# MATHEMATICAL ECOLOGY AND EPIDEMIOLOGY - 2020/1

Module code: MAT3040

In light of the Covid-19 pandemic, and in a departure from previous academic years and previously published information, the University has had to change the delivery (and in some cases the content) of its programmes, together with certain University services and facilities for the academic year 2020/21.

These changes include the implementation of a hybrid teaching approach during 2020/21. Detailed information on all changes is available at: https://www.surrey.ac.uk/coronavirus/course-changes. This webpage sets out information relating to general University changes, and will also direct you to consider additional specific information relating to your chosen programme.

Prior to registering online, you must read this general information and all relevant additional programme specific information. By completing online registration, you acknowledge that you have read such content, and accept all such changes.

Module Overview

An introduction to the applications of ordinary, delay and partial differential equations to ecology and epidemiology.

Module provider

Mathematics

Module Leader

LLOYD David (Maths)

Number of Credits: 15

ECTS Credits: 7.5

Framework: FHEQ Level 6

JACs code: G120

Module cap (Maximum number of students): N/A

Module Availability

Semester 2

Prerequisites / Co-requisites

MAT2007 Ordinary Differential Equations

Module content

Indicative content includes:

- Review of simple ODE models in ecology such as the logistic and Lotka-Volterra models. Extensions of such models such as the use of the Holling functional responses. Phase plane analysis of such models.
- ODE models in epidemiology. The Kermack McKendrick model. Higher dimensional models that include, for example, an exposed compartment, or which incorporate treatment, vaccination or quarantining. Analytical techniques useful in the linearised analysis of high dimensional systems, such as the Routh Hurwitz conditions. The calculation of the basic reproduction number and its importance in epidemiological modelling.
- Age structured models and their reformulation into delay differential equations or renewal integral equations. The study of the characteristic equations resulting from the linear stability analysis of such models. Use of such equations in ecology and epidemiology, to include the Ross Macdonald model of malaria transmission. The basic reproduction number for models with delay.
- Reaction-diffusion equations. Travelling wave solutions; applications to ecology and epidemiology.

Assessment pattern

Assessment type | Unit of assessment | Weighting |
---|---|---|

School-timetabled exam/test | IN-SEMESTER TEST (50 MINS) | 20 |

Examination | EXAMINATION | 80 |

Alternative Assessment

N/A

Assessment Strategy

The __assessment strategy__ is designed to provide students with the opportunity to demonstrate

· Understanding of how to model real life ecological and epidemiological scenarios, and an understanding of the meaning of the terms in a given model.

· Knowledge of appropriate mathematical techniques to analyse the models.

· Ability to make predictions.

Thus, the __summative assessment__ for this module consists of:

· One two-hour examination (80%)

· One in-semester test at roughly the half way stage (20%).

__Formative assessment and feedback__

There will be 4 marked exercise sheets issued at roughly equal intervals. Written feedback is provided.

Module aims

- introduce students to basic principles involved in mathematical modelling in ecology and epidemiology
- give students an appreciation of how ordinary differential equations, delay differential equations and partial differential equations can apply in various ecological and epidemiological scenarios
- teach appropriate analytical techniques for studying such models
- give students an appreciation of how to interpret the results and make predictions

Learning outcomes

Attributes Developed | ||
---|---|---|

1 | An understanding of how to model ecological and epidemiological problems using differential equations (ordinary, partial and delay) | KCT |

2 | An understanding of appropriate analytical techniques for the study of such problems | KC |

3 | An understanding of how to interpret the results of the analysis and how to make predictions | KCT |

Attributes Developed

**C** - Cognitive/analytical

**K** - Subject knowledge

**T** - Transferable skills

**P** - Professional/Practical skills

Overall student workload

Methods of Teaching / Learning

The __learning and teaching__ strategy is designed to provide:

- Skills in modelling ecological and epidemiological phenomena mathematically
- Knowledge of mathematical techniques appropriate to the study of those problems.
- An appreciation of how to interpret the results and make ecological or epidemiological predictions as appropriate.

The

__learning and teaching__methods include:

3 one-hour lectures per week for 11 weeks, involving traditional lecturing and class discussion.

Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.

Reading list

Reading list for MATHEMATICAL ECOLOGY AND EPIDEMIOLOGY : http://aspire.surrey.ac.uk/modules/mat3040

Programmes this module appears in

Programme | Semester | Classification | Qualifying conditions |
---|---|---|---|

Mathematics MSc | 2 | Optional | A weighted aggregate mark of 40% is required to pass the module |

Mathematics with Music BSc (Hons) | 2 | Optional | A weighted aggregate mark of 40% is required to pass the module |

Economics and Mathematics BSc (Hons) | 2 | Optional | A weighted aggregate mark of 40% is required to pass the module |

Mathematics and Computer Science BSc (Hons) | 2 | Optional | A weighted aggregate mark of 40% is required to pass the module |

Mathematics MMath | 2 | Optional | A weighted aggregate mark of 40% is required to pass the module |

Mathematics with Statistics BSc (Hons) | 2 | Optional | A weighted aggregate mark of 40% is required to pass the module |

Mathematics BSc (Hons) | 2 | Optional | A weighted aggregate mark of 40% is required to pass the module |

Financial Mathematics BSc (Hons) | 2 | Optional | A weighted aggregate mark of 40% is required to pass the module |

Mathematics and Physics BSc (Hons) | 2 | Optional | A weighted aggregate mark of 40% is required to pass the module |

Mathematics and Physics MPhys | 2 | Optional | A weighted aggregate mark of 40% is required to pass the module |

Mathematics and Physics MMath | 2 | Optional | A weighted aggregate mark of 40% is required to pass the module |

Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2020/1 academic year.