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MA4M1 Epidemiology by Example

Lecturer: Dr Kat Rock

Term(s): Term 2

Status for Mathematics students: List C

Commitment: 30 Lectures

Assessment: 100% assessed through coursework

Prerequisites: There are no strict prerequisites, but other modules that could provide a useful background include those on modelling (e.g. MA254 Theory of ODEs, MA257 Introduction to Systems Biology, MA390 Topics in Mathematical Biology, MA3J4 Mathematical modelling with PDE), programming (e.g. MA124 Maths by Computer, MA117 Programming for Scientists, MA261 Differential Equations: Modelling and Numerics) and/or statistics (e.g. ST202 Stochastic Processes).

Leads To: Academic and non-academic research in epidemiology and modelling.

Content:

Epidemiology by Example is a new course for 2020/21 which focuses on the application of numerical methods to address real-world problems in infectious diseases. Starting with programming for basic infectious disease models, the module will progress on to implementation of stochastic models, fitting models to real-world data, adaptive management of diseases and health economic analyses for decision making. The course is designed to give an overview of key methods currently used in epidemiology research and will be 100% assessed through coursework.

Programming language: Matlab.

Aims:

Objectives:

Books:

Additional Resources

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Year 1 regs and modules
G100 G103 GL11 G1NC

yr2.jpg
Year 2 regs and modules
G100 G103 GL11 G1NC

yr3.jpg
Year 3 regs and modules
G100 G103

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Year 4 regs and modules
G103

Archived Material
Past Exams
Core module averages