Northwestern Events Calendar

Oct
19
2020

Jessica Conway: HIV Viral Rebound Heterogeneity Following Treatment Interruption

When: Monday, October 19, 2020
4:00 PM - 5:00 PM  

Where: Online
Webcast Link

Audience: Faculty/Staff - Student - Public - Post Docs/Docs - Graduate Students

Contact: Madeline Kennedy   847.491.3345

Group: McCormick-Engineering Sciences and Applied Mathematics

Category: Lectures & Meetings, Academic

Description:

Title: HIV Viral Rebound Heterogeneity Following Treatment Interruption

Speaker: Jessica Conway, PhD, Penn State University

Special Note: To attend this zoom-talk, please register using the following link:  https://northwestern.zoom.us/meeting/register/tJMpfuCoqDwjGtQ2nJ00QhB9SmOAWO7m43Qq. Upon registering, you will receive an email containing information about joining the meeting. When clicking at the link please make sure it is not split into two lines.

Abstract: Antiretroviral therapy (ART) effectively controls HIV infection, suppressing HIV viral loads to levels undetectable using commercial testing. Typically, suspension of therapy is rapidly followed by rebound of viral loads to high, pre-therapy levels. However recent observations give nuance to that statement: in a small fraction of cases, rebound may be delayed by months, years, or even possibly, permanently. We will discuss a proposed phenomenological model assuming simple heterogeneous dynamics in latent reservoir activation, which we assume is the source of viral rebound, to make predictions on time to rebound post-treatment suspension. In particular, we rely on time-inhomogeneous branching processes to derive a mechanistically-motivated survival function for time-to-rebound. We validate our model with data from Li et al. (2016), specifically a collection of observations of times to viral rebound across 235 study participants following treatment suspension. We show that our model provides good agreement with survival curves generated from study participants. Finally if there's time we will discuss hypotheses for biology underlying the phenomenological model and aimed at generating testable predictions on achieving durable infection control following interruption of ART.

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