Lab Matters Fall 2024 | Page 93

APHL 2024 POSTER ABSTRACTS

Analysis of Clinical , Demographic and Genomic SARS-CoV-2 Data Reveals Similar Illness Severity Across Variants

S . Getabecha 1 , S . Gilliam 1 , M . Wood 2 , K . Benson 2 , P . Arunleung 1 , G . Gautham 1 , M . Salas 1 , J . Schapiro 2 , E . Dilda 2 , J . Skarbinski 2 , C . Morales 1 , E . Baylis 1 , C . Glaser 1 , D . Wadford 1 , California Department of Public Health 1 , Kaiser Permanente of Northern California 2

Genomic surveillance of SARS-CoV-2 is an essential tool for virus characterization and public health response . Variant monitoring and characterization can be further strengthened through the integration of genomic data with relevant clinical and demographic data to identify associations between emerging variants and clinical outcomes . In June 2021 , the California Department of Public Health Viral and Rickettsial Disease Laboratory ( CDPH VRDL ) partnered with Kaiser Permanente ( KP ) of Northern California to develop a system to integrate and analyze laboratory and patient data to support the active monitoring of SARS-CoV-2 variant trends in California through the Kaiser-COVIDNet project . As of January 3 , 2024 , 54,116 specimens were successfully sequenced and securely linked to demographic and clinical data . Chi-square testing was performed to determine the association between variant infection and illness severity . The proportion of severe hospitalized patients among Delta cases ( 5 %) compared to Omicron ( 4 %) was not significantly different ( p =. 52 ). Although XBB . 1.16 . x and XBB . 1.9 . x cases had higher proportions of hospitalized patients compared to other variants , the proportions were still quite similar ( 14 % for XBB . 1.16 . x cases and 12 % for XBB . 1.9 . x cases , compared to 10 % for other variants , p <. 001 ). As new variants and lineages emerge and circulate , leveraging public-private partnerships like Kaiser- COVIDNet , where datasets containing extensive clinical information can be linked to SARS-CoV-2 lineages , will be vital to inform and support public health surveillance and response efforts .

Presenter : Shiffen Getabecha , shiffen . getabecha @ cdph . ca . gov

Antimicrobial Resistance Genomic Surveillance : Finding the Needle in the Haystack

K . Gali 1 , A . Lorentz 1 , E . Craig 1 , K . DiBiase 1 , L . Turner 1 , N . Chen 1 , A . Hale 1 , M . Creighton 1 , K . Saphrey 2 , A . Myrick-West 2 , Virginia Division of Consolidated Laboratory Services 1 , Virginia Department of

Health 2

Abstract : Historically , surveillance of carbapenem-resistant organisms ( CROs ), particularly Acinetobacter baumannii , has been limited . In 2022 , DCLS began using whole genome sequencing ( WGS ) data to perform surveillance of CROs to look for clusters of genetically similar isolates . Genomic surveillance greatly enhanced DCLS ’ s ability to find genetically similar organisms and to share these potential clusters of illness with epidemiologists at the Virginia Department of Health ( VDH ). As a result of this surveillance , epidemiologists have been able to identify additional outbreaks and investigate cases that were previously unknown .

Methods : Short read sequencing was performed using the Illumina MiSeq instrument . Surveillance was performed using submission of sequencing FASTA files to the National Center for Biotechnology Information ( NCBI ) Pathogen Detection project . Confirmatory analysis of NCBI surveillance data was performed using Dryad for antimicrobial resistance gene prediction and single nucleotide polymorphism ( SNP ) distance calculations . Using an APHL template , DCLS developed a standard reporting format for communication of cluster data including sample information , the SNP matrix , antimicrobial resistance genes predictions and carbapenemase gene PCR data .

Results : In a three-month period , DCLS sent out 25 carbapenemresistant A . baumannii ( CRAB ) surveillance cluster reports . Half of those reports were for new surveillance isolates found to be related to a previously reported cluster . Through genomic surveillance , DCLS identified a cluster of genetically similar OXA-24 positive CRAB isolates . Reporting this cluster of genetically similar CRAB isolates precipitated an investigation to identify epidemiologic linkages ultimately finding several smaller subclusters of related patients that were more genetically similar than the larger cluster . One subcluster was found to occur in a skilled nursing facility and was related to wound care practices . Carbapenemase colonization screening of wound swabs of other patients within this facility identified additional OXA-24 positive CRAB isolates . Collaboration with the Tennessee Public Health Laboratory for the testing and sequencing of these colonization swabs furthered our ability to investigate this outbreak .

Conclusions : As a result of using genomic surveillance , DCLS was able to identify genetically similar isolates and assist epidemiologists in detecting an outbreak within a high-risk facility that was previously unknown . Collaboration with Antimicrobial Resistance Laboratory Network partners for carbapenemase colonization screening , sequencing and genetic comparison further characterized the extent of the outbreak . Genomic surveillance can play an important role in detecting and reporting potential outbreaks that can be used to understand and prevent the spread of antimicrobial resistant pathogens .

Presenter : Katelin Gali , katelin . gali @ dgs . virginia . gov

Applying Genomic Epidemiology to Link Interstate Hospital Outbreaks of Burkholderia multivorans

S . Baird 1 , D . Mallal 1 , C . Mayle 1 , B . Bardach 1 , J . Nichols 1 , M . Barton 1 , W . Deaderick 1 , J . LiPuma 2 , C . Czaja 1 , L . Bankers 1 , S . Matzinger 1 , Colorado Department of Public Health and Environment 1 , University of Michigan 2

Background : Burkholderia multivorans is an opportunistic pathogen within the Burkholderia cepacia complex , a group of gram-negative bacteria typically found in water and soil . The Burkholderia cepacia complex has been associated with outbreaks in health care facilities . In 2023 , the Colorado Department of Public Health and Environment ( CDPHE ) identified eight patients colonized or infected with B . cepacia complex in a Colorado health care facility . Using whole genome sequencing ( WGS ), we determined that seven of the eight isolate genomes from the Colorado facility were B . multivorans sequence type ( ST ) 659 . We consulted the University of Michigan Burkholderia cepacia Laboratory , which identified 38 clinical ST659 isolates in three hospital outbreaks in two regions in another state starting in 2020 . Additionally , they collected three environmental B . multivorans isolates from two ice machines . With this knowledge , CDPHE also cultured ice machines for B . multivorans and recovered a ST659 isolate from one of the ice machines .

Methods : We sequenced 11 Colorado isolates and 31 isolates from the other state that were collected but not yet sequenced by the University of Michigan . We downloaded sequencing data from NCBI of the 10 isolates that were already sequenced by the University of Michigan , as well as six publicly available ST659 genomes found