Developing the SIR Model
Master mathematical modeling of infectious diseases using the SIR framework. Learn to build and analyze compartmental models for epidemic dynamics.
Master mathematical modeling of infectious diseases using the SIR framework. Learn to build and analyze compartmental models for epidemic dynamics.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Infectious Disease Modelling Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
4.8
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What you'll learn
Construct valid mathematical models for infectious diseases
Interpret compartmental models using rates and proportions
Analyze fundamental processes driving SIR epidemic dynamics
Model changes in population susceptibility over time
Implement epidemic models using R programming
Evaluate different vaccination and immunity scenarios
Skills you'll gain
This course includes:
1.1 Hours PreRecorded video
1 assignment
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FullTime access
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There are 4 modules in this course
This comprehensive course focuses on developing mathematical models for infectious disease dynamics using the SIR (Susceptible-Infected-Recovered) framework. Students learn to construct and interpret compartmental models, understand epidemic behavior, and analyze disease transmission patterns. The course covers fundamental concepts including basic reproduction numbers, force of infection, and population susceptibility dynamics, with practical applications using R programming.
Modelling the Basics
Module 1 · 8 Hours to complete
Anatomy of an Epidemic
Module 2 · 2 Hours to complete
Combining Modelling and Insights
Module 3 · 3 Hours to complete
Dynamics of Susceptibles
Module 4 · 7 Hours to complete
Fee Structure
Instructor
Innovator in Mathematical Epidemiology
Dr. Nimalan Arinaminpathy is a Reader in Mathematical Epidemiology at Imperial College London's Faculty of Medicine, specifically within the School of Public Health. His research focuses on applying mathematical and statistical tools to understand the transmission dynamics of infectious diseases, with a particular emphasis on tuberculosis and public health policy. Dr. Arinaminpathy's work bridges the gap between basic scientific research and practical applications, aiming to inform and enhance public health strategies through rigorous modeling.
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4.8 course rating
263 ratings
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