection of disease outbreaks clusters. Both space-time disease clusters and prospective space-time permutation scan statistic was conducted using the SaTScan software. The results were mapped using Maptitude software. The space-time retrospective analysis shows clustering of repeat infections in the south-east part of the district, covering Wards 5, 6, 7 and 8. The disease outbreak analysis using space-time permutation model of STI repeaters show clustering in the Wards of 1 and 2.

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