Join us for the 4th talk of the OMNI-RÉUNIS Super Spreader Seminar Series on NOV 17, 11:00-12:00 ET with Yi Tan
Mark your calendars and join us this Thursday for another OMNI-RÉUNIS Super Spreader Seminar Series talk! We would appreciate it very much if you could share this seminar series with your networks, affiliated organizations, and other interested researchers. To learn more about OMNI-RÉUNIS, please visit www.omni-reunis.ca
Date and time: November 17, 2022 @11:00-12:00 ET
Zoom link: Attend the talk here
Title: The stochasticity in adherence to nonpharmaceutical interventions and booster doses and the mitigation of COVID-19
Speaker: Yi Tan, York University
Bio: Yi Tan is a Ph.D. candidate in the Department of Mathematics and Statistics at York University, a member of LAMPS, CCDM and OMNI-RÉUNIS. Her research interests are stochastic differential equations and their applications in biology she has been working on modelling of infectious diseases and zoonotic diseases. She participated and contributed to several projects on COVID-19 and monkeypox
The pandemic of Coronavirus Disease 2019 (COVID-19) has been around for almost three years. The fatigue of individuals on interventions has been increasing over time, despite the presence of the more contagious variant, Omicron. Although the nonpharmaceutical interventions (NPIs) are still in place and booster doses are proposed to mitigate the epidemic, the uncertainty and stochasticity in individuals’ behaviours toward the NPIs and booster dose increase, and how this randomness affects the transmission remains poorly understood. Random fluctuations are important factors for the spread and prevalence of COVID-19 due to the transmission nature of COVID-19 being probabilistic and thus stochastic. In this talk, I will present a model framework that incorporates demographic stochasticity and two kinds of stochasticity (notably variations in adherence to NPIs and acceptance of booster doses) for the spread of COVID-19. The data from December 31, 2021, to March 8, 2022, on daily reported cases and hospitalizations, cumulative cases, deaths and vaccinations for booster doses in the city of Toronto is used for stochastic model calibration. I will explain how different forms of stochasticity affect the transmission of COVID-19. I will present the results developed here that can guide the implementation of control measures, including vaccination strategies, given the presence of stochastic perturbations.
Language of talk: English
The Super Spreader Seminar Series is organized by the OMNI-RÉUNIS HQP Organizing Committee – Dr. Joseph Baafi (Memorial University of Newfoundland and Labrador), Dr. Suzan Farhang Sardroodi (University of Manitoba), Dr. Shivdeep Singh Hayer (University of Guelph), Dr. Jeta Molla (York University), Dr. Pei Yuan (York University), and IT support by Steven Chen (York University).
If you have any questions, please contact Natasha Ketter, Program Manager of OMNI-RÉUNIS at email@example.com