Presentation Title

Using Time-Dependent Sensitivity Analysis to Combat Tuberculosis

Faculty Mentor

Dr. Allison L. Lewis

Start Date

17-11-2018 8:45 AM

End Date

17-11-2018 9:00 AM

Location

C335

Session

Oral 1

Type of Presentation

Oral Talk

Subject Area

physical_mathematical_sciences

Abstract

Although many organizations throughout the world have worked tirelessly to control tuberculosis (TB) epidemics, no country has yet been able to eradicate the disease completely. In this talk, we present two compartmental models representing the spread of a TB epidemic throughout a population. The first is a general TB model; the second is an adaptation for regions in which HIV is prevalent, accounting for the effects of TB/HIV co-infection. Using active subspaces, we conduct time-dependent sensitivity analysis on both models to explore the significance of certain parameters with respect to the spread of TB. We use the results of this sensitivity analysis to determine the most effective strategies for treatment and prevention throughout the epidemic.

Summary of research results to be presented

Our goal is to determine the best ways to eradicate tuberculosis (TB) using time-dependent sensitivity analysis. We built a model, consisting of many parameters, to show how TB spreads in a population. Our objective is to identify which parameters, or combinations of parameters, contribute most to the spread of the disease. We also ask ourselves if the significance of these parameters actually changes over time and what that means in terms of eradicating TB. By conducting time-dependent sensitivity analysis, we find that at the start of an epidemic it is important to limit the spread of TB by targeting the contact and infection rates. Towards the middle, the vaccination rate and the latent treatment rate become significant, meaning that we would want to focus resources on vaccinations and also on treating individuals who have an inactive strain of TB in them. Finally, towards the end we find that targeting the relapse rate is also important. As briefly mentioned in our abstract, we also built a model to represent the spread of TB in an area where HIV/TB co-infection is prevalent. The sensitivity analysis of this co-infection model shows almost identical results, the only difference being that towards the end of the epidemic, the HIV contraction rate plays a large role in the spread of TB. We hope that medical professionals and researchers can use these results to better understand and know what the best strategies are for targeting tuberculosis in any epidemic at any given point in time.

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Nov 17th, 8:45 AM Nov 17th, 9:00 AM

Using Time-Dependent Sensitivity Analysis to Combat Tuberculosis

C335

Although many organizations throughout the world have worked tirelessly to control tuberculosis (TB) epidemics, no country has yet been able to eradicate the disease completely. In this talk, we present two compartmental models representing the spread of a TB epidemic throughout a population. The first is a general TB model; the second is an adaptation for regions in which HIV is prevalent, accounting for the effects of TB/HIV co-infection. Using active subspaces, we conduct time-dependent sensitivity analysis on both models to explore the significance of certain parameters with respect to the spread of TB. We use the results of this sensitivity analysis to determine the most effective strategies for treatment and prevention throughout the epidemic.