This two-hour talk provides a focused introduction to epidemic modeling as a vital tool for understanding disease transmission, guiding public health policy, and forecasting outbreaks. It begins with foundational concepts such as SIR and SEIR models, the basic reproduction number, and transmission dynamics through differential equations. Realworld case studies—including COVID-19 (SEIR) and vector-borne diseases like Malaria and Dengue (SEIR-SEI)—illustrate how models are tailored to different diseases and intervention strategies. The session concludes with practical numerical methods using MATLAB, covering the solution of ordinary differential equations (e.g., with ode45) and visualizing the impact of varying parameters. Designed for public health professionals, researchers, and students, the talk bridges theoretical understanding and computational techniques, equipping participants with the tools to simulate, analyze, and apply epidemic models effectively.

 

Expected Participants

Undergraduate and graduate students, early career PhD researchers, and professionals in epidemiology, public health, and mathematical modeling.

 

Basic Skills of Participants

Fundamental knowledge of differential equations, mathematical modeling, and public health, along with familiarity with MATLAB.

 

Basic Needs of Participants

A computer with MATLAB installed and basic proficiency in handling datasets and simulations.