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Network Science and Engineering Group

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3108 Engineering Hall
1701D Platt St.
Manhattan, KS 66506
Fax: 785-532-1188

Hours: 8 am-12pm, 1pm-5pm M-F

Optimizing antimicrobial treatment regimens to minimize the spread of resistance


PI: Ronette Gehring (VetMed);

Co-PI: Caterina Scoglio (ECE);

Students: Phillip Schumm (ECE), Mina Youssef (ECE).


Antimicrobial drugs are powerful instruments for the treatment and management of bacterial disease. The inappropriate use of these drugs can, however, increase the prevalence of resistance in bacterial populations. Not only does the use of antimicrobial drugs selectively promote the survival of resistant individuals, but it also increases the horizontal spread of genetic elements encoding for resistance within the population. This leads to infections that fail to respond to treatment, resulting in death, prolonged illness and longer hospital stays estimated to cost the US healthcare industry up to $7 billion annually. Our proposal seeks to develop a mathematical model that links the dynamic concentrations of an antimicrobial drug in the body with changes in the size and composition of target bacterial populations over time. The overlay of pharmacokinetic, epidemiological and contact network models make it possible to incorporate multiple factors, including the rate at the antimicrobial drug kills susceptible bacteria, the relationship between drug concentrations and the rate of transfer of genetic resistance elements between individuals, as well as characteristics of the site of infection that may affect opportunities for contact between donor and recipient bacteria. Model parameters will be calculated independently from in vitro experiments. Predictions will be compared with results from in vivo models of clinical infection. The aim of this project is to develop this model that it may be used as a tool to optimize treatment regimens.

Presentations & Publications

R. Gehring, P. Schumm, M. Youssef, C. Scoglio

"A Network-based Approach for Resistance Transmission in Bacterial Populations"

Journal of Theoretical Biology, Volume 262, Issue 1, 7 January 2010, Pages 97-106.


C. Scoglio, T. Easton, R. Gehring, P. Schumm

"Validated Mathematical Models for Epidemics: Utopia or Reality"

Presentation at DMP Seminar Series Fall 2007, November 2007.