Lab Matters Fall 2023 | Page 101

APHL 2023 POSTER ABSTRACTS had been submitted by the facility to the CDPHE laboratory through routine surveillance and successfully performed whole genome sequencing on 32 samples spanning all four years ( eight samples from 2019 , four from 2020 , 16 from 2021 , four from 2022 ). Using the WGS data , we generated de novo assemblies for each sample and performed WGS-based serotyping , multi-locus sequence typing ( MLST ) and phylogenetic analyses . Results : Cases were median age 61.8 ( range 41-76 ), 48 % female , and 96 % either had a hematologic malignancy and / or underwent BMT . All cases were housed on the same two units . On-site observations were notable for the close proximity of sinks to clean supplies and medication preparation areas . WGS-based serotyping analysis demonstrated that all 32 samples from the facility were the same serotype ( O5 ). Twentyseven of the 32 samples had the same MLST ( ST235 ) and were highly related with a mean pairwise distance of 0.00011 ( 99.989 % sequence identity among the ST235 samples ). To determine whether the facility samples cluster together phylogenetically , which would be suggestive of a single outbreak , we compared the facility samples to 23 publicly available serotype O5 CRPA genomes ( 5 ST235 ) that were not epidemiologically associated with the facility . This analysis shows that while the 27 ST235 facility samples share a common ancestor with the five publicly available ST235 sequences ( mean pairwise distance of 0.00021 , 99.979 % sequence identity among all ST235s ), they form a distinct cluster and are more closely related to each other than to any other sample analyzed by WGS . Conclusions : Supported by epidemiological evidence , our WGS analyses confirmed that these samples represent a single CRPA outbreak spanning multiple years in an immunosuppressed patient population . The prolonged nature of the outbreak , the ability of CRPA to form biofilms within plumbing systems , and findings from infection control assessments suggested that the source of infections was possibly an environmental reservoir . In conclusion , by integrating genomic and epidemiological data , we were better able to understand and inform hypotheses regarding transmission of an important pathogen of public health concern .

Presenter : Laura Bankers , laura . bankers @ state . co . us

Human Adenovirus Surveillance and the Impact of the COVID-19 Pandemic on Participation – United States , January 2017 – August 2022

F . Abdirizak , A . Winn , H . Scobie , X . Lu , E . Vega , O . Almendares , H . Kirking , B . Silk ; US Centers for Disease Control and Prevention

More than 100 human adenovirus ( HAdV ) genotypes exist , and their clinical and epidemiologic characteristics vary . Many HAdVs are commonly associated with respiratory infections and outbreaks of respiratory illness . The National Respiratory and Enteric Virus Surveillance System ( NREVSS ) collects untyped weekly aggregate tests and detections of HAdVs . The National Adenovirus Type Reporting System ( NATRS ) collects HAdV typing results accompanied by clinical and demographic data . We describe trends in HAdV data reported to NREVSS ( tests , detections , percent positivity ) and NATRS ( detections , types ) from January 2017 through August 2022 , including seasonality , type circulation and the impact of the COVID-19 pandemic on surveillance reporting and HAdV epidemiology . From January 2017 – August 2022 , 3,558,316 respiratory tests were reported to NREVSS ; 113,218 ( 3.1 %) were HAdV positive ( annual range : 2.1 %– 3.9 %). From 2017 – 2019 , the annual number of respiratory HAdV detections and percent positivity remained relatively consistent in NREVSS ( range : 14,720 – 21,005 ;

2.1 % to 3.9 %). Additionally , the annual number of respiratory HAdV detections and percent positivity reported from 2021 – 2022 ( ranged : 20,775 – 24,393 ; 3.0 – 3.9 %) were comparable to previous years , however , there was a statistically significant decrease in detections and percent positivity in 2020 ( n = 11,702 ; 2.1 %) ( p≤0.01 ). Weekly HAdV positivity peaked bi-annually in the summer ( May – July ) and winter ( November – January ) from 2017 – 2019 and 2022 , but seasonality was disrupted by the COVID-19 pandemic during 2020 and early 2021 . Weekly HAdV positivity did not vary by region from 2017 – 2019 ; but HAdV positivity was higher in the South and Midwest from 2020 – 2022 . In NATRS , the annual number of HAdV typing results reported increased from 389 ( 2017 ) to 547 ( 2019 ). During the COVID-19 pandemic , annual number of results in NATRS declined to 58 ( 2020 ), 101 ( 2021 ) and 148 ( 2022 ). From 2017 – 2019 , the most common HAdV types reported were types 4 ( 22.9 %), 3 ( 22.0 %) and 7 ( 17.3 %). Between 2020 – 2021 , HAdV types 2 ( 38.2 %) and 1 ( 25.5 %) were most common . In 2022 , an increase was noted for type 41 ( 21.6 %), which was likely attributed to a national investigation of children with acute hepatitis of unknown etiology . Types 4 ( 19.6 %), 2 ( 17.6 %) and 5 ( 17.6 %) were also frequently reported in 2022 . HAdVs circulation continued during the COVID-19 pandemic , with observed decreases in 2020 and impacts to seasonality . Reporting of HAdV types to NATRs decreased during the pandemic . Expanded HAdV typing and reporting could allow for better understanding of factors associated with seasonal variation , geographic patterns and clinical syndromes of this respiratory virus ; understanding these factors could inform the development of control measures , diagnostics tools , antivirals and vaccines .

Presenter : Fatima Abdirizak , fabdirizak @ gmail . com

Implementing FungiNet in the Antimicrobial Resistance Laboratory Network

L . Parnell , A . Santos , E . Misas , U . Bagal , K . Forsberg , M . Lyman , L . Gade , M . Seabolt , A . Boddapati , D . Batra , S . Gumbis , R . Aubert , N . Chow ; US Centers for Disease Control and Prevention

Introduction : Pathogen genomic sequencing is a powerful tool that has transformed the public health landscape — providing the resolution to enhance investigation of disease clusters and outbreaks , characterize transmission dynamics , identify introductions of new strains and monitor concerning strains . With fungal diseases becoming a growing concern , there is a need to establish a community of practice that bolsters fungal sequencing capacity and accelerates data generation for public health action . Since 2021 , the US Centers for Disease Control and Prevention ( CDC ) has been working with domestic and global partners to stand up FungiNet , a network that aims to lift global capacity for conducting genomic surveillance and genomic epidemiology of fungal diseases and to equip the public health workforce with tools and resources to rapidly generate , analyze , share and act on genomic data . Domestically , FungiNet is being launched through the Antimicrobial Resistance Laboratory Network ( AR Lab Network ). Here , we highlight the process for implementing FungiNet in the AR Lab Network , with early stages focusing on Candida auris . Methods : First , a pilot was launched in collaboration with CDC , the Association of Public Health Laboratories ( APHL ) and two AR Lab Network regional laboratories to test and establish approaches for C . auris whole genome sequencing ( WGS ), which later informed broader guidance and standard operating procedures . Second , MycoSNP ,