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  <title><![CDATA[PhD Defense by Gyuhyon Cha]]></title>
  <body><![CDATA[<p><span><span><strong><span><span>School of Civil and Environmental Engineering</span></span></strong></span></span></p>

<p><span><span><strong><span><span>Ph.D. Thesis Defense Announcement</span></span></strong></span></span></p>

<p><span><span><span><span>Advancing Wastewater-based Epidemiology: Engineered Solutions for Efficient Sampling and RNA Preservation of SARS-CoV-2</span></span></span></span></p>

<p><span><span><strong><span><span>By</span></span></strong><span><span>&nbsp;Gyuhyon Cha</span></span></span></span></p>

<p><span><span><strong><span><span>Advisor:</span></span></strong></span></span></p>

<p><span><span><span><span>Dr. Konstantinos T. Konstantinidis</span></span></span></span></p>

<p><span><span><strong><span><span>Committee Members: </span></span></strong><span><span>&nbsp;Dr. Xing Xie (CEE/Georgia Tech), Dr. Ameet Pinto (CEE/Georgia Tech), Dr. Katherine Graham (CEE/Georgia Tech), Dr. Joe Brown (Gillings School of Global Public Health/UNC-Chapel Hill)</span></span></span></span></p>

<p><span><span><strong><span><span>Date and Time</span></span></strong><span><span>:&nbsp; April 12, 2024. 3:00 PM</span></span></span></span></p>

<p><span><span><strong><span><span>Location:</span></span></strong><span><span>&nbsp;Ford Environmental Science &amp; Technology Building, Room L1205</span></span></span></span></p>

<p>&nbsp;</p>

<p><span><span><span><span>ABSTRACT<br />
Wastewater-based epidemiology (WBE) has long been used to monitor infectious<br />
disease trends in communities and has received special attention during the recent<br />
SARS-CoV-2 pandemic. Composite sampling using autosamplers has been shown<br />
to provide more robust representation of SARS-CoV-2 RNA levels in sewage<br />
compared to traditional grab samples. However, autosamplers have cost- and<br />
operation-related limitations for application for small-scale surveillance (e.g., at<br />
the neighborhood or university campus level), for which identifying specific<br />
infection hotspots is critical. Passive sampling may offer a cost-effective<br />
alternative in such settings but there is limited field data on the efficacy of this<br />
methodology. This thesis describes a study conducted on the Georgia Tech<br />
campus that aimed to monitor SARS-CoV-2 dynamics in the wastewater from four<br />
dormitories using various sampling methodologies. The results suggested that<br />
passive Moore swabs can be as suitable as, if not more than, autosamplers for</span></span></span></span></p>

<p><span><span><span><span>sewage surveillance due to their increased sensitivity when wastewater flow is low<br />
or intermittent. Furthermore, bioinformatics analysis of the resulting data offered<br />
early signals of the introduction of new viral variants and guided prevention<br />
strategies. Follow-up in-situ experiments showed that for the campus conditions<br />
studied here the optimal deployment time of Moore swabs is about 6 hours before<br />
they begin to saturate with fecal solids. Finally, the rapid degradation of SARSCoV-<br />
2 RNA in sewage is a major limitation for the wide adoption of WBE,<br />
particularly in remote locations where traditional cold-chain logistics are<br />
challenging. To address this limitation, a novel cold-chain-free RNA preservation<br />
method using porous superabsorbent polymer (PSAP) beads was validated as an<br />
effective means to preserve SARS-CoV-2 RNA at room temperature. Collectively,<br />
these results and methodologies advance the toolbox of WBE and make it more<br />
widely accessible for public health monitoring.</span></span></span></span></p>
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