Lab Matters Fall 2024 | Page 130

APHL 2024 POSTER ABSTRACTS

3 gene ( H3 ), Pandemic Influenza A ( pdmInfA ), Pandemic 2009 Hemagglutinin 1 ( pdmH1 ) and Influenza B Victoria ( VIC ). The amplified subtyping qPCR products underwent bead cleanup and high-throughput sequencing using the Illumina DNA prep and NextSeq platform .

The wastewater samples were amplified with the A and B targets , as well as all subtype targets , regardless of prior A or B detection via dPCR . Following sequencing , a comparative analysis was conducted aligning raw read data to the targeted gene segment for each PCR product . Results confirmed the initial dPCR and qPCR type and subtyping outcomes , confirming the identified type from dPCR and ensuring overall consistency between all results . This sequential approach demonstrates the usefulness of sequencing as a confirmatory assay for the detection of influenza subtyping and typing targets in complex wastewater matrices .

This proof-of-concept study contributes to the advancement of wastewater infectious disease surveillance , demonstrating the ability to quickly assess the specificity of newly developed or adapted qPCR and dPCR target assays and giving confidence to results identified in real world wastewater samples quickly is a benefit in a rapidly growing field .

Presenter : Van Nguyen , van . nguyen @ state . co . us

Correlation of SARS-CoV-2 Levels in Wastewater With Clinical Cases and Hospitalizations Across Different Lineage Periods – Chicago [ February 2022 — July 2023 ]

C . Korban , J . Koech , D . Yuce , A . Kittner , P . Ruestow , M . Pacilli , Chicago Department of Public Health ,

Throughout the COVID-19 pandemic , public health surveillance strategies have relied on laboratories and healthcare providers to report and provide information about individual cases . Wastewater ( WW ) surveillance is a newer and promising tool , yet how it can be used in a public health context against other metrics is still being explored . In addition , the SARS-CoV-2 virus has undergone extensive mutation since the start of the pandemic , impacting its infectivity , spread and virulence . We aim to assess how WW levels of SARS- CoV-2 correlate with these metrics across periods where different lineages were more prevalent , to better contextualize WW data .

The Chicago Department of Public Health ( CDPH ) facilitates collection and testing of WW samples for SARS-CoV-2 at eight neighborhood sewer sites and three pumping stations twice weekly across Chicago . COVID-19 cases and hospitalizations reported to CDPH were geocoded to the area covered by the sampled sewer site based on home address . Seven of the neighborhood sewer sites were included for this analysis as sampling began at the other sites after the start of the study period . Spearman ’ s rank correlation analysis was performed to compare weekly average WW PMMoVnormalized viral levels to weekly total case and hospitalization counts for each sampling site based on specimen collection date . Correlations were assessed separately for three time periods according to variant predominance (> 50 % of variants identified ): 2022 Morbidity and Mortality Weekly Report ( MMWR ) weeks 5-25 for BA . 1.1 , BA . 2 and BA . 2.12.1 ; 2022 MMWR weeks 26-45 for BA . 5 ; and 2023 MMWR weeks 1-26 for XBB . 1.5 .

For the period covering BA . 1.1 , BA . 2 and BA . 2.12.1 , levels were significantly ( p < 0.05 ) positively correlated with case counts at all 7 sites and were significantly positively correlated with hospitalizations at 3 / 7 sites . Viral levels were significantly positively correlated with case counts at 4 / 7 sites during the BA . 5 period but were not significantly correlated with hospitalizations at any sites during this period . During the XBB . 1.5 period 5 / 7 sites saw viral levels significantly positively correlated with case counts and 1 / 7 sites with viral levels significantly positively correlated with hospitalizations . One site during the XBB . 1.5 period saw viral levels significantly negatively correlated with hospitalizations .

WW SARS-CoV-2 viral levels seemed to correlate well with case counts across the lineage periods however there was a slight decrease in the number of sites that had a significant correlation . This could be attributed to less confirmatory testing , increased use of at-home tests , or a result of more subclinical cases . A decreasing association of WW levels with hospitalizations was seen over time with no correlation during the BA . 5 period and only one site positively correlated during the XBB . 1.5 period . This may reflect less severe disease due to lineages not causing as severe illness , or the impact of vaccination efforts against the disease . Regardless , this shows that as WW increases , in the most recent period , an associated increase in hospitalizations was seen in less sites . With the ever-changing lineages of the virus , having an up to date understanding of how WW levels relate to clinical metrics will help us better interpret results to inform on public health action .

Presenter : Colin Korban , colin . korban @ cityofchicago . org

Detection and Tracking of Novel and Recurrent SARS-Cov-2 Mutations in Wastewater Can Enhance Lineage-Based Wastewater and Clinical Surveillance Efforts

A . Smith , L . Bankers , K . Weisbeck , A . Rossheim , A . Wellbrock , E . Austin , A . Wheeler , S . Matzinger , Colorado Department of Public Health and Environment

Whole genome sequencing ( WGS ) of SARS-CoV-2 from clinical and wastewater samples has had a critical role in surveillance efforts throughout the SARS-CoV-2 pandemic . As the pandemic progressed , clinical testing frequency decreased , putting wastewater surveillance at the forefront of tracking the evolution and geographic spread of SARS-CoV-2 . We have previously shown a significant correlation between aggregated lineage proportions in wastewater and clinical samples and SARS-CoV-2 activity in wastewater has been shown to be a leading indicator of clinical activity . However , our analyses were limited to urban Colorado during a period of relatively high viral concentrations in wastewater and high clinical testing rates . The often small number of mutational differences between a parent lineage and its sublineages has made accurately calling lineages from wastewater challenging , particularly with a large number of closely related circulating lineages and / or during periods of low viral concentration . In addition , emerging lineages must be manually curated and made available to software tools before bioinformatic analyses can identify them in real time . Here , we demonstrate a new tool to serve as an early warning system for potential emerging SARS-CoV-2 lineages by tracking and analyzing mutations detected in wastewater .

Since March 2021 , the Colorado State Public Health Laboratory and Wastewater Surveillance Program at CDPHE has partnered with wastewater facilities from across Colorado to collect bi-weekly wastewater samples . These samples undergo dPCR for SARS- CoV-2 detection and quantification and then WGS for genomic characterization . Clinical samples from across the state are also