OBJECTIVES/GOALS: HelpBeatCOVID19.org, a novel self-reporting symptom tracking surveillance system, is based at the University of Alabama, Birmingham. Helpbeatcovid19.org captures social determinants of health (SDOH) data. This presentation will report research in progress to understand the utility of self-reported data with communicable disease outbreaks. METHODS/STUDY POPULATION: Individuals voluntarily completed an online questionnaire at HelpBeatCOVID19.org which captured SDOH data and other disease surveillance variables including zip code, gender, age group, race, ethnicity, symptoms, underlying conditions, type of home (e.g., single-family, mobile home, etc.), and household COVID-19 diagnosis status. The data are stored on HIPAA-compliant servers. De-identified self-reported data were culled from the HelpBeatCOVID19 database, cleaned, sorted, and analyzed by zip code. Using STATA/SE 16.1, we employed regression analysis to determine if there might be any statistically significant associations that could be made based on zip codes, especially where there are health disparities in historically African American neighborhoods in Jefferson County. RESULTS/ANTICIPATED RESULTS: To date, 102,308 people have reported their symptoms in HelpBeatCOVID19. Of those, 77,903 are from Alabama. More than half of the people who completed HelpBeatCOVID19.org reported zero symptoms. However, 19.3% of Alabamians reported having underlying health conditions. Midfield, AL, a predominantly African-American neighborhood (81.1%), has 74.1% of people reporting underlying conditions where the median household income is $38,750. By comparison, Vestavia Hills, AL, a more affluent neighborhood with an 88.8% White population and median household income being $109,485, had more people participating in HelpBeatCOVID19 (3,920), yet a smaller percentage (15.2%) with underlying health conditions. Final results will be reported during the ACTS Conference. DISCUSSION/SIGNIFICANCE: Our analysis of the data reveals that in Jefferson County, AL, a greater number of people in affluent communities participated in the study. Whereas state-wide, a greater percentage of individuals indicated that they had zero symptoms. Identifying self-reported underlying conditions that impact persons with COVID-19 symptoms will be significant.

Background: Medulloblastoma (MB) is the most common solid malignant pediatric brain neoplasm. Group 3 (G3) MB, particularly MYC amplified G3 MB, is the most aggressive subgroup with the highest frequency of children presenting with metastatic disease, and is associated with a poor prognosis. To further our understanding of the role of MSI1 in MYC amplified G3 MB, we performed an unbiased integrative analysis of eCLIP binding sites, with changes observed at the transcriptome, the translatome, and the proteome after shMSI1 inhibition. Methods: Primary human pediatric MBs, SU_MB002 and HD-MB03 were kind gifts from Dr. Yoon-Jae Cho (Harvard, MS) and Dr. Till Milde (Heidelberg) and cultured for in vitro and in vivo experiments. eCLIP, RNA-seq, Polysome-seq, and TMT-MS were completed as previously described. Results:MSI1 is overexpressed in G3 MB. shRNA Msi1 interference resulted in a reduction in tumour burden conferring a survival advantage to mice injected with shMSI1 G3MB cells. Robust ranked multiomic analysis (RRA) identified an unconventional gene set directly perturbed by MSI1 in G3 MB. Conclusions: Our robust unbiased integrative analysis revealed a distinct role for MSI1 in the maintenance of the stem cell state in G3 MB through post-transcriptional modification of multiple pathways including identification of unconventional targets such as HIPK1.

Salmonella enterica serovar Wangata (S. Wangata) is an important cause of endemic salmonellosis in Australia, with human infections occurring from undefined sources. This investigation sought to examine possible environmental and zoonotic sources for human infections with S. Wangata in north-eastern New South Wales (NSW), Australia. The investigation adopted a One Health approach and was comprised of three complimentary components: a case–control study examining human risk factors; environmental and animal sampling; and genomic analysis of human, animal and environmental isolates. Forty-eight human S. Wangata cases were interviewed during a 6-month period from November 2016 to April 2017, together with 55 Salmonella Typhimurium (S. Typhimurium) controls and 130 neighbourhood controls. Indirect contact with bats/flying foxes (S. Typhimurium controls (adjusted odds ratio (aOR) 2.63, 95% confidence interval (CI) 1.06–6.48)) (neighbourhood controls (aOR 8.33, 95% CI 2.58–26.83)), wild frogs (aOR 3.65, 95% CI 1.32–10.07) and wild birds (aOR 6.93, 95% CI 2.29–21.00) were statistically associated with illness in multivariable analyses. S. Wangata was detected in dog faeces, wildlife scats and a compost specimen collected from the outdoor environments of cases’ residences. In addition, S. Wangata was detected in the faeces of wild birds and sea turtles in the investigation area. Genomic analysis revealed that S. Wangata isolates were relatively clonal. Our findings suggest that S. Wangata is present in the environment and may have a reservoir in wildlife populations in north-eastern NSW. Further investigation is required to better understand the occurrence of Salmonella in wildlife groups and to identify possible transmission pathways for human infections.

During May 2015, an increase in Salmonella Agona cases was reported from western Sydney, Australia. We examine the public health actions used to investigate and control this increase. A descriptive case-series investigation was conducted. Six outbreak cases were identified; all had consumed cooked tuna sushi rolls purchased within a western Sydney shopping complex. Onset of illness for outbreak cases occurred between 7 April and 24 May 2015. Salmonella was isolated from food samples collected from the implicated premise and a prohibition order issued. No further cases were identified following this action. Whole genome sequence (WGS) analysis was performed on isolates recovered during this investigation, with additional S. Agona isolates from sporadic-clinical cases and routine food sampling in New South Wales, January to July 2015. Clinical isolates of outbreak cases were indistinguishable from food isolates collected from the implicated sushi outlet. Five additional clinical isolates not originally considered to be linked to the outbreak were genomically similar to outbreak isolates, indicating the point-source contamination may have started before routine surveillance identified an increase. This investigation demonstrated the value of genomics-guided public health action, where near real-time WGS enhanced the resolution of the epidemiological investigation.