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Macroscopic Models of Epidemic Dynamics - Week 6

Offered By: The Julia Programming Language via YouTube

Tags

Epidemiology Courses Differential Equations Courses Mathematical Modeling Courses Stochastic Processes Courses Statistical Mechanics Courses

Course Description

Overview

Explore macroscopic models of epidemic dynamics in this 27-minute lecture from MIT's 18.S191 Fall 2020 course. Transition from microscopic, stochastic SIR models to macroscopic, deterministic models by examining means and expectations. Delve into discrete and continuous (differential equations) approaches. Learn about simple recovery models, deterministic dynamics for mean values, and derivations using stochastic processes. Investigate macroscopic descriptions in continuous time, full SIR models, discrete-time SIR models, and standard continuous-time SIR models. Gain insights into epidemic modeling techniques and their applications in understanding disease spread dynamics.

Syllabus

Introduction.
Simple model of recovery.
Deterministic dynamics for the mean: Intuitive derivation.
Derivation using mean of stochastic process.
Macroscopic description in Continuous-time.
Full SIR model.
Discrete-time SIR model.
Standard(continuous-time) SIR model.
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Taught by

The Julia Programming Language

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