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Two UBC Statistics MSc student presentations (Yuwei Yang & Marc Wettengel)

Tuesday, April 18, 2023 - 11:00 to 12:00
Yuwei Yang, UBC Statistics MSc student; Marc Wettengel, UBC Statistics MSc student

To join this seminar: Please request Zoom connection details from headsec [at]

Presentation 1

Time: 11:00am – 11:30am

Speaker: Yuwei Yang, UBC Statistics MSc student

Title: Statistical Consulting and Process

Abstract: Improvement in Surgical Research Projects The use of statistical analysis and data-driven approaches in healthcare is crucial for improving patient outcomes and optimizing resource allocation. During my co-op at UBC Province Wide Division of General Surgery at Vancouver General Hospital, I contributed to over 15 surgical research projects around the province, focusing on study design, data analysis, and statistical consulting. My work involved managing missing data, validating data integrity, collaborating on grant applications and abstracts, conduct statistical analysis, and supporting quality improvement initiatives through metrics monitoring and assessment. Through this co-op experience, I have gained valuable insights into the application of statistical methods in healthcare and the importance of data-driven decision-making in surgical research and quality improvement.

Presentation 2

Time: 11:30am – 12:00pm

Speaker: Marc Wettengel, UBC Statistics MSc student

Title: Analysis of the associations between environmental conditions and norovirus outbreaks in shellfish harvest zones on Vancouver Island

Abstract: Norovirus is a common cause of gastroenteritis with infection characterized by diarrhea, vomiting, and stomach pain. Bivalve molluscan shellfish (oysters, muscles, scallops, etc.) are common sources of community norovirus outbreaks in the Lower Mainland. This project uses longitudinal and time series methods to analyze the relationship between environmental conditions and norovirus outbreaks in shellfish harvesting zones on Vancouver Island. Weekly measurements on rainfall, ocean salinity, sea surface temperature and other environmental conditions were compiled from 2003 through 2019. Community norovirus case counts were also included as norovirus is not naturally present environment. This covariate is used as a proxy to determine if norovirus could potentially be present in the inter tidal zones which shellfish harvesting occurs. These covariates were compared to outbreak periods in shellfish harvesting zones during the same time period. Generalized linear mixed effect models, generalized estimating equations, and distributed lag non-linear models were fitted and compared with each other to determine the associations between environmental conditions and norovirus outbreaks in shellfish.