Speaker Name: Dr. Rakesh Aggarwal, (Professor and Head, Department of Gastroenterology, Sanjay Gandhi Institute of Medical Sciences, Lucknow)
Date: 17-10-2025 (Friday)
Time: 10 am - 11 am
Venue: Lecture classroom, KR 224, KreSIT
Abstract: Mathematical modelling of infectious diseases uses mathematical equations to represent disease transmission, progression and outcomes, and helps inform public health policies by simulating disease outbreaks, forecasting changes in disease burden over time, assessing the impact of various public health interventions, such as contact tracing, vaccination programs, and drug treatment, and comparing their cost-effectiveness and budget impact. This technique permits a rapid comparison of various alternative interventions, whereas clinical trials to compare these often take years, delaying introduction of useful healthcare interventions, are costly, and may be unethical or impossible. While such models are routinely used to guide public health policy for controlling infectious diseases in several countries, their use in India has lagged.
Successful development of mathematical models requires experts who know biomedicine as well as mathematics and computer science. However, in India, educational streams for medicine and mathematics/computer science diverge early, resulting in 'innumerate physicians' and 'bio-blind mathematicians'. Though efforts have been made to bring experts in these fields to work together, the modelling output has been mixed. There are two major reasons for this.
First, it is often thought that principles underlying mathematical models, such as deterministic compartmental models, Markov chains, are similar across various diseases. However, infectious disease biology is more complex than that, and with each individual disease/pathogen possessing certain inherent biological characteristics, that necessitate the use of more complex and specific models. Second, each model needs to be calibrated and/or validated using high-quality epidemiological data, which are often not available in our setting.
The speaker has extensive experience in the fields of infectious diseases, vaccination and healthcare economic analyses. Though not a modeler himself, he has been involved in interpretation and use of modelling data for deciding health policy. Besides presenting his work on economic analyses in relation to viral hepatitis, he will use various diseases to exemplify the complexities involved in disease modelling. He will argue that, for mathematical modelling to flourish, a sustained interaction between experts in mathematics and in individual disease domains to cross-learn the peculiarities of biology of specific diseases and principles of mathematics, respectively, is mandatory.