APHL 2022 POSTER ABSTRACTS which prompted them to seek medical care on 25 July . At this time , stool specimens were collected and sent to the local laboratory for testing .
Bacteriology : Stool samples from both patients were reported out as detected for both the Vibrio and the V . cholerae targets using the FilmArray Gastrointestinal Panel ( BioFire Diagnostics ). These stools were subsequently forwarded to the Nebraska Public Health Laboratory where presumptive V . cholerae was isolated from each stool using TCBS agar and other phenotypic testing . Whole genome sequencing was subsequently performed on the isolates using an Illumina MiSeq platform . Bioinformatics analysis for assessing sequencing quality , genome assembly , organism identification and toxin detection were performed with software available on https :// github . com , using default parameters . Bioinformatics analysis showed the isolates to be unrelated by SNP analysis but confirmed the identifications of V . cholerae and the absence of the cholerae toxin genes . Further analysis of the isolates at the Centers for Disease Control and Prevention showed that the isolates were not serogroup O1 or O139 .
Conclusion : These cases demonstrate the use of CIDT , along with confirmatory culture testing , in the assessment of risk factors to improve public health detection and case management . Additional studies are needed to better define what role various serogroups of V . cholerae play in disease progression in the U . S .
Presenter : Taylor Wahlig , University of Nebraska Medical Center , twahlig @ unmc . edu
Differences in the Spatiotemporal Factors Associated With Salmonella and Listeria monocytogenes Likelihood in Environmental Samples From Virginia Produce Farms
C Murphy1 , D Weller2 , L Strawn1 ; 1Virginia Tech , 2State University of New York College of Environmental Science and Forestry
Introduction : Foodborne pathogen contamination risk is not uniform within produce growing environments ; thus , managing contamination risks of preharvest produce is challenging . This study aimed to identify spatiotemporal factors associated with Salmonella and Listeria isolation from soil , drag swab and water samples from Virginia produce farms .
Methods : Soil ( N &# 3f400 ), drag swab ( N &# 3f400 ) and water ( N &# 3f120 ) samples were longitudinally collected from ten Virginia produce farms . All samples were tested for Salmonella and Listeria and PCR confirmed . Presumptive Listeria isolates were identified to species-level by sigB typing . Conditional forest analysis and Bayesian mixed models were used to identify associations between spatial ( e . g ., growing region ) and temporal ( e . g ., weather ) factors , and the likelihood of Salmonella , L . monocytogenes and Listeria spp . ( excluding monocytogenes ) isolation . Surrogate trees were used to visualize conditional forest results .
Results : Salmonella was isolated from 5.3 % ( 49 / 920 ) of samples , with the majority coming from Virginia ’ s Eastern Shore ( 46 / 49 ). Of the 49 Salmonella positive samples , 14 unique serovars were isolated with Newport yielding the predominant serovar ( 32.7 %; 16 / 49 ) followed by Braenderup ( 10.2 %; 5 / 49 ). L . monocytogenes and Listeria spp . were isolated from 2.3 % ( 21 / 920 ) and 1.8 % ( 17 / 920 ) of samples , respectively . Based on the mixed models , the likelihood of Salmonella detection was significantly higher in water compared to terrestrial samples ( Odds Ratio = 6.5 , 89 % Credibility Interval = 3.3 , 14.9 ). Additionally , the likelihood of isolating L . monocytogenes and Listeria spp . was significantly higher in samples collected in winter , compared to fall , spring and summer ( P9.4 ° C ( P < 0.001 ). L . monocytogenes was most likely to be isolated from water samples collected in winter from sites where forest and wetlands accounted for < 36 % of land cover ( P < 0.001 ). Listeria spp . were most likely to be isolated from drag swabs samples collected in winter when no rainfall occurred 1-2 days before sample collection ( P < 0.001 ).
Significance : These findings identify factors that increased the likelihood of isolating Salmonella and Listeria in preharvest environments and are helpful in development of control strategies within small scale growing regions for specific scenarios to minimize produce contamination .
Presenter : Claire Murphy , Virginia Tech , cmarik @ vt . edu
GLOBAL HEALTH
The Global Laboratory Leadership Programme Provides Lessons for One Health Collaboration and Laboratory System Building
J Isadore , S Emery , S Musumeci , B Wilcke and L Maryogo-Robinson , Association of Public Health Laboratories
One Health was recently defined by a joint tripartite [ Food and Agriculture Organization of the United Nations ( FAO ), the World Organisation for Animal Health ( OIE ) and the World Health Organization ( WHO )] and United Nations Environment Programme statement as “ an integrated , unifying approach that aims to sustainably balance and optimize the health of people , animals and ecosystems .” ( 1 ) The approach seeks to engage and mobilize multiple sectors and disciplines to address threats to health and ecosystems . Throughout the world , the sectors that make up national laboratory systems are often siloed with minimal communication or collaboration among sectors . Through a unique collaboration , six international partners came together to support a One Health approach to laboratory professional development and laboratory system building . The Association of Public Health Laboratories ( APHL ), the Centers for Disease Control and Prevention , the European Centre for Disease Prevention and Control , FAO , OIE and WHO collaborated on the development of the Laboratory Leadership Competency Framework and a One Health professional development program , the Global Laboratory Leadership Programme ( GLLP ), designed to support the leadership competencies . Through this on-going collaboration , the partners developed an inclusive leadership program designed to connect laboratory sectors and encourage their engagement . The partners are currently supporting program development and implementation in 23 countries across the globe and continue to support the One Health approach by engaging multisectoral participation in the programs and collaborating among partners to allow for engagement of all sectors . Eight countries have initiated program activities and engaged their first cohorts , including 126 laboratorians from across the sectors . Sixty-seven percent of participants are from the human health sector , 29 % from the animal health sector , 9 % from food / water / environmental health sector and 3 % from research laboratories . As part of the GLLP , participants
Food Safety / Global Health