Models for SARS-CoV-2 health policies

Title: Models for SARS-CoV-2 health policies: Social Distancing amidst Vaccination and Virus Variants

Abstract: Policy decisions during the SARS-CoV-2 pandemic were important to contain the spread of the virus, but complicated due to virus variants and the varying impact of societal restrictions. In this talkwe report results from a model that utilized population behaviour to predict the impact of SARS-CoV-2 transmission in India over a number of months from June 2021 to March 2022. The model utilizes deterministic population compartments, incorporating a dynamic transmission factor dependent on the population's behavior as a function of reported confirmed cases. The model also incorporates the state of vaccination and virus variants as part of the transmission dynamics. The model projections, used for advice towards preemptive policy actions by NITI AAYOG, a pivotal government of India organization involved in developing a national public health strategy, culminated in early warning projections for the Omicron variant.

Host: Justin Shea, Mehdi Jeddi, Erik Pak, and Sou-Cheng Choi

Talk Format: This is a hybrid event. To attend online, join us on Zoom here at 6pm:
https://iit-edu.zoom.us/j/89379230295?pwd=NdETyE5sdYuSrvsrBZXSBFkUESBVkg.1

Meeting ID: 893 7923 0295
Passcode: 5t5WYn

Sponsor: Adyen, UIC College of Business, and PyData Chicago co-host this event. UIC will provide the meeting site. Adyen will sponsor pizza and soft drinks for the onsite participants.

Address: TBD

Logistics: TBD