Event Title

Modelling the Antibiotic Use in Intensive Care Units

Description

Antimicrobial de-escalation refers to the treatment mechanism of switching from empiric antibiotics with good coverage to alternatives based on laboratory susceptibility test results, with the aims of reducing costs and avoiding unnecessary use of broad-spectrum antibiotics. Though widely practiced and recommended, the benefits and tradeoffs of this strategy have not been well understood. In this talk, we will first show our preliminary simulation results of a set of multi-strain-multi-drug models in an intensive care unit setting, to numerically compare de-escalation with the conventional strategy called antimicrobial continuation. Then we simplify the previous models to compare the long-term dynamical behaviors between de-escalation and continuation systems under a double-strain-double-drug scenario. Finally we extend our models to seek for optimal antibiotic use strategies under a triple-strain-triple-drug scenario. The major conclusion of this study shows that, suppose there are two identical intensive care units that separately adopt de-escalation and continuation as the major drug use strategy, then the one following de-escalation: (1) could maintain either higher or lower percentage of colonized patients in the two-strain transmission scenario; (2) is superior in preventing outbreaks of strains resistant to the empiric antibiotic.

Presenter Bio

I received my PhD in Mathematics from Vanderbilt University in 2014, under the supervision of Dr. Glenn Webb. I am originally from China, and I got my B.S. in Mathematics from University of Science and Technology of China in 2008.

After graduating from Vanderbilt and before joining UMiami, I worked as a postdoc with Dr. Jianhong Wu and his team of Industrial and Applied Mathematics in Toronto, Canada. In the past three years, I have been teaching courses and co-mentoring students at York University and Ryerson University.

My research interest lies in the area of mathematical biology, which typically involves collaborations between mathematicians and biologists. Specifically, I am interested in developing differential equation models and applying mathematical theory of dynamical systems to simulate and understand problems arising from the broad area of life sciences. The biological topics of interests include (but not limited to) antimicrobial drug resistance and healthcare acquired infections, emerging and re-emerging human infectious diseases, and vector-borne diseases.

Presenter Profile Page(s)

http://www.math.miami.edu/news/stories/2017newfaculty/huo.htm

Date of Event

Tuesday, November 27, 2018

Location

Parker Building, Room 301

Share

COinS
 
Nov 27th, 12:05 PM Nov 27th, 12:55 PM

Modelling the Antibiotic Use in Intensive Care Units

Parker Building, Room 301

Antimicrobial de-escalation refers to the treatment mechanism of switching from empiric antibiotics with good coverage to alternatives based on laboratory susceptibility test results, with the aims of reducing costs and avoiding unnecessary use of broad-spectrum antibiotics. Though widely practiced and recommended, the benefits and tradeoffs of this strategy have not been well understood. In this talk, we will first show our preliminary simulation results of a set of multi-strain-multi-drug models in an intensive care unit setting, to numerically compare de-escalation with the conventional strategy called antimicrobial continuation. Then we simplify the previous models to compare the long-term dynamical behaviors between de-escalation and continuation systems under a double-strain-double-drug scenario. Finally we extend our models to seek for optimal antibiotic use strategies under a triple-strain-triple-drug scenario. The major conclusion of this study shows that, suppose there are two identical intensive care units that separately adopt de-escalation and continuation as the major drug use strategy, then the one following de-escalation: (1) could maintain either higher or lower percentage of colonized patients in the two-strain transmission scenario; (2) is superior in preventing outbreaks of strains resistant to the empiric antibiotic.