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Overview
Overview - Modelling & the Dynamics of Infectious Diseases
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This module provides an introduction to the use of mathematical modelling of infectious diseases. It provides students with an introduction to the theory of infectious disease modelling, illustrates applications of models in infectious disease research and determining the impact of interventions and provides the skills to develop and apply simple models of infectious diseases and interpret infectious disease data.

The overall module aim is to introduce students to key methods for setting up models of the transmission dynamics of infectious diseases and their application.

Intended learning outcomes

Upon successful completion of the module a student will be able to:

  1. Understand the basic methods for setting up deterministic and stochastic infectious disease models and identify appropriate model structures/key epidemiological parameters to describe the dynamics of infectious diseases;
  2. Describe some of the host and pathogen factors determining variation in infectious diseases over time and adapt simple models to incorporate these factors;
  3. Design simple mathematical models to apply to infectious disease epidemiological data, incorporating appropriate control strategies and analyse and interpret the results;
  4. Critically read modelling papers to identify their strengths and limitations.

Mode of delivery

This module is delivered predominantly face-to-face. Where specific teaching methods (lectures, seminars, discussion groups) are noted in this module specification these will be delivered by predominantly face-to-face sessions. There will be a combination of live and interactive activities (synchronous learning) as well as self-directed study (asynchronous learning).

Assessment

The assessment for this module has been designed to measure student learning against the module intended learning outcomes (ILOs) as listed above. The grade for summative assessment(s) only will go towards the overall award GPA. The assessment for this module will be online.

  1. Group Work (20%)
  2. Timed Test (in-module test e.g. MCQ - 80%).

Credits

  • CATS: 15
  • ECTS: 7.5

Module specification

For full information regarding this module please see the module specification.

Entry requirements
Entry requirements - Modelling & the Dynamics of Infectious Diseases
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The module aims to bring a conceptual understanding of mathematical models and their applications in infectious disease research to individuals who have some prior mathematical training (equivalent to UK A-level). It is also suitable for individuals with a more advanced background in mathematical disciplines who wish to obtain an understanding of the broad range of applications of mathematical models in infectious disease epidemiology and who may wish to specialize in this area in the future.

This module builds on and consolidates many of the themes covered in the module on the Epidemiology of Infectious Disease (2437), and attendance at that module (or equivalent knowledge) is beneficial, but not required. Students will need to have an understanding of basic epidemiology. Students will benefit from reading the first chapter of the book “An Introduction to Infectious Disease Modelling” by E Vynnycky and RG White before the start of the module. They may also find it helpful to work through the exercises in the basic maths chapter of this book or through the maths refresher that will be posted on Moodle before the module. Familiarity with the spreadsheet package Excel is important (those with no experience should attend introductory courses).

Training in the modelling package Berkeley Madonna is provided. Specialist mathematical training is not required as the emphasis is on developing a conceptual understanding of the basic methods and their practical application. Students who have attained the equivalent of a good high school mathematics training have generally been able to benefit from the module.

How to apply
How to apply (D1)
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Applications for Terms 2 D1 modules are currently open and will close on 20 January 2025. Applications should be made online via our application portal.