The Dean’s Seminar Series on Infectious Disease Modeling is co-hosted by the Department of Environmental Health Science, Department of Epidemiology, and ICAP at Columbia Mailman School of Public Health. This seminar series features experts presenting the latest research in infectious disease modeling and epidemiology from various disciplines.
This series will be online only. Attending over Zoom requires registration. Affiliates outside of Columbia are welcome to attend via Zoom.
This series is presented by Dr. Grewn Knight, Associate Professor, London School of Hygiene and Tropical Medicine, UK.
Seminar Title: How important is antibiotic use to antibiotic resistance?
Abstract:
Antibiotics are a cornerstone of modern medicine but also the agents of their own downfall in that their use drives the global public health problem that is antimicrobial resistance (AMR). However, quantifying the relationship between AMR and antibiotic exposure is difficult, requiring an understanding of the complex interactions between selection pressure and AMR transmission. Mathematical models are powerful tools for dissecting these complexities, allowing us to explore various concepts and synthesize data across different levels of biological and clinical organization.
In this talk, I will present my interdisciplinary research aiming to quantify the impact of antibiotic selection on resistance, beginning with an outline of the general structure of compartmental transmission models of AMR, emphasizing the common assumptions that underpin these models. Following this, I will discuss data from Great Ormond Street Hospital (GOSH), which challenge conventional expectations about the effects of antibiotics. To address these discrepancies, I will demonstrate the value of integrating modelling with laboratory research, highlighting the critical role of single data systems and the potential double-edged sword of (bacterio)phage therapy as a solution to combat AMR. Furthermore, I will present ecological analyses that align with the GOSH data, using disaggregated data on how AMR varies by age and sex to reveal new complexities in selection by antibiotics.
This interdisciplinary talk will underscore the unexpected, complex, and context-specific nature of antibiotic effects, illustrating the importance of using different levels of modelling and data analysis to tackle AMR.
For the speakers and dates of the future events, please check our website.